A kind of clutch system life evaluation method, device, electronic equipment and storage medium

Abstract

The application provides a clutch system life evaluation method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence. The clutch system life evaluation method comprises the following steps: according to the current rotating speed of the motor obtained, a loss life prediction model is used to generate the loss life of the clutch system when the clutch system is started at the current rotating speed; and the current residual life of the clutch system is subtracted by the loss life to obtain the residual life of the clutch system after the rotating speed is started. The application can effectively improve the accuracy of the residual life evaluation of the clutch system.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, and more specifically, to a method, apparatus, electronic device, and storage medium for assessing the lifespan of a brake system. Background Technology

[0002] Electric motors play a vital role in industry and daily life as driving devices. The motor control system is responsible for performing various functions such as starting, stopping, and speed regulation of the motor, ensuring that the motor can operate safely and efficiently. Among them, the brake system, as a key component of the motor control system, plays a crucial role in the control and protection of the motor.

[0003] When the servo system is disabled, it means that the servo system stops outputting control signals to the motor, and the motor will be in a disabled state and unable to operate. In this situation, in order to ensure that the motor can stop safely and prevent accidental operation, an emergency stop of the motor is usually achieved through a braking system. However, since the deceleration process of the motor will cause varying degrees of wear to the braking system, the reduced lifespan of the braking system will affect the control effect on the motor. Therefore, it is necessary to test the lifespan of the braking system. Current technology usually relies on manual visual inspection, but the accuracy of manual inspection is low. Summary of the Invention

[0004] The problem addressed by this invention is how to improve the accuracy of estimating the remaining life of a brake system.

[0005] To address the aforementioned problems, this invention provides a method, apparatus, electronic device, and storage medium for assessing the lifespan of a brake system.

[0006] In a first aspect, the present invention provides a method for assessing the lifespan of a brake system, applicable to the brake system of a motor;

[0007] The method for assessing the lifespan of the brake system includes:

[0008] Based on the current speed of the motor, the loss life of the brake system at the starting speed is generated using a preset loss life prediction model.

[0009] The remaining lifespan of the brake system after starting at the specified speed is obtained by subtracting the lost lifespan from the current remaining lifespan of the brake system.

[0010] Optionally, before determining the quantity of the requested information, the method for constructing the loss lifetime prediction model includes:

[0011] The brake system is tested based on multiple preset test motor speeds to obtain the average test loss life of the brake system when it is started at each of the test motor speeds.

[0012] The loss life prediction model is constructed based on all the test motor speeds and the average test loss life corresponding to the test motor speeds.

[0013] Optionally, the step of testing the brake system based on multiple preset test motor speeds to obtain the average test loss life of the brake system when started at each of the test motor speeds includes:

[0014] Based on the test motor speed, the brake system is repeatedly started until the brake system malfunctions, and the total number of times the brake system is started is determined as the total number of starts corresponding to the test motor speed.

[0015] Dividing the preset initial lifespan of the brake system by the total number of starts yields the average test loss lifespan of the brake system when the test motor starts at the specified speed.

[0016] Optionally, constructing the loss lifetime prediction model based on all the test motor speeds and the average test loss lifetime corresponding to the test motor speeds includes:

[0017] Based on all the test motor speeds and the corresponding average test loss life, the fitting coefficient vector is determined by the least squares method.

[0018] The loss lifetime prediction model is constructed based on the fitting coefficient vector.

[0019] Optionally, the fitting coefficient vector includes a first fitting coefficient, a second fitting coefficient, a third fitting coefficient, a fourth fitting coefficient, a fifth fitting coefficient, and a constant term fitting coefficient; the loss lifetime prediction model satisfies:

[0020] Y = a5X 5 +a4X 4 +a3X 3 +a2X 2 +a1X 1 +a0;

[0021] Where Y is the lost life, X is the motor speed, a5 is the fifth fitting coefficient, a4 is the fourth fitting coefficient, a3 is the third fitting coefficient, a2 is the fourth fitting coefficient, a1 is the first fitting coefficient, and a0 is the constant term fitting coefficient.

