Brake wear monitoring method and device, equipment, storage medium and product

Abstract

The invention provides a brake abrasion monitoring method and device, equipment, a storage medium and a product, and the method comprises the steps that current abrasion data of a vehicle are collected and obtained, and the current abrasion data of the vehicle comprise the current thickness of each friction plate, the current temperature of a brake disc, the current brake pressure and the current rotating speed of each wheel; inputting the current wear data of the vehicle and pre-stored historical wear data into the residual life prediction model to obtain the residual life prediction value and wear rate of each friction plate output by the residual life prediction model; wherein the residual life prediction model is constructed on the basis of a neural network and is obtained through pre-training on the basis of a training set, the training set comprises multiple pieces of training data, and each piece of training data comprises historical wear data of the vehicle, the residual life reference value of each friction plate and the wear rate reference value of each friction plate. According to the scheme, the accuracy and reliability of brake wear monitoring are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle brake control, in particular to a brake wear monitoring method, device, equipment, storage medium and product. BACKGROUND

[0002] The disc brake is the core component of commercial vehicle safety, and the friction plate wear directly affects the braking efficiency. In the prior art, brake wear monitoring relies on a single sensor (such as a micro switch or a mechanical trigger device) to realize threshold alarm, for example, through the linkage of a wear sensor and a controller to realize alarm, or a micro switch and a screw rod structure are used to monitor the wear limit.

[0003] The existing brake wear monitoring has the following defects: on the one hand, only the wear threshold is concerned, and the influence of the running deviation, uneven load and the like in braking on the wear is ignored; on the other hand, the wear trend cannot be predicted to adaptively adjust the braking; and on the other hand, the maintenance needs to rely on manual inspection, and the accuracy and efficiency of the wear monitoring are low.

[0004] Therefore, the accuracy and reliability of the existing brake wear monitoring are poor. SUMMARY

[0005] The present application provides a brake wear monitoring method, device, equipment, storage medium and product to solve the defects of poor accuracy and reliability of the existing brake wear monitoring in the prior art, and realize accurate and reliable brake wear monitoring.

[0006] The present application provides a brake wear monitoring method, comprising the following steps: acquiring current wear data of a vehicle, wherein the current wear data of the vehicle includes the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure and the current rotating speed of each wheel; inputting the current wear data of the vehicle and pre-stored historical wear data into a remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model; wherein the remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, and the training set includes a plurality of training data, and each training data includes historical wear data of a vehicle, a remaining life reference value of each friction plate and a wear rate reference value of each friction plate.

[0007] According to the brake wear monitoring method provided by the present application, after obtaining the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model, the method further comprises: According to the remaining life prediction value and the wear rate of each friction plate, the clamping force of each axle brake caliper is dynamically adjusted through a hydraulic system to balance the wear of the multiple axle brakes, and the braking force of each wheel is dynamically distributed through an electronic braking system.

[0008] According to the brake wear monitoring method provided by the application, after the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model are obtained, the method further comprises: According to the current thickness and the wear rate of each friction plate, the estimated remaining driving mileage of the vehicle is determined. The remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving mileage of the vehicle are displayed on the central large screen in the cab and the vehicle instrument panel. According to the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving mileage of the vehicle, a hierarchical alarm prompt is performed.

[0009] According to the brake wear monitoring method provided by the application, the current wear data of the vehicle is collected, which comprises: The current thickness of each friction plate is collected by a non-contact displacement sensor. The current temperature of the brake disc is collected by a temperature sensor. The current brake pressure is collected by a pressure sensor. The current rotational speed of each wheel is collected by a speed sensor.

[0010] According to the brake wear monitoring method provided by the application, the method further comprises: If the current temperature of the brake disc is greater than a temperature threshold, an auxiliary heat dissipation device is started and / or the continuous braking time is limited.

[0011] According to the brake wear monitoring method provided by the application, before the current wear data of the vehicle and the pre-stored historical wear data are input into the remaining life prediction model, the method further comprises: The current wear data of the vehicle is preprocessed, and the preprocessing comprises at least one of the following: data cleaning, data denoising, data completion, data standardization, and feature extraction.

