Temperature monitoring system for power equipment based on platinum thermal resistance temperature sensor

Abstract

The present invention belongs to the field of temperature monitoring and relates to data analysis technology. The present invention is used to solve the problem in the prior art that the temperature monitoring system of electric power equipment cannot adopt different monitoring methods to perform temperature monitoring on components with different temperature performance characteristics. Specifically, the present invention is a temperature monitoring system of electric power equipment based on a platinum thermal resistor temperature sensor, comprising a temperature monitoring platform. The temperature monitoring platform is communicatively connected with a feature analysis module, a data processing module, a combined monitoring module and a storage module. The feature analysis module is used to analyze the fault temperature characteristics of the electric power equipment: when the electric power equipment fails, the monitored object is marked as a clear object or a fuzzy object through the analysis process; a platinum thermal resistor temperature sensor is added to the fuzzy object. The present invention can analyze the fault temperature characteristics of the electric power equipment, differentiate the temperature characteristics of the monitored object through an appearance coefficient, and add a platinum thermal resistor temperature sensor to the fuzzy object to improve the accuracy of the temperature monitoring result.

Description

Technical Field

[0001] The invention belongs to the field of temperature monitoring and relates to data analysis technology, and in particular to a temperature monitoring system for electric power equipment based on a platinum thermal resistor temperature sensor. Background Art

[0002] The power equipment temperature monitoring system can monitor the temperature of power equipment in real time and accurately, detect abnormal conditions in time, avoid equipment failures, and improve the operating efficiency and safety of power equipment. At the same time, the system can also provide rich data analysis functions to help managers better understand the operating status of the equipment and optimize the equipment maintenance strategy.

[0003] However, the temperature monitoring system for power equipment in the prior art still has the following defects: different components of the power equipment have different temperature performance characteristics when they fail, and the use of conventional thermistor temperature sensors cannot monitor the temperature anomalies of all components of the power equipment, which leads to low accuracy of the monitoring results of the traditional temperature monitoring system. When components with flat temperature performance cause power equipment operation failures, there is often a serious delay in the warning trigger time.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a power equipment temperature monitoring system based on a platinum thermal resistor temperature sensor, which is used to solve the problem that the power equipment temperature monitoring system in the prior art cannot use different monitoring methods to monitor the temperature of components with different temperature performance characteristics;

[0006] The technical problem to be solved by the present invention is: how to provide a temperature monitoring system for electric equipment based on platinum thermal resistor temperature sensors which can monitor the temperature of components with different temperature performance characteristics using different monitoring methods.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The temperature monitoring system of electric power equipment based on platinum thermal resistance temperature sensor comprises a temperature monitoring platform, wherein the temperature monitoring platform is communicatively connected with a feature analysis module, a data processing module, a combined monitoring module and a storage module;

[0009] The characteristic analysis module is used to analyze the fault temperature characteristics of the power equipment: mark each component of the power equipment as a monitoring object, set a thermistor sensor on the monitoring object, and when the power equipment fails, mark L1 seconds before the fault warning moment as a fault warning process, mark all historical fault warning processes of the power equipment as analysis processes, and mark the monitoring object as a clear object or a fuzzy object through the analysis process; and install a platinum thermistor temperature sensor for the fuzzy object;

[0010] The data processing module is used to process and analyze the temperature data of the historical fault warning process: the appearance values ​​of the monitored object in all analysis processes constitute an appearance set, the variance of the appearance set is calculated to obtain the concentration coefficient of the appearance set, the processing object is marked by the concentration coefficient, and the temperature data of the processing object in the analysis process is processed to obtain a standard curve;

[0011] The combined monitoring module is used to perform combined analysis on the various monitoring objects of the power equipment: the monitoring objects of the power equipment are grouped according to the line transmission path of the power equipment to obtain several monitoring combinations; if the monitoring combination contains fuzzy objects, the fuzzy monitoring method is used to perform temperature monitoring on the monitoring combination; if the monitoring combination does not contain fuzzy objects, the clear monitoring method is used to perform temperature monitoring on the monitoring combination.

