Operation control system for industrial frequency transformer

Abstract

The invention belongs to the field of industrial frequency transformers, relates to an operation control technology, and aims to solve the problem that an operation control system of an industrial frequency transformer in the prior art cannot predict an operation fault of the transformer in combination with historical operation data, in particular to an operation control system for the industrial frequency transformer, which comprises an operation control platform, the operation control platform is in communication connection with an operation monitoring module, a fault analysis module, a fault prediction module, a maintenance analysis module and a storage module; the operation monitoring module is used for monitoring and analyzing the operation state of the industrial frequency transformer: marking the industrial frequency transformer as a monitoring object, performing statistics on continuous operation duration when the monitoring object operates, and performing continuous operation early warning when the continuous operation duration reaches an operation duration threshold value; according to the invention, the operation state of the industrial frequency transformer can be monitored and analyzed, the operation state of the industrial frequency transformer can be fed back through the monitoring coefficient, and an alarm can be given in time when an abnormity occurs.

Description

Technical Field

[0001] The invention belongs to the field of power frequency transformers, relates to operation control technology, and specifically is an operation control system for power frequency transformers. Background Art

[0002] The industrial frequency transformer is also called a low-frequency transformer to distinguish it from the high-frequency transformer used in switching power supplies. Industrial frequency transformers were widely used in traditional power supplies in the past, and the stability of these power supplies was achieved through linear regulation, so those traditional power supplies were also called linear power supplies.

[0003] In the prior art, the operation control system of the power frequency transformer can generally only monitor the operating status of the transformer and issue an alarm when a fault occurs, but it cannot predict the operating fault of the transformer in combination with historical operation data, resulting in the inability to control the probability of fault occurrence.

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

[0005] The object of the present invention is to provide an operation control system for an industrial frequency transformer, which is used to solve the problem that the operation control system of the industrial frequency transformer in the prior art cannot predict the operation fault of the transformer in combination with historical operation data;

[0006] The technical problem to be solved by the present invention is: how to provide an operation control system for an industrial frequency transformer which can predict the operation faults of the transformer in combination with historical operation data.

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

[0008] An operation control system for an industrial frequency transformer, comprising an operation control platform, wherein the operation control platform is communicatively connected with an operation monitoring module, a fault analysis module, a fault prediction module, a maintenance analysis module and a storage module;

[0009] The operation monitoring module is used to monitor and analyze the operation status of the power frequency transformer: mark the power frequency transformer as a monitoring object, count the continuous operation time when the monitoring object is running, and issue a continuous operation warning when the continuous operation time reaches the operation time threshold YSmax; obtain the monitoring coefficient JC of the monitoring object in real time during the operation process; use the monitoring coefficient JC to determine whether the operation status of the monitoring object meets the requirements, and generate a fault analysis signal if it does not meet the requirements and send the fault analysis signal to the fault analysis module through the operation control platform;

[0010] The fault analysis module is used to identify and analyze the operation faults of the power frequency transformer: the difference between the time when the fault analysis signal is received and the time when the monitored object starts to run is marked as the continuous operation time, the operation time threshold YSmax is obtained through the storage module, and the time monitoring value SJ is obtained through the formula SJ=t1*YSmax, where t1 is the proportionality coefficient, and 0.85≤t1≤0.95; the continuous operation time is compared with the time monitoring value SJ, and the comparison result is used to determine whether the monitored object has an operation fault;

[0011] The fault prediction module is used to predict and analyze the operation faults of the power frequency transformer: the number of fault curves received by the storage module is marked as a fault value, and when the fault value is not less than L1, a fault prediction analysis is performed on the operation process of the monitored object;

[0012] The fault analysis module is used to identify and analyze operating faults of the power frequency transformer.

[0013] Furthermore, the process of obtaining the monitoring coefficient JC of the monitored object includes: obtaining impedance data ZK, load data FZ and surface temperature data BW, the impedance data ZK is the impedance voltage value when the monitored object is running, the load data FZ is the load current value when the monitored object is running, and the surface temperature data BW is the surface temperature value when the monitored object is running; the monitoring coefficient JC of the monitored object is obtained by the formula JC=k1*ZK+k2*FZ+k3*BW, wherein k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1.

[0014] Furthermore, the specific process of determining whether the operating status of the monitored object meets the requirements includes: obtaining the monitoring threshold JCmax through the storage module, and comparing the monitoring coefficient JC with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, it is determined that the operating status of the monitored object meets the requirements; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, it is determined that the operating status of the monitored object does not meet the requirements.

