Program control method and system based on busway

Abstract

This application relates to the field of program control technology, and particularly to a program control method and system based on bus ducts. The method includes the following steps: dividing the total bus duct line into multiple independently maintainable bus duct sub-lines; obtaining the bus duct modules included in the bus duct sub-lines; collecting the working environment data of the working environment where each bus duct module is located; for each bus duct module, taking the power parameters of each bus duct module as variables, combining the working environment data of each bus duct module, and predicting the working life curve of each bus duct module varying with the power parameters through the first life prediction model; determining the position where all the working life curves converge as the convergence point; 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. This application can improve the operating efficiency and maintenance efficiency of bus ducts.

Description

Technical Field

[0001] This application relates to the technical field of program control, and in particular, to a program control method and system based on bus ducts. 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 operates under different environmental conditions, for example, there are differences in parameters such as temperature and humidity. These differences lead to different aging speeds and lifetimes of each bus duct module.

[0004] At the same time, in order to increase the lifetime of bus duct modules located in a poor environment, generally, the load capacity of the bus duct modules is also reduced to achieve this, but this will sacrifice their operating performance, and due to the limitation of a certain node in the line, the operating efficiency of the entire bus duct line is reduced. If not adjusted reasonably, it will only lead to a reduction in the usage efficiency of the entire line, and the maintenance cycle of the entire line is unreasonably extended.

[0005] Therefore, traditional bus duct maintenance is usually only carried out based on a fixed time period or after a failure occurs. This method cannot consider the actual usage situation and environmental impact of each bus duct module, which may cause some modules to be prematurely replaced before reaching their service life, resulting in waste of resources. Or, due to late maintenance, a failure may be triggered, affecting the stable operation of the system.

[0006] Therefore, there are still some problems in the existing technology, resulting in low operating efficiency and maintenance efficiency of the bus duct line system. Summary of the Invention

[0007] In order to solve the above technical problems or at least partially solve the above technical problems, this application provides a program control method and system based on bus ducts, which can improve the operating efficiency and maintenance efficiency of bus ducts.

[0008] In a first aspect, this application provides a program control method based on bus ducts, and the program control method based on bus ducts includes the following steps:

[0009] Divide the total bus duct line into multiple independently maintainable bus duct sub-lines;

[0010] For each bus duct sub-line, perform the following steps:

[0011] Obtain the bus duct modules included in the bus duct sub-line;

[0012] Collect the working environment data of the working environment where each bus duct module is located;

[0013] For each busbar trunking module, taking the electrical parameters of each busbar trunking module as variables, combining the operating environment data of each busbar trunking module, and predicting the operating life curve of each busbar trunking module varying with the electrical parameters through a preset first life prediction model. The operating life is the time interval from when the busbar trunking module starts to be used until the contact resistance between the busbar trunking module and the busbar connector is greater than a preset resistance threshold;

[0014] Determine the position where all the operating life curves converge through a preset convergence point determination algorithm as the convergence point;

[0015] Set the time corresponding to the convergence point as the unified maintenance time of the busbar trunking sub-line, and set the electrical parameters corresponding to the convergence point as the standard operating electrical parameters of the busbar trunking sub-line.

[0016] Optionally, it further includes the following steps:

[0017] Set the busbar trunking module corresponding to the life curve at the bottom as the reference busbar trunking module;

[0018] Obtain the operating data of the reference busbar trunking module, and based on the operating data, predict the life of the reference busbar trunking module through a second life prediction model at a preset frequency;

[0019] Adjust the standard operating electrical parameters of the busbar trunking sub-line according to the difference between the life prediction result of the reference busbar trunking module each time and the unified maintenance time, so that the estimated life of the reference busbar trunking module is close to the unified maintenance time.

[0020] Optionally, the operating data includes the daily average working current, daily average working voltage, daily maximum working current, the corresponding maximum working current output time, daily average ambient temperature, daily average ambient humidity, and daily actual contact resistance;

[0021] The second life prediction model is trained through the following steps:

[0022] Collect multiple pieces of second training data, where the second training data includes a sequence of operating data composed of the operating data of multiple current days and a preset number of operating data before that, and the actual remaining operating life after the current day;

[0023] Taking a recurrent neural network as the model framework of the second life prediction model, using the sequence of operating data in the second training data as the input of the model framework of the second life prediction model, and using the actual remaining operating life in the second training data as the label of the model framework of the second life prediction model, thus training to obtain the second life prediction model.