[0012] The application also provides a brake wear monitoring device, which comprises the following modules: The collection module is used to collect the current wear data of the vehicle, and the current wear data of the vehicle comprises the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure, and the current rotational speed of each wheel. a prediction module configured to input the current wear data of the vehicle and the pre-stored historical wear data into a remaining life prediction model to obtain a remaining life prediction value and a wear rate of each friction plate output by the remaining life prediction model, wherein the remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, and the training set includes a plurality of training data, and each training data includes historical wear data of a vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

[0013] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the brake wear monitoring method according to any one of the preceding aspects when executing the computer program.

[0014] The application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and the computer program implements the brake wear monitoring method according to any one of the preceding aspects when executed by a processor.

[0015] The application further provides a computer program product comprising a computer program, and the computer program implements the brake wear monitoring method according to any one of the preceding aspects when executed by a processor.

[0016] The brake wear monitoring method, device, equipment, storage medium and product provided by the application can realize comprehensive brake wear monitoring by comprehensively considering multiple parameters related to brake wear, i.e., the current wear data of the vehicle, including the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure, and the current rotation speed of each wheel. Further, the current wear data of the vehicle and the pre-stored historical wear data are input into a pre-trained remaining life prediction model to obtain a remaining life prediction value of each friction plate output by the remaining life prediction model, so that accurate and reliable brake wear monitoring can be realized, and brake failure caused by excessive wear can be avoided. Therefore, the scheme of the application improves the accuracy and reliability of brake wear monitoring, and further improves the safety and reliability of the vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0018] Figure 1 is a flowchart of the brake wear monitoring method provided by the application.

[0019] Figure 2 is a structural schematic diagram of the brake wear monitoring device provided by the present application.

[0020] Figure 3 is a structural schematic diagram of the electronic device provided by the present application. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely below in conjunction with the drawings in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0022] It should be noted that the brief description of the terms in the present application is only for the convenience of understanding the subsequently described embodiments, and is not intended to limit the embodiments of the present application. Unless otherwise specified, these terms should be understood according to their ordinary and general meanings.

[0023] The terms "first", "second", and the like in the specification and claims of the present application and the above drawings are used to distinguish similar or similar objects or entities, and do not necessarily mean a specific order or sequence, unless otherwise indicated. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, for example, those other than the order given in the embodiment illustration or description of the present application can be implemented.

[0024] In addition, the terms "include" and "have" and any variations thereof are intended to cover but not exclusive inclusion, for example, a product or device including a series of components does not have to be limited to those components clearly listed, but can include other components not clearly listed or inherent to these products or devices. The term "module" used in the present application refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or a combination of hardware or / and software code capable of performing functions related to the element.

[0025] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The following will be described in conjunction with Figure 1 The brake wear monitoring method of the present application is described.

[0026] Figure 1 is a flowchart of the brake wear monitoring method provided by the present application, asFigure 1 As shown, the method comprises step 101 and step 102.

[0027] Step 101, collecting the current wear data of the vehicle, the current wear data of the vehicle comprising the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure and the current rotation speed of each wheel.

[0028] Step 102, inputting the current wear data of the vehicle and the pre-stored historical wear data into the residual life prediction model to obtain the residual life prediction value and the wear rate of each friction plate output by the residual life prediction model.

[0029] Wherein, the residual life prediction model is constructed based on a neural network and obtained by pre-training based on a training set, the training set comprising a plurality of training data, each training data comprising historical wear data of the vehicle, a residual life reference value of each friction plate and a wear rate reference value of each friction plate.

[0030] In actual application, the execution subject of the brake wear monitoring method can be a brake wear monitoring device, and the brake wear monitoring device can be implemented in various ways, such as through a computer program, for example, application software, etc.; or, for example, a chip, etc. It can also be realized as a medium storing relevant computer programs, such as a U disk, a cloud disk, etc.; or, it can also be realized through an entity device integrated or installed with relevant computer programs, such as a server, a smart device, etc.

[0031] In the following, the brake wear monitoring device is taken as an example of the execution subject of the brake wear monitoring method to illustrate the brake wear monitoring method.

[0032] Specifically, step 101 comprises collecting the current wear data of the vehicle, the current wear data of the vehicle comprising the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure and the current rotation speed of each wheel.

[0033] In practice, the brake is the main component of the vehicle braking system, used to slow down or stop the movement of the vehicle. The brake comprises a plurality of components, such as a brake disc (or a brake drum), a brake caliper, a friction plate, a hydraulic system, etc.