[0012] As a preferred embodiment of the present invention, the specific process of marking a monitored object as a clear object or a fuzzy object includes: obtaining the maximum output temperature and the minimum output temperature of the thermistor sensor of the monitored object during the analysis process, marking the difference between the maximum output temperature and the minimum output temperature as the appearance value of the analysis process, summing and averaging the appearance values ​​of the monitored object in all analysis processes to obtain the appearance coefficient of the monitored object, obtaining the appearance threshold through the storage module, and comparing the appearance coefficient of the monitored object with the appearance threshold: if the appearance coefficient is less than the appearance threshold, the fault temperature feature of the monitored object is marked as fuzzy, and the corresponding monitored object is marked as a fuzzy object; if the appearance coefficient is greater than or equal to the appearance temperature threshold, the fault temperature feature of the monitored object is marked as clear, and the corresponding monitored object is marked as a clear object.

[0013] As a preferred embodiment of the present invention, the specific process of marking the processing object includes: obtaining the concentration threshold through the storage module, and comparing the concentration coefficient with the concentration threshold: if the concentration coefficient is less than the concentration threshold, the maximum image value and the minimum image value in the image set constitute the warning range of the monitored object; if the concentration coefficient is greater than or equal to the concentration threshold, the maximum image value and the minimum image value in the image set are eliminated, and then the concentration coefficient of the image set is recalculated, and so on, until the concentration coefficient is less than the concentration threshold; the warning range of the fuzzy object is marked as the monitoring range, and the clear object whose image value is within the warning range is marked as the processing object.

[0014] As a preferred embodiment of the present invention, the process of obtaining the standard curve includes: dividing the fault warning process into several warning periods, obtaining the temperature value of the processing object at the end of the warning period, establishing a rectangular coordinate system with the duration of the fault warning process as the X-axis and the temperature value of the processing object as the Y-axis, and making several temperature broken lines of the processing object in the rectangular coordinate system. The process of drawing the temperature broken line includes: marking several warning points in the rectangular coordinate system with the end time of the warning period as the horizontal coordinate and the temperature value of the processing object as the vertical coordinate, and connecting the warning points from left to right in sequence to obtain a temperature broken line graph; summing up the slope values ​​of all temperature broken line graphs in the same warning period and taking the average value to obtain the standard value of the warning period, and then making a standard broken line in the rectangular coordinate system with point M1 as the starting point and the standard value of the warning period as the slope value, the horizontal coordinate of M1 is zero, and the vertical coordinate is the average value of the temperature value of the processing object at the beginning of all fault warning processes; smoothing the standard broken line to obtain a standard curve.

[0015] As a preferred embodiment of the present invention, the specific process of temperature monitoring the monitoring combination using a clear monitoring method includes: generating a monitoring cycle and dividing the monitoring cycle into a number of monitoring time periods, obtaining the temperature curve of the clear object in the monitoring combination during the monitoring time period, setting a number of comparison data groups on the X-axis of the coordinate system where the standard curve is located, each comparison data group includes two comparison data points, and the horizontal coordinate difference between the two comparison data points in each group is equal to the duration of the monitoring time period; moving the temperature curve to the rectangular coordinate system according to the comparison data points in the comparison data group, and taking the comparison data points as endpoints in the first A ray perpendicular to the X-axis is drawn in a quadrant and marked as an intercepted ray. The area value of the closed figure composed of the two intercepted rays, the temperature curve and the standard curve is marked as the comparison value of the comparison data group. The comparison threshold is obtained through the storage module. If the comparison values ​​of all comparison data groups are not less than the comparison threshold, it is determined that the temperature of the clear object during the monitoring period meets the requirements; otherwise, it is determined that the temperature of the clear object during the monitoring period does not meet the requirements, and a temperature warning signal is generated and sent to the temperature monitoring platform. After receiving the temperature warning signal, the temperature monitoring platform sends the temperature warning signal to the mobile phone terminal of the manager.