[0024] Optionally, according to the difference between the life prediction result of each reference busbar trunking module and the unified maintenance time, adjust the standard operating power parameters of the busbar trunking sub-circuit so that the predicted life of the reference busbar trunking module is close to the unified maintenance time, including the following steps:

[0025] Fine-tune the standard operating power parameters according to the difference between the life prediction result of each reference busbar trunking module and the unified maintenance time through a preset first fine-tuning function. The setting rule of the first fine-tuning function is such that when the predicted life of the reference busbar trunking module is less than the unified maintenance time, the lower the standard operating power parameters after adjustment;

[0026] When the predicted life of the reference busbar trunking module is greater than the unified maintenance time, the higher the standard operating power parameters after adjustment.

[0027] Optionally, through a preset convergence point determination algorithm, determine the position where all working life curves converge as the convergence point, including the following steps:

[0028] Set the life curve at the bottom as the reference curve;

[0029] For each power parameter point, calculate the life difference between the reference curve and other life curves, and sum them up to obtain the total life difference;

[0030] After traversing all power parameter points, obtain the power parameter point with the smallest total life difference, and set the point corresponding to the reference curve as the convergence point.

[0031] Optionally, the working environment data includes ambient temperature and / or ambient humidity, and the power parameters include average working current and / or average working voltage;

[0032] The first life prediction model is trained through the following steps:

[0033] Collect a plurality of first training data, where the first training data includes a plurality of different power parameters, working environment data, and their corresponding actual working lives of the busbar trunking module;

[0034] Use a fully connected neural network 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, and thus the first life prediction model is trained.

[0035] In a second aspect, the present application provides a program control system based on a busbar trunking system, which includes a processor and a memory. At least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the program control method based on the busbar trunking system according to any one of the first aspects.

[0036] The technical solution provided by the present application has the following advantages compared with the prior art:

[0037] The present application provides a program control method based on a busbar trunking system. The core lies in using a preset life prediction model, combining the power parameters and working environment data of each busbar trunking module to predict the working life curve of each module under different power parameters. On this basis, by analyzing all the life curves, using a preset convergence point determination algorithm, from the low power parameter to the high power parameter direction, dynamically determine the convergence point based on all the life curves, and find the position where all the life curves start to converge, so as to achieve the balance of the life of all busbar trunking modules and the standard operating power parameters.

[0038] Set the power parameter corresponding to this convergence point as the standard operating power parameter of the busbar trunking sub-line, and the time corresponding to the convergence point as the unified maintenance time. On the one hand, because the overall maintenance time determined by this method can ensure that the overall can be maintained while ensuring that the life of each module is extended as much as possible. This is because when the life difference between modules is the smallest at the convergence point, the weakest module can also reach a longer life, thus extending the maintenance cycle of the overall line. On the other hand, the power parameter corresponding to the convergence point can also be as high as possible. Determining it as the standard operating power parameter can make the busbar trunking line operate in a high-efficiency and high-performance state, and give full play to the capabilities of the busbar trunking modules.

[0039] Therefore, a program control method and system based on a busbar trunking system provided by the present application can improve the operation efficiency and maintenance efficiency of the busbar trunking system.

[0040] The discussion of the second beneficial effect is that although the standard operating power parameter that can make all busbar trunking modules on the line be maintained simultaneously has been determined in the initial stage. However, due to the non-linear attenuation of the life of the busbar trunking module and the changeable actual operating conditions, allowing the line to transmit a current higher than the standard operating power parameter by a certain amplitude in actual operation may cause individual modules to fail prematurely and disrupt the original maintenance plan.

[0041] Therefore, this application will regularly predict the lifespan of the reference busbar trunking module, and according to the prediction results, regularly adjust the standard operating power parameters of the entire busbar trunking line to ensure that the busbar trunking line can be maintained along the pre-established period. In this way, this application can appropriately increase or decrease the initially set power parameters according to the actual operating conditions and lifespan prediction results to fit the influence of the actual working conditions, and ensure that the estimated lifespan of the reference busbar trunking module is close to the unified maintenance time.