[0015] Furthermore, the specific process of comparing the continuous operating time with the duration monitoring value SJ includes: if the continuous operating time is less than the duration monitoring value SJ, it is determined that the monitored object has an operating fault, and a rectangular coordinate system is established with the continuous operating time of the monitored object during operation as the X-axis and the monitoring coefficient JC as the Y-axis. A monitoring curve of the monitored object is drawn in the rectangular coordinate system according to the monitoring coefficient JC and the continuous operating time and marked as a fault curve, and the fault curve is sent to the storage module for storage; if the continuous operating time is greater than or equal to the duration monitoring value SJ, it is determined that the monitored object does not have an operating fault, a maintenance demand signal is generated, and the maintenance demand signal is sent to the maintenance analysis module through the operation control platform.

[0016] Furthermore, the specific process of performing fault prediction analysis on the operation process of the monitored object includes: calling all fault curves in the storage module, marking the horizontal coordinate of the termination point of the fault curve as the termination value, arranging the fault curve in order from small to large according to the termination value to obtain a termination sequence, counting the continuous operation time when the monitored object is running and drawing the monitoring curve, obtaining the fault coincidence value of the monitored object when the continuous operation time reaches the termination value of the fault curve of the termination sequence, obtaining the fault coincidence threshold through the storage module, and comparing the fault coincidence value with the fault coincidence threshold: if the fault coincidence value is less than the fault coincidence threshold, a fault prediction signal is generated and the fault prediction signal is sent to the mobile terminal of the manager through the operation control platform; if the fault coincidence value is greater than or equal to the fault coincidence threshold, then when the continuous operation time of the monitored object reaches the termination value of the next fault curve of the termination sequence, the fault coincidence value analysis is performed again, and so on, until the continuous operation time of the monitored object reaches the operation time threshold YSmax, the monitoring coefficient JC is not less than the monitoring threshold JCmax, or the fault coincidence value is less than the fault coincidence threshold.

[0017] Furthermore, the process of obtaining the fault coincidence value of the monitored object includes: translating the corresponding fault curve to the rectangular coordinate system of the monitoring curve, connecting the end point of the fault curve with the end point of the monitoring curve, and then marking the sum of the area values ​​of all closed figures formed by the fault curve, the monitoring curve and the Y-axis as the fault coincidence value.

[0018] Furthermore, the specific process of the maintenance analysis module analyzing the necessity of maintenance of the power frequency transformer includes: generating an analysis cycle, obtaining the number of times the maintenance analysis module receives the maintenance analysis signal within the analysis cycle and marking it as the maintenance value WH, marking the number of operations of the monitored object within the analysis cycle as the operation value YX, and marking the number of fault curves received by the storage module within the analysis cycle as the fault value GZ; obtaining the necessary coefficient BY of the analysis cycle through the formula BY=(m1*GZ+m2*WH) / (m3*YX), wherein m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1; obtaining the necessary threshold BYmax through the storage module, and comparing the necessary coefficient BY of the analysis cycle with the necessary threshold BYmax: if the necessary coefficient BY is less than the necessary threshold BYmax, it is determined that the monitored object does not have the necessity of maintenance within the analysis cycle; if the necessary coefficient BY is greater than or equal to the necessary threshold BYmax, it is determined that the monitored object has the necessity of maintenance within the analysis cycle, generating a maintenance processing signal, and sending the maintenance processing signal to the mobile terminal of the manager through the operation control platform.

[0019] Furthermore, the working method of the operation control system for the power frequency transformer comprises the following steps:

[0020] Step 1: Monitor and analyze the operating status of the power frequency transformer: mark the power frequency transformer as the monitoring object, obtain the impedance data ZK, load data FZ and surface temperature data BW of the monitoring object in real time during operation, and perform numerical calculation to obtain the monitoring coefficient JC. Use the monitoring coefficient JC to determine whether the operating status of the monitoring object meets the requirements;

[0021] Step 2: Identify and analyze the operating fault of the power frequency transformer: mark the difference between the time when the fault analysis signal is received and the time when the monitored object starts to operate as the continuous operation time, and determine whether the monitored object has an operating fault based on the continuous operation time;

[0022] Step 3: Mark the number of fault curves received by the storage module as a fault value, and when the fault value is not less than L1, perform fault prediction analysis on the operation process of the monitored object;

[0023] Step 4: Analyze the necessity of maintenance of the power frequency transformer: generate an analysis cycle, obtain the necessary coefficient BY of the analysis cycle, and determine whether the monitored object has the necessity of maintenance within the analysis cycle through the necessary coefficient BY.

