Program control method and system based on bus duct

Abstract

The invention relates to the technical field of program control, in particular to a program control method and system based on a bus duct. The method comprises the following steps: dividing a bus duct main line into a plurality of bus duct sub-lines which can be independently maintained; obtaining bus duct modules contained in the bus duct sub-lines; collecting working environment data of a working environment where each bus duct module is located; for each bus duct module, taking the electric power parameter of each bus duct module as a variable, combining the working environment data of each bus duct module, and predicting a working life curve of each bus duct module along with the change of the electric power parameter through a first life prediction model; determining convergence positions of all the working life curves as convergence points; and setting the time corresponding to the convergence point as the unified maintenance time of the bus duct sub-line, and setting the electric power parameter corresponding to the convergence point as the standard operation electric power parameter of the bus duct sub-line. The operation efficiency and the maintenance efficiency of the bus duct can be improved.

Description

Technical Field

[0001] The present application relates to the field of program control technology, and in particular to a program control method and system based on a bus duct. Background Art

[0002] In modern power transmission and distribution systems, bus ducts, as important power transmission equipment, are widely used due to their high efficiency, reliability and flexibility.

[0003] However, each bus duct module in the bus duct line system works under different environmental conditions, such as temperature and humidity, which lead to different aging speed and life of each bus duct module.

[0004] At the same time, in order to increase the life of bus duct modules located in poor environments, it is generally achieved by reducing the load capacity of the bus duct modules, but this will sacrifice its operating performance. Due to the limitation of a certain node in the line, the operating efficiency of the entire bus duct line will be reduced. If it cannot be adjusted reasonably, it will only lead to a reduction in the use efficiency of the entire line, and the maintenance cycle of the entire line will be unreasonably extended. Therefore, traditional bus duct maintenance is usually only based on a fixed time period or after a fault occurs. This method cannot take into account the actual use and environmental impact of each bus duct module, which may cause some modules to be replaced prematurely before reaching the end of their service life, resulting in a waste of resources. Or failures may occur due to late maintenance, affecting the stable operation of the system.

[0005] Therefore, the prior art still has some problems, resulting in low operating efficiency and maintenance efficiency of the bus duct line system. Summary of the invention

[0006] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a program control method and system based on bus duct, which can improve the operation efficiency and maintenance efficiency of the bus duct.

[0007] In a first aspect, the present application provides a program control method based on a bus duct, the program control method based on a bus duct comprising the following steps: Divide the bus duct main line into multiple bus duct sub-lines that can be maintained independently; For each busway sub-circuit, perform the following steps: Get the bus duct modules included in the bus duct sub-circuit; Collect the working environment data of each bus duct module's working environment; For each bus duct module, the power parameters of each bus duct module are used as variables, combined with the working environment data of each bus duct module, and the working life curve of each bus duct module as the power parameters change is predicted by a preset first life prediction model. The working life is the time interval from the start of use of the bus duct module to the time when the contact resistance between the bus duct module and the bus duct connector is greater than a preset resistance threshold; By using a preset convergence point determination algorithm, the position where all working life curves converge is determined as the convergence point; The time corresponding to the convergence point is set as the unified maintenance time of the bus duct sub-line, and the power parameter corresponding to the convergence point is set as the standard operation power parameter of the bus duct sub-line.

[0008] Optionally, the following steps are also included: The bus duct module corresponding to the life curve at the bottom is set as the reference bus duct module; Acquire the operating data of the reference bus duct module, and predict the life of the reference bus duct module by using a second life prediction model at a preset frequency based on the operating data; According to the difference between the life prediction result of the reference bus duct module and the unified maintenance time each time, the standard operating power parameters of the bus duct sub-line are adjusted so that the estimated life of the reference bus duct module is close to the unified maintenance time.

