CN120007191A - Pile foundation drilling technology, drilling control system and drilling rig in gravel and bedrock areas - Google Patents

Abstract

The invention relates to the field of construction engineering technology, and discloses a pile foundation drilling process in gravel and bedrock areas, including the following steps: drilling data acquisition: real-time acquisition of drilling parameters such as drilling pressure, drilling speed, drill bit temperature and vibration data; fractal crushing model calculation, and also provides a pile foundation drilling control system in gravel and bedrock areas, including: a drilling data acquisition module: used for real-time acquisition of data on drilling pressure, drilling speed, drill bit temperature and vibration parameters; a fractal crushing calculation module, and also provides a drilling rig for pile foundation drilling in gravel and bedrock areas, including: a drill bit module: used for striking and cutting rock formations, and cooperating with a continuous crushing mechanism for efficient drilling. The invention realizes automatic adjustment of drilling pressure and drilling speed by introducing an intelligent real-time feedback control system and a particle swarm optimization algorithm, improves drilling efficiency, reduces equipment wear, reduces energy consumption, and effectively adapts to changes in complex formations.

Description

Sand pebble and bedrock area pile foundation drilling process, drilling control system and drilling machine

Technical Field

The invention relates to the technical field of constructional engineering, in particular to a sand pebble and bedrock area pile foundation drilling process, a drilling control system and a drilling machine.

Background

Along with the acceleration of the urban process, pile foundation construction is increasingly widely applied to constructional engineering, in particular to projects such as high-rise buildings, bridges, infrastructure and the like. The construction of pile foundations requires an efficient and stable drilling process to ensure the strength and reliability of the pile foundations. However, in actual construction, the complexity and variability of formation conditions makes the drilling process challenging. How to optimize the ratio of the weight on bit and the drilling speed, reduce the energy consumption and improve the drilling efficiency becomes a key problem for solving the problem of pile foundation construction.

Existing pile foundation drilling techniques rely primarily on fixed weight-on-bit and rate-of-penetration settings, and most adjustments rely on manual experience. In the prior art, construction is performed by setting fixed weight on bit and drilling speed, and although the method can ensure smooth construction under certain conditions, the method cannot cope with the change of complex geological conditions in real time. For ordinary rock formations, conventional techniques may provide reasonable drilling efficiency, but when hard rock formations or complex geology are encountered, the drilling efficiency is significantly reduced. Some modern drilling equipment can simply adjust the weight on bit, but this is not enough to cope with all geological changes, and the abrasion of the drill bit is serious, the energy consumption is high, and the service life of the equipment is short.

The main disadvantage of the prior art is the lack of intelligent control of the drilling process, especially in terms of weight on bit and rate of penetration adjustment, often relying on manual experience for adjustment. While the prior art is capable of operating under certain basic geological conditions, drilling parameters cannot be quickly and accurately adjusted in complex or unstable formations. Conventional drilling techniques fail to respond in real time to changes in formation hardness, drilling resistance, etc., which can lead to problems of excessive equipment load or inefficient drilling. In addition, excessive energy consumption and excessive wear of the drill bit also severely impact construction costs and overall efficiency.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides a sandy pebble and bedrock area pile foundation drilling process, a drilling control system and a drilling machine, and solves the problems that the drilling process in the prior art lacks intelligent control and the drilling pressure and the drilling speed cannot be adjusted in real time to cope with complex stratum changes.

The invention is realized by the following technical scheme that the drilling process for the pile foundation in the sandy pebble and bedrock area comprises the following steps:

Drilling data acquisition, namely acquiring drilling parameters of drilling weight, drilling speed, drill bit temperature and vibration data in real time;

The fractal crushing model calculation, namely analyzing the crushing complexity of the rock stratum through the fractal geometric model, calculating the fractal dimension and determining the drilling force;

analyzing the optimal relation between the drilling weight and the drilling speed according to the drilling dynamics model;

The intelligent optimization algorithm is used for adjusting, namely the weight on bit and the drilling rate are automatically adjusted according to real-time data by utilizing the particle swarm optimization algorithm;

And (3) real-time feedback control, namely dynamically adjusting drilling parameters according to real-time sensor data, and ensuring that the drilling process is always in a high-efficiency working state.

Preferably, the intelligent optimization algorithm adjustment includes:

The real-time drilling data monitoring comprises the steps of judging the current state of drilling according to the parameters of the drilling pressure and the drilling speed monitored in real time in the drilling process, and optimizing and adjusting the drilling parameters in real time by utilizing a particle swarm optimization algorithm according to the changes of the drilling pressure and the drilling speed in the drilling process so as to realize the optimal drilling efficiency;

and updating feedback data, namely updating optimization parameters in real time, and ensuring continuous and efficient operation of the drilling system.

The invention also provides a control system for drilling the pile foundation in the sandy pebble and bedrock areas, which comprises the following components:

the drilling data acquisition module is used for acquiring data of drilling weight, drilling speed, drill bit temperature and vibration parameters in real time;

The fractal crushing calculation module is used for analyzing the crushing complexity of the rock stratum through a fractal geometric model according to drilling data and the stratum type and calculating the drilling force;

The drilling dynamics analysis module is used for analyzing the relation between the drilling weight and the drilling speed and optimizing various parameters in the drilling process according to the real-time data;

The intelligent optimization control module integrates a particle swarm optimization algorithm, and adjusts the drilling weight and the drilling speed in real time so as to optimize the drilling efficiency;

And the real-time feedback control module is used for adjusting the weight on bit and the drilling speed parameters in real time so as to maintain the stability and the efficiency of the drilling process.