[0016] As a preferred embodiment of the present invention, the specific process of using a fuzzy detection method to monitor the temperature of the monitoring combination includes: generating a verification cycle and dividing the verification cycle into a number of verification time periods, the duration of the verification time period is equal to the duration of the monitoring time period, obtaining the temperature value of the fuzzy object in real time during the verification time period and comparing the temperature value with the monitoring range of the fuzzy object: if the temperature value is within the fuzzy range, it is determined that a fuzzy fault occurs in the fuzzy object, and a cleaning monitoring method is used to determine whether the temperature of the clear object in the monitoring combination meets the requirements. If so, it is determined that the fuzzy fault is established; if not, it is determined that the fuzzy fault is not established, and the monitoring range of the fuzzy object is numerically updated: the maximum value and minimum value of the monitoring range of the fuzzy object are marked as JCmin and JCmax respectively, and the formula JCx=t1*JCm is used. in and JCd=t2*JCmax to obtain the updated low value JCx and the updated high value JCd, where t1 and t2 are both proportional coefficients, and 1.05≤t1≤1.15, 0.85≤t2≤0.95; the maximum value and the minimum value of the monitoring range are replaced by the updated low value JCx and the updated high value JCd; after the verification cycle is completed, a monitoring cycle is generated and the monitoring cycle is divided into several monitoring time periods, and during the monitoring period, a clear monitoring method is used to perform temperature monitoring on the clear object, while the temperature value of the fuzzy object is obtained in real time. If the temperature value is within the warning range of the fuzzy object, it is determined that the monitoring combination has a fault, a fault warning signal is generated and the fault warning signal is sent to the temperature monitoring platform, and the temperature monitoring platform sends the fault warning signal to the mobile phone terminal of the manager after receiving the fault warning signal.

[0017] The present invention has the following beneficial effects:

[0018] 1. The characteristic analysis module can be used to analyze the fault temperature characteristics of power equipment, and the temperature data of each component of power equipment in the historical fault warning process can be statistically analyzed to obtain the appearance coefficient, so as to differentiate the temperature characteristics of the monitored object through the appearance coefficient, and add platinum thermal resistance temperature sensors to fuzzy objects to improve the accuracy of temperature monitoring results;

[0019] 2. The data processing module can process and analyze the temperature data of the historical fault warning process to obtain the warning range of the monitored object. At the same time, the warning range of the clear object can be processed graphically to obtain the standard curve. The temperature of the clear object can be monitored based on the standard curve to provide data support for the temperature monitoring combined analysis process;

[0020] 3. Through the combined monitoring module, the various monitoring objects of the power equipment can be combined for analysis, and different temperature monitoring methods can be used to monitor the temperature of the monitoring combination. The warning range of the fuzzy object can be optimized by verification analysis. The platinum resistance temperature sensor and fuzzy monitoring method can be combined to improve the temperature monitoring accuracy of power components with smooth temperature changes during faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0023] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] like Figure 1 As shown, the temperature monitoring system of electric power equipment based on platinum thermal resistor temperature sensor includes a temperature monitoring platform, and the temperature monitoring platform is communicatively connected with a feature analysis module, a data processing module, a combined monitoring module and a storage module.

[0025] The feature analysis module is used to analyze the fault temperature features of the power equipment: mark each component of the power equipment as a monitoring object, set a thermistor sensor on the monitoring object, and when the power equipment fails, mark L1 seconds before the fault warning moment as the fault warning process, mark all historical fault warning processes of the power equipment as the analysis process, obtain the maximum and minimum output temperature values ​​of the thermistor sensor of the monitoring object during the analysis process, mark the difference between the maximum and minimum output temperature values ​​as the representation value of the analysis process, sum and average the representation values ​​of the monitoring object in all analysis processes to obtain the representation coefficient of the monitoring object, obtain the representation threshold through the storage module, and store the monitoring object. The appearance coefficient of the image is compared with the appearance threshold: if the appearance coefficient is less than the appearance threshold, the fault temperature characteristic of the monitored object is marked as fuzzy, and the corresponding monitored object is marked as a fuzzy object; if the appearance coefficient is greater than or equal to the appearance temperature threshold, the fault temperature characteristic of the monitored object is marked as clear, and the corresponding monitored object is marked as a clear object; a platinum thermistor temperature sensor is installed for the fuzzy object; the fault temperature characteristics of the power equipment are analyzed, and the temperature data of each component of the power equipment in the historical fault warning process are statistically analyzed to obtain the appearance coefficient, so as to differentiate the temperature characteristics of the monitored object through the appearance coefficient, and a platinum thermistor temperature sensor is installed for the fuzzy object to improve the accuracy of the temperature monitoring results.