[0009] Optionally, the operating data includes daily average working current, daily average working voltage, daily maximum working current, corresponding maximum working current output time, daily average ambient temperature, daily average ambient humidity and daily actual contact resistance; The second life prediction model is trained by the following steps: Collecting a plurality of second training data, wherein the second training data includes a plurality of operation data of the current day and an operation data sequence consisting of a preset number of operation data before the current day, and an actual remaining working life after the current day; A recurrent neural network is used as the model framework of the second life prediction model, the operating data sequence in the second training data is used as the input of the model framework of the second life prediction model, and the actual remaining working life in the second training data is used as the label of the model framework of the second life prediction model, so as to train the second life prediction model.

[0010] Optionally, according to the difference between the life prediction result of each reference bus duct module and the unified maintenance time, adjusting the standard operating power parameters of the bus duct sub-circuit so that the estimated life of the reference bus duct module is close to the unified maintenance time, including the following steps: The standard operation power parameter is fine-tuned according to the difference between the life prediction result of the reference bus duct module and the unified maintenance time each time by presetting a first fine-tuning function, and the setting rule of the first fine-tuning function makes the standard operation power parameter lower after adjustment when the estimated life of the reference bus duct module is less than the unified maintenance time; The greater the estimated life of the reference bus duct module is than the unified maintenance time, the higher the standard operating power parameters are adjusted.

[0011] Optionally, the position where all the working life curves converge is determined by a preset convergence point determination algorithm, and the convergence point includes the following steps: Set the life curve at the bottom as the reference curve; For each power parameter point, the life difference between the reference curve and other life curves is calculated and summed up to get the total life difference; After traversing all the power parameter points, the power parameter point with the smallest total life difference is obtained, and the point on the reference curve corresponding to the power parameter point is set as the convergence point.

[0012] Optionally, the working environment data includes ambient temperature and / or ambient humidity, and the power parameter includes average working current and / or average working voltage; The first life prediction model is trained by the following steps: Collecting a plurality of first training data, wherein the first training data includes a plurality of different power parameters, working environment data and actual working life of the corresponding bus duct modules; A fully connected neural network is used as the model framework of the first life prediction model, the power parameters and working environment data in the first training data are used as the input of the model framework of the first life prediction model, and the corresponding actual working life in the first training data is used as the label of the model framework of the first life prediction model, so as to train and obtain the first life prediction model.

[0013] In a second aspect, the present application provides a bus duct-based program control system, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement a bus duct-based program control method as described in any one of the first aspects.

[0014] Compared with the prior art, the technical solution provided by this application has the following advantages: The present application provides a program control method based on bus duct, the core of which is to use a preset life prediction model, combined with the power parameters and working environment data of each bus duct module, to predict the working life curve of each module under different power parameters. On this basis, by analyzing all life curves, using a preset convergence point determination algorithm, from low power parameters to high power parameters, dynamically determine the convergence point based on all life curves, and find the position where all life curves begin to converge, so as to achieve a balance between the life of all bus duct modules and the standard operating power parameters.

[0015] The power parameters corresponding to the convergence point are set as the standard operating power parameters of the bus duct sub-line, and the time corresponding to the convergence point is used as the unified maintenance time. On the one hand, because the overall maintenance time determined by this method can ensure that the life of each module is extended as much as possible while ensuring that the whole can be maintained. This is because when the difference in life between modules is the smallest at the convergence point, the weakest module can also achieve a longer life, thereby extending the maintenance cycle of the entire line. On the other hand, the power parameters corresponding to the convergence point can also be as high as possible. Determining them as standard operating power parameters can enable the bus duct line to operate in a high-efficiency, high-performance state, giving full play to the capabilities of the bus duct modules.

[0016] Therefore, the program control method and system based on bus duct provided in the present application can improve the operation efficiency and maintenance efficiency of the bus duct.

[0017] The second beneficial effect is that although the standard operating power parameters that can make all bus duct modules on the line maintain at the same time have been determined in the initial stage, the attenuation of the life of the bus duct module is nonlinear and the actual operating conditions are changeable. In actual operation, allowing the line to transmit a current higher than the standard operating power parameters by a certain amplitude may cause individual modules to fail prematurely, disrupting the original maintenance plan.

