CN118859818B - Intelligent hardware equipment monitored control system based on thing networking - Google Patents
Intelligent hardware equipment monitored control system based on thing networking Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention discloses an intelligent hardware equipment monitoring system based on the Internet of things, which relates to the field of the Internet of things and comprises a data acquisition module, a wireless communication module, an Internet of things service platform, a monitoring terminal and an output device, wherein the data acquisition module is arranged at an intelligent hardware equipment and used for acquiring working environment state information of the intelligent hardware equipment, the wireless communication module is used for communication connection between the intelligent hardware equipment and the monitoring terminal, the Internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal, the monitoring terminal is used for receiving the acquired data and processing and analyzing the data, and the output device comprises a display, a printer and an interaction unit and is used for displaying monitoring results and printing reports. The invention can realize alarming by adopting a threshold control mode, introduces error coefficients, can increase the alarming precision, adopts the past monitoring data and adopts a time node weight method, and can realize the prediction of future parameters, thereby realizing the early warning function.
Description
Technical Field
The invention relates to the field of Internet of things, in particular to an intelligent hardware equipment monitoring system based on the Internet of things.
Background
The internet of things (InternetofThings, ioT) technology refers to a network which is used for connecting any article with the internet according to a agreed protocol through information sensing equipment such as a Radio Frequency Identification (RFID), an infrared sensor, a global positioning system, a laser scanner and the like, and carrying out information exchange and communication so as to realize intelligent identification, positioning, tracking, monitoring and management. The development of the Internet of things technology is a necessary result of the progress of the scientific technology, the application range of the Internet is greatly expanded, and the seamless connection between the physical world and the information world is realized.
Through retrieval, the patent with the publication number of CN109981617A discloses a method, a system and an electronic device for monitoring equipment of the Internet of things, wherein the method comprises the steps of obtaining transmission data of the equipment of the Internet of things and determining event message data in the transmission data; and acquiring coding rules corresponding to the types of the target Internet of things equipment, analyzing the event message data by utilizing the coding rules to obtain the running state information of the target Internet of things equipment so as to monitor the Internet of things equipment.
The patent has the defects that the time can be monitored only, the alarm and early warning functions can not be realized, and certain limitations exist.
Therefore, the invention provides an intelligent hardware equipment monitoring system based on the Internet of things.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an intelligent hardware equipment monitoring system based on the Internet of things.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
An intelligent hardware device monitoring system based on the internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
Preferably, the working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps of:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
Preferably, in the step S2, the communication is any one of wire harness connection communication, bluetooth communication or local area network communication.
Preferably, in the step S2, the logic of the optimal communication strength path principle is as follows:
s21, determining a signal loss coefficient k% of a transmission relative distance, wherein the signal loss coefficient k% represents a loss proportion of signal intensity per unit transmission distance;
S22, determining a signal strength loss ratio p% when the transition node is used for indirect communication, wherein the signal strength loss ratio p% represents the signal strength loss ratio at a transmission position after a signal is input from one node;
s23, determining the distance between every two sensors according to the arrangement positions of the sensors Which represents the distance between the o-sensor and the i-sensor, and determines the distance of each sensor from the monitoring terminalWhich represents i the distance of the sensor from the monitoring terminal;
And S24, determining each sensor signal transmission path by adopting a transmission mode based on communication intensity or a transmission mode with the lowest intensity loss.
Preferably, in the step S24, the transmission mode based on the communication strength includes the following steps:
S241A, determining the lowest signal strength of the monitoring terminal capable of receiving the complete data ;
S242A of obtaining initial signal intensity of data sent by sensor;
S243A, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S244A, initial Signal Strength Multiplying the total amount of the light loss proportion, and screening all results to be larger thanAnd then randomly determining a path as a transmission path.
Preferably, in the step S243A, the total light loss ratio isWhere n is the total distance of the path and m is the number of transition sensors.
Preferably, in the step S24, the transmission mode with the lowest strength loss includes the following steps:
S241B, acquiring initial signal strength of data sent by the sensor ;
S242B, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S243B, calculating the final signal intensity of the theoretical transmission through each path, and then selecting the path with the strongest signal intensity as the optimal path.
Preferably, in the step S243B, the final signal strength*(1-) Where n is the total distance of the path and m is the number of transition sensors.
Preferably, in the step S3, the alarming method includes the following steps:
S31A, determining a threshold range (a, b) of a normal working state of the intelligent equipment according to the working of the intelligent equipment;
S32A, determining an accuracy error c of the sensor according to the accuracy of the sensor;
S33A, acquiring an actual acquisition value M, and if M-C > b or M+C < a, alarming, otherwise, normal.