[0024] The present invention has the following beneficial effects:

[0025] 1. The operation monitoring module can monitor and analyze the operation status of the power frequency transformer. When the power frequency transformer is running, multiple operation data are collected and comprehensively analyzed and calculated to obtain the monitoring coefficient. The monitoring coefficient is used to provide feedback on the operation status of the power frequency transformer, and then an alarm is issued in time when an abnormality occurs;

[0026] 2. The fault analysis module can identify and analyze the operating faults of the power frequency transformer. It can evaluate whether the power frequency transformer has an operating fault based on the continuous operation time when the power frequency transformer has an abnormal operation. When it is determined that the power frequency transformer has an operating fault, the data characteristics of the operating fault are collected and stored to provide data support for the fault prediction and analysis process.

[0027] 3. The fault prediction module can predict and analyze the operation faults of the power frequency transformer. It can analyze the fault characteristics in the historical operation data of the power frequency transformer. When the continuous operation time of the monitored object reaches the analysis node, the fault prediction process is automatically triggered. The fault risk of the power frequency transformer continuing to operate is predicted by curve comparison to reduce its actual failure rate.

[0028] 4. The maintenance analysis module can be used to analyze the necessity of maintenance of the power frequency transformer, and the necessary coefficients can be obtained by statistics and calculation of multiple parameters within the analysis period. According to the necessary coefficients, feedback can be given on the necessity of maintenance of the monitored object within the analysis period, and the power frequency transformer can be operated and maintained at the appropriate time to improve the utilization rate of equipment maintenance resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] 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.

[0030] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0031] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] Embodiment 1

[0034] like Figure 1 As shown, an operation control system for an industrial frequency transformer includes an operation control platform, and the operation control platform is communicatively connected with an operation monitoring module, a fault analysis module, a fault prediction module, a maintenance analysis module and a storage module.

[0035] The operation monitoring module is used to monitor and analyze the operation status of the power frequency transformer: mark the power frequency transformer as the monitoring object, count the continuous operation time when the monitoring object is running, and issue a continuous operation warning when the continuous operation time reaches the operation time threshold YSmax; obtain the impedance data ZK, load data FZ and surface temperature data BW of the monitoring object in real time during the operation process, the impedance data ZK is the impedance voltage value when the monitoring object is running, the load data FZ is the load current value when the monitoring object is running, and the surface temperature data BW is the surface temperature value when the monitoring object is running; the monitoring coefficient JC of the monitoring object is obtained by the formula JC=k1*ZK+k2*FZ+k3*BW, where k1, k2 and k3 are Proportional coefficient, and k1>k2>k3>1; obtain the monitoring threshold JCmax through the storage module, and compare the monitoring coefficient JC with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, it is determined that the operating state of the monitored object meets the requirements; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, it is determined that the operating state of the monitored object does not meet the requirements, and a fault analysis signal is generated and sent to the fault analysis module through the operation control platform; when the power frequency transformer is running, a number of operating data are collected and comprehensively analyzed and calculated to obtain the monitoring coefficient, and the operating state of the power frequency transformer is fed back through the monitoring coefficient, so as to promptly alarm when an abnormality occurs.

[0036] The fault analysis module is used to identify and analyze the operation faults of the power frequency transformer: the difference between the time when the fault analysis signal is received and the time when the monitored object starts to run is marked as the continuous operation time, the operation time threshold YSmax is obtained through the storage module, and the time monitoring value SJ is obtained through the formula SJ=t1*YSmax, where t1 is the proportional coefficient, and 0.85≤t1≤0.95; the continuous operation time is compared with the time monitoring value SJ: if the continuous operation time is less than the time monitoring value SJ, it is determined that the monitored object has an operation fault, and a right angle is established with the continuous operation time of the monitored object during operation as the X-axis and the monitoring coefficient JC as the Y-axis. Coordinate system, draw the monitoring curve of the monitored object in the rectangular coordinate system according to the monitoring coefficient JC and the continuous operation time and mark it as the fault curve, and send the fault curve to the storage module for storage; if the continuous operation time is greater than or equal to the time monitoring value SJ, it is determined that there is no operation fault in the monitored object, generate a maintenance demand signal and send the maintenance demand signal to the maintenance analysis module through the operation control platform; evaluate whether the power frequency transformer has an operation fault according to the continuous operation time when the power frequency transformer has an operation abnormality, and collect and store the data characteristics of the operation fault when it is determined that the power frequency transformer has an operation fault, so as to provide data support for the fault prediction and analysis process.