[0026] The data processing module is used to process and analyze the temperature data of the historical fault warning process: the appearance values ​​of the monitored object in all analysis processes constitute an appearance set, the variance of the appearance set is calculated to obtain the concentration coefficient of the appearance set, the concentration threshold is obtained through the storage module, and the concentration coefficient is compared with the concentration threshold: if the concentration coefficient is less than the concentration threshold, the maximum appearance value and the minimum appearance value in the appearance set constitute the warning range of the monitored object; if the concentration coefficient is greater than or equal to the concentration threshold, the maximum appearance value and the minimum appearance value in the appearance set are eliminated, and then the concentration coefficient of the appearance set is recalculated, and so on, until the concentration coefficient is less than the concentration threshold; the warning range of the fuzzy object is marked as the monitoring range, and the clear object whose appearance value is within the warning range is marked as the processing object, the fault warning process is divided into several warning periods, and the temperature value of the processing object at the end of the warning period is obtained, and the fault warning process is established with the duration of the fault warning process as the X-axis and the temperature value of the processing object as the Y-axis. A rectangular coordinate system is used. Several temperature broken lines are drawn for the processing object in the rectangular coordinate system. The drawing process of the temperature broken lines includes: marking several warning points in the rectangular coordinate system with the end time of the warning period as the horizontal coordinate and the temperature value of the processing object as the vertical coordinate, and connecting the warning points from left to right in sequence to obtain a temperature broken line graph; summing up the slope values ​​of all temperature broken line graphs in the same warning period and taking the average value to obtain the standard value of the warning period, and then drawing a standard broken line in the rectangular coordinate system with point M1 as the starting point and the standard value of the warning period as the slope value, wherein the horizontal coordinate of M1 is zero, and the vertical coordinate is the average value of the temperature value of the processing object at the beginning of all fault warning processes; smoothing the standard broken line to obtain a standard curve; processing and analyzing the temperature data of the historical fault warning process to obtain the warning range of the monitored object, and at the same time performing graphical processing on the warning range of the clear object to obtain the standard curve, and performing temperature monitoring on the clear object based on the standard curve to provide data support for the temperature monitoring combined analysis process.

[0027] The combined monitoring module is used to perform combined analysis on each monitoring object of the power equipment: the monitoring objects of the power equipment are grouped according to the line transmission path of the power equipment to obtain several monitoring combinations; if the monitoring combination contains fuzzy objects, the fuzzy monitoring method is used to perform temperature monitoring on the monitoring combination; if the monitoring combination does not contain fuzzy objects, the clear monitoring method is used to perform temperature monitoring on the monitoring combination; the specific process of using the clear monitoring method to perform temperature monitoring on the monitoring combination includes: generating a monitoring cycle and dividing the monitoring cycle into several monitoring time periods, obtaining the temperature curve of the clear object in the monitoring combination during the monitoring time period, setting several comparison data groups on the X-axis of the coordinate system where the standard curve is located, each comparison data group includes two comparison data points, and the horizontal coordinate difference of each group of two comparison data points is The values ​​are equal to the duration of the monitoring period; the temperature curve is moved to the rectangular coordinate system according to the comparison data points in the comparison data group, and a ray perpendicular to the X-axis is made in the first quadrant of the rectangular coordinate system with the comparison data point as the endpoint and marked as an intercepted ray, and the area value of the closed figure composed of the two intercepted rays, the temperature curve and the standard curve is marked as the comparison value of the comparison data group, and the comparison threshold is obtained through the storage module. If the comparison values ​​of all comparison data groups are not less than the comparison threshold, it is determined that the temperature of the clear object during the monitoring period meets the requirements; otherwise, it is determined that the temperature of the clear object during the monitoring period does not meet the requirements, and a temperature warning signal is generated and sent to the temperature monitoring platform. After receiving the temperature warning signal, the temperature monitoring platform sends the temperature warning signal to the mobile phone terminal of the manager.