[0022] Optionally, before generating the loss life of the brake system at the start of the speed based on the obtained current speed of the motor using a preset loss life prediction model, the method further includes:

[0023] Based on the comparison between the current remaining lifespan and the preset lifespan threshold, determine whether to replace the brake system;

[0024] If yes, replace the brake system and update the remaining lifespan to the initial lifespan; otherwise, continue using the brake system.

[0025] Optionally, determining whether to replace the brake system based on a comparison between the remaining lifespan and a preset lifespan threshold includes:

[0026] When the current remaining lifespan is less than or equal to the lifespan threshold, it is determined that the brake system needs to be replaced, and an alarm message indicating that the brake system's lifespan is insufficient is generated.

[0027] If the current remaining lifespan is greater than the lifespan threshold, it is determined that the brake system does not need to be replaced.

[0028] Secondly, the present invention provides a brake system life assessment device, applied to a motor brake system, comprising:

[0029] The prediction module is used to generate the loss life of the brake system at the starting speed based on the current speed of the motor and a preset loss life prediction model.

[0030] The processing module is used to subtract the lost life from the current remaining life of the brake system to obtain the remaining life of the brake system after starting at the specified speed.

[0031] Thirdly, the present invention provides an electronic device, including a memory and a processor;

[0032] The memory is used to store computer programs;

[0033] The processor is configured to implement the brake system life assessment method as described in the first aspect when executing the computer program.

[0034] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the brake system life assessment method as described in the first aspect.

[0035] The beneficial effects of the brake system life assessment method, device, electronic device, and storage medium of the present invention are as follows: Based on the current actual instantaneous speed of the motor, the life loss prediction model can be used to obtain the life loss of the brake system after starting at that speed. This life loss can then be used to determine the impact of brake startup on the brake system's lifespan, i.e., the degree of wear caused by the brake system during motor deceleration after each startup. Furthermore, the health status of the brake system after startup can be accurately assessed based on this life loss. By subtracting the life loss after brake startup from the current remaining lifespan of the brake system, the remaining lifespan after starting the brake system at the current motor speed can be obtained. The remaining lifespan after startup can accurately determine the health status of the brake system. The accurate remaining lifespan of the brake system can be assessed after each startup. Calculating the remaining lifespan after each startup effectively avoids unexpected equipment failures during use. Simultaneously, it allows for timely and accurate judgment and alarm prompts when the remaining lifespan is too low, preventing the continued use of potentially faulty brake systems due to inaccurate lifespan assessments, thus improving the safety and stability of equipment use. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating a method for assessing the lifespan of a brake system according to an embodiment of the present invention.

[0037] Figure 2 This is a schematic diagram of the polynomial fitting curve in an embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of the structure of a brake system life assessment device according to an embodiment of the present invention;

[0039] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0040] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0041] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0042] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0043] It should be noted that the terms "one" and "more" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0044] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0045] In related technologies, for laparoscopic surgical robots, the brake system's function is to ensure that other parts of the robotic arm remain fixed during robot movement, preventing accidental collisions or loss of control. Therefore, the brake system's control needs to work synchronously with the robotic arm's motion control system to ensure the robot's stability and safety. By controlling the brake system, more flexible and precise control can be achieved, ensuring that the brake action is synchronized with the robotic arm's movement, triggering the brake system's opening or closing action as needed. This effectively ensures that the laparoscopic surgical robot remains stable, safe, and efficient during operation. The brake system control logic is as follows: when the servo is enabled, the brake opens and the motor runs; when the servo is deenabled, the brake closes and the motor stops running. When the servo motor is deactivated, the brake closes. This instantaneous deceleration of the motor causes wear on the brake system. Prolonged wear reduces the lifespan of the brake system, potentially leading to brake failure and arm drop. To address this, the wear level of the brake system is usually assessed manually. When the wear reaches a certain point, the brake system is replaced. However, due to the uncertainty of this assessment, timely replacement may be delayed, affecting normal equipment operation. Therefore, it is necessary to accurately determine the remaining lifespan of the brake system and replace it promptly to ensure normal equipment operation.