[0018] Therefore, this application will regularly predict the life of the reference bus duct module, and based on the prediction results, regularly adjust the standard operating power parameters of the entire bus duct line to ensure that the bus duct line can be maintained along the pre-set period. In this way, this application can appropriately increase or decrease the initially set power parameters according to the actual operating conditions and life prediction results to fit the impact of actual working conditions and ensure that the estimated life of the reference bus duct module is close to the unified maintenance time.

[0019] In addition, the present application can utilize the more sensitive characteristics of vulnerable nodes in the line, that is, use the reference bus duct module as a monitoring anchor point to adjust the standard operating power parameters of the sub-line, thereby eliminating the need for daily monitoring of all modules, while achieving greater sensitivity to data and reducing computing power requirements.

[0020] The third beneficial effect is that, as the current increases, the heat generated is proportional to the square of the current, and the heat generated by the current passing through the bus duct module will increase sharply. The increase in heat causes the problem of increased contact resistance, and the life curves of multiple bus duct modules will initially show a similar downward trend. Although the heat generation increases rapidly, the heat dissipation device of the bus duct module itself can still effectively dissipate heat and maintain the temperature within a controllable range. At this time, the design structure and material properties of the module play a leading role. Since all modules have the same material and design and the same active heat dissipation capacity, the temperature of each module will be close to a temperature critical value, and the aging rate will also tend to be consistent. Therefore, the life curve will begin to converge, showing a similar service life.

[0021] However, as the current increases further, the heat generated exceeds the range that the bus duct module's own heat dissipation mechanism can handle. At this point, the difference in heat dissipation capacity begins to significantly affect the life of the module. Although the materials and designs of the modules are the same, in actual operation, the temperature and humidity of the air will also affect the heat dissipation efficiency, and a high temperature and high humidity environment will reduce the heat dissipation effect. These factors lead to differences in the aging speed of each module under high current conditions. Modules with better heat dissipation conditions can still reduce the temperature more effectively, slow down the rate at which the temperature continues to rise from the temperature critical value, and slow down the aging process; while modules with poor heat dissipation conditions will continue to increase the temperature at a relatively faster rate from the critical value, accelerating aging. Therefore, the life curve will diverge again at this stage.

[0022] The program control method based on bus duct provided in the present application obtains the total life difference by calculating the difference between the reference curve and other life curves, and obtains the convergence point by selecting the point with the smallest total life difference.

[0023] By selecting the convergence point as the reference point for operation and maintenance, the power parameters corresponding to the convergence point will not cause excessive heat aging of the module, thus avoiding the problem of widening module life differences and reduced reliability of bus duct modules under high current. Under the current corresponding to the convergence point, the line can operate with the highest possible standard power parameters to meet higher load requirements, improve the operating efficiency of the bus duct, and not lead to unreasonable life extension.

[0024] Moreover, it ensures that the life span of all modules tends to be consistent, thus achieving a unified maintenance plan and avoiding frequent maintenance due to premature failure of individual modules, thereby improving maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flowchart of a program control method based on a bus duct module provided in an embodiment of the present application; Figure 2This is a data example diagram of the working life curve and convergence point of the bus duct module provided in the embodiment of the present application. DETAILED DESCRIPTION

[0026] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0027] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application can also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only part of the embodiments of the present application, not all of the embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0028] In a first aspect, the present application embodiment provides a program control method based on a bus duct, referring to Figure 1 , the program control method based on bus duct comprises the following steps: S101: Divide the bus duct main line into multiple bus duct sub-lines that can be maintained independently.

[0029] Specifically, in the embodiment of the present application, the sub-circuits arranged in different functional areas in the bus duct main circuit are divided. In other embodiments, multiple floors can also be divided into multiple sub-circuits, generally in accordance with the principle of facilitating power outage maintenance.

[0030] For each busway sub-circuit, perform the following steps: S102: Obtain the bus duct module included in the bus duct sub-circuit; Specifically, the bus duct modules included in the divided bus duct sub-circuits and the identifiers or numbers of the bus duct modules are obtained.

