CN112149868A - Intelligent diagnosis method for gas use habit and safety analysis - Google Patents
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Abstract
The invention provides an intelligent diagnosis method for analyzing gas use habits and safety, which comprises the following steps: historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users are taken; aiming at each basic data parameter, establishing a data model for analyzing the use habits and safety of a user to obtain a new data sequence hl = X (t) -ml; predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient; comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter; and outputting a diagnosis result according to the values of the sudden change and the jump and a preset diagnosis strategy. According to the method, the diagnosis result can be conveniently and quickly output by establishing a data model for analyzing the use habits and safety of the user and predicting the new data sequence hl by adopting the Pearson correlation coefficient.
Description
Technical Field
The invention belongs to the field of intelligent diagnosis, and particularly relates to an intelligent diagnosis method for gas use habit and safety analysis.
Background
With the rapid development of economy, the living standard of human beings is continuously improved, natural gas is used as an environment-friendly clean energy and becomes a preferred fuel for various users, particularly, the proportion of natural gas used in industrial and commercial users is increased year by year, but the fuel gas used in the industrial and commercial users has some common metering and safety problems. The particularity of the gas consumption of industrial and commercial users is not as stable and reliable as that of the gas consumption of residential users. Especially, the gas is used at night and day, season and non-season, and the maintenance of gas facilities and equipment directly influences the safe operation of the whole gas pipe network. The intelligent diagnosis and prediction of gas consumption habits and safety problems of industrial and commercial users are pain points of gas companies and are places where the gas companies have more input of manpower and financial resources.
If a plurality of gas consumption points are distributed on each floor in a market, in order to ensure the accuracy of natural gas metering, a gas supply system is provided with 1 general meter and a plurality of flowmeters as metering sub-meters, and the gas consumption is 400m generally3About/d, holidays 800m3About/d; and (3) finding out through data reading: the metering number of the general table and the sub table is less than 17m in average per day3Left and right; in two months in the initial period of use, the difference between the accumulated gas consumption of the general table and the accumulated gas consumption of the sub-tables exceeds ten thousand meters3. The kiln is used in tens production in a certain industrial factory, when the kiln is debugged, the phenomenon that the flow meter in the pressure regulating metering box stops or moves is found, and if only part of the kiln is started or only part of the fire head of the kiln is used, the phenomenon that the flow meter cannot measure or the measurement error is large can occur.
Disclosure of Invention
In order to solve the above problems, it is necessary to provide an intelligent diagnosis method for gas usage habits and safety analysis.
In a first aspect, the present invention provides an intelligent diagnosis method, including the following steps:
historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users are taken;
establishing a data model for analyzing the use habits and safety of the user aiming at each basic data parameter, wherein the data model comprises the following steps: finding out all maximum value points of the original data sequence X (t) and fitting the maximum value points by using a cubic spline interpolation function to form an upper envelope line of the original data; finding out all minimum value points, fitting all the minimum value points through a cubic spline interpolation function to form a lower envelope line of data, recording the mean value of the upper envelope line and the lower envelope line as ml, and subtracting the mean envelope ml from an original data sequence X (t) to obtain a new data sequence hl = X (t) -ml;
predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient;
comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter;
and outputting a diagnosis result according to the values of the sudden change and the jump and a preset diagnosis strategy.
Based on the above, the basic data parameters include pressure, flow, temperature, gas leakage concentration, and valve state.
Based on the above, the outputting the diagnosis result according to the values of the sudden change and the jump and the preset diagnosis strategy includes: when the flow is reduced and the pressure is unchanged or reduced, outputting a diagnosis result of gas leakage or gas stealing; when the pressure value changes suddenly, outputting the diagnosis result of surge of the pressure regulator; when the flow is increased, outputting a diagnosis result of the aging of the plug of the pressure regulator; when the flow suddenly decreases or becomes 0, if the valve state is not closed, the pressure is not 0, and the diagnosis result of the fault of the valve or the flow meter is output; when the pressure is reduced suddenly when the pressure is short, the diagnosis result that the pipeline is dug up is output.