Preferably, the drilling data acquisition module comprises:

The weight-on-bit sensor is used for measuring the weight-on-bit in the drilled hole in real time;

the drilling speed sensor is used for monitoring the drilling speed in the drilling process;

and the temperature and vibration sensor is used for monitoring the temperature and vibration state of the drill bit and equipment and ensuring the stability of the equipment in the drilling process.

Preferably, the intelligent optimization control module includes:

The particle swarm optimization algorithm is used for optimizing the relation between the drilling pressure and the drilling speed through the drilling data acquired in real time to ensure the maximization of the drilling efficiency, and the feedback adjustment algorithm is used for adjusting the drilling parameters according to the feedback data acquired in the drilling process to ensure the stability and the safety in the drilling process.

The invention also provides a drilling machine for drilling pile foundations in sandy pebble and bedrock areas, which comprises:

the drill bit module is used for striking and cutting rock strata and is matched with the continuous crushing mechanism to perform high-efficiency drilling;

The micro-blasting system module is used for controlling the release energy of micro-blasting through intelligent frequency conversion when the bedrock is drilled, and improving the drilling efficiency by matching with a diamond bit;

The grouting system module is used for injecting cement paste or chemical curing agent, ensuring the stability of the hole wall and preventing collapse by grouting technology, and the real-time monitoring system module is used for monitoring the drilling pressure, drilling speed, drill bit state and equipment temperature parameters in the drilling process.

Preferably, the drill bit module includes:

a hydraulic hammer for preliminary loosening the rock formation to reduce drilling resistance;

and the spiral blade is matched with a hydraulic hammering device to cut and crush the loose rock stratum.

Preferably, the micro blasting system module includes:

The intelligent variable frequency control module is used for accurately controlling the release energy of micro blasting and ensuring the maximization of the crushing effect of the rock stratum in the drilling process;

And the explosion energy adjusting module is used for adjusting the energy intensity and the release time of explosion according to the real-time data and the drilling state so as to avoid excessive influence on the surrounding environment.

Preferably, the real-time monitoring system module includes:

The drilling pressure monitoring module is used for monitoring drilling pressure data in the drilling process in real time;

The drilling speed monitoring module is used for monitoring the change of the drilling speed and ensuring the stability in the drilling process;

And the temperature and vibration monitoring module is used for detecting the temperature and vibration conditions of the drill bit and the equipment and adjusting the working state through a feedback mechanism.

Preferably, the grouting system module comprises:

The grouting pumping system is used for injecting cement paste or chemical curing agent into the drill hole and ensuring stable pressure and flow;

and the grouting pressure control system monitors and adjusts the grouting pressure in real time to ensure that the hole wall is fully reinforced in the drilling process.

The invention provides a sand pebble and bedrock area pile foundation drilling process, a drilling control system and a drilling machine. The beneficial effects are as follows:

1. according to the invention, the weight on bit and the drilling speed are automatically adjusted through a particle swarm optimization algorithm, so that the drilling parameters are ensured to be in an optimal state all the time. Compared with the prior art, the manual intervention is reduced, the drilling efficiency is improved, and the equipment load is obviously reduced.

2. By means of the real-time sensor data, the system can monitor various parameters in the drilling process, such as temperature and vibration, and automatically adjust drilling parameters. This not only avoids equipment failure, but also improves the safety of the construction process, reducing the risk of unexpected downtime.

3. The energy consumption optimization strategy of the invention adjusts drilling parameters according to real-time data, effectively reduces unnecessary energy consumption, ensures high-efficiency operation and saves energy. Compared with the traditional fixed parameter operation mode, the method saves energy cost and reduces the overall construction cost.

Drawings

FIG. 1 is a flow chart of the method of the present invention;

FIG. 2 is a system block diagram of the present invention;

fig. 3 is a block diagram of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Referring to fig. 1, the embodiment of the invention provides a process for drilling pile foundations in sandy pebble and bedrock areas, which comprises the following steps of S1, drilling data acquisition, namely acquiring drilling parameters of drilling weight, drilling speed, drilling bit temperature and vibration data in real time;

Each parameter in the drilling process directly affects the construction efficiency and the stability of the equipment, so that the real-time monitoring and acquisition of the key parameters are important. Through comprehensive drilling data acquisition, comprehensive understanding of a plurality of key factors such as weight on bit, drilling speed, drill bit temperature and vibration is ensured, and data support is provided for follow-up intelligent control and optimization.

In this embodiment, the drilling data acquisition module includes a plurality of high-precision sensors for monitoring and acquiring various data during the drilling process in real time. With these sensors, the system is able to capture dynamic changes in drilling in real time and provide feedback. These data will serve as the basis for subsequent calculations and optimization, ensuring that the drilling process proceeds efficiently and safely.

The weight-on-bit sensor is used for monitoring the contact pressure between the drill bit and the stratum in real time. Weight on bit is one of the key parameters that determine drilling rate and equipment stability. Too high weight on bit may cause excessive wear of the drill bit and even equipment damage, while too low weight on bit may cause too slow drilling rate, affecting construction efficiency.

The working principle of weight-on-bit sensors is generally based on strain gauge technology, measuring weight-on-bit values by sensing the pressure transmitted at the bottom of the drilling machine. Through the real-time monitoring of weight on bit, control system can in time adjust drilling parameter according to the hardness of stratum, avoids too big pressure to cause equipment damage or too low pressure inefficiency.

The drilling speed sensor is used for monitoring the footage speed of the drill bit in real time. Too fast or too slow drilling rate can directly affect the accuracy and overall efficiency of pile foundation construction. If the drilling rate is too high, the drill bit may experience sticking or vibration problems, while too slow a rate may result in extended working time and increased equipment wear.

