An operation control system for power frequency transformer

Abstract

The present invention belongs to the field of power frequency transformers and relates to operation control technology. It is used to solve the problem in the prior art that the operation control system of the power frequency transformer cannot predict the operation faults of the transformer in combination with historical operation data. Specifically, it is an operation control system for the power frequency transformer, including an operation control platform. The operation control platform is communicatively connected to 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: the power frequency transformer is marked as a monitoring object, the continuous operation time is counted when the monitoring object is running, and a continuous operation early warning is issued when the continuous operation time reaches an operation time threshold; the present invention can monitor and analyze the operation status of the power frequency transformer, and provide feedback on the operation status of the power frequency transformer through a monitoring coefficient, so as to promptly issue an alarm when an abnormality occurs.

Description

Technical Field

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

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

[0003] In the existing technology, 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 based on historical operation data, resulting in the inability to control the probability of fault occurrence.

[0004] In response to 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 a power frequency transformer, which is used to solve the problem in the prior art that the operation control system of the power frequency transformer cannot predict the operation fault of the transformer by combining 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 that can predict 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 a power frequency transformer, comprising an operation control platform, wherein the operation control platform is communicatively connected to 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 operating status of the power frequency transformer: mark the power frequency transformer as a monitoring object, count the continuous operating time when the monitoring object is running, and issue a continuous operation warning when the continuous operating time reaches the operating 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 operating status of the monitoring object meets the requirements, and if it does not meet the requirements, generate a fault analysis signal 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 fault 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 operate 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 by 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, and the comparison result is used to determine whether the monitored object has an operation fault;

[0011] The fault prediction module is used to perform a prediction analysis on the operation fault 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, 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, where 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 end 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 value 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, generating a fault prediction signal and sending the fault prediction signal to the mobile phone 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 in the termination sequence, performing fault coincidence value analysis 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 maintenance analysis signals within the analysis cycle and marking it as a maintenance value WH, marking the number of times the monitored object operates within the analysis cycle as an operation value YX, and marking the number of fault curves received by the storage module within the analysis cycle as a fault value GZ; obtaining 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; 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 need 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 needs maintenance within the analysis cycle, generating a maintenance processing signal, and sending the maintenance processing signal to the administrator's mobile terminal through the operation control platform.

[0019] Furthermore, the working method of the operation control system for the power frequency transformer includes 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 calculations to obtain the monitoring coefficient JC. The monitoring coefficient JC is used 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: the difference between the time when the fault analysis signal is received and the time when the monitored object starts to operate is marked as the continuous operation time, and the continuous operation time is used to determine whether the monitored object has an operating fault;

[0022] Step 3: Mark the number of fault curves received by the storage module as a fault value. 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 use the necessary coefficient BY to determine whether the monitored object has the necessity of maintenance within the analysis cycle.

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

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

[0026] 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 the power frequency transformer is identified as having 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] The fault prediction module can predict and analyze the operating faults of the power frequency transformer. It combines the fault characteristics in the historical operating data of the power frequency transformer to analyze the fault characteristics. 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, thereby reducing its actual failure rate.

[0028] 4. The maintenance analysis module can be used to analyze the necessity of maintenance of the power frequency transformer. The necessary coefficients can be obtained by statistics and calculation of multiple parameters within the analysis period. Based on the necessary coefficients, feedback can be given on the necessity of maintenance of the monitored object within the analysis period. 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 following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0030] Figure 1 This 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 solutions of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0033] Example 1: Figure 1 As shown, an operation control system for an industrial frequency transformer includes an operation control platform, which is communicatively connected to an operation monitoring module, a fault analysis module, a fault prediction module, a maintenance analysis module, and a storage module.

[0034] The operation monitoring module is used to monitor and analyze the operation status of the power frequency transformer: the power frequency transformer is marked as the monitoring object, the continuous operation time is counted when the monitoring object is running, and a continuous operation warning is issued when the continuous operation time reaches the operation time threshold YSmax; the impedance data ZK, load data FZ and surface temperature data BW of the monitoring object are obtained 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 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, 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, multiple operating data are collected and comprehensively analyzed and calculated to obtain the monitoring coefficient, and the monitoring coefficient is used to provide feedback on the operating status of the power frequency transformer, so that an alarm is issued in time when an abnormality occurs.

[0035] 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 based on 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.

[0036] 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: all fault curves in the storage module are retrieved, the horizontal coordinate of the end point of the fault curve is marked as the end value, and the fault curves are arranged in order from small to large according to the end 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 end 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, and the end point of the fault curve is connected with the end point of the monitoring curve. 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 manager's mobile terminal 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 power frequency transformer continuing to operate is predicted by curve comparison, thereby reducing its actual failure rate.