The second aspect of the invention provides an intelligent diagnosis method and system for gas use habit and safety analysis, comprising the following steps:
the historical basic data parameter acquisition module is used for acquiring historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users;
the data model module for analyzing the use habits and safety of the users is used for establishing a data model for analyzing the use habits of the users aiming at each basic data parameter, and comprises the following steps: finding out all maximum value points of the original data sequence X (t) and fitting the maximum value points by using a cubic spline interpolation function to form an upper envelope line of the original data; finding out all minimum value points, fitting all the minimum value points through a cubic spline interpolation function to form a lower envelope line of data, recording the mean value of the upper envelope line and the lower envelope line as ml, and subtracting the mean envelope ml from an original data sequence X (t) to obtain a new data sequence hl = X (t) -ml;
the data prediction module is used for predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient;
and the data diagnosis module is used for comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter, and outputting a diagnosis result according to the values of sudden change and jump and a preset diagnosis strategy.
A third aspect of the present invention provides a terminal, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the intelligent diagnosis method for gas usage habit and safety analysis when executing the computer program.
A fourth aspect of the present invention is directed to a computer readable storage medium having stored thereon computer instructions, which when executed by a processor, perform the steps of the intelligent diagnosis method for gas usage habits and safety analysis.
Compared with the prior art, the invention has prominent substantive characteristics and remarkable progress, particularly: according to the invention, by establishing a data model for analyzing the use habits and safety of users and predicting the new data sequence hl by adopting the Pearson correlation coefficient, the diagnosis result can be conveniently and quickly output, the management risk of industrial and commercial users is eliminated, the accident rate of the gas engineering is reduced, meanwhile, the informatization intelligent management and safety monitoring level of the operation management of the gas company is improved, and the method is suitable for large-scale multi-field popularization.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be described in further detail with reference to specific embodiments. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Example 1
The embodiment provides an intelligent diagnosis method for gas use habit and safety analysis, which comprises the following steps:
historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users are taken;
establishing a data model for analyzing the use habits and safety of the user aiming at each basic data parameter, wherein the data model comprises the following steps: finding out all maximum value points of the original data sequence X (t) and fitting the maximum value points by using a cubic spline interpolation function to form an upper envelope line of the original data; finding out all minimum value points, fitting all the minimum value points through a cubic spline interpolation function to form a lower envelope line of data, recording the mean value of the upper envelope line and the lower envelope line as ml, and subtracting the mean envelope ml from an original data sequence X (t) to obtain a new data sequence hl = X (t) -ml;
predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient;
comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter;
and outputting a diagnosis result according to the values of the sudden change and the jump and a preset diagnosis strategy.
Specifically, the basic data parameters include pressure, flow, temperature, gas leakage concentration, and valve state.
Specifically, the outputting the diagnosis result according to the values of the sudden change and the jump and the preset diagnosis strategy includes: when the flow is reduced and the pressure is unchanged or reduced, outputting a diagnosis result of gas leakage or gas stealing; when the pressure value changes suddenly, outputting the diagnosis result of surge of the pressure regulator; when the flow is increased, outputting a diagnosis result of the aging of the plug of the pressure regulator; when the flow suddenly decreases or becomes 0, if the valve state is not closed, the pressure is not 0, and the diagnosis result of the fault of the valve or the flow meter is output; when the pressure is reduced suddenly when the pressure is short, the diagnosis result that the pipeline is dug up is output.
The method comprises the steps of collecting basic data parameters collected by a plurality of industrial and commercial user terminals, classifying, storing, counting, comparing, modeling, analyzing and the like, and establishing a series of data models through a software algorithm. And the statistical analysis of the gas use habits of industrial and commercial users is realized.
Through the real-time and historical data statistics comparison of the flow and the valve state, whether the industrial and commercial users use the habits of seasonal gas, day and night gas, periodic gas and the like is analyzed.