The drilling speed sensor adopts a rotary encoder or laser speed measuring equipment, can accurately measure the rotating speed or the propelling speed of the drill bit, and transmits data to a control system in real time. The control system adjusts the weight on bit and the rate of penetration based on the data to ensure that the drilling process remains within an efficient range at all times.

The bit temperature sensor is to ensure that the bit is not damaged or excessively worn by overheating. During the drilling process, factors such as friction, weight on bit, drilling speed and the like can cause the drill bit to generate high temperature. If the temperature is too high, the drill bit is easily damaged, and even safety accidents can be caused. Therefore, the temperature sensor monitors the working state of the drill bit in real time by measuring the temperature of the contact part of the drill bit and the rock stratum.

Common temperature monitoring methods include thermocouples, infrared thermometers, and the like. Through the technologies, the system can adjust drilling parameters according to real-time temperature data, and the drill bit is prevented from being damaged due to overhigh temperature.

The vibration sensor monitors the amplitude of vibrations generated by the drill bit during drilling. Excessive vibration may not only affect drilling accuracy, but may also lead to equipment failure or bit damage. Vibration sensors typically employ accelerometers or piezoelectric sensors to detect the amplitude, frequency, and range of fluctuations in the vibration of the drill bit.

The vibration sensor monitors the state of the drill bit in real time, and if the vibration amplitude exceeds the preset safety range, the control system reduces the vibration by adjusting parameters such as the weight on bit, the drilling speed and the like, and avoids the damage of the drill bit caused by excessive vibration.

The data acquisition module transmits all data acquired by the sensor to the main control system in real time through a wireless communication technology. In the main control system, after the data is processed and analyzed, a basis is provided for the drilling optimization decision. The real-time feedback of the data such as the drilling pressure, the drilling speed, the temperature, the vibration and the like can ensure that the drilling process is carried out in a high-efficiency state, and the drilling parameters can be adjusted in real time to avoid equipment damage and improve the construction efficiency.

In one possible implementation manner, the data acquisition module transmits real-time data to the cloud control system through a wireless transmission technology, and the main control system performs comprehensive analysis according to various data received by the cloud platform. The system can dynamically adjust control parameters such as drilling weight, drilling speed and the like, and ensures that drilling work is performed efficiently and safely.

In order to ensure the rationality and accuracy of parameters such as weight on bit, drilling speed, drill bit temperature, vibration and the like in the drilling process, the invention introduces a plurality of basic formulas and models to optimize the relation among various parameters in the drilling process. In particular, in the calculation of weight on bit and rate of drilling, real-time data provided by weight on bit sensors directly influences the calculation formula of drilling force.

The relationship between weight on bit and drilling force formula: weight on bit P ₁ and drilling force F is calculated by the following formula:

F₁＝P₁·A;

Wherein F ₁ is drilling force (unit: newton), P ₁ is weight on bit (unit: pascal), and A is the area of the drill bit in contact with the formation (unit: square meter).

The formula shows that the product of the weight on bit and the contact area of the drill bit is the drilling force. Through real-time monitoring weight on bit, can effectively control the drilling power, prevent that too high drilling power from leading to equipment trouble or drill bit damage.

The relation between the drilling speed and the drilling efficiency can be described by the following dynamics model:

Where η is drilling efficiency (in units of efficiency ratio), F ₁ is drilling force (in units of Newton) and v is drilling rate (in units of meters/second).

This formula shows that a reasonable match between the drilling force and the drilling rate will directly affect the drilling efficiency during the drilling process. An optimal drilling effect can be achieved while maintaining a balance of drilling force and drilling rate.

Weight on bit (P) is the pressure generated when the bit is in contact with the formation, directly affecting the rate of penetration and the operational stability of the device. Excessive weight on bit may cause equipment to overload operation or even malfunction, and excessive weight on bit may reduce drilling efficiency and prolong operation time.

The drilling force (F) is the force required to move the drill bit through the formation and is dependent on weight on bit and bit contact area. Too much drilling force may result in severe equipment wear and too little may not effectively break through the formation.

The rate of penetration (v) refers to the distance the drill bit advances per second. While proper rate of penetration helps to increase drilling efficiency, too high a rate of penetration may result in bit wear or sticking, and too low a rate of penetration may decrease work efficiency.

The bit temperature (T) is a key parameter to determine whether the bit is within a safe operating range. Excessive temperatures can cause excessive wear and even damage to the drill bit, and controlling the temperature helps to extend the life of the equipment.

Vibration (V) can affect drilling accuracy and equipment stability. Excessive vibration may cause bit misalignment, increasing equipment failure rates. Monitoring and control of the vibrations helps to ensure the smoothness of the drilling process.

The data acquired in real time not only provides decision basis for subsequent optimization control, but also realizes remote monitoring and data analysis through the cloud platform, so that the drilling process is more intelligent, and the safety, precision and efficiency of the whole construction process are improved.

S2, calculating a fractal crushing model, namely analyzing the crushing complexity of the rock stratum through a fractal geometric model, calculating a fractal dimension, and determining the drilling force;

The fracture complexity of the formation is analyzed by introducing a fractal geometric model to accurately calculate the drilling force required. By analyzing the fractal dimension of the rock stratum, the breaking difficulty of the rock can be quantified, and drilling parameters can be correspondingly adjusted, so that the purposes of optimizing drilling efficiency and avoiding equipment abrasion are achieved.