[0037] The fault prediction module is used to predict and analyze the operation faults of the power frequency transformer: the number of fault curves received by the storage module is marked as the fault value, and when the fault value is not less than L1, the operation process of the monitored object is predicted and analyzed: all fault curves in the storage module are retrieved, the horizontal coordinate of the termination point of the fault curve is marked as the termination value, and the fault curves are arranged in order from small to large according to the termination value to obtain a termination sequence. When the monitored object is running, the continuous operation time is counted and the monitoring curve is drawn. When the continuous operation time reaches the termination value of the fault curve ranked first in the termination sequence, the corresponding fault curve is translated to the rectangular coordinate system of the monitoring curve, the termination point of the fault curve is connected with the termination point of the monitoring curve, and then the sum of the area values ​​of all closed figures composed of the fault curve, the monitoring curve and the Y-axis is marked as the fault coincidence value, and the fault coincidence value is obtained through the storage module. The fault coincidence value is compared with the fault coincidence threshold: if the fault coincidence value is less than the fault coincidence threshold, a fault prediction signal is generated and sent to the mobile terminal of the manager through the operation control platform; if the fault coincidence value is greater than or equal to the fault coincidence threshold, then when the continuous operation time of the monitored object reaches the termination value of the next fault curve of the termination sequence, the fault coincidence value analysis is performed again, and so on, until the continuous operation time of the monitored object reaches the operation time threshold YSmax, the monitoring coefficient JC is not less than the monitoring threshold JCmax or the fault coincidence value is less than the fault coincidence threshold; combined with the fault characteristics in the historical operation data of the power frequency transformer, the fault prediction process is automatically triggered when the continuous operation time of the monitored object reaches the analysis node, and the fault risk of the continued operation of the power frequency transformer is predicted by curve comparison to reduce its actual failure rate.

[0038] The maintenance analysis module is used to analyze the necessity of maintenance of the power frequency transformer: generate an analysis cycle, obtain the number of times the maintenance analysis module receives the maintenance analysis signal within the analysis cycle and mark it as the maintenance value WH, mark the number of operations of the monitored object within the analysis cycle as the operation value YX, and mark the number of fault curves received by the storage module within the analysis cycle as the fault value GZ; obtain the necessary coefficient BY of the analysis cycle through the formula BY = (m1*GZ+m2*WH) / (m3*YX), where m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1; obtain the necessary threshold BYmax through the storage module, and convert the necessary coefficient of the analysis cycle into BY is compared with the necessary threshold BYmax: if the necessary coefficient BY is less than the necessary threshold BYmax, it is determined that the monitored object does not need maintenance within the analysis period; if the necessary coefficient BY is greater than or equal to the necessary threshold BYmax, it is determined that the monitored object needs maintenance within the analysis period, and a maintenance processing signal is generated and sent to the mobile terminal of the manager through the operation control platform; multiple parameters within the analysis period are statistically calculated and the necessary coefficient is obtained, and the maintenance necessity of the monitored object within the analysis period is fed back according to the necessary coefficient, and the power frequency transformer is operated and maintained at an appropriate time to improve the utilization rate of equipment maintenance resources.

[0039] Embodiment 2

[0040] like Figure 2 As shown, an operation control method for an industrial frequency transformer comprises the following steps:

[0041] Step 1: Monitor and analyze the operating status of the power frequency transformer: mark the power frequency transformer as the monitoring object, obtain the impedance data ZK, load data FZ and surface temperature data BW of the monitoring object in real time during operation, and perform numerical calculation to obtain the monitoring coefficient JC. Use the monitoring coefficient JC to determine whether the operating status of the monitoring object meets the requirements;

[0042] Step 2: Identify and analyze the operating fault of the power frequency transformer: mark the difference between the time when the fault analysis signal is received and the time when the monitored object starts to operate as the continuous operation time, and determine whether the monitored object has an operating fault based on the continuous operation time;

[0043] Step 3: Mark the number of fault curves received by the storage module as a fault value, and when the fault value is not less than L1, perform fault prediction analysis on the operation process of the monitored object;

[0044] Step 4: Analyze the necessity of maintenance of the power frequency transformer: generate an analysis cycle, obtain the necessary coefficient BY of the analysis cycle, and determine whether the monitored object has the necessity of maintenance within the analysis cycle through the necessary coefficient BY.