[0042] Moreover, this application can utilize the more sensitive characteristics of the vulnerable nodes in the line, that is, use the reference busbar trunking module as a monitoring anchor point to adjust the standard operating power parameters of the sub-line, thus achieving the goal of not needing to monitor all modules daily, while being more sensitive to data touch and reducing the requirement for computing power.

[0043] The discussion of the third beneficial effect is that as the current increases, the generation of heat is proportional to the square of the current, and the heat generated by the current passing through the busbar trunking module will increase sharply. The increase in heat causes the problem of increased contact resistance, and the lifespan curves of multiple busbar trunking modules will show a similar downward trend at first. Although the heat generation increases rapidly, the self-cooling device of the busbar trunking module 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 the materials and designs of all modules are the same and the active heat dissipation capabilities are the same, the temperatures of each module will be close to a temperature critical value, and the aging speeds will also tend to be the same. Therefore, the lifespan curves will start to converge and show similar service lives.

[0044] However, as the current further increases, the heat generation exceeds the range that the self-cooling mechanism of the busbar trunking module can handle. At this time, the difference in heat dissipation capacity begins to significantly affect the lifespan 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 cause differences in the aging speeds of each module under high-current conditions. The modules with better heat dissipation conditions can still more effectively reduce the temperature, delay the speed of the temperature continuing to rise from the temperature critical value, and delay the aging process; while the modules with poor heat dissipation conditions will continue to rise in temperature at a relatively higher speed from the critical value, accelerating the aging. Therefore, the lifespan curves will diverge again at this stage.

[0045] The program control method based on the busbar trunking provided by this application obtains the total lifespan difference by calculating the difference between the reference curve and other lifespan curves, and selects the convergence point by selecting the point with the smallest total lifespan difference.

[0046] By selecting the convergence point as the reference point for operation and maintenance, the electrical parameters corresponding to the convergence point will not cause the module to overheat and age, avoiding the problems of the expansion of the module life difference and the decline of reliability of the busbar trunking module under high current. At the current corresponding to the convergence point, the line can operate with electrical parameters as high as possible to meet higher load requirements, improve the operation efficiency of the busbar trunking, and will not cause unreasonable life extension.

[0047] Moreover, it also ensures that the lives of all modules tend to be consistent, thus realizing a unified maintenance plan, avoiding frequent maintenance caused by the premature failure of individual modules, and improving the maintenance efficiency. Description of the Drawings

[0048] Figure 1 It is a flowchart of the program control method based on the busbar trunking module provided by the embodiment of the present application;

[0049] Figure 2 It is a data example diagram of the working life curve and the convergence point of the busbar trunking module provided by the embodiment of the present application. Detailed Embodiments

[0050] Next, the technical solutions in the present application will be described in conjunction with the drawings.

[0051] Many specific details are set forth in the following description in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways different from those described herein; obviously, the embodiments in the specification are only a part of the embodiments of the present application, rather than all of the embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0052] In a first aspect, the embodiment of the present application provides a program control method based on a busbar trunking, with reference to Figure 1 , the program control method based on the busbar trunking includes the following steps:

[0053] S101: Divide the total busbar trunking line into multiple independently maintainable busbar trunking sub-lines.

[0054] Specifically, in the embodiment of the present application, it is obtained by dividing the sub-lines arranged in different functional areas in the total busbar trunking line. In other embodiments, it is also possible to divide multiple floors into multiple sub-lines, generally following the principle of facilitating power outage maintenance for division.

[0055] For each busbar trunking sub-line, perform the following steps:

[0056] S102: Obtain the busbar trunking modules included in the busbar trunking sub-line;

[0057] Specifically, obtain the busbar trunking modules included in the divided busbar trunking sub-circuits, as well as the identifiers or numbers of these busbar trunking modules.

[0058] S103: Collect the working environment data of the working environment where each busbar trunking module is located.

[0059] The working environment data includes ambient temperature and / or ambient humidity. Specifically, in the embodiments 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 within a preset number of days measured at the installation position of the corresponding busbar trunking module. Here, the preset number of days is a value set artificially, generally 3 - 15 days.

[0060] S104: For each busbar trunking module, using the power parameters of each busbar trunking module as variables, combining the working environment data of each busbar trunking module, predict the working life curve of each busbar trunking module varying with the power parameters through a preset first life prediction model. The working life is the time interval from when the busbar trunking module starts to be used until the contact resistance between the busbar trunking module and the busbar connector is greater than a preset resistance threshold.