The fragility of rock is closely related to its internal microstructure. The conventional drilling mechanics model often fails to accurately describe the impact of different particle sizes, hardness, and crack distributions in the formation on the drilling effect. The fractal geometric model can more accurately describe the microstructure of the rock, and particularly can provide more accurate crushing force calculation compared with the traditional method for irregular cracks and distribution characteristics of particles.

The fractal dimension is a key index for describing the rock breaking complexity, and the higher the fractal dimension is, the more complex the breaking structure of the rock stratum is, and the breaking difficulty is increased. Typically, the fractal dimension of the formation ranges between 0 and 2, with higher fractal dimensions meaning more complex crack distribution of the formation and greater force required for drilling.

In this embodiment, the calculation of the drilling force is based on a fractal geometrical model, and the magnitude of the drilling force is calculated mainly by calculating the fractal dimension of the rock stratum. The magnitude of the drilling force is positively correlated with the fracture complexity of the formation, i.e., the higher the fractal dimension of the formation, the greater the drilling force that needs to be applied. Specifically, the relationship between the drilling force and the fractal dimension is calculated by the following formula:

Wherein P ₂ is crushing power in watts and represents energy required by a drill bit to crush rock in a rock stratum, F ₂ is acting force in newtons and represents contact force between the drill bit and the rock stratum, A is contact area between the drill bit and the rock stratum and represents square meter and influences friction force between the drill bit and the rock, C is a constant and depends on physical properties of the rock and efficiency of the drill bit, D is fractal dimension and describes crushing complexity of the rock stratum, and the higher the fractal dimension is, the greater difficulty of rock stratum crushing is represented.

By the formula, the drilling system can calculate the required drilling force according to the real-time data so as to ensure that the drilling process can be efficiently and stably carried out. In this embodiment, the real-time monitoring data (such as weight on bit, drilling rate, temperature, etc.) and the fractal dimension of the rock stratum are combined, so that the drilling parameters can be accurately adjusted, and the high efficiency of the drilling process is ensured.

The fractal dimension reflects the microstructural complexity of the formation. For calculating the fractal dimension of the formation, a common fractal geometrical algorithm such as a box counting method can be adopted. By scanning microscopic cracks of the rock stratum and analyzing the distribution density and morphology of the cracks, the fractal dimension of the rock stratum can be obtained.

Specifically, in practice, image data of the formation is first acquired by digital image processing techniques and then the fractal dimension of the formation is analyzed using box counting. The method calculates crack distribution in each small unit by dividing a two-dimensional image of the rock stratum into a plurality of small units (namely 'boxes') so as to further calculate fractal dimension of the whole rock stratum.

The basic principle of the box counting method is to divide the structure of a rock stratum into boxes with different dimensions, and then count the number of cracks contained in the boxes with different dimensions. By calculating the distribution of these cracks, the fractal dimension of the formation can be derived. In general, a formation with a higher fractal dimension has a more complex crack distribution and requires more drilling force during the drilling process.

In some embodiments, the calculation of the fractal dimension may also incorporate three-dimensional scanning techniques in order to increase the accuracy of the calculation. Three-dimensional scanning can provide more detailed formation structure data, particularly under complex geological conditions, which can more accurately reflect the microstructure characteristics of the formation. Under the condition of using three-dimensional scanning data, the calculation process of the fractal dimension can be finer, and the drilling force is optimized more accurately.

In some embodiments, the system may dynamically adjust weight on bit and rate of penetration by continuous real-time data updates. For example, if the system detects a formation with a higher fractal dimension, the control system may increase the weight on bit or adjust the bit shape to more efficiently penetrate the formation. If the system detects a looser or simpler formation, the weight on bit is reduced appropriately to reduce energy waste and improve drilling efficiency.

Based on the calculation result of the fractal crushing model, the optimal adjustment of the drilling force directly influences the drilling efficiency and the equipment stability. The control system dynamically adjusts drilling parameters according to the fractal dimension change so as to ensure the high efficiency and the safety of the drilling process. For example, during drilling, if the fractal dimension of the formation is high, the drilling system may increase weight on bit, ensuring that the drill bit can successfully penetrate hard rock. If the fractal dimension of the formation is low, the weight on bit is suitably reduced, thereby avoiding energy waste and equipment burden during drilling.

Through the drilling force optimization model based on the fractal geometry, the system can respond to the change of the rock stratum in real time and automatically adjust drilling parameters. The automatic adjustment not only reduces errors caused by manual operation, but also greatly improves the efficiency in the drilling process.

The higher the fractal dimension is, the larger the drilling force required in the drilling process is, and the system ensures that the drill bit can efficiently crush the rock stratum by adjusting parameters such as the weight on bit, the drilling speed and the like, so that excessive drilling or drill bit abrasion is avoided. And for the rock stratum with lower fractal dimension, the drilling force requirement is smaller, the system can reduce the weight on bit, improve the working efficiency and reduce the equipment burden.

S3, drilling dynamics model analysis, namely analyzing the optimal relation between the weight and the drilling speed according to the drilling dynamics model, wherein the core task of the drilling dynamics model analysis is to analyze the optimal relation between the weight and the drilling speed through the drilling dynamics model. The step is closely connected with the step S1 and the step S2, the former provides real-time data support of weight on bit, drilling speed, vibration and the like for the step, the latter calculates the breaking characteristics of rock stratum through a fractal geometric model, provides theoretical basis for subsequent drilling optimization, and the step S3 further finely adjusts drilling parameters through a dynamic model, so that the drilling efficiency is maximized and long-term stable operation of equipment is ensured.