[0031] S103: Collecting working environment data of the working environment of each bus duct module.

[0032] The working environment data includes ambient temperature and / or ambient humidity. Specifically, in the embodiment of the present application, the working environment data includes ambient temperature and ambient humidity, and the ambient temperature and ambient humidity are the average ambient temperature and ambient humidity measured at the corresponding bus duct module installation position within a preset number of days, where the preset number of days is a manually set value, generally 3-15 days.

[0033] S104: For each bus duct module, the power parameters of each bus duct module are used as variables, combined with the working environment data of each bus duct module, and a preset first life prediction model is used to predict the working life curve of each bus duct module as the power parameters change. The working life is the time interval from the start of use of the bus duct module to the time when the contact resistance between the bus duct module and the bus duct connector is greater than a preset resistance threshold.

[0034] Specifically, the preset resistance threshold is a manually set value.

[0035] The power parameter includes an average operating current and / or an average operating voltage. Specifically, in the embodiment of the present application, the power parameter is the average operating current.

[0036] Specifically, the first life prediction model is trained by the following steps: Collecting a plurality of first training data, wherein the first training data includes a plurality of different power parameters, working environment data and actual working life of the corresponding bus duct modules; A fully connected neural network is used as the model framework of the first life prediction model, the power parameters and working environment data in the first training data are used as the input of the model framework of the first life prediction model, and the corresponding actual working life in the first training data is used as the label of the model framework of the first life prediction model, so as to train and obtain the first life prediction model.

[0037] The actual working life mentioned here is the time interval from the actual start of use of the bus duct module to the time when the contact resistance between the bus duct module and the bus duct connector is greater than the preset resistance threshold. Specifically, the power parameter used in the training is the average working current over the entire actual working life, and the working environment data used in the training is the average temperature and average humidity over the entire actual working life.

[0038] Specifically, the working life curve is obtained by selecting 500 average working current data points as sampling data points for each bus duct module in the range of 0-1000A, each average working current data point is used as one of the inputs of the first life prediction model, and the working environment data of the bus duct module is used as the second input of the first life prediction model. The preset first life prediction model is used to predict 500 points in the working life-average working current diagram of the bus duct module, and these points are connected to obtain the working life curve of each bus duct module.

[0039] Reference Figure 2 , the embodiment of the present application provides a data example diagram of the working life curve and convergence point of the bus duct module, wherein the multiple curves are the working life curves of each bus duct module.

[0040] It should be noted that, since the data collected during the actual training of the first life prediction model is only the actual working life data when the average working current is 200A-800A, the actual working life data provided in the embodiment of the present application is Figure 2 For the prediction results, more attention should be paid to the changes within the 200A-800A curve, as the confidence level of the prediction results outside this range is relatively low.

[0041] S105: using a preset convergence point determination algorithm, determine the position where all the working life curves converge as the convergence point.

[0042] Specifically, the positions where all the working life curves converge are determined by a preset convergence point determination algorithm, and the convergence points include the following steps: Set the life curve at the bottom as the reference curve; For each power parameter point, the value of the reference curve on the horizontal axis and the value of the other life curves on the horizontal axis are calculated to obtain the life difference between the reference curve and the other life curves. These results are added together to obtain the total life difference.

[0043] After traversing all the power parameter points, the power parameter point with the smallest total life difference is obtained, and the point on the reference curve corresponding to the power parameter point is set as the convergence point.

[0044] Its working principle and beneficial effect are that as the current increases, the heat generated is proportional to the square of the current, and the heat generated by the current passing through the bus duct module will increase sharply. The increase in heat causes the problem of increased contact resistance, and the life curves of multiple bus duct modules will show a similar downward trend at the beginning. Although the heat generation increases rapidly, the heat dissipation device of the bus duct module itself can still effectively dissipate heat and maintain the temperature within a controllable range. At this time, the design structure and material properties of the module play a leading role. Since all modules have the same material and design and the same active heat dissipation capacity, the temperature of each module will be close to a temperature critical value, and the aging rate will also tend to be consistent. Therefore, the life curve will begin to converge, showing a similar service life.