[0061] Specifically, the preset resistance threshold is a value set artificially.

[0062] The power parameters include average working current and / or average working voltage. Specifically, in the embodiments of the present application, the power parameter is the average working current.

[0063] Specifically, the first life prediction model is trained through the following steps:

[0064] Collect a plurality of first training data, where the first training data includes a plurality of different power parameters, working environment data, and the actual working life of the corresponding busbar trunking modules;

[0065] Use a fully connected neural network 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, and thus the first life prediction model is trained.

[0066] The actual working life mentioned here is the time interval from when the actual busbar trunking module starts to be used until the contact resistance between the busbar trunking module and the busbar connector is greater than a preset resistance threshold. Specifically, the power parameter used during training is the average working current throughout the actual working life, and the working environment data used during training is the average temperature and average humidity throughout the actual working life.

[0067] Specifically, for each busbar trunking module, within the range of 0 - 1000A, 500 average working current data points are evenly selected as sampling data points. 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 busbar trunking module is used as the second input of the first life prediction model. Through the preset first life prediction model, 500 points of the busbar trunking module in the working life - average working current chart are predicted. Connecting these points results in the working life curve of each busbar trunking module.

[0068] Referring to Figure 2 , the embodiment of the present application provides a data example diagram of the working life curve and the convergence point of the busbar trunking module, where multiple curves are the working life curves of each busbar trunking module.

[0069] It should be noted that during the actual training process of the first life prediction model, the collected data only includes the actual working life data when the average working current is 200A - 800A. Therefore, for Figure 2 the actual situation provided by the embodiment of the present application, more attention should be paid to the changes within the 200A - 800A curve, and the confidence level of the prediction results outside this interval is relatively low.

[0070] S105: Through the preset convergence point determination algorithm, determine the position where all the working life curves converge as the convergence point.

[0071] Specifically, determining the position where all the working life curves converge as the convergence point through the preset convergence point determination algorithm includes the following steps:

[0072] Set the life curve at the bottom as the reference curve;

[0073] For each power parameter point, calculate the value of the reference curve at this abscissa and the values of other life curves at this abscissa, respectively obtaining the life differences between the reference curve and other life curves. Add these results to obtain the total life difference.

[0074] After traversing all the power parameter points, obtain the power parameter point with the smallest total life difference, and set the point corresponding to the reference curve at this power parameter point as the convergence point.

[0075] Its working principle and beneficial effects are as follows. Since the generation of heat is proportional to the square of the current as the current increases, the heat generated by the current passing through the busbar trunking module will increase sharply. The increase in heat causes the problem of increased contact resistance, and the life curves of multiple busbar trunking modules will show a similar downward trend at the beginning. Although the heat generation increases rapidly, the heat dissipation device of the busbar trunking 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 the materials and designs of all modules are the same and the active heat dissipation capabilities are the same, the temperatures of each module will approach a temperature critical value, and the aging rates will also tend to be the same. Therefore, the life curves will start to converge and show similar service lives.

[0076] However, as the current further increases, the heat generation exceeds the range that the self-cooling mechanism of the busbar trunking module can handle. At this time, 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 cause differences in the aging rates of each module under high-current conditions. The modules with better heat dissipation conditions can still more effectively reduce the temperature, delay the rate of temperature increase from the temperature critical value, and delay the aging process; while the modules with poor heat dissipation conditions will continue to increase the temperature at a relatively greater rate from the critical value, accelerating the aging. Therefore, the life curves will diverge again at this stage.

[0077] The program control method based on the busbar trunking provided by the embodiment of the present application obtains the total life difference by calculating the difference between the reference curve and other life curves, and selects the convergence point by selecting the point with the smallest total life difference.

[0078] By selecting the convergence point as the reference point for operation and maintenance, the power parameters corresponding to the convergence point will not cause the module to overheat and age, avoiding the problems of the expansion of the module life difference and the decline in reliability of the busbar trunking module under high current. At the current corresponding to the convergence point, the line can operate with power parameters as high as possible to meet higher load requirements, improve the operation efficiency of the busbar trunking, and will not cause unreasonable life extension.

[0079] Moreover, it also ensures that the lives of all modules tend to be the same, thus realizing a unified maintenance plan, avoiding frequent maintenance caused by the premature failure of individual modules, and thus improving the maintenance efficiency.