Preferably, in the step S3, the early warning method includes the following steps:
S31B, acquiring data acquired by a past sensor, starting with a current node, and acquiring n nodes forwards by taking a fixed time length as a period to obtain n+1 data Representing node acquisition values n time periods away from the current;
S32B, selecting a predicted time node, making a difference between the predicted time node and a current time node, making a quotient with a time period, and removing an integer part to obtain m < n;
S33B, performing adjacent node difference on n+1 nodes to obtain n difference values ;
S34B, giving weight to each difference valueWherein<;
S35B, according to the formulaAnd calculating a predicted value of the predicted node, and operating the predicted value as an actual value of the step S33A to realize early warning.
The invention has the beneficial effects that 1. The invention can realize alarming by adopting a threshold control mode, can increase the alarming precision by introducing error coefficients, and can realize the prediction of future parameters by adopting the past monitoring data and adopting a time node weight method so as to realize the early warning function.
Drawings
Fig. 1 is a working logic diagram of an intelligent hardware equipment monitoring system based on the internet of things.
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the specific embodiments.
In the description of the present invention, it should be noted that, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "disposed" are to be construed broadly, and may be, for example, fixedly connected, disposed, detachably connected, disposed, or integrally connected and disposed. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances. Embodiment 1 of an intelligent hardware equipment monitoring system based on the internet of things, which comprises:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
and the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report. Embodiment 2 an intelligent hardware device monitoring system based on internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
The working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
In the step S2, the communication is realized by adopting wire harness connection communication. Embodiment 3 embodiment 4 an intelligent hardware device monitoring system based on internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
The working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
In the step S2, local area network communication is adopted for communication. An intelligent hardware device monitoring system based on the internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
The working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
In the step S2, bluetooth communication is adopted for communication. Embodiment 5 an intelligent hardware device monitoring system based on internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
The working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
In the step S2, the communication is any one of wire harness connection communication, bluetooth communication or local area network communication.
In the step S2, the logic of the optimal communication strength path principle is as follows:
s21, determining a signal loss coefficient k% of a transmission relative distance, wherein the signal loss coefficient k% represents a loss proportion of signal intensity per unit transmission distance;
S22, determining a signal strength loss ratio p% when the transition node is used for indirect communication, wherein the signal strength loss ratio p% represents the signal strength loss ratio at a transmission position after a signal is input from one node;
s23, determining the distance between every two sensors according to the arrangement positions of the sensors Which represents the distance between the o-sensor and the i-sensor, and determines the distance of each sensor from the monitoring terminalWhich represents i the distance of the sensor from the monitoring terminal;
and S24, determining each sensor signal transmission path by adopting a transmission mode based on the communication intensity.
In the step S24, the transmission mode based on the communication intensity includes the following steps:
S241A, determining the lowest signal strength of the monitoring terminal capable of receiving the complete data ;
S242A of obtaining initial signal intensity of data sent by sensor;
S243A, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S244A, initial Signal Strength Multiplying the total amount of the light loss proportion, and screening all results to be larger thanAnd then randomly determining a path as a transmission path.
In the step S243A, the total light loss ratio isWhere n is the total distance of the path and m is the number of transition sensors. Embodiment 6 an intelligent hardware device monitoring system based on internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
The working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
In the step S2, the communication is any one of wire harness connection communication, bluetooth communication or local area network communication.
In the step S2, the logic of the optimal communication strength path principle is as follows:
s21, determining a signal loss coefficient k% of a transmission relative distance, wherein the signal loss coefficient k% represents a loss proportion of signal intensity per unit transmission distance;
S22, determining a signal strength loss ratio p% when the transition node is used for indirect communication, wherein the signal strength loss ratio p% represents the signal strength loss ratio at a transmission position after a signal is input from one node;
s23, determining the distance between every two sensors according to the arrangement positions of the sensors The method comprises the steps of determining the distance between each sensor and a monitoring terminal, wherein the distance represents the distance between an o sensor and an i sensor, and the distance between each sensor and the monitoring terminal;
And S24, determining each sensor signal transmission path by adopting a transmission mode based on the lowest strength loss.
In the step S24, the transmission method based on the lowest strength loss includes the following steps:
S241B, acquiring initial signal strength of data sent by the sensor ;
S242B, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S243B, calculating the final signal intensity of the theoretical transmission through each path, and then selecting the path with the strongest signal intensity as the optimal path.