[0045] However, as the current increases further, the heat generated exceeds the range that the bus duct module's own heat dissipation mechanism can handle. At this point, the difference in heat dissipation capacity begins to significantly affect the life of the module. Although the materials and designs of the modules are the same, in actual operation, the temperature and humidity of the air will also affect the heat dissipation efficiency, and a high temperature and high humidity environment will reduce the heat dissipation effect. These factors lead to differences in the aging speed of each module under high current conditions. Modules with better heat dissipation conditions can still reduce the temperature more effectively, slow down the rate at which the temperature continues to rise from the temperature critical value, and slow down the aging process; while modules with poor heat dissipation conditions will continue to increase the temperature at a relatively faster rate from the critical value, accelerating aging. Therefore, the life curve will diverge again at this stage.

[0046] The program control method based on bus duct provided in the embodiment of the present application obtains the total life difference by calculating the difference between the reference curve and other life curves, and obtains the convergence point by selecting the point with the smallest total life difference.

[0047] By selecting the convergence point as the reference point for operation and maintenance, the power parameters corresponding to the convergence point will not cause excessive heat aging of the module, thus avoiding the problem of widening module life differences and reduced reliability of bus duct modules under high current. Under the current corresponding to the convergence point, the line can operate with the highest possible standard power parameters to meet higher load requirements, improve the operating efficiency of the bus duct, and not lead to unreasonable life extension.

[0048] Moreover, it ensures that the life span of all modules tends to be consistent, thus achieving a unified maintenance plan and avoiding frequent maintenance due to premature failure of individual modules, thereby improving maintenance efficiency.

[0049] S106: setting the time corresponding to the convergence point as the unified maintenance time of the bus duct sub-line, and setting the power parameters corresponding to the convergence point as the standard operating power parameters of the bus duct sub-line.

[0050] Specifically, the results of standard operating power parameters are configured in the transmission control section of the bus duct, and unified maintenance is organized at a unified maintenance time.

[0051] S107: Set the bus duct module corresponding to the life curve at the bottom as a reference bus duct module; obtain the operating data of the reference bus duct module, and predict the life of the reference bus duct module through a second life prediction model at a preset frequency based on the operating data.

[0052] Specifically, the operating data includes daily average working current, daily average working voltage, daily maximum working current, corresponding maximum working current output time, daily average ambient temperature, daily average ambient humidity and daily actual contact resistance.

[0053] The second life prediction model is trained by the following steps: Collecting a plurality of second training data, wherein the second training data includes a plurality of operation data of the current day and an operation data sequence consisting of a preset number of operation data before the current day, and an actual remaining working life after the current day; A recurrent neural network (RNN) is used as the model framework of the second life prediction model, the operating data sequence in the second training data is used as the input of the model framework of the second life prediction model, and the actual remaining working life in the second training data is used as the label of the model framework of the second life prediction model, so as to train and obtain the second life prediction model.

[0054] Specifically, the preset number and the preset frequency are both manually preset values.

[0055] Specifically, in the embodiment of the present application, predicting the life of the reference bus duct module by using the second life prediction model includes the following steps: The preset frequency is weekly; The preset number per week is 7. Taking Sunday as the current day as an example, the daily operation data of the previous 7 days are collected to form an operation data sequence, and the operation data sequence is input into the second life prediction model to obtain the remaining operation life of the reference bus duct module.

[0056] The life prediction result of the reference bus duct module is obtained by adding the time interval from the operation day when the standard operation power parameters are set to the current day to the remaining operation life obtained above.

[0057] S108: According to the difference between the life prediction result of each reference bus duct module and the unified maintenance time, the standard operating power parameters of the bus duct sub-circuit are adjusted so that the estimated life of the reference bus duct module is close to the unified maintenance time.