[0034] Among them, the friction plate is a key component in the brake, and for disc brakes, it is usually installed on the brake caliper. The friction plate is made of high-performance friction material and is used to contact the brake disc or brake drum to generate braking force through friction to slow down or stop the vehicle. The friction plate is a consumable part that will gradually wear out with use, and its wear condition directly affects the braking efficiency and safety.

[0035] Wherein, the current thickness of the friction plate refers to the thickness of the friction plate measured at the current time. In practical applications, by monitoring the thickness change of the friction plate in real time, the wear rate can be accurately calculated, and the wear condition of the friction plate can be evaluated. Further, in combination with historical thickness data, the remaining life of the friction plate can be predicted to ensure timely replacement before excessive wear. Further, according to the current thickness of the friction plate, the clamping force of the brake caliper is dynamically adjusted to optimize wear uniformity.

[0036] Wherein, the current temperature of the brake disc refers to the temperature of the brake disc measured at the current time. In practical applications, excessive brake disc temperature can lead to reduced braking efficiency (thermal decay), and the application can take timely cooling measures by monitoring the temperature. Further, excessive brake disc temperature can accelerate the wear of the friction plate, and the wear condition can be more accurately evaluated by considering the brake disc temperature. Further, abnormal brake disc temperature indicates that the brake system may have a fault, such as brake jamming or poor heat dissipation, etc.

[0037] Wherein, the current brake pressure refers to the pressure in the brake caliper hydraulic system measured at the current time. In practical applications, brake pressure directly affects the size of braking force, and by monitoring the pressure, the normality of the braking force can be evaluated. Higher brake pressure can lead to faster wear, and by considering the brake pressure, the wear condition can be more accurately evaluated. Further, according to the brake pressure, the clamping force of the brake caliper is dynamically adjusted to optimize wear uniformity.

[0038] Wherein, the current rotational speed of each wheel refers to the rotational speed of the wheel measured at the current time. In practical applications, by monitoring the wheel speed, the electronic braking system (Electronic Braking System, EBS) can dynamically adjust the braking force distribution of each wheel end to ensure consistent braking efficiency. The difference in rotational speed of different wheels can indicate uneven distribution of braking force, and the rotational speed data can be used to more accurately evaluate the wear condition. Abnormal rotational speed difference can indicate that the brake system has a fault, such as brake jamming or insufficient braking force.

[0039] Optionally, in one possible implementation, the above step 101 comprises: acquiring the current thickness of each friction plate through a non-contact displacement sensor; acquiring the current temperature of the brake disc through a temperature sensor; acquiring the current brake pressure through a pressure sensor; acquiring the current rotational speed of each wheel through a speed sensor.

[0040] In practical applications, a non-contact displacement sensor is installed on the brake caliper to calculate the thickness of each friction plate by measuring the distance change between the friction plate surface and the sensor. For example, the non-contact displacement sensor can be a miniature laser displacement meter, a laser displacement sensor, a capacitive displacement sensor, an electromagnetic displacement sensor, an ultrasonic displacement sensor, etc.

[0041] In practical applications, the temperature sensor can be installed near the surface of the brake disc to directly measure the temperature of the brake disc. For example, the temperature sensor is installed near the brake disc through a fixed support to ensure the stability and accuracy of the measurement. For example, the temperature sensor can be a thermocouple temperature sensor, an infrared temperature sensor, etc.

[0042] In practical applications, the pressure sensor is usually installed in the brake caliper hydraulic system to monitor the pressure in the brake caliper hydraulic system in real time. For example, the pressure sensor can be a strain pressure sensor, a piezoresistive pressure sensor, a capacitive pressure sensor, a piezoelectric pressure sensor, etc.

[0043] In practical applications, the speed sensor is usually installed on the wheel to directly measure the rotational speed of the wheel. For example, the speed sensor can be a wheel speed sensor, an optical speed sensor, a Hall effect speed sensor, etc.

[0044] In one example, the brake wear monitoring device is connected to a multi-sensor fusion system to obtain the current wear data of the vehicle collected by the multi-sensor fusion system. The multi-sensor fusion system includes a wear monitoring unit and a working condition monitoring unit. Specifically, the wear monitoring unit is integrated with a non-contact displacement sensor to collect the current thickness of each friction plate through the non-contact displacement sensor. The working condition monitoring unit is integrated with a temperature sensor, a pressure sensor, and a speed sensor; the current temperature of the brake disc is collected through the temperature sensor; the current brake pressure is collected through the pressure sensor; and the current rotational speed of each wheel is collected through the speed sensor.