[0046] To address the problems existing in the aforementioned related technologies, this embodiment provides a method, apparatus, electronic device, and storage medium for assessing the lifespan of a brake system.

[0047] like Figure 1 As shown, an embodiment of the present invention provides a method for assessing the lifespan of a brake system, which is applied to the brake system of a motor.

[0048] The method for assessing the lifespan of the brake system includes:

[0049] S100, based on the current speed of the motor, the loss life of the brake system at the starting speed is generated by a preset loss life prediction model.

[0050] Specifically, the instantaneous rotational speed of the motor is obtained at the current moment. Using a pre-built loss-of-life prediction model, the potential lifespan loss of the brake system after activation at the current instantaneous motor speed is determined. The pre-built loss-of-life prediction model can be obtained through statistical methods such as linear fitting. Based on a pre-built model training dataset, a suitable fitting curve is generated. The coefficients in this fitting curve are then readjusted based on the training dataset. Finally, the curve equation generated from the adjusted fitting curve coefficients serves as the loss-of-life prediction model for the brake system. The training dataset includes different average loss-of-life values ​​corresponding to the brake system after activation at different motor speeds. The coefficients of the curve equation that best fits the training dataset are then obtained. Based on these coefficients, the loss-of-life prediction model is constructed. The final loss-of-life prediction model can accurately predict the precise loss-of-life of the brake system caused by activation of the system at different motor speeds.

[0051] S200, subtract the lost life from the current remaining life of the brake system to obtain the remaining life of the brake system after starting at the specified speed.

[0052] Specifically, the remaining lifespan of the brake system is obtained, and the lifespan loss after starting the brake system at the current speed is subtracted from the current remaining lifespan to obtain the remaining lifespan of the brake system after starting at the current motor speed.

[0053] For example, assuming the initial lifespan of the brake system is 100%, the current instantaneous speed of the motor is 0.02° / ms, and the actual remaining lifespan of the brake system is 80%, it means that the brake system has undergone wear and tear from previous use, and the remaining lifespan is 80% of the initial lifespan. Furthermore, using the lifespan loss prediction model, based on the current motor speed of 0.02° / ms, it is predicted that the lifespan loss caused by starting the brake system may be 15%. Therefore, by calculation, the remaining lifespan of the brake system after starting at the current motor speed is 80% - 15% = 65%.

[0054] In this embodiment, based on the motor's current instantaneous speed, the lifespan loss of the brake system after activation at that speed can be determined using a lifespan loss prediction model. This lifespan loss allows for the assessment of the impact of brake activation on wear on the brake system, specifically the degree of wear caused by the brake system during motor deceleration after each activation. Furthermore, this lifespan loss allows for an accurate assessment of the remaining lifespan of the brake system after activation. By subtracting the lifespan loss after activation from the current remaining lifespan of the brake system, the accurate remaining lifespan after activation at the current motor speed is obtained. This allows for an accurate assessment of the brake system's health status after activation. The accurate remaining lifespan calculation after each activation effectively prevents unexpected equipment failures. Furthermore, accurate lifespan assessment allows for timely and accurate judgment and alarm prompts when the remaining lifespan is too low, preventing the continued use of potentially faulty brake systems due to inaccurate lifespan predictions, thus improving equipment safety and stability.

[0055] Optionally, before determining the quantity of the requested information, the method for constructing the loss lifetime prediction model includes:

[0056] The brake system is tested based on multiple preset test motor speeds to obtain the average test loss life of the brake system when it is started at each of the test motor speeds.

[0057] The loss life prediction model is constructed based on all the test motor speeds and the average test loss life corresponding to the test motor speeds.

[0058] Specifically, based on different motor speeds during motor operation, multiple test motor speeds are selected for testing. These test motor speeds represent the instantaneous motor speeds that may occur when the brake system is started. The brake system is tested at each test speed by controlling the motor to rotate at a specific test motor speed and continuously starting the brake system at that speed until the brake system malfunctions and cannot function properly. The total number of starts of the brake system is recorded. The initial lifespan of the brake system is set to 100%. By dividing 100% by the total number of starts, the average percentage of lifespan lost per start at that test motor speed is obtained, i.e., the average lifespan loss.