[0037] 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 during the analysis cycle and mark it as the maintenance value WH, mark the number of operations of the monitored object during the analysis cycle as the operation value YX, and mark the number of fault curves received by the storage module during 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 set the necessary coefficient of the analysis cycle 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 manager's mobile terminal through the operation control platform; multiple parameters within the analysis period are statistically calculated and the necessary coefficient is obtained, and the necessity of maintenance of the monitored object within the analysis period is fed back based on the necessary coefficient, and the power frequency transformer is operated and maintained at the appropriate time to improve the utilization rate of equipment maintenance resources.

[0038] Example 2: Figure 2 As shown, an operation control method for an industrial frequency transformer includes the following steps:

[0039] 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 calculations to obtain the monitoring coefficient JC. The monitoring coefficient JC is used to determine whether the operating status of the monitoring object meets the requirements;

[0040] Step 2: Identify and analyze the operating fault 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 operate is marked as the continuous operation time, and the continuous operation time is used to determine whether the monitored object has an operating fault;

[0041] Step 3: Mark the number of fault curves received by the storage module as a fault value. When the fault value is not less than L1, perform fault prediction analysis on the operation process of the monitored object.

[0042] 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 use the necessary coefficient BY to determine whether the monitored object has the necessity of maintenance within the analysis cycle.

[0043] An operation control system for an industrial frequency transformer, when in operation, marks the industrial frequency transformer as a monitoring object, obtains impedance data ZK, load data FZ, and surface temperature data BW of the monitored object in real time during operation, performs numerical calculation to obtain a monitoring coefficient JC, and uses the monitoring coefficient JC to determine whether the operating state of the monitored object meets requirements; marks the difference between the time when a fault analysis signal is received and the time when the monitored object starts operating as the continuous operating time, and determines whether the monitored object has an operating fault based on the continuous operating time; marks the number of fault curves received by a storage module as a fault value, and performs fault prediction analysis on the operating process of the monitored object when the fault value is not less than L1; generates an analysis cycle, obtains a necessary coefficient BY of the analysis cycle, and uses the necessary coefficient BY to determine whether maintenance is necessary for the monitored object within the analysis cycle.

[0044] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments 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 scope of protection of the present invention.

[0045] The above formulas are all obtained by collecting a large amount of data and performing software simulation to obtain a formula close to the actual value. The coefficients in the formula are set by those skilled in the art based on actual conditions; for example: formula JC = k1 × ZK + k2 × FZ + k3 × BW; those skilled in the art collect multiple groups of sample data and set corresponding monitoring coefficients for each group of sample data; the set monitoring coefficients and the collected sample data are substituted into the formula, and any three formulas form a system of three linear equations. The calculated coefficients are screened and averaged, and the values ​​of k1, k2, and k3 are obtained as 3.48, 2.65, and 2.13, respectively;

[0046] The size of the coefficient is to quantify each parameter to obtain a specific numerical value, which is convenient for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary 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.

[0047] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0048] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An operation control system for a power frequency transformer, characterized in that: It includes an operation control platform, which is communicatively connected to 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 operating 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; The monitoring coefficient JC is used to determine whether the operating status of the monitored object meets the requirements. 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 fault 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 operate 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 by 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, and the comparison result is used to determine whether the monitored object has an operation fault; The fault prediction module is used to perform a prediction analysis on the operation fault 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 maintenance analysis module is used to analyze the necessity of maintenance of the power frequency transformer; The specific process of comparing the continuous operating time with the time monitoring value SJ includes: if the continuous operating time is less than the time 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 time 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; 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 end 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 value 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, generating a fault prediction signal and sending the fault prediction signal to the mobile phone terminal of the administrator 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, performing fault coincidence value analysis 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; 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.

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, where 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 the maintenance analysis module analyzing the necessity of maintenance of the power frequency transformer includes: generating an analysis cycle, obtaining the number of maintenance analysis signals received by the maintenance analysis module 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), where 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 need 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 needs maintenance within the analysis cycle, and a maintenance processing signal is generated and sent to the administrator's mobile terminal through the operation control platform.

5. An operation control system for a power frequency transformer according to any one of claims 1 to 4, 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 calculations to obtain the monitoring coefficient JC. The monitoring coefficient JC is used 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: the difference between the time when the fault analysis signal is received and the time when the monitored object starts to operate is marked as the continuous operation time, and the continuous operation time is used to determine whether the monitored object has an operating fault; Step 3: Mark the number of fault curves received by the storage module as a fault value. 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 use the necessary coefficient BY to determine whether the monitored object has the necessity of maintenance within the analysis cycle.

Images