In this embodiment, the application of the drilling dynamics model can effectively describe the interaction relationship between the weight on bit and the drilling rate. The reasonable proportion between the weight on bit and the drilling speed is a key factor for improving the drilling efficiency, reducing the equipment abrasion and ensuring the stable operation of the drill bit. Therefore, the drilling control system needs to dynamically adjust the ratio of the weight on bit and the drilling speed according to different characteristics of geological layers, so that the stability and the high efficiency of the drilling process are ensured.

During drilling, there is a complex correlation between weight on bit and rate of penetration. When the weight on bit is too high, the drilling force is increased, but excessive abrasion of the drill bit or overload operation of equipment may be caused, while when the weight on bit is too low, the drilling efficiency may be reduced, and even the drill bit cannot effectively crush the rock stratum. If the drilling rate is too high, the drilling rate can be increased, but the rock may be broken incompletely, and the construction accuracy may be affected. Conversely, too low a drilling rate may result in reduced drilling efficiency and extended working time.

In order to accurately control the relation between the weight on bit and the drilling speed in the drilling process, the invention describes the dynamic relation between the weight on bit and the drilling speed based on a drilling dynamics model by using the following formula:

F₁＝P₁·A-C·v²;

Wherein F ₁ is drilling force (unit: newton), which is the contact force between the drill bit and the rock stratum, which affects the drilling efficiency and stability, P ₁ is drilling pressure (unit: pascal), which is the pressure applied to the drill bit, which is usually monitored by a weight-on-bit sensor, A is the contact area of the drill bit and the rock stratum (unit: square meter), which is the contact surface area of the drill bit and the rock stratum, which is usually determined by the size of the drill bit, C is the friction coefficient (unit: dimensionless), which reflects the friction strength between the drill bit and the rock stratum, which is usually obtained through experiments, and v is drilling speed (unit: meters/second), which is the advancing speed of the drill bit, which affects the drilling efficiency.

The function of the formula is to adjust the weight on bit and the drilling rate in real time by modeling the relation between the drilling force and the weight on bit, the contact area and the drilling rate so as to ensure the optimization of the drilling process. In the drilling process, the system calculates the current drilling force according to real-time data (such as the drilling pressure, the drilling speed, the drilling bit temperature, the vibration and the like) through the formula, and adjusts the ratio of the drilling pressure to the drilling speed according to the required drilling force, so that the efficient and stable drilling is ensured.

The contact area (a) is the area where the drill bit contacts the formation, which determines the friction and the drilling force. The greater the contact area, the greater the drilling force generated by weight on bit, but also the increased wear. The contact area is typically determined by the design and specifications of the drill bit.

The coefficient of friction (C) is one of the important factors affecting the drilling force. The hardness and surface roughness of the formation may affect the coefficient of friction and thus the drilling force calculation. Formations with a higher coefficient of friction typically require more weight on bit and drilling force to ensure efficient fracturing.

In practical applications, the drilling control system calculates through a drilling dynamics model based on real-time data of weight on bit, rate of drilling and contact area. During the drilling process, the control system will continuously monitor the drilling force and adjust the weight on bit and the rate of penetration as required. For example, when the drilling system detects a hard rock formation, the system will increase weight on bit to increase drilling force, but the rate of drilling will decrease moderately based on real-time monitoring data to avoid overburdening the equipment. When the system encounters a soft rock stratum, the system automatically reduces the drilling pressure, improves the drilling speed, improves the drilling efficiency and saves energy.

In certain embodiments, the drilling control system employs an adaptive control strategy. Through a machine learning algorithm, the system can gradually optimize the adjustment strategy of the weight on bit and the drilling rate according to the feedback of the historical drilling data and the real-time data. These algorithms can predict the characteristics of different formations and automatically adjust weight and rate of penetration to account for different geological conditions.

For example, the system may identify different characteristics of hard and soft rock formations by learning historical data, automatically adjust drilling parameters based on this information, ensuring drilling efficiency and equipment stability. With the continuous accumulation of data of the system, the machine learning algorithm can make intelligent decisions in the drilling process, so that the drilling efficiency is further improved and the equipment failure rate is reduced.

The system automatically adjusts drilling parameters according to the real-time monitoring data and the change of geological conditions, and ensures that the drilling process is always in an optimal state. The intelligent control mode not only improves the drilling efficiency, but also prolongs the service life of equipment, and ensures the safety and stability of construction.

And S4, adjusting an intelligent optimization algorithm, namely automatically adjusting the weight on bit and the drilling speed according to real-time data by using a particle swarm optimization algorithm, wherein the particle swarm optimization algorithm can adaptively adjust the ratio of the weight on bit and the drilling speed, so that the drilling efficiency is maximized, the equipment abrasion is reduced, and the stability and the safety of drilling operation are improved.

During actual drilling, the changing formation conditions and the operating conditions of the drilling equipment may result in a constant change in the optimization requirements for the drilling parameters. Thus, conventional fixed weight and rate-of-drilling strategies are unable to cope with complex and varying geological conditions. According to the embodiment, a particle swarm optimization algorithm is adopted, and the drilling weight and the drilling speed are continuously adjusted by simulating the cooperative work of particles in the search space, so that the drilling process is always kept in an optimal working state, and the drilling efficiency and the service life of equipment are ensured.

Particle Swarm Optimization (PSO) algorithm is a heuristic global optimization algorithm and is widely applied to optimization of high-dimensional complex problems. In the invention, the PSO algorithm continuously adjusts the state of each particle according to an objective function (namely an optimization target in the drilling process) by simulating the searching behaviors of a plurality of particles so as to find the optimal weight-on-bit and bit rate matching.