[0059] Furthermore, the speed of each test motor is tested using the above method to obtain the average loss life corresponding to each test motor speed. Based on the speeds of all test motors and their corresponding average loss life, a loss life prediction model for the brake system is constructed.

[0060] In this optional embodiment, the brake system is tested according to different test motor speeds to obtain the accurate average loss life corresponding to each test motor speed. The data obtained through testing makes the average loss life more realistic, thereby improving the accuracy of the loss life prediction model built based on the average loss life and the test motor speed, and making the final estimated remaining life more accurate and closer to the true value.

[0061] Optionally, the step of testing the brake system based on multiple preset test motor speeds to obtain the average test loss life of the brake system when started at each of the test motor speeds includes:

[0062] Based on the test motor speed, the brake system is repeatedly started until the brake system malfunctions, and the total number of times the brake system is started is determined as the total number of starts corresponding to the test motor speed.

[0063] Dividing the preset initial lifespan of the brake system by the total number of starts yields the average test loss lifespan of the brake system when the test motor starts at the specified speed.

[0064] For example, assume that all test motor speeds include 0.01° / ms, 0.02° / ms, 0.03° / ms, 0.04° / ms, 0.05° / ms, 0.06° / ms, 0.07° / ms, 0.08° / ms, 0.09° / ms, and 0.1° / ms. The brake system is tested based on each test motor speed, i.e., the brake system is repeatedly started multiple times at a fixed test motor speed until the brake system malfunctions, fails, or cannot start. The total number of starts during this process is calculated, representing the total number of times the brake system can function normally after each start, i.e., the number of times the motor deceleration process can be completed after the brake is closed. The tests showed that 0.01° / ms corresponds to 100 total startups, 0.02° / ms to 90, 0.03° / ms to 80, 0.04° / ms to 70, 0.05° / ms to 60, 0.06° / ms to 50, 0.07° / ms to 40, 0.08° / ms to 30, 0.09° / ms to 20, and 0.1° / ms to 10.

[0065] Furthermore, the average lifespan loss corresponding to each test motor speed is calculated using a preset initial lifespan. Here, the initial lifespan is set to 1, but it can also be set to any value such as 100% or 10. This initial lifespan represents a brand-new, unused brake system. Then, by using the total number of starts corresponding to each test motor speed of 1, the average test lifespan loss after the brake system starts at each test motor speed is obtained. That is, the average test lifespan loss corresponding to 0.01° / ms is 1 / 100, the average test lifespan loss corresponding to 0.02° / ms is 1 / 90, and the average test lifespan loss corresponding to 0.03° / ms is... The average test lifespan loss is 1 / 80 for 0.04° / ms, 1 / 70 for 0.05° / ms, 1 / 60 for 0.06° / ms, 1 / 50 for 0.07° / ms, 1 / 40 for 0.08° / ms, 1 / 30 for 0.09° / ms, and 1 / 20 for 0.1° / ms. When the initial lifespan is set to 100%, the above-mentioned lifespan loss can also be converted into the corresponding percentage gauge.

[0066] In this optional embodiment, the service life of the brake system is tested at different test motor speeds, thereby obtaining the actual average test loss life of the brake system after each start-up for each different test motor speed, thus improving the accuracy and authenticity of the constructed loss life prediction model.

[0067] Optionally, constructing the loss lifetime prediction model based on all the test motor speeds and the average test loss lifetime corresponding to the test motor speeds includes:

[0068] Based on all the test motor speeds and the corresponding average test loss life, the fitting coefficient vector is determined by the least squares method.

[0069] The loss lifetime prediction model is constructed based on the fitting coefficient vector.