In the step S243B, the final signal strength*(1-) Where n is the total distance of the path and m is the number of transition sensors. Embodiment 7 an intelligent hardware device monitoring system based on the internet of things, comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
And the output device comprises a display, a printer and an interaction unit and is used for displaying the monitoring result and printing a report.
The working method of the intelligent hardware equipment monitoring system based on the Internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
In the step S2, the communication is any one of wire harness connection communication, bluetooth communication or local area network communication.
In the step S2, the logic of the optimal communication strength path principle is as follows:
s21, determining a signal loss coefficient k% of a transmission relative distance, wherein the signal loss coefficient k% represents a loss proportion of signal intensity per unit transmission distance;
S22, determining a signal strength loss ratio p% when the transition node is used for indirect communication, wherein the signal strength loss ratio p% represents the signal strength loss ratio at a transmission position after a signal is input from one node;
s23, determining the distance between every two sensors according to the arrangement positions of the sensors Which represents the distance between the o-sensor and the i-sensor, and determines the distance of each sensor from the monitoring terminalWhich represents i the distance of the sensor from the monitoring terminal;
And S24, determining each sensor signal transmission path by adopting a transmission mode based on communication intensity or a transmission mode with the lowest intensity loss.
In the step S24, the transmission mode based on the communication intensity includes the following steps:
S241A, determining the lowest signal strength of the monitoring terminal capable of receiving the complete data ;
S242A of obtaining initial signal intensity of data sent by sensor;
S243A, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S244A, multiplying the initial signal intensity by the total amount of the light loss proportion, and screening all results to be larger than And then randomly determining a path as a transmission path.
In the step S243A, the total light loss ratio isWhere n is the total distance of the path and m is the number of transition sensors.
In the step S24, the transmission method based on the lowest strength loss includes the following steps:
S241B, acquiring initial signal strength of data sent by the sensor ;
S242B, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S243B, calculating the final signal intensity of the theoretical transmission through each path, and then selecting the path with the strongest signal intensity as the optimal path.
In the step S243B, the final signal strength*(1-) Where n is the total distance of the path and m is the number of transition sensors.
In the step S3, the alarming method includes the following steps:
S31A, determining a threshold range (a, b) of a normal working state of the intelligent equipment according to the working of the intelligent equipment;
S32A, determining an accuracy error c of the sensor according to the accuracy of the sensor;
S33A, acquiring an actual acquisition value M, and if M-C > b or M+C < a, alarming, otherwise, normal.
In the step S3, the early warning method includes the following steps:
S31B, acquiring data acquired by a past sensor, starting with a current node, and acquiring n nodes forwards by taking a fixed time length as a period to obtain n+1 data Representing node acquisition values n time periods away from the current;
S32B, selecting a predicted time node, making a difference between the predicted time node and a current time node, making a quotient with a time period, and removing an integer part to obtain m < n;
S33B, performing adjacent node difference on n+1 nodes to obtain n difference values ;
S34B, giving weight to each difference valueWherein<;
S35B, according to the formulaAnd calculating a predicted value of the predicted node, and operating the predicted value as an actual value of the step S33A to realize early warning.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (8)
1. An intelligent hardware equipment monitored control system based on thing networking, characterized by comprising:
The data acquisition module is arranged at the intelligent hardware equipment and is used for acquiring the working environment state information of the intelligent hardware equipment;
The wireless communication module is used for communication connection between the intelligent hardware devices and the monitoring terminal;
The internet of things service platform is used for storing and reading monitoring data and is in communication connection with the monitoring terminal;
The monitoring terminal is used for collecting the collected data and processing and analyzing the data;
the output device comprises a display, a printer and an interaction unit and is used for displaying monitoring results and printing reports;
the data acquisition module is used for acquiring data in real time by adopting a sensor, determining a communication method according to an optimal communication intensity path principle and transmitting the acquired data to the monitoring terminal;
The logic of the optimal communication strength path principle is as follows:
s21, determining a signal loss coefficient k% of a transmission relative distance, wherein the signal loss coefficient k% represents a loss proportion of signal intensity per unit transmission distance;
S22, determining a signal strength loss ratio p% when the transition node is used for indirect communication, wherein the signal strength loss ratio p% represents the signal strength loss ratio at a transmission position after a signal is input from one node;
S23, determining the distance L oi between every two sensors according to the arrangement positions of the sensors, wherein the distance represents the distance between an o sensor and an i sensor, and determining the distance L i between each sensor and a monitoring terminal, wherein the distance represents the distance between the i sensor and the monitoring terminal;
s24, determining a signal transmission path of each sensor by adopting a transmission mode based on communication intensity or a transmission mode with the lowest intensity loss;
in the step S24, the transmission mode based on the communication intensity includes the following steps:
S241A, determining the lowest signal strength Q min of the monitoring terminal capable of receiving complete data;
S242A, acquiring initial signal intensity Q Initial initiation of data sent by a sensor;
S243A, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S244A, multiplying the initial signal intensity Q Initial initiation by the total light loss proportion, screening all paths with the result being larger than Q min, and then randomly determining one path as a transmission path.