[0045] In practical applications, after collecting the current wear data of the vehicle, the current wear data of the vehicle is stored. The pre-stored historical wear data refers to the historical wear data in the historical period before the current time. Specifically, the historical wear data includes the thickness of each friction plate, the temperature of the brake disc, the brake pressure, and the rotational speed of each wheel at each historical time in the historical period.

[0046] It should be noted that the pre-stored historical wear data can provide background information for the wear prediction of the remaining life prediction model, help the remaining life prediction model learn and understand the pattern and trend of wear, and thus improve the accuracy and reliability of the prediction.

[0047] It can be understood that by collecting the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure, and the current rotation speed of each wheel, the wear of the brake can be monitored in real time and accurately. Further, according to the current wear data of the vehicle and the pre-stored historical wear data, the remaining life prediction value of each friction plate is determined.

[0048] Specifically, step 102 comprises: inputting the current wear data of the vehicle and the pre-stored historical wear data into the remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model.

[0049] The remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set. The training set includes a plurality of training data. Each training data includes historical wear data of the vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

[0050] In this embodiment, the current wear data of the vehicle and the pre-stored historical wear data are input into the remaining life prediction model. The current wear data of the vehicle and the pre-stored historical wear data are analyzed by the remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate.

[0051] The remaining life prediction value of the friction plate refers to the expected life of the friction plate before it needs to be replaced and can be expressed in percentage or time. The wear rate refers to the reduction in thickness per unit time.

[0052] In combination with the above description, the present application comprehensively considers a plurality of parameters related to brake wear. Inputting the current wear data of the vehicle into the remaining life prediction model can achieve comprehensive brake wear monitoring.

[0053] It can be understood that the historical wear data records the thickness change of the friction plate at different time points and reflects the wear trend and rate. By inputting the pre-stored historical wear data into the remaining life prediction model, the wear trend of the friction plate (such as linear wear, accelerated wear, etc.) can be understood, so that the future wear condition can be more accurately predicted.

[0054] For example, the neural network can be a deep feedforward neural network (Deep Feedforward Neural Network), a convolutional neural network (Convolutional Neural Network, CNN), a recurrent neural network (Recurrent Neural Network, RNN), etc., which is not limited in the present application.

[0055] For the training process of the remaining life prediction model, before step 101, the above brake wear monitoring method further includes, in an example: a training set is constructed, the training set including a plurality of training data, each training data including historical wear data of the vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate; an initial remaining life prediction model is constructed based on a neural network; the initial remaining life prediction model is trained based on the training set until the remaining life prediction model is obtained.

[0056] It can be understood that the remaining life prediction model is constructed based on a neural network and obtained by pre-training based on the training set. Therefore, by inputting the current wear data of the vehicle and the pre-stored historical wear data into the remaining life prediction model, accurate remaining life prediction values and wear rates of each friction plate can be obtained, precise and reliable brake wear monitoring can be achieved, and brake failure caused by excessive wear can be avoided.

[0057] In actual application, after obtaining the remaining life prediction value of each friction plate output by the remaining life prediction model, brake adaptive control is performed according to the remaining life prediction value and the wear rate of each friction plate.

[0058] Specifically, in a possible implementation, after step 102, the above brake wear monitoring method further includes: According to the remaining life prediction value and the wear rate of each friction plate, the clamping force of each axle brake caliper is dynamically adjusted by a hydraulic system to balance the wear of the multiple axle brakes, and the brake force of each wheel is dynamically distributed by an electronic brake system.

[0059] In actual application, the target clamping force of each axle brake caliper is calculated according to the remaining life prediction value and the wear rate of each friction plate. The clamping force of each axle brake caliper is adjusted by the hydraulic system to reach the calculated target clamping force. It can be understood that by dynamically adjusting the clamping force of each axle brake caliper, the wear of the multiple axle brakes can be balanced, and the overall service life of the brake can be prolonged.

[0060] In an example, for each axle, the average wear rate of all friction plates on the entire axle is calculated to obtain the wear rate of the axle, which is used to evaluate the wear condition of the axle. For example, if the wear rate of a certain axle is high, the clamping force of the axle is appropriately reduced to slow down the wear rate. If the wear rate of a certain axle is low, the clamping force of the axle is appropriately increased to optimize the wear uniformity.