The method can realize the statistical analysis of maintenance conditions of gas facility aging, blockage, surge, gas leakage and the like. The pressure before and after the gas pressure regulation and the gas leakage amount are compared with historical data in a statistical mode, and if the pressure value changes suddenly, the safety problem that the pressure regulator surges is solved; if the gas leakage amount is increased, analyzing the possible aging of a pressure regulator plug and poor interface sealing, and comprehensively diagnosing the aging, plug removing, poor sealing and other fault conditions of the gas facility; if the collected flow suddenly becomes small or 0, then whether the valve or the flow meter has faults is analyzed and judged by collecting whether the state of the gas valve is half-closed or full-closed and combining the pressures before and after gas pressure regulation.
The method can realize the analysis of regional measurement and statistics. The pressure difference of pipeline transmission and distribution is analyzed by collecting each pressure and metering point of an urban gas pipeline, if the pressure of a certain point is suddenly reduced by a large amount, a gas user at the rear end is influenced, and the pipeline is possibly dug off; the method comprises the steps of collecting the flow of each industrial and commercial user, counting and analyzing peak value pressure regulation in an area, analyzing the gas usage amount of the user, and judging whether the sudden change of the flow is a sudden change of the flow in one day, whether the industrial and commercial stop is caused, the gas usage amount is increased suddenly, and the tail end leaks gas or measures faults.
The method can realize the statistics and analysis of the field matching of the equipment. And collecting the flow of each industrial and commercial user, and analyzing whether the equipment is matched in use or not by combining meter parameters. The situations of inaccurate metering, full-load running of the meter and the like caused by the fact that the large-flow meter is installed in a small-flow user and the small-flow meter is installed in a large-flow user are prevented.
Example 2
The embodiment provides an intelligent diagnostic system for gas use habit and safety analysis, which comprises:
the historical basic data parameter acquisition module is used for acquiring historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users;
the data model module for analyzing the use habits and safety of the users is used for establishing a data model for analyzing the use habits of the users aiming at each basic data parameter, and comprises the following steps: finding out all maximum value points of the original data sequence X (t) and fitting the maximum value points by using a cubic spline interpolation function to form an upper envelope line of the original data; finding out all minimum value points, fitting all the minimum value points through a cubic spline interpolation function to form a lower envelope line of data, recording the mean value of the upper envelope line and the lower envelope line as ml, and subtracting the mean envelope ml from an original data sequence X (t) to obtain a new data sequence hl = X (t) -ml;
the data prediction module is used for predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient;
and the data diagnosis module is used for comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter, and outputting a diagnosis result according to the values of sudden change and jump and a preset diagnosis strategy.
It should be noted that, for convenience and brevity of description, the specific working process of the intelligent diagnosis system for fuel gas usage habits and safety analysis described above may refer to the corresponding process of the method described in embodiment 1, and is not described herein again.
Example 3
The embodiment provides a terminal, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the intelligent diagnosis method for the gas use habit and safety analysis.
It should be understood that in the present embodiment, the Processor may be a Central Processing Unit (CPU), and the Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory, and provides instructions and data to the processor. Some or all of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
The memory stores a computer program that is executable on the processor. The processor implements the steps of the intelligent diagnosis method for gas use habit and safety analysis when executing the computer program. Or, the processor implements the functions of the units in the intelligent diagnosis system for gas usage habit and safety analysis when executing the computer program.
Example 4
The present embodiment provides a computer readable storage medium, on which computer instructions are stored, which when executed by a processor implement the steps of the intelligent diagnosis method for gas usage habit and safety analysis described above.
The present embodiment provides a computer program product, which when running on a terminal device, causes the terminal device to execute the steps of the intelligent diagnosis method for gas usage habit and safety analysis in the above embodiments.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described device/terminal embodiments are merely illustrative, and for example, the division of the above-described modules is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated module may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, all or part of the flow in the method of the embodiments described above may be implemented by a computer program, which may be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. The computer program includes computer program code, and the computer program code may be in a source code form, an object code form, an executable file or some intermediate form.