[0058] Specifically, the following steps are included: The standard operating power parameters are fine-tuned according to the difference between the life prediction result of the reference bus duct module and the unified maintenance time each time by presetting the first fine-tuning function. The setting rule of the first fine-tuning function makes the standard operating power parameters lower after adjustment when the estimated life of the reference bus duct module is less than the unified maintenance time.

[0059] The greater the estimated life of the reference bus duct module is than the unified maintenance time, the higher the standard operating power parameters are adjusted.

[0060] Specifically, in the embodiment of the present application, the first fine-tuning function is: in, To unify the maintenance time minus the life prediction result of the reference bus duct module, For standard operating power parameters, To unify the maintenance time, and is an empirical parameter.

[0061] It should be noted that the specific form of the first fine-tuning function can have more than one variant, and its variant form can also achieve the same technical effect. Therefore, the scope of protection requested by this application should not be limited to the specific calculation formula proposed in the embodiment of this application.

[0062] Its working principle and beneficial effect are that, although in the initial stage, the embodiment of the present application has determined the standard operating power parameters that can make all bus duct modules on the line maintain at the same time as much as possible, but because the decay of the life of the bus duct module is nonlinear and the actual operating conditions are changeable, in actual operation, allowing the line to transmit a current higher than the standard operating power parameters by a certain amplitude may cause individual modules to fail prematurely, disrupting the original maintenance plan.

[0063] Therefore, the embodiment of the present application will regularly predict the life of the reference bus duct module, and according to the prediction results, regularly adjust the standard operating power parameters of the entire bus duct line to ensure that the bus duct line can be maintained along the pre-set period. In this way, the present application can appropriately increase or decrease the initially set power parameters according to the actual operating conditions and life prediction results to fit the impact of the actual working conditions and ensure that the estimated life of the reference bus duct module is close to the unified maintenance time.

[0064] In addition, the present application can utilize the more sensitive characteristics of vulnerable nodes in the line, that is, use the reference bus duct module as a monitoring anchor point to adjust the standard operating power parameters of the sub-line, thereby eliminating the need for daily monitoring of all modules, while achieving greater sensitivity to data and reducing computing power requirements.

[0065] In summary, the embodiment of the present application provides a program control method based on bus duct, the core of which is to use a preset life prediction model, combined with the power parameters and working environment data of each bus duct module, to predict the working life curve of each module under different power parameters. On this basis, by analyzing all life curves, using a preset convergence point determination algorithm, from low power parameters to high power parameters, dynamically determine the convergence point based on all life curves, and find the position where all life curves begin to converge, so as to achieve a balance between the life of all bus duct modules and the standard operating power parameters.

[0066] The power parameters corresponding to the convergence point are set as the standard operating power parameters of the bus duct sub-line, and the time corresponding to the convergence point is used as the unified maintenance time. On the one hand, because the overall maintenance time determined by this method can ensure that the life of each module is extended as much as possible while ensuring that the whole can be maintained. This is because when the difference in life between modules is the smallest at the convergence point, the weakest module can also achieve a longer life, thereby extending the maintenance cycle of the entire line. On the other hand, the power parameters corresponding to the convergence point can also be as high as possible. Determining them as standard operating power parameters can enable the bus duct line to operate in a high-efficiency, high-performance state, giving full play to the capabilities of the bus duct modules.

[0067] Therefore, the program control method and system based on the bus duct provided in the embodiment of the present application can improve the operation efficiency and maintenance efficiency of the bus duct.

[0068] In a second aspect, the present application provides a bus duct-based program control system, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the bus duct-based program control method as described in the aforementioned embodiment.

[0069] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. In addition, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. Moreover, in the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can represent A or B; "and / or" in this article is only a kind of association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. Furthermore, in the description of the embodiments of the present application, “plurality” refers to two or more than two.