[0061] In practical applications, the braking force of each wheel is dynamically allocated by an electronic brake system (EBS) to ensure the consistency of the braking efficiency of each wheel and improve the braking performance and safety of the vehicle. The EBS system monitors the running state of the vehicle (such as speed, load, road conditions, etc.) in real time. According to the real-time monitoring data and the remaining life prediction value, the EBS system dynamically adjusts the braking force allocation of each wheel.

[0062] In one example, a brake system digital twin model and a finite element analysis model are established. The brake system digital twin model is used to simulate different braking force allocation schemes in real time to find the optimal braking force allocation scheme to improve the braking performance and safety of the vehicle. The finite element analysis model is used to predict the microstructure evolution of the friction material to predict its service life in advance and avoid brake failure caused by excessive wear of the friction material.

[0063] In this embodiment, according to the remaining life prediction value and the wear rate of each friction plate, the clamping force of each axle brake caliper is dynamically adjusted by the hydraulic system to balance the wear of multiple axle brakes, and the braking force of each wheel is dynamically allocated by the electronic brake system, thereby prolonging the overall service life of the brake and improving the safety and reliability of the brake system.

[0064] In addition, in one possible implementation, after the above step 102, the brake wear monitoring method further includes: determining the estimated remaining driving distance of the vehicle according to the current thickness and wear rate of each friction plate; displaying the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle on the central large screen in the cab and the vehicle instrument panel; performing a hierarchical alarm prompt according to the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle.

[0065] The estimated remaining driving distance refers to the distance that the vehicle can continue to travel before replacing the friction plate, which is calculated according to the remaining life prediction value and the wear rate of each friction plate.

[0066] Specifically, the estimated remaining driving distance of the vehicle is calculated according to the current thickness and wear rate of each friction plate. In one example, the ratio of the current thickness and wear rate of each friction plate is calculated to obtain the estimated remaining driving distance corresponding to each friction plate. The minimum value of the estimated remaining driving distances corresponding to all friction plates is taken as the estimated remaining driving distance of the vehicle.

[0067] Further, the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle are displayed on the center screen in the cab and the vehicle instrument panel. In an example, the brake wear monitoring device transmits the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle to the center screen in the cab and the vehicle instrument panel through the CAN bus, and the center screen in the cab and the vehicle instrument panel visually display the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle.

[0068] Further, according to the remaining life prediction value, wear rate, and estimated remaining driving distance of each friction plate, different levels of alarm prompts are automatically issued. For example, different alarm value ranges can be set, and according to the alarm value range to which the remaining life prediction value, wear rate, and estimated remaining driving distance of each friction plate belong, the level of the current alarm prompt is determined, and the alarm of that level is performed. For different levels of alarm, different alarm modes can be implemented, such as audible and visual alarms, alarm light always on, voice prompts, etc.

[0069] In this embodiment, according to the remaining life prediction value and wear rate of each friction plate, the estimated remaining driving distance of the vehicle is determined, and these information are displayed on the center screen in the cab and the vehicle instrument panel, and at the same time, a hierarchical alarm prompt is performed, which intuitively and quantitatively displays the braking state, improves the decision-making efficiency of the driver, reduces the driving risk caused by excessive wear, and improves the safety and reliability of the braking system.

[0070] In addition, in a possible implementation, the above brake wear monitoring method further comprises: If the current temperature of the brake disc is greater than the temperature threshold, the auxiliary cooling device is started and / or the continuous braking time is limited.

[0071] In commercial vehicle braking systems, temperature management of the brake disc is a key safety feature. If the temperature of the brake disc exceeds the temperature threshold, it may cause a decrease in braking efficiency (thermal recession), deformation or damage of the brake disc. Therefore, measures need to be taken to control the temperature of the brake disc to ensure the safety and reliability of the braking system.

[0072] The auxiliary cooling device is an additional cooling system for reducing the temperature of the brake disc. The auxiliary cooling device quickly reduces the temperature of the brake disc through additional cooling measures such as fans, cooling liquid injection, etc., thereby avoiding the decrease in braking efficiency caused by high temperature.

[0073] The limiting of the continuous braking duration refers to limiting the number of times or the duration of continuous braking of the vehicle within a certain time. By limiting the continuous braking, the heat accumulation of the brake disc is reduced, and the temperature is prevented from being too high to ensure that the braking system operates within a safe temperature range and avoids brake failure due to overheating.