The computer readable medium may include: any entity or device capable of carrying the above-described computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier signal, telecommunications signal, software distribution medium, and the like.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (8)
1. An intelligent diagnosis method for gas usage habit and safety analysis, characterized in that the method comprises the following steps:
historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users are taken;
establishing a data model for analyzing the use habits and safety of the user aiming at each basic data parameter, wherein the data model comprises the following steps: finding out all maximum value points of the original data sequence X (t) and fitting the maximum value points by using a cubic spline interpolation function to form an upper envelope line of the original data; finding out all minimum value points, fitting all the minimum value points through a cubic spline interpolation function to form a lower envelope line of data, recording the mean value of the upper envelope line and the lower envelope line as ml, and subtracting the mean envelope ml from an original data sequence X (t) to obtain a new data sequence hl = X (t) -ml;
predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient;
comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter;
and outputting a diagnosis result according to the values of the sudden change and the jump and a preset diagnosis strategy.
2. The intelligent diagnostic method for gas usage habit and safety analysis according to claim 1, characterized in that, the basic data parameters include pressure, flow, temperature, gas leakage concentration and valve status.
3. The intelligent diagnosis method for gas usage habit and safety analysis according to claim 2, wherein the outputting the diagnosis result according to the values of mutation and jump and the preset diagnosis strategy comprises: when the flow is reduced and the pressure is unchanged or reduced, outputting a diagnosis result of gas leakage or gas stealing; when the pressure value changes suddenly, outputting the diagnosis result of surge of the pressure regulator; when the flow is increased, outputting a diagnosis result of the aging of the plug of the pressure regulator; when the flow suddenly decreases or becomes 0, if the valve state is not closed, the pressure is not 0, and the diagnosis result of the fault of the valve or the flow meter is output; when the pressure is reduced suddenly when the pressure is short, the diagnosis result that the pipeline is dug up is output.
4. An intelligent diagnostic system for gas usage habit and safety analysis, comprising:
the historical basic data parameter acquisition module is used for acquiring historical basic data parameters before and after the on-site voltage regulation of industrial and commercial users;
the data model module for analyzing the use habits and safety of the users is used for establishing a data model for analyzing the use habits of the users aiming at each basic data parameter, and comprises the following steps: finding out all maximum value points of the original data sequence X (t) and fitting the maximum value points by using a cubic spline interpolation function to form an upper envelope line of the original data; finding out all minimum value points, fitting all the minimum value points through a cubic spline interpolation function to form a lower envelope line of data, recording the mean value of the upper envelope line and the lower envelope line as ml, and subtracting the mean envelope ml from an original data sequence X (t) to obtain a new data sequence hl = X (t) -ml;
the data prediction module is used for predicting each obtained new data sequence hl by adopting a Pearson correlation coefficient;
and the data diagnosis module is used for comparing the basic data parameters acquired in real time with the corresponding predicted values to obtain the values of sudden change and jump of each basic data parameter, and outputting a diagnosis result according to the values of sudden change and jump and a preset diagnosis strategy.
5. The intelligent diagnostic system for gas usage habit and safety analysis according to claim 4, characterized in that, the basic data parameters include pressure, flow, temperature, gas leakage concentration and valve status.
6. The intelligent diagnosis system for gas usage habit and safety analysis according to claim 2, wherein the outputting the diagnosis result according to the values of mutation and jump and the preset diagnosis strategy comprises: when the flow is reduced and the pressure is unchanged or reduced, outputting a diagnosis result of gas leakage or gas stealing; when the pressure value changes suddenly, outputting the diagnosis result of surge of the pressure regulator; when the flow is increased, outputting a diagnosis result of the aging of the plug of the pressure regulator; when the flow suddenly decreases or becomes 0, the valve state (how to change), the pressure (how to change) and the diagnosis result of the fault of the output valve or the flow meter are obtained; when the pressure is reduced suddenly when the pressure is short, the diagnosis result that the pipeline is dug up is output.
7. A terminal comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: the processor, when executing the computer program, realizes the steps of the method of any of claims 1-3.
8. A computer-readable storage medium having stored thereon computer instructions, which, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 3.
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