[0028] The specific process of temperature monitoring the monitoring combination using the fuzzy detection method includes: generating a verification cycle and dividing the verification cycle into several verification time periods, the duration of the verification time period is equal to the duration of the monitoring time period, obtaining the temperature value of the fuzzy object in real time during the verification time period and comparing the temperature value with the monitoring range of the fuzzy object: if the temperature value is within the fuzzy range, it is determined that a fuzzy fault occurs in the fuzzy object, and a cleaning monitoring method is used to determine whether the temperature of the clear object in the monitoring combination meets the requirements. If so, it is determined that the fuzzy fault is established; if not, it is determined that the fuzzy fault is not established, and the monitoring range of the fuzzy object is numerically updated: the maximum and minimum values ​​of the monitoring range of the fuzzy object are marked as JCmin and JCmax respectively, and the updated low value JCx and the updated high value JCd are obtained by the formula JCx=t1*JCmin and JCd=t2*JCmax, where t1 and t2 are both proportional coefficients, and 1.05≤t1≤1.15 , 0.85≤t2≤0.95; the maximum value and the minimum value of the monitoring range are replaced by the updated low value JCx and the updated high value JCd; after the verification cycle is over, a monitoring cycle is generated and divided into several monitoring periods, and during the monitoring period, a clear monitoring method is used to monitor the temperature of the clear object, and the temperature value of the fuzzy object is obtained in real time. If the temperature value is within the warning range of the fuzzy object, it is determined that the monitoring combination has a fault, and a fault warning signal is generated and sent to the temperature monitoring platform. After receiving the fault warning signal, the temperature monitoring platform sends the fault warning signal to the mobile phone terminal of the manager; a combination analysis is performed on each monitoring object of the power equipment, and different temperature monitoring methods are used to monitor the temperature of the monitoring combination. The warning range of the fuzzy object is optimized by verification analysis, and the temperature monitoring accuracy of the power components with smooth temperature changes during faults is improved by combining the platinum thermal resistance temperature sensor and the fuzzy monitoring method.

[0029] The power equipment temperature monitoring system based on platinum thermal resistor temperature sensor analyzes the fault temperature characteristics of the power equipment and marks each component of the power equipment as a clear object or a fuzzy object when working, and processes and analyzes the temperature data of the historical fault warning process: the appearance value of the monitored object in all analysis processes constitutes an appearance set, the variance of the appearance set is calculated to obtain the concentration coefficient of the appearance set, the processing object is marked by the value of the concentration coefficient, and the standard curve of the processing object is obtained; the fuzzy monitoring method or the clear monitoring method is used to perform temperature monitoring and analysis on the monitoring combination.