[0074] In the embodiment, if the current temperature of the brake disc is greater than the temperature threshold, the auxiliary heat dissipation device is started and / or the continuous braking duration is limited, so that the temperature of the brake disc can be effectively controlled, and the safety and reliability of the braking system are ensured.

[0075] In addition, in a possible implementation, before the step 102, the brake wear monitoring method further includes: The current wear data of the vehicle is preprocessed, and the preprocessing includes at least one of data cleaning, data denoising, data completion, data standardization, and feature extraction.

[0076] In the embodiment, after the current wear data of the vehicle is collected, the current wear data of the vehicle is preprocessed, so that the accuracy and reliability of the current wear data can be effectively ensured, reliable support is provided for subsequent brake wear monitoring, and the accuracy and reliability of the brake wear monitoring are improved.

[0077] In addition, in a possible implementation, the brake monitoring method further includes: After the friction plate is replaced, the current thickness of the friction plate is set as the initial thickness.

[0078] In the embodiment, after the friction plate is replaced, the current thickness of the friction plate is set as the initial thickness, without manual calibration, so that the system can accurately monitor and predict the wear condition of the new friction plate, optimize the braking force distribution, improve the system reliability, optimize the maintenance plan, reduce the maintenance cost, and improve the safety and reliability of the braking system.

[0079] In addition, in a possible implementation, the brake wear monitoring method further includes: The vibration signal and the noise signal between the friction plate and the brake disc are collected. The wear state of each friction plate is analyzed by analyzing the frequency spectrum characteristics of the vibration signal and the noise signal.

[0080] In actual braking, the friction between the friction plate and the brake disc generates vibration and noise. The vibration signal and the noise signal contain rich information reflecting the wear condition of the brake. By installing vibration sensors and acoustic sensors on the vehicle, the vibration and noise signals can be collected in real time, and frequency spectrum analysis is performed to determine the wear state of each friction plate.

[0081] The brake wear monitoring method provided by the embodiment comprehensively considers multiple parameters related to brake wear to achieve comprehensive brake wear monitoring by acquiring current wear data of the vehicle, which includes the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure and the current rotating speed of each wheel. Further, the current wear data of the vehicle and the prestored historical wear data are input into the pre-trained remaining life prediction model to obtain the remaining life prediction value of each friction plate output by the remaining life prediction model, so that accurate and reliable brake wear monitoring can be achieved to avoid brake failure caused by excessive wear. Therefore, the scheme of the embodiment improves the accuracy and reliability of brake wear monitoring, and further improves the safety and reliability of the vehicle.

[0082] The brake wear monitoring device provided by the application is described below, and the brake wear monitoring device described below can be referred to in correspondence with the brake wear monitoring method described above.

[0083] Figure 2 is a structural schematic diagram of the brake wear monitoring device provided by the application, as Figure 2 shown, the brake wear monitoring device includes an acquisition module 21 and a prediction module 22.

[0084] The acquisition module 21 is configured to acquire current wear data of the vehicle, which includes the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure and the current rotating speed of each wheel.

[0085] The prediction module 22 is configured to input the current wear data of the vehicle and the prestored historical wear data into a remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model.

[0086] The remaining life prediction model is constructed based on a neural network and obtained by pre-training based on a training set. The training set includes multiple training data, and each training data includes historical wear data of the vehicle, a remaining life reference value of each friction plate and a wear rate reference value of each friction plate.

[0087] In actual application, the brake wear monitoring device can be implemented in multiple ways, such as through a computer program, for example, application software, etc.; or, for example, a chip, etc. It can also be implemented as a medium storing a related computer program, for example, a U disk, a cloud disk, etc.; or, it can also be implemented through an entity device integrated or installed with a related computer program, such as a server, a smart device, etc.

[0088] Specifically, the collection module 21 is configured to collect current wear data of the vehicle, the current wear data of the vehicle including a current thickness of each friction plate, a current temperature of the brake disc, a current brake pressure, and a current rotating speed of each wheel.

[0089] In practice, the brake is a main component of the vehicle braking system, used to slow down or stop the movement of the vehicle. The brake includes multiple components, such as a brake disc (or brake drum), a brake caliper, a friction plate, a hydraulic system, etc.