[0070] Optionally, the fitting coefficient vector includes a first fitting coefficient, a second fitting coefficient, a third fitting coefficient, a fourth fitting coefficient, a fifth fitting coefficient, and a constant term fitting coefficient; the loss lifetime prediction model satisfies:

[0071] Y = a5X 5 +a4X 4 +a3X 3 +a2X 2 +a1X 1 +a0;

[0072] Where Y is the lost life, X is the motor speed, a5 is the fifth fitting coefficient, a4 is the fourth fitting coefficient, a3 is the third fitting coefficient, a2 is the fourth fitting coefficient, a1 is the first fitting coefficient, and a0 is the constant term fitting coefficient.

[0073] Specifically, modeling is performed based on the speeds of all tested motors and their corresponding average test loss life. First, multiple pre-defined fitting polynomials are constructed, such as first-order, third-order, and fifth-order polynomials. Based on the speeds of all tested motors and their corresponding average loss life, the relationship between the fitting polynomial and the true value is calculated for each polynomial with different coefficients. The coefficients of the fitting polynomial closest to the true value are then used as the fitting coefficient vector. That is, for each polynomial, the estimated polynomial value corresponding to all tested motor speeds is calculated based on different polynomial coefficients. The least squares method is used to calculate the quasi-polynomial coefficients that are closest to the actual average loss life for each polynomial coefficient estimate. This set of polynomial coefficients is then used as the fitting coefficient vector for the final model. The final loss life prediction model is determined based on this fitting coefficient vector. This fitting vector can be obtained by writing a program using MATLAB, manual testing and calculation, or other programming languages. Figure 2As shown, the polynomial finally determined by the above method is used to plot the most suitable fitting curves for the coefficient vectors based on the speed of all tested motors. Here, 1 is the fitting curve corresponding to the first-order polynomial, 2 is the fitting curve corresponding to the third-order polynomial, and 3 is the fitting curve corresponding to the fifth-order polynomial. The fitting curve estimates corresponding to the three fitting curves are compared with the corresponding average test loss life plotted data, and the fifth-order polynomial that is closest to the actual value is selected as the final loss life prediction model.

[0074] For example, a motor speed vector V = [0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.10] is generated based on all tested motor speeds, and a test loss life vector L = [1 / 100, 1 / 90, 1 / 80, 1 / 70, 1 / 60, 1 / 50, 1 / 40, 1 / 30, 1 / 20, 1 / 10] is generated based on all corresponding average test loss lifespans. The optimal value is obtained through polynomial fitting. The fitting coefficient vector of the five polynomials that meet the requirements is [19775.13, -45141.4, 3852.9, -146.5, 2.50], where the fifth fitting coefficient is 19775.13, the fourth fitting coefficient is -45141.4, the third fitting coefficient is 3852.9, the fourth fitting coefficient is -146.5, the first fitting coefficient is 2.5, and the constant term fitting coefficient is 0. The final loss lifetime prediction model is p(v) = 197751.3X 5 -45141.4X 4 +3852.9X 3 -146.5X 2 +2.5X-0.

[0075] In this optional embodiment, a loss life prediction model for the brake system is constructed by using all test motor speeds and corresponding average test loss lifespans obtained from testing. By constructing the model using real test data, the prediction results of the loss life prediction model are closer to the true values, thereby improving the accuracy and reliability of the model prediction.

[0076] Optionally, before generating the loss life of the brake system at the start of the speed based on the obtained current speed of the motor using a preset loss life prediction model, the method further includes:

[0077] Based on the comparison between the current remaining lifespan and the preset lifespan threshold, determine whether to replace the brake system;

[0078] If so, replace the brake system and update the corresponding remaining lifespan to the initial lifespan.

[0079] Optionally, determining whether to replace the brake system based on a comparison between the remaining lifespan and a preset lifespan threshold includes:

[0080] When the current remaining lifespan is less than or equal to the lifespan threshold, it is determined that the brake system needs to be replaced, and an alarm message indicating that the brake system's lifespan is insufficient is generated.

[0081] If the current remaining lifespan is greater than the lifespan threshold, it is determined that the brake system does not need to be replaced.