[0080] S106: Set the time corresponding to the convergence point as the unified maintenance time of the busbar trunking sub-line, and set the power parameters corresponding to the convergence point as the standard operating power parameters of the busbar trunking sub-line.

[0081] Specifically, configure the results of the standard operating power parameters in the power transmission control section of the busbar trunking, and organize unified maintenance during the unified maintenance time.

[0082] S107: Set the busbar trunking module corresponding to the life curve at the bottom as the reference busbar trunking module; obtain the operating data of the reference busbar trunking module, and based on the operating data, predict the life of the reference busbar trunking module through the second life prediction model at a preset frequency.

[0083] Specifically, the operating data includes the daily average working current, daily average working voltage, daily maximum working current, the corresponding maximum working current output time, daily average ambient temperature, daily average ambient humidity, and daily actual contact resistance.

[0084] The second life prediction model is trained through the following steps:

[0085] Collect a plurality of second training data, where the second training data includes an operating data sequence composed of the operating data of multiple current days and a preset number of operating data before that, and the actual remaining working life after the current day;

[0086] Use a recurrent neural network (RNN) as the model framework of the second life prediction model, use the operating data sequence in the second training data as the input of the model framework of the second life prediction model, and use the actual remaining working life in the second training data as the label of the model framework of the second life prediction model, and thus train the second life prediction model.

[0087] Specifically, both the preset number and the preset frequency are artificially preset values.

[0088] Specifically, in the embodiment of the present application, predicting the life of the reference busbar trunking module through the second life prediction model includes the following steps:

[0089] The preset frequency is once a week;

[0090] Taking Sunday as the current day as an example, the preset number is 7 once a week. Collect the daily operating data of the previous 7 days to form an operating data sequence, and input the operating data sequence into the second life prediction model to obtain the remaining operating life of the reference busbar trunking module.

[0091] Add the time interval from the operating day when the standard operating power parameters were initially set to the current day to the remaining operating life obtained above to get the life prediction result of the reference busbar trunking module.

[0092] S108: According to the difference between the life prediction result of the reference busbar trunking module each time and the unified maintenance time, adjust the standard operating power parameters of the busbar trunking sub-line so that the estimated life of the reference busbar trunking module is close to the unified maintenance time.

[0093] Specifically, the following steps are included:

[0094] 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.

[0095] 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.

[0096] Specifically, in the embodiment of the present application, the first fine-tuning function is:

[0097]

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] Moreover, this application can utilize the more sensitive characteristics of the vulnerable nodes in the circuit, that is, use the reference busbar module as the monitoring anchor point to regulate the standard operating power parameters of the sub-circuit, thereby achieving the goal of not requiring daily monitoring of all modules. While being more sensitive to data touch, it reduces the requirement for computing power.

[0103] In summary, the embodiment of this application provides a program control method based on busbars. The core lies in using a preset life prediction model, combining the power parameters and working environment data of each busbar module to predict the working life curves of each module under different power parameters. On this basis, by analyzing all the life curves, using a preset convergence point determination algorithm, from the low power parameter to the high power parameter direction, dynamically determine the convergence point based on all the life curves, and find the position where all the life curves start to converge, so as to achieve the balance of the life and standard operating power parameters of all busbar modules.

[0104] Set the power parameter corresponding to this convergence point as the standard operating power parameter of the busbar sub-circuit, and the time corresponding to the convergence point as the unified maintenance time. On the one hand, because the overall maintenance time determined by this method can ensure that the overall can be maintained while ensuring that the life of each module can be extended as much as possible. This is because at the convergence point, when the life difference between modules is the smallest, the weakest module can also reach a relatively long life, thereby extending the maintenance cycle of the overall circuit. On the other hand, the power parameter corresponding to the convergence point can also be as high as possible. Determining it as the standard operating power parameter can enable the busbar circuit to operate in a high-efficiency and high-performance state, giving full play to the capabilities of the busbar modules.

[0105] Therefore, the program control method and system based on busbars provided by the embodiment of this application can improve the operating efficiency and maintenance efficiency of the busbars.

[0106] In the second aspect, this application provides a program control system based on busbars, including a processor and a memory. At least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the program control method based on busbars as described in the foregoing embodiments.