In particular, the particles represent one possible solution (i.e. one combination of weight on bit and rate of penetration) in the search space. The searching process of the particles simulates the foraging behavior of the bird group, and the optimal solution is searched by continuously updating the position and the speed. Each particle calculates its own velocity and position by the following formula, gradually approaching the optimal solution.

The particle update formula is as follows:

Wherein: the speed of the ith particle at the t generation is given in meters per second (affecting the speed of movement of the particle in the search space); The method comprises the steps of determining the position of an ith particle in a t generation (namely, the current combination of weight on bit and drilling speed), determining the historical optimal position of the particle by P _best,i (namely, the combination of the optimal weight on bit and the drilling speed found by the particle in historical search), determining the global optimal position by G _best (namely, the combination of the optimal weight on bit and the drilling speed found by the whole particle swarm), controlling the degree of keeping the original speed of the particle by w to be between 0.4 and 0.9, determining the convergence speed of the particle to the individual optimal position and the global optimal position by c ₁ and c ₂ as learning factors, and determining the random number by r ₁,r₂ to be between 0 and 1, wherein the random number is used for increasing the randomness in the searching process.

According to the formula, each particle can adjust the speed according to the historical optimal position and the global optimal position, and the position of the combination of the weight on bit and the drilling speed is updated in each iteration. Through multiple iterations, the particle swarm will gradually converge to an optimal weight-on-bit and rate-of-drilling combination, even if the drilling process is always in an optimal working state.

In the application of particle swarm optimization algorithms, the optimization objectives are to minimize energy consumption during drilling, bit temperature, drilling vibration, and maximize drilling efficiency. The control system can optimize the ratio of the weight on bit and the drilling speed through a PSO algorithm according to the data (such as the weight on bit, the drilling speed, the temperature, the vibration and the like) monitored in real time. The following is a detailed description of the optimization objectives:

Drilling energy consumption (E) energy consumption is one of the goals that need to be minimized in the optimization process. Higher weight on bit and bit rates generally increase energy consumption, while too low a bit rate or bit rate may decrease drilling efficiency. By optimizing the ratio of the weight on bit and the drilling rate, unnecessary energy waste can be reduced while drilling efficiency is ensured.

The optimization objective of these parameters can be described by the following fitness function:

The method comprises the steps of (1) setting f (X) as a fitness function value of particles, wherein the f (X) is a fitness function value of the particles and represents the advantages and disadvantages of the current weight on bit and drilling rate combination, w ₁,w₂,w₃,w₄ is a weight coefficient and represents the relative importance of each optimization target, E is drilling energy consumption, V is drilling rate, T is bit temperature, T _opt is an optimal temperature range, V is drilling vibration, and V _opt is an optimal vibration range.

By optimizing the fitness function, the PSO algorithm can minimize drilling energy consumption and maximize drilling efficiency while ensuring that bit temperature and vibration remain within reasonable ranges throughout.

In the actual implementation process, the optimization control system executes a particle swarm optimization algorithm by the following steps:

Data acquisition and initialization of particle swarm the system first acquires drilling parameters (e.g., weight on bit, rate of penetration, bit temperature, vibration, etc.) in real time and inputs these data into the PSO algorithm. From the real-time data, a plurality of particles (i.e., a plurality of weight-on-bit and rate-of-penetration combinations) are generated.

And calculating the fitness value of each particle according to parameters such as weight on bit, drilling speed and the like by the system, and judging the quality of the current combination.

Particle update and position adjustment-updating the speed and position of the particles according to the formula. And each particle is adjusted according to the historical optimal solution and the global optimal solution, and gradually approaches to the optimal drilling parameters.

And judging convergence and outputting an optimal solution, namely stopping iteration when the adaptability of all particles reaches stability or meets convergence conditions, and outputting the combination of the optimal weight on bit and the optimal drilling rate to a drilling control system to be applied to actual drilling operation.

By applying the particle swarm optimization algorithm, the invention can dynamically optimize the ratio of the weight on bit and the drilling speed according to the real-time data and the change of geological conditions, and ensure the drilling efficiency and the equipment stability. The PSO algorithm is introduced to greatly improve the automation degree in the drilling process, so that the drilling control is more intelligent, the intervention of manual operation is reduced, and the drilling efficiency and the safety are improved.

S5, real-time feedback control, namely dynamically adjusting drilling parameters according to real-time sensor data to ensure that the drilling process is always in a high-efficiency working state;

The core task of the real-time feedback control is to ensure that drilling parameters (such as weight on bit and drilling rate) are always in an optimal working state through the real-time feedback control. This step closely links the previous steps S1 to S4, where S1 provides real-time weight on bit, rate of penetration, temperature and vibration data, S2 calculates the fracture characteristics of the formation by a fractal model, S3 analyzes the optimal relationship between weight on bit and rate of penetration, and S4 further optimizes the ratio of weight on bit and rate of penetration by a particle swarm optimization algorithm. Step S5, based on the data and the model result, the drilling parameters are dynamically adjusted by means of a real-time feedback mechanism, and the drilling process is ensured to be always efficient and safe.

In this embodiment, the real-time feedback control system dynamically adjusts the weight on bit and the drilling rate according to real-time data collected during the drilling process, so as to effectively cope with formation changes and the working state of the drilling equipment. The system monitors data such as weight on bit, drilling speed, drill bit temperature, vibration and the like in real time through the sensor, and compares the data with preset optimal drilling parameters. When a deviation is detected, the system automatically adjusts the weight and rate of drilling to ensure that the drilling process remains in an optimal operating state throughout.