[0082] Specifically, based on the current remaining lifespan of the brake system, it is compared with a preset lifespan threshold. When the remaining lifespan is less than or equal to the lifespan threshold, it is determined that the brake system may experience an abnormality or malfunction during the next startup. Therefore, the brake system needs to be replaced, and an alarm message indicating insufficient lifespan is generated and sent to the control status to remind the operator to replace the brake system in a timely manner. When the remaining lifespan is greater than the preset threshold, it is determined that the brake system does not need to be replaced. For example, if the remaining lifespan of the current brake system is 5%, while the preset lifespan threshold is 10%, the system needs to be replaced because the remaining lifespan is less than the threshold. An alarm message indicating insufficient lifespan is generated. Upon receiving this alarm, the operator organizes the replacement of the brake system. After replacing the system, the remaining lifespan is adjusted to the initial lifespan, which can be set to 100%. The lifespan threshold is set based on the different lifespan losses caused by the motor speed of each brake system. For example, a threshold of 10% indicates that the maximum lifespan loss during startup may exceed 10%. Therefore, when the remaining lifespan of the brake system is less than 10%, it should be replaced promptly to avoid abnormalities or malfunctions during the next startup, which could damage the equipment.

[0083] In this optional embodiment, by comparing the remaining lifespan of the brake system with its lifespan threshold before the brake system is started, the current state of the ignition system can be accurately determined, and brake systems with insufficient lifespan can be replaced in a timely manner. This can effectively prevent the risk of failure and avoid damage to the equipment caused by unexpected failures of the brake system during use.

[0084] like Figure 3 As shown in the figure, an embodiment of the present invention provides a brake system life assessment device, applied to the brake system of a motor, comprising:

[0085] The prediction module is used to generate the loss life of the brake system at the starting speed based on the current speed of the motor and a preset loss life prediction model.

[0086] The processing module is used to subtract the lost life from the current remaining life of the brake system to obtain the remaining life of the brake system after starting at the specified speed.

[0087] The brake system life assessment device of this embodiment is used to implement the brake system life assessment method as described above. Its advantages over the prior art are the same as the advantages of the brake system life assessment method over the prior art, and will not be repeated here.

[0088] like Figure 4 As shown in the figure, an electronic device provided by an embodiment of the present invention includes a memory and a processor; the memory is used to store a computer program; the processor is used to implement the brake system life assessment method as described above when the computer program is executed.

[0089] Alternatively, an electronic device includes a memory and a processor coupled to the memory; the memory is configured to store a computer program; the processor is configured to perform the following operations when the computer program is executed:

[0090] Get the request information;

[0091] The number of request messages is determined, and the batch size of the batch processing is adjusted according to the number of request messages to obtain the adjusted batch size, wherein the adjusted batch size is positively correlated with the number of request messages;

[0092] Based on the adjusted batch size, the corresponding number of request information entries are input into the model for parallel processing to obtain the inference results corresponding to the request information.

[0093] This invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the brake system life assessment method as described above.

[0094] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations:

[0095] Get the request information;

[0096] The number of request messages is determined, and the batch size of the batch processing is adjusted according to the number of request messages to obtain the adjusted batch size, wherein the adjusted batch size is positively correlated with the number of request messages;

[0097] Based on the adjusted batch size, the corresponding number of request information entries are input into the model for parallel processing to obtain the inference results corresponding to the request information.

[0098] The present invention will now describe electronic devices that can serve as servers or clients of the present invention, which are examples of hardware devices that can be applied to various aspects of the present invention. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0099] Electronic devices include a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM can also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0100] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0101] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for evaluating the service life of a band brake system, characterized by, A band brake system applied to a motor; The band brake system life evaluation method comprises: According to the current speed of the motor obtained, a loss life prediction model is used to generate the loss life of the band brake system when starting at the speed; The current residual life of the band brake system is subtracted from the loss life to obtain the residual life of the band brake system after starting at the speed; The construction method of the loss life prediction model comprises: Based on a plurality of preset test motor speeds, the band brake system is tested to obtain the average test loss life of the band brake system when starting at each test motor speed; The loss life prediction model is constructed according to all the test motor speeds and the average test loss life corresponding to the test motor speeds; The construction of the loss life prediction model according to all the test motor speeds and the average test loss life corresponding to the test motor speeds comprises: According to all the test motor speeds and the average test loss life corresponding to the test motor speeds, a fitting coefficient vector is determined by the least square method; The loss life prediction model is constructed according to the fitting coefficient vector; The fitting coefficient vector comprises a first fitting coefficient, a second fitting coefficient, a third fitting coefficient, a fourth fitting coefficient, a fifth fitting coefficient and a constant term fitting coefficient; the loss life prediction model satisfies: Y = a5X 5 + a4X 4 + a3X 3 + a2X 2 + a1X 1 + a0; wherein Y is the loss life, X is the motor speed, a5 is the fifth fitting coefficient, a4 is the fourth fitting coefficient, a3 is the third fitting coefficient, a2 is the second fitting coefficient, a1 is the first fitting coefficient, and a0 is the constant term fitting coefficient.