2. The intelligent hardware equipment monitoring system based on the internet of things according to claim 1, wherein the working method of the intelligent hardware equipment monitoring system based on the internet of things comprises the following steps:
S1, determining the type of parameters monitored by intelligent hardware equipment, selecting a corresponding sensor according to the type of the parameters, and installing the sensor at the intelligent hardware equipment;
S2, the sensor collects data in real time, a communication method is determined according to an optimal communication intensity path principle, and collected data are transmitted to the monitoring terminal;
s3, the monitoring terminal collects and processes the data, establishes an early warning and alarming model, inputs the data into the early warning model and the alarming model, and carries out early warning and alarming;
S4, the acquired data are transmitted to an Internet of things service platform for storage in real time or at fixed time;
And S5, when the paper is required to output the monitoring result, the monitoring data is called through the monitoring terminal and then sent to the output device for printing.
3. The intelligent hardware equipment monitoring system based on the internet of things according to claim 2, wherein in the step S2, the communication is any one of wire harness connection communication, bluetooth communication or local area network communication.
4. The intelligent hardware equipment monitoring system based on the internet of things according to claim 3, wherein in the step S243A, the total light loss ratio is k npm%, where n is the total path distance, and m is the number of transition sensors.
5. The intelligent hardware equipment monitoring system based on the internet of things according to claim 4, wherein in the step S24, the transmission mode based on the lowest strength loss comprises the following steps:
S241B, acquiring initial signal intensity Q Initial initiation of data sent by a sensor;
S242B, determining a plurality of paths from the sensor to the monitoring terminal in a permutation and combination mode, and calculating the total light loss proportion of each path;
S243B, calculating the final signal intensity of the theoretical transmission through each path, and then selecting the path with the strongest signal intensity as the optimal path.
6. The intelligent hardware equipment monitoring system based on the internet of things according to claim 5, wherein in the step S243B, the final signal strength Q Initial initiation *(1-knpm%), where n is the total path distance, and m is the number of transition sensors.
7. The intelligent hardware equipment monitoring system based on the internet of things according to claim 6, wherein in the step S3, the method for alarming comprises the following steps:
S31A, determining a threshold range (a, b) of a normal working state of the intelligent equipment according to the working of the intelligent equipment;
S32A, determining an accuracy error c of the sensor according to the accuracy of the sensor;
S33A, acquiring an actual acquisition value M, and if M-C > b or M+C < a, alarming, otherwise, normal.
8. The intelligent hardware equipment monitoring system based on the internet of things according to claim 7, wherein in the step S3, the early warning method comprises the following steps:
S31B, acquiring data acquired by a past sensor, starting with a current node, and acquiring n nodes forwards by taking a fixed time length as a period to obtain n+1 data A n+1 which represent node acquisition values from the current n time periods;
S32B, selecting a predicted time node, making a difference between the predicted time node and a current time node, making a quotient with a time period, and removing an integer part to obtain m < n;
S33B, performing adjacent node difference on n+1 nodes to obtain n difference values delta n＝An+1-An;
S34B, assigning a weight q n to each difference, wherein q n＜qn-1;
S35B, according to the formula And calculating a predicted value of the predicted node, and operating the predicted value as an actual value of the step S33A to realize early warning.
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| CN112383892A (en) * | 2020-10-16 | 2021-02-19 | 国网山东省电力公司鱼台县供电公司 | Transformer substation electric energy quality monitoring system and method |
| CN116776081A (en) * | 2023-06-12 | 2023-09-19 | 上海城建智慧城市运营管理有限公司 | An intelligent safety supervision system and method for bridge ancillary facilities based on the Internet of Things |
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| CN116776081A (en) * | 2023-06-12 | 2023-09-19 | 上海城建智慧城市运营管理有限公司 | An intelligent safety supervision system and method for bridge ancillary facilities based on the Internet of Things |
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