[0090] Among them, the friction plate is a key component in the brake, and is usually installed on the brake caliper for disc brakes. The friction plate is made of high-performance friction material and is used to contact the brake disc or brake drum to generate braking force through friction to slow down or stop the vehicle. The friction plate is a consumable part that will gradually wear out with use, and its wear condition directly affects the braking efficiency and safety.

[0091] Among them, the current thickness of the friction plate refers to the thickness of the friction plate measured at the current time. In practical applications, by monitoring the thickness change of the friction plate in real time, the wear rate can be accurately calculated, and the wear condition of the friction plate can be evaluated. Further, in combination with historical thickness data, the remaining life of the friction plate can be predicted to ensure timely replacement before excessive wear. Further, according to the current thickness of the friction plate, the clamping force of the brake caliper is dynamically adjusted to optimize wear uniformity.

[0092] Among them, the current temperature of the brake disc refers to the temperature of the brake disc measured at the current time. In practical applications, excessively high brake disc temperature can lead to a decrease in braking efficiency (thermal decay), and the application can take timely cooling measures by monitoring the temperature. Further, excessively high brake disc temperature can accelerate the wear of the friction plate, and the wear condition can be more accurately evaluated by considering the brake disc temperature. Further, abnormal brake disc temperature indicates that the braking system may have a fault, such as brake jamming or poor heat dissipation, etc.

[0093] Among them, the current brake pressure refers to the pressure in the brake caliper hydraulic system measured at the current time. In practical applications, the brake pressure directly affects the size of the braking force, and the pressure can be monitored to evaluate whether the braking force is normal. Higher brake pressure can lead to faster wear, and the wear condition can be more accurately evaluated by considering the brake pressure. Further, according to the brake pressure, the clamping force of the brake caliper is dynamically adjusted to optimize wear uniformity.

[0094] wherein the current rotational speed of each wheel refers to the rotational speed of the wheel measured at the current time. In practical applications, by monitoring the rotational speed of the wheels, the electronic braking system (EBS) can dynamically adjust the distribution of braking force at each wheel end, ensuring consistent braking efficiency. Differences in rotational speed of different wheels may indicate uneven distribution of braking force, and rotational speed data can be used to more accurately assess wear and tear. Abnormal rotational speed differences may indicate a fault in the braking system, such as brake sticking or insufficient braking force.

[0095] Optionally, in a possible implementation, the collection module 21 is specifically used for: collecting the current thickness of each friction plate through a non-contact displacement sensor; collecting the current temperature of the brake disc through a temperature sensor; collecting the current brake pressure through a pressure sensor; collecting the current rotational speed of each wheel through a speed sensor.

[0096] In practical applications, a non-contact displacement sensor is installed on the brake caliper, and the thickness of each friction plate is calculated by measuring the change in distance between the friction plate surface and the sensor. For example, the non-contact displacement sensor can be a micro-laser displacement meter, a laser displacement sensor, a capacitive displacement sensor, an electromagnetic displacement sensor, an ultrasonic displacement sensor, etc.

[0097] In practical applications, the temperature sensor can be installed near the surface of the brake disc to directly measure the temperature of the brake disc. For example, the temperature sensor is installed near the brake disc through a fixed support to ensure the stability and accuracy of the measurement. For example, the temperature sensor can be a thermocouple temperature sensor, an infrared temperature sensor, etc.

[0098] In practical applications, the pressure sensor is usually installed in the brake caliper hydraulic system to monitor the pressure in the brake caliper hydraulic system in real time. For example, the pressure sensor can be a strain pressure sensor, a piezoresistive pressure sensor, a capacitive pressure sensor, a piezoelectric pressure sensor, etc.

[0099] In practical applications, the speed sensor is usually installed on the wheel to directly measure the rotational speed of the wheel. For example, the speed sensor can be a wheel speed sensor, an optical speed sensor, a Hall effect speed sensor, etc.

[0100] In an example, the acquisition module 21 is connected with the multi-sensor fusion system to acquire the current wear data of the vehicle collected by the multi-sensor fusion system. The multi-sensor fusion system includes a wear monitoring unit and a working condition monitoring unit. Specifically, the wear monitoring unit is integrated with a non-contact displacement sensor, and the current thickness of each friction plate is acquired by the non-contact displacement sensor. The working condition monitoring unit is integrated with a temperature sensor, a pressure sensor, and a speed sensor; the current temperature of the brake disc is acquired by the temperature sensor; the current brake pressure is acquired by the pressure sensor; and the current rotating speed of each wheel is acquired by the speed sensor.