2. The method of claim 1, wherein The testing of the band brake system based on a plurality of preset test motor speeds to obtain the average test loss life of the band brake system when starting at each test motor speed comprises: Based on the test motor speed, the band brake system is repeatedly started until the band brake system is abnormal, and the total number of starts of the band brake system is determined as the total start number corresponding to the test motor speed; The initial life of the band brake system is divided by the total start number to obtain the average test loss life of the band brake system when starting at the test motor speed.

3. The method of claim 1, wherein Before the generation of the loss life of the band brake system when starting at the speed according to the current speed of the motor obtained through the preset loss life prediction model, the method further comprises: According to the comparison result of the current residual life and the preset life threshold, it is judged whether the band brake system needs to be replaced; If yes, the band brake system is replaced, and the corresponding residual life is updated to the initial life; if no, the band brake system is continued to be used.

4. The method of claim 3, wherein The judgment of whether the band brake system needs to be replaced according to the comparison result of the residual life and the preset life threshold comprises: When the current residual life is less than or equal to the life threshold, it is judged that the band brake system needs to be replaced, and an alarm prompt of insufficient life of the band brake system is generated; When the current residual life is greater than the life threshold, it is judged that the band brake system does not need to be replaced.

5. A device for evaluating the service life of a band brake system, characterized by The application discloses a brake system applied to a motor, which comprises: a prediction module, configured to generate a loss life of the brake system when the brake system is started at a current rotating speed of the motor according to the current rotating speed of the motor and a preset loss life prediction model; wherein the loss life prediction model is constructed by: testing the brake system based on a plurality of preset test motor rotating speeds to obtain an average test loss life of the brake system when the brake system is started at each test motor rotating speed; constructing the loss life prediction model according to all the test motor rotating speeds and the average test loss life corresponding to the test motor rotating speeds; the construction of the loss life prediction model according to all the test motor rotating speeds and the average test loss life corresponding to the test motor rotating speeds comprises: determining a fitting coefficient vector by a least square method according to all the test motor rotating speeds and the average test loss life corresponding to the test motor rotating speeds; constructing the loss life prediction model according to the fitting coefficient vector; the fitting coefficient vector comprises a first fitting coefficient, a second fitting coefficient, a third fitting coefficient, a fourth fitting coefficient, a fifth fitting coefficient and a constant term fitting coefficient; and the loss life prediction model satisfies: Y = a5X5 + a4X4 + a3X3 + a2X2 + a1X1 + a0; wherein Y is the loss life, X is the motor rotating speed, a5 is the fifth fitting coefficient, a4 is the fourth fitting coefficient, a3 is the third fitting coefficient, a2 is the second fitting coefficient, a1 is the first fitting coefficient, and a0 is the constant term fitting coefficient a processing module, configured to subtract the loss life from a current residual life of the brake system to obtain the residual life of the brake system after the brake system is started at the rotating speed.

6. An electronic device, comprising: comprise a memory and a processor; the memory is configured to store a computer program; the processor is configured to implement the brake system life evaluation method according to any one of claims 1 to 4 when the computer program is executed.

7. A computer readable storage medium characterized in that, The storage medium has a computer program stored thereon, and the brake system life evaluation method according to any one of claims 1 to 4 is implemented when the computer program is executed by the processor.

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