[0030] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0031] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0032] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The power equipment temperature monitoring system based on platinum thermal resistance temperature sensor is characterized by: It includes a temperature monitoring platform, which is communicatively connected with a feature analysis module, a data processing module, a combined monitoring module and a storage module; The characteristic analysis module is used to analyze the fault temperature characteristics of the power equipment: mark each component of the power equipment as a monitoring object, set a thermistor sensor on the monitoring object, and when the power equipment fails, mark L1 seconds before the fault warning moment as a fault warning process, mark all historical fault warning processes of the power equipment as analysis processes, and mark the monitoring object as a clear object or a fuzzy object through the analysis process; and install a platinum thermistor temperature sensor for the fuzzy object; The data processing module is used to process and analyze the temperature data of the historical fault warning process: the appearance values ​​of the monitored object in all analysis processes constitute an appearance set, the variance of the appearance set is calculated to obtain the concentration coefficient of the appearance set, the processing object is marked by the concentration coefficient, and the temperature data of the processing object in the analysis process is processed to obtain a standard curve; The combined monitoring module is used to perform combined analysis on each monitoring object of the power equipment: the monitoring objects of the power equipment are grouped according to the line transmission path of the power equipment to obtain a number of monitoring combinations; if the monitoring combination contains a fuzzy object, the temperature of the monitoring combination is monitored using a fuzzy monitoring method; if the monitoring combination does not contain a fuzzy object, the temperature of the monitoring combination is monitored using a clear monitoring method; The specific process of marking the monitored object as a clear object or a fuzzy object includes: obtaining the maximum value and the minimum value of the output temperature of the thermistor sensor of the monitored object during the analysis process, marking the difference between the maximum value and the minimum value of the output temperature as the appearance value of the analysis process, summing and averaging the appearance values ​​of the monitored object in all analysis processes to obtain the appearance coefficient of the monitored object, obtaining the appearance threshold through the storage module, and comparing the appearance coefficient of the monitored object with the appearance threshold: if the appearance coefficient is less than the appearance threshold, the fault temperature feature of the monitored object is marked as fuzzy, and the corresponding monitored object is marked as a fuzzy object; if the appearance coefficient is greater than or equal to the appearance temperature threshold, the fault temperature feature of the monitored object is marked as clear, and the corresponding monitored object is marked as a clear object; The specific process of marking the processing object includes: obtaining the concentration threshold through the storage module, comparing the concentration coefficient with the concentration threshold: if the concentration coefficient is less than the concentration threshold, the maximum image value and the minimum image value in the image set constitute the warning range of the monitoring object; if the concentration coefficient is greater than or equal to the concentration threshold, the maximum image value and the minimum image value in the image set are eliminated, and then the concentration coefficient of the image set is recalculated, and so on, until the concentration coefficient is less than the concentration threshold; the warning range of the fuzzy object is marked as the monitoring range, and the clear object whose image value is within the warning range is marked as the processing object; The specific process of temperature monitoring the monitoring combination using the clear monitoring method includes: generating a monitoring cycle and dividing the monitoring cycle into several monitoring time periods, obtaining the temperature curve of the clear object in the monitoring combination during the monitoring time period, setting several comparison data groups on the X-axis of the coordinate system where the standard curve is located, each comparison data group includes two comparison data points, and the horizontal coordinate difference between the two comparison data points in each group is equal to the duration of the monitoring time period; moving the temperature curve according to the comparison data points in the comparison data group to the rectangular coordinate system, and making a vertical curve in the first quadrant of the rectangular coordinate system with the comparison data points as endpoints. The rays perpendicular to the X-axis are marked as intercepted rays, and the area value of the closed figure composed of the two intercepted rays, the temperature curve and the standard curve is marked as the comparison value of the comparison data group. The comparison threshold is obtained through the storage module. If the comparison values ​​of all comparison data groups are not less than the comparison threshold, it is determined that the temperature of the clear object during the monitoring period meets the requirements; otherwise, it is determined that the temperature of the clear object during the monitoring period does not meet the requirements, and a temperature warning signal is generated and sent to the temperature monitoring platform. After receiving the temperature warning signal, the temperature monitoring platform sends the temperature warning signal to the mobile phone terminal of the manager; The specific process of using the fuzzy detection method to monitor the temperature of the monitoring combination includes: generating a verification cycle and dividing the verification cycle into several verification time periods, the duration of the verification time period is equal to the duration of the monitoring time period, obtaining the temperature value of the fuzzy object in real time during the verification time period and comparing the temperature value with the monitoring range of the fuzzy object: if the temperature value is within the fuzzy range, it is determined that a fuzzy fault occurs in the fuzzy object, and a cleaning monitoring method is used to determine whether the temperature of the clear object in the monitoring combination meets the requirements. If so, it is determined that the fuzzy fault is established; if not, it is determined that the fuzzy fault is not established, and the monitoring range of the fuzzy object is numerically updated: the maximum and minimum values ​​of the monitoring range of the fuzzy object are marked as JCmin and JCmax respectively, and the formulas JCx=t1*JCmin and JCd=t 2*JCmax obtains the updated low value JCx and the updated high value JCd, where t1 and t2 are both proportional coefficients, and 1.05≤t1≤1.15, 0.85≤t2≤0.95; the maximum and minimum values ​​of the monitoring range are replaced by the updated low value JCx and the updated high value JCd; after the verification cycle is completed, a monitoring cycle is generated and the monitoring cycle is divided into several monitoring periods, and during the monitoring period, a clear monitoring method is used to monitor the temperature of the clear object, while the temperature value of the fuzzy object is obtained in real time. If the temperature value is within the warning range of the fuzzy object, it is determined that the monitoring combination has a fault, a fault warning signal is generated and sent to the temperature monitoring platform, and the temperature monitoring platform sends the fault warning signal to the mobile phone terminal of the manager after receiving the fault warning signal.

2. The power equipment temperature monitoring system based on platinum thermal resistance temperature sensor according to claim 1 is characterized in that: The process of obtaining the standard curve includes: dividing the fault warning process into several warning periods, obtaining the temperature value of the processing object at the end of the warning period, establishing a rectangular coordinate system with the duration of the fault warning process as the X-axis and the temperature value of the processing object as the Y-axis, and making several temperature broken lines of the processing object in the rectangular coordinate system. The process of drawing the temperature broken line includes: marking several warning points in the rectangular coordinate system with the end time of the warning period as the horizontal coordinate and the temperature value of the processing object as the vertical coordinate, connecting the warning points from left to right in sequence to obtain a temperature broken line graph; summing up the slope values ​​of all temperature broken line graphs in the same warning period and taking the average value to obtain the standard value of the warning period, and then making a standard broken line in the rectangular coordinate system with point M1 as the starting point and the standard value of the warning period as the slope value, the horizontal coordinate of M1 is zero, and the vertical coordinate is the average value of the temperature value of the processing object at the beginning of all fault warning processes; smoothing the standard broken line to obtain the standard curve.

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