[0045] An operation control system for an industrial frequency transformer, when working, marks the industrial frequency transformer as a monitoring object, obtains impedance data ZK, load data FZ and surface temperature data BW of the monitoring object in real time during operation, performs numerical calculation to obtain a monitoring coefficient JC, and determines whether the operation state of the monitoring object meets the requirements through the monitoring coefficient JC; marks the difference between the time when a fault analysis signal is received and the time when the monitoring object starts to operate as the continuous operation time, and determines whether the monitoring object has an operation fault through the continuous operation time; marks the number of fault curves received by a storage module as a fault value, and performs fault prediction analysis on the operation process of the monitoring object when the fault value is not less than L1; generates an analysis cycle, obtains a necessary coefficient BY of the analysis cycle, and determines whether the monitoring object has the necessity of maintenance within the analysis cycle through the necessary coefficient BY.

[0046] 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.

[0047] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; such as: formula JC = k1*ZK+k2*FZ+k3*BW; technicians in this field collect multiple groups of sample data and set corresponding monitoring coefficients for each group of sample data; substitute the set monitoring coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of k1, k2 and k3 as 3.48, 2.65 and 2.13 respectively;

[0048] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding monitoring coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the monitoring coefficient is proportional to the value of the impedance data.

[0049] 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.

[0050] 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. An operation control system for an industrial frequency transformer, characterized in that: It includes an operation control platform, which is communicatively connected with an operation monitoring module, a fault analysis module, a fault prediction module, a maintenance analysis module and a storage module; The operation monitoring module is used to monitor and analyze the operation status of the power frequency transformer: mark the power frequency transformer as a monitoring object, count the continuous operation time when the monitoring object is running, and issue a continuous operation warning when the continuous operation time reaches the operation time threshold YSmax; Obtain the monitoring coefficient JC of the monitored object in real time during operation; Whether the operating status of the monitored object meets the requirements is determined by monitoring coefficient JC. If the requirements are not met, a fault analysis signal is generated and sent to the fault analysis module through the operation control platform; The fault analysis module is used to identify and analyze the operation faults of the power frequency transformer: the difference between the time when the fault analysis signal is received and the time when the monitored object starts to run is marked as the continuous operation time, the operation time threshold YSmax is obtained through the storage module, and the time monitoring value SJ is obtained through the formula SJ=t1*YSmax, where t1 is the proportionality coefficient, and 0.85≤t1≤0.95; the continuous operation time is compared with the time monitoring value SJ, and the comparison result is used to determine whether the monitored object has an operation fault; The fault prediction module is used to predict and analyze the operation faults of the power frequency transformer: the number of fault curves received by the storage module is marked as a fault value, and when the fault value is not less than L1, a fault prediction analysis is performed on the operation process of the monitored object; The fault analysis module is used to identify and analyze operating faults of the power frequency transformer.

2. The operation control system for an industrial frequency transformer according to claim 1, characterized in that: The process of obtaining the monitoring coefficient JC of the monitored object includes: obtaining impedance data ZK, load data FZ and surface temperature data BW, where the impedance data ZK is the impedance voltage value when the monitored object is running, the load data FZ is the load current value when the monitored object is running, and the surface temperature data BW is the surface temperature value when the monitored object is running; the monitoring coefficient JC of the monitored object is obtained by the formula JC=k1*ZK+k2*FZ+k3*BW, wherein k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1.

3. The operation control system for an industrial frequency transformer according to claim 2, characterized in that: The specific process of determining whether the operating status of the monitored object meets the requirements includes: obtaining the monitoring threshold JCmax through the storage module, and comparing the monitoring coefficient JC with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, it is determined that the operating status of the monitored object meets the requirements; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, it is determined that the operating status of the monitored object does not meet the requirements.