[0107] It should be noted that in this document, 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 actual relationship or order between these entities or operations. Additionally, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising said element. Moreover, in the description of the embodiments of the present application, unless otherwise specified, " / " means "or", for example, A / B may mean A or B; "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. And, in the description of the embodiments of the present application, "a plurality of" means two or more than two.

[0108] The above are only specific embodiments of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be obvious 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 these embodiments described herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A program control method based on a busway, characterized in that, The program control method based on the busbar trunking includes the following steps: Divide the total busbar trunking line into multiple independently maintainable busbar sub-lines; For each busbar sub-line, perform the following steps: Obtain the busbar modules included in the busbar sub-line; Collect the working environment data of the working environment where each busbar module is located; For each busbar module, using the power parameters of each busbar module as variables, combined with the working environment data of each busbar module, predict the working life curve of each busbar module with the change of power parameters through a preset first life prediction model. The working life is the time interval from the start of use of the busbar module to when the contact resistance between the busbar module and the busbar connector is greater than the preset resistance threshold; Determine the position where all the working life curves converge through a preset convergence point determination algorithm as the convergence point; Set the time corresponding to the convergence point as the unified maintenance time of the busbar sub-line, and set the power parameter corresponding to the convergence point as the standard operating power parameter of the busbar sub-line.

2. The program control method based on a busbar trunking according to claim 1, wherein It further includes the following steps: Set the busbar module corresponding to the lowest life curve as the reference busbar module; Obtain the operation data of the reference busbar module, and based on the operation data, predict the life of the reference busbar module through the second life prediction model at a preset frequency; According to the difference between the life prediction result of the reference busbar module each time and the unified maintenance time, adjust the standard operating power parameter of the busbar sub-line so that the predicted life of the reference busbar module is close to the unified maintenance time.

3. The program control method based on a busbar trunking according to claim 2, wherein The operation data includes the daily average working current, daily average working voltage, daily maximum working current, the 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 through the following steps: Collect multiple second training data, where the second training data includes a sequence of operation data composed of the operation data of multiple current days and a preset number of operation data before that, and the actual remaining working life after the current day; Use a recurrent neural network as the model framework of the second life prediction model, use the sequence of operation data in the second training data as the input of the model framework of the second life prediction model, and use the actual remaining working life in the second training data as the label of the model framework of the second life prediction model, and thus train the second life prediction model.

4. The program control method based on a busbar trunking according to claim 2, characterized in that, According to the difference between the life prediction result of the reference busbar module each time and the unified maintenance time, adjusting the standard operating power parameter of the busbar sub-line so that the predicted life of the reference busbar module is close to the unified maintenance time includes the following steps: Fine-tune the standard operating power parameter according to the difference between the life prediction result of the reference busbar module each time and the unified maintenance time through a preset first fine-tuning function. The setting rule of the first fine-tuning function is such that when the predicted life of the reference busbar module is less than the unified maintenance time, the lower the standard operating power parameter after adjustment; When the estimated life of the reference busbar trunking module is greater than the unified maintenance time, the adjusted standard operating power parameters are higher.

5. The program control method based on a busbar trunking according to claim 1, wherein Through a preset convergence point determination algorithm, determining the position where all working life curves converge, and the steps for the convergence point include: Setting the life curve at the bottom as the reference curve; For each power parameter point, calculating the life difference between the reference curve and other life curves, and summing them up to obtain the total life difference; After traversing all power parameter points, obtaining the power parameter point with the smallest total life difference, and setting the point corresponding to this power parameter point on the reference curve as the convergence point.

6. The program control method based on a busbar trunking according to claim 1, wherein The working environment data includes ambient temperature and / or ambient humidity, and the power parameters include average working current and / or average working voltage; The first life prediction model is trained through the following steps: Collecting a plurality of first training data, the first training data including a plurality of different power parameters, working environment data, and the corresponding actual working life of the busbar trunking module; Using a fully connected neural network as the model framework of the first life prediction model, taking the power parameters and working environment data in the first training data as the input of the model framework of the first life prediction model, and taking the corresponding actual working life in the first training data as the label of the model framework of the first life prediction model, and training to obtain the first life prediction model in this way.

7. Program control system based on busbar trunking, characterized in that, Including a processor and a memory, at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the program control method based on the busbar trunking as described in any one of claims 1-6.

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