The real-time feedback control system mainly comprises a data acquisition module, a signal processing module, a control module and an execution module. The data acquisition module is responsible for collecting real-time data in the drilling process from various sensors, including weight on bit, drilling rate, temperature, vibration and the like. The signal processing module performs denoising, filtering and other processing on the data, so that the accuracy of the data is ensured. The control module dynamically calculates the bit weight and bit rate to be adjusted according to the difference between the real-time data and the preset optimization parameters, and sends out a control signal. Finally, the execution module adjusts the working state of the drilling machine (such as adjusting the drill bit speed, adjusting the hydraulic system and the like) according to the instruction of the control module.

In general, the real-time feedback control system is tightly integrated with the optimization control system, and the drilling parameters are adjusted in real time by using the results of the particle swarm optimization algorithm and the dynamics model. The system can quickly respond to the changes of external environment and internal equipment by comprehensively analyzing various key data in the drilling process, and ensures that the drilling operation is smoothly carried out.

The real-time adjustment strategy for weight on bit and rate of penetration depends on a number of factors including formation type, bit status, construction environment, etc. The system adjusts weight on bit and rate of penetration by the following strategy:

adjustment of formation hardness as the drilling process encounters harder formations, the control system automatically increases weight on bit to enhance drilling. At the same time, the system may reduce the rate of penetration properly to prevent excessive bit wear or equipment overload.

Adjustment of formation porosity as formation porosity changes in unconsolidated formations where drilling force requirements are lower, the control system may reduce weight on bit to reduce energy consumption and increase drilling efficiency by increasing rate of penetration. At this time, the reduction in weight on bit helps to reduce equipment wear.

Temperature and vibration monitoring-drill bit temperature and vibration are key factors affecting drilling efficiency and equipment stability. The system monitors the temperature and the vibration amplitude of the drill bit in real time, and once abnormal conditions are found, the system can keep the drill bit in a safe temperature range by adjusting the weight on bit and the drilling speed, so that equipment faults caused by excessive vibration are avoided.

Equipment load and efficiency balance-when the system detects that the equipment load is too high, possibly due to excessive weight-on-bit or rate-of-bit, the control module will automatically adjust the weight-on-bit or rate-of-bit to avoid excessive wear or equipment damage. By means of real-time feedback control, the system can keep stable operation of equipment, and shutdown or faults caused by excessive load are avoided.

In general, the real-time feedback control system can quickly respond to the change in the drilling process, and ensures that the adjustment of the weight on bit and the drilling speed is in place in time. The response time of the system is determined by a number of factors, including the sampling frequency of the sensor, the data processing speed, and the computational power of the control system. In some embodiments, the system predicts possible drilling problems in advance by an optimization algorithm and performs pre-adjustment, thereby reducing the delay of system response and ensuring the timeliness of real-time adjustment.

For example, when complex geological changes are encountered, the control system may predict resistance changes or equipment load fluctuations that may be encountered during drilling through analysis of historical data and real-time monitoring data. By adjusting the weight and the drilling rate in advance, the system can effectively avoid overload, reduce the downtime and keep the drilling efficiency stable.

By means of real-time feedback control, the invention can ensure that the drilling process is always in an optimal state. The system has the greatest advantages that the system is automatic and intelligent, the weight on bit and the drilling speed can be dynamically adjusted according to various real-time data in the drilling process, and errors and instabilities possibly caused by manual adjustment are avoided. Through real-time monitoring and adjustment, the system can automatically adapt to various geological conditions, optimize drilling efficiency, prolong equipment service life and ensure high efficiency and safety of the construction process.

In addition, the real-time feedback control system can also effectively avoid excessive wear of equipment and unnecessary energy consumption. By monitoring the temperature, vibration and drilling force of the drill bit in real time, the system can automatically adjust the weight and the drilling speed, and ensure that the equipment runs in an optimal working state. The intelligent control mode not only improves the operation efficiency, but also obviously reduces the maintenance cost of equipment in the construction process and ensures the smooth operation of engineering.

Through the intelligent control strategy, the system can adaptively adjust drilling parameters, improve drilling efficiency, reduce energy consumption and reduce equipment faults.

Referring to fig. 2, the present invention further provides a system for controlling drilling of pile foundations in sandy pebble and bedrock areas, comprising:

the drilling data acquisition module is used for acquiring data of drilling weight, drilling speed, drill bit temperature and vibration parameters in real time;

The fractal crushing calculation module is used for analyzing the crushing complexity of the rock stratum through a fractal geometric model according to drilling data and the stratum type and calculating the drilling force;

The drilling dynamics analysis module is used for analyzing the relation between the drilling weight and the drilling speed and optimizing various parameters in the drilling process according to the real-time data;

The intelligent optimization control module integrates a particle swarm optimization algorithm, and adjusts the drilling weight and the drilling speed in real time so as to optimize the drilling efficiency;

And the real-time feedback control module is used for adjusting the weight on bit and the drilling speed parameters in real time so as to maintain the stability and the efficiency of the drilling process.

Referring to fig. 3, the present invention further provides a drilling machine for drilling pile foundations in sandy pebble and bedrock areas, comprising:

the drill bit module is used for striking and cutting rock strata and is matched with the continuous crushing mechanism to perform high-efficiency drilling;

The micro-blasting system module is used for controlling the release energy of micro-blasting through intelligent frequency conversion when the bedrock is drilled, and improving the drilling efficiency by matching with a diamond bit;

The grouting system module is used for injecting cement paste or chemical curing agent, ensuring the stability of the hole wall and preventing collapse by grouting technology, and the real-time monitoring system module is used for monitoring the drilling pressure, drilling speed, drill bit state and equipment temperature parameters in the drilling process.

Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (10)

1. The drilling process of the pile foundation in the sandy pebble and bedrock area is characterized by comprising the following steps of:

Drilling data acquisition, namely acquiring drilling parameters of drilling weight, drilling speed, drill bit temperature and vibration data in real time;

The fractal crushing model calculation, namely analyzing the crushing complexity of the rock stratum through the fractal geometric model, calculating the fractal dimension and determining the drilling force;

analyzing the optimal relation between the drilling weight and the drilling speed according to the drilling dynamics model;

The intelligent optimization algorithm is used for adjusting, namely the weight on bit and the drilling rate are automatically adjusted according to real-time data by utilizing the particle swarm optimization algorithm;

And (3) real-time feedback control, namely dynamically adjusting drilling parameters according to real-time sensor data, and ensuring that the drilling process is always in a high-efficiency working state.

2. The sandy pebble and bedrock area pile foundation drilling process of claim 1, wherein the intelligent optimization algorithm adjustment comprises:

Real-time drilling data monitoring, namely judging the current state of drilling according to parameters of the drilling pressure and the drilling speed monitored in real time in the drilling process;

The optimal adjustment process is to utilize a particle swarm optimization algorithm to adjust drilling parameters in real time according to the change of the drilling pressure and the drilling speed in the drilling process so as to realize optimal drilling efficiency;

and updating feedback data, namely updating optimization parameters in real time, and ensuring continuous and efficient operation of the drilling system.

3. A sandy pebble and bedrock area pile foundation drilling control system, characterized in that the sandy pebble and bedrock area pile foundation drilling process according to any one of claims 1 or 2 is used, comprising:

the drilling data acquisition module is used for acquiring data of drilling weight, drilling speed, drill bit temperature and vibration parameters in real time;

The fractal crushing calculation module is used for analyzing the crushing complexity of the rock stratum through a fractal geometric model according to drilling data and the stratum type and calculating the drilling force;

The drilling dynamics analysis module is used for analyzing the relation between the drilling weight and the drilling speed and optimizing various parameters in the drilling process according to the real-time data;

The intelligent optimization control module integrates a particle swarm optimization algorithm, and adjusts the drilling weight and the drilling speed in real time so as to optimize the drilling efficiency;

And the real-time feedback control module is used for adjusting the weight on bit and the drilling speed parameters in real time so as to maintain the stability and the efficiency of the drilling process.

4. The sandy pebble and bedrock section pile foundation drilling control system of claim 3, wherein the drilling data acquisition module comprises:

The weight-on-bit sensor is used for measuring the weight-on-bit in the drilled hole in real time;

the drilling speed sensor is used for monitoring the drilling speed in the drilling process;

and the temperature and vibration sensor is used for monitoring the temperature and vibration state of the drill bit and equipment and ensuring the stability of the equipment in the drilling process.

5. The sandy pebble and bedrock area pile foundation drilling control system of claim 3, wherein the intelligent optimization control module comprises:

The particle swarm optimization algorithm is used for optimizing the relation between the drilling pressure and the drilling speed through drilling data acquired in real time, so as to ensure the maximization of the drilling efficiency;

And the feedback adjustment algorithm is used for adjusting drilling parameters according to feedback data acquired in the drilling process, so that the stability and the safety in the drilling process are ensured.

6. A drilling machine for drilling a sandy pebble and bedrock area pile foundation, characterized in that the drilling process for the sandy pebble and bedrock area pile foundation according to any one of claims 1 or 2 is used, comprising:

the drill bit module is used for striking and cutting rock strata and is matched with the continuous crushing mechanism to perform high-efficiency drilling;

The micro-blasting system module is used for controlling the release energy of micro-blasting through intelligent frequency conversion when the bedrock is drilled, and improving the drilling efficiency by matching with a diamond bit;

the grouting system module is used for injecting cement paste or chemical curing agent, and ensuring the stability of the hole wall and preventing collapse through a grouting technology;

and the real-time monitoring system module is used for monitoring parameters of the weight on bit, the drilling speed, the state of the drill bit and the temperature of equipment in the drilling process.

7. The drilling rig for drilling pile foundations in sandy pebble and bedrock areas of claim 6 wherein said bit module comprises:

a hydraulic hammer for preliminary loosening the rock formation to reduce drilling resistance;

and the spiral blade is matched with a hydraulic hammering device to cut and crush the loose rock stratum.

8. The drilling rig for drilling pile foundations in sandy pebble and bedrock areas of claim 6 wherein said micro-blasting system module comprises:

The intelligent variable frequency control module is used for accurately controlling the release energy of micro blasting and ensuring the maximization of the crushing effect of the rock stratum in the drilling process;

And the explosion energy adjusting module is used for adjusting the energy intensity and the release time of explosion according to the real-time data and the drilling state so as to avoid excessive influence on the surrounding environment.

9. The drilling rig for drilling pile foundations in sandy pebble and bedrock areas of claim 6 wherein said real-time monitoring system module comprises:

The drilling pressure monitoring module is used for monitoring drilling pressure data in the drilling process in real time;

The drilling speed monitoring module is used for monitoring the change of the drilling speed and ensuring the stability in the drilling process;

And the temperature and vibration monitoring module is used for detecting the temperature and vibration conditions of the drill bit and the equipment and adjusting the working state through a feedback mechanism.

10. The drilling rig for drilling pile foundations in sandy pebble and bedrock areas of claim 6 wherein said grouting system module comprises:

The grouting pumping system is used for injecting cement paste or chemical curing agent into the drill hole and ensuring stable pressure and flow;

and the grouting pressure control system monitors and adjusts the grouting pressure in real time to ensure that the hole wall is fully reinforced in the drilling process.