4. The operation control system for an industrial frequency transformer according to claim 3, characterized in that: The specific process of comparing the continuous operating time with the duration monitoring value SJ includes: if the continuous operating time is less than the duration monitoring value SJ, it is determined that the monitored object has an operating fault, a rectangular coordinate system is established with the continuous operating time of the monitored object during operation as the X-axis and the monitoring coefficient JC as the Y-axis, a monitoring curve of the monitored object is drawn in the rectangular coordinate system according to the monitoring coefficient JC and the continuous operating time and marked as a fault curve, and the fault curve is sent to the storage module for storage; if the continuous operating time is greater than or equal to the duration monitoring value SJ, it is determined that the monitored object does not have an operating fault, a maintenance demand signal is generated and the maintenance demand signal is sent to the maintenance analysis module through the operation control platform.

5. The operation control system for an industrial frequency transformer according to claim 4, characterized in that: The specific process of performing fault prediction analysis on the operation process of the monitored object includes: calling all fault curves in the storage module, marking the horizontal coordinate of the termination point of the fault curve as the termination value, arranging the fault curve in order from small to large according to the termination value to obtain a termination sequence, counting the continuous operation time when the monitored object is running and drawing the monitoring curve, obtaining the fault coincidence value of the monitored object when the continuous operation time reaches the termination value of the fault curve of the termination sequence, obtaining the fault coincidence threshold through the storage module, and comparing the fault coincidence value with the fault coincidence threshold: if the fault coincidence value is less than the fault coincidence threshold, a fault prediction signal is generated and sent to the mobile terminal of the manager through the operation control platform; if the fault coincidence value is greater than or equal to the fault coincidence threshold, then when the continuous operation time of the monitored object reaches the termination value of the next fault curve of the termination sequence, the fault coincidence value analysis is performed again, and so on, until the continuous operation time of the monitored object reaches the operation time threshold YSmax, the monitoring coefficient JC is not less than the monitoring threshold JCmax, or the fault coincidence value is less than the fault coincidence threshold.

6. The operation control system for an industrial frequency transformer according to claim 5, characterized in that: The process of obtaining the fault coincidence value of the monitored object includes: translating the corresponding fault curve to the rectangular coordinate system of the monitoring curve, connecting the end point of the fault curve with the end point of the monitoring curve, and then marking the sum of the area values ​​of all closed figures formed by the fault curve, the monitoring curve and the Y-axis as the fault coincidence value.

7. The operation control system for an industrial frequency transformer according to claim 6, characterized in that: The specific process of the maintenance analysis module analyzing the necessity of maintenance of the power frequency transformer includes: generating an analysis cycle, obtaining the number of times the maintenance analysis module receives the maintenance analysis signal within the analysis cycle and marking it as the maintenance value WH, marking the number of operations of the monitored object within the analysis cycle as the operation value YX, and marking the number of fault curves received by the storage module within the analysis cycle as the fault value GZ; obtaining the necessary coefficient BY of the analysis cycle through the formula BY=(m1*GZ+m2*WH) / (m3*YX), wherein m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1; obtaining the necessary threshold BYmax through the storage module, and comparing the necessary coefficient BY of the analysis cycle with the necessary threshold BYmax: if the necessary coefficient BY is less than the necessary threshold BYmax, it is determined that the monitored object does not have the necessity of maintenance within the analysis cycle; if the necessary coefficient BY is greater than or equal to the necessary threshold BYmax, it is determined that the monitored object has the necessity of maintenance within the analysis cycle, generating a maintenance processing signal, and sending the maintenance processing signal to the mobile terminal of the manager through the operation control platform.

8. An operation control system for an industrial frequency transformer according to any one of claims 1 to 7, characterized in that: The working method of the operation control system for the power frequency transformer comprises the following steps: Step 1: Monitor and analyze the operating status of the power frequency transformer: mark the power frequency transformer as the monitoring object, obtain the impedance data ZK, load data FZ and surface temperature data BW of the monitoring object in real time during operation, and perform numerical calculation to obtain the monitoring coefficient JC. Use the monitoring coefficient JC to determine whether the operating status of the monitoring object meets the requirements; Step 2: Identify and analyze the operating fault of the power frequency transformer: mark the difference between the time when the fault analysis signal is received and the time when the monitored object starts to operate as the continuous operation time, and determine whether the monitored object has an operating fault based on the continuous operation time; Step 3: Mark the number of fault curves received by the storage module as a fault value, and when the fault value is not less than L1, perform fault prediction analysis on the operation process of the monitored object; Step 4: Analyze the necessity of maintenance of the power frequency transformer: generate an analysis cycle, obtain the necessary coefficient BY of the analysis cycle, and determine whether the monitored object has the necessity of maintenance within the analysis cycle through the necessary coefficient BY.

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