[0070] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A program control method based on bus duct, characterized in that: The program control method based on bus duct comprises the following steps: Divide the bus duct main line into multiple bus duct sub-lines that can be maintained independently; For each busway sub-circuit, perform the following steps: Get the bus duct modules included in the bus duct sub-circuit; Collect the working environment data of each bus duct module's working environment; For each bus duct module, the power parameters of each bus duct module are used as variables, combined with the working environment data of each bus duct module, and the working life curve of each bus duct module as the power parameters change is predicted by a preset first life prediction model. The working life is the time interval from the start of use of the bus duct module to the time when the contact resistance between the bus duct module and the bus duct connector is greater than a preset resistance threshold; By using a preset convergence point determination algorithm, the position where all working life curves converge is determined as the convergence point; The time corresponding to the convergence point is set as the unified maintenance time of the bus duct sub-line, and the power parameter corresponding to the convergence point is set as the standard operation power parameter of the bus duct sub-line.

2. The program control method based on bus duct according to claim 1 is characterized in that: The following steps are also included: The bus duct module corresponding to the life curve at the bottom is set as the reference bus duct module; Acquire the operating data of the reference bus duct module, and predict the life of the reference bus duct module by using a second life prediction model at a preset frequency based on the operating data; According to the difference between the life prediction result of the reference bus duct module and the unified maintenance time each time, the standard operating power parameters of the bus duct sub-line are adjusted so that the estimated life of the reference bus duct module is close to the unified maintenance time.

3. The program control method based on bus duct according to claim 2 is characterized in that: The operating data includes daily average working current, daily average working voltage, daily maximum working current, corresponding maximum working current output time, daily average ambient temperature, daily average ambient humidity and daily actual contact resistance; The second life prediction model is trained by the following steps: Collecting a plurality of second training data, wherein the second training data includes a plurality of operation data of the current day and an operation data sequence consisting of a preset number of operation data before the current day, and an actual remaining working life after the current day; A recurrent neural network is used as the model framework of the second life prediction model, the operating data sequence in the second training data is used as the input of the model framework of the second life prediction model, and the actual remaining working life in the second training data is used as the label of the model framework of the second life prediction model, so as to train the second life prediction model.

4. The program control method based on bus duct according to claim 2 is characterized in that: According to the difference between the life prediction result of each reference bus duct module and the unified maintenance time, the standard operating power parameters of the bus duct sub-line are adjusted so that the estimated life of the reference bus duct module is close to the unified maintenance time, including the following steps: The standard operation power parameter is fine-tuned according to the difference between the life prediction result of the reference bus duct module and the unified maintenance time each time by presetting a first fine-tuning function, and the setting rule of the first fine-tuning function makes the standard operation power parameter lower after adjustment when the estimated life of the reference bus duct module is less than the unified maintenance time; The greater the estimated life of the reference bus duct module is than the unified maintenance time, the higher the standard operating power parameters are adjusted.

5. The program control method based on bus duct according to claim 1 is characterized in that: The convergence point determination algorithm is used to determine the position where all the working life curves converge. The convergence point includes the following steps: Set the life curve at the bottom as the reference curve; For each power parameter point, the life difference between the reference curve and other life curves is calculated and summed up to get the total life difference; After traversing all the power parameter points, the power parameter point with the smallest total life difference is obtained, and the point on the reference curve corresponding to the power parameter point is set as the convergence point.

6. The program control method based on bus duct according to claim 1 is characterized in that: The working environment data includes the ambient temperature and / or the ambient humidity, and the power parameters include the average working current and / or the average working voltage; The first life prediction model is trained by the following steps: Collecting a plurality of first training data, wherein the first training data includes a plurality of different power parameters, working environment data and actual working life of the corresponding bus duct modules; A fully connected neural network is used as the model framework of the first life prediction model, the power parameters and working environment data in the first training data are used as the input of the model framework of the first life prediction model, and the corresponding actual working life in the first training data is used as the label of the model framework of the first life prediction model, so as to train and obtain the first life prediction model.

7. The program control system based on bus duct is characterized by: It includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the bus duct-based program control method as described in any one of claims 1 to 6.

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