[0101] In actual application, after the current wear data of the vehicle is acquired, the current wear data of the vehicle is stored. The pre-stored historical wear data refers to the historical wear data in the historical period before the current time. Specifically, the historical wear data includes the thickness of each friction plate, the temperature of the brake disc, the brake pressure, and the rotating speed of each wheel at each historical time in the historical period.

[0102] It should be noted that the pre-stored historical wear data can provide background information for the wear prediction of the remaining life prediction model, help the remaining life prediction model learn and understand the pattern and trend of wear, and thus improve the prediction accuracy and reliability.

[0103] It can be understood that by acquiring the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure, and the current rotating speed of each wheel, the wear condition of the brake can be monitored in real time and accurately. Further, according to the current wear data of the vehicle and the pre-stored historical wear data, the remaining life prediction value of each friction plate is determined.

[0104] Specifically, the prediction module 22 is configured to input the current wear data of the vehicle and the pre-stored historical wear data into the remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model.

[0105] The remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set. The training set includes multiple training data, and each training data includes historical wear data of a vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

[0106] In this embodiment, the current wear data of the vehicle and the pre-stored historical wear data are input into the remaining life prediction model, and the current wear data of the vehicle and the pre-stored historical wear data are analyzed by the remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate.

[0107] The remaining life prediction value of the friction plate refers to the expected life of the friction plate before it needs to be replaced and can be expressed in percentage or time. The wear rate refers to the reduction in thickness per unit time.

[0108] In combination with the above description, the present application comprehensively considers multiple parameters related to brake wear. By inputting the current wear data of the vehicle into the remaining life prediction model, comprehensive brake wear monitoring can be achieved.

[0109] It can be understood that the historical wear data records the thickness changes of the friction plate at different time points, reflecting the wear trend and rate. By inputting the pre-stored historical wear data into the remaining life prediction model, the wear trend of the friction plate (such as linear wear, accelerated wear, etc.) can be understood, thereby more accurately predicting future wear conditions.

[0110] For example, the neural network can be a deep feedforward neural network (Deep Feedforward Neural Network), a convolutional neural network (Convolutional Neural Network, CNN), a recurrent neural network (Recurrent Neural Network, RNN), etc., which is not limited in the present application.

[0111] For the training process of the remaining life prediction model, in an example, the above brake wear monitoring device further comprises a training module, which is configured to: construct a training set, the training set comprising a plurality of training data, each training data comprising historical wear data of the vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate; construct an initial remaining life prediction model based on the neural network; train the initial remaining life prediction model based on the training set until the remaining life prediction model is obtained.

[0112] It can be understood that the remaining life prediction model is constructed based on the neural network and obtained by pre-training based on the training set. Therefore, by inputting the current wear data of the vehicle and the pre-stored historical wear data into the remaining life prediction model, accurate remaining life prediction values and wear rates of each friction plate can be obtained, thereby achieving precise and reliable brake wear monitoring and avoiding brake failure due to excessive wear.

[0113] In actual application, after obtaining the remaining life prediction value of each friction plate output by the remaining life prediction model, brake adaptive control is performed according to the remaining life prediction value and the wear rate of each friction plate.

[0114] Specifically, in one possible implementation, the brake wear monitoring device further includes: a brake control module configured to dynamically adjust the clamping force of each axle brake caliper through a hydraulic system according to the remaining life prediction value and the wear rate of each friction plate, to balance the wear of the multiple axle brakes, and dynamically distribute the braking force of each wheel through an electronic brake system.

[0115] In actual applications, the target clamping force of each axle brake caliper is calculated according to the remaining life prediction value and the wear rate of each friction plate. The clamping force of each axle brake caliper is adjusted through the hydraulic system to reach the calculated target clamping force. It can be understood that by dynamically adjusting the clamping force of each axle brake caliper, the wear of the multiple axle brakes can be balanced, and the overall service life of the brake can be prolonged.

[0116] In an example, for each axle, the average wear rate of all friction plates on the entire axle is calculated to obtain the wear rate of the axle, which is used to evaluate the wear of the axle. For example, if the wear rate of a certain axle is high, the clamping force of the axle is appropriately reduced to slow down the wear rate. If the wear rate of a certain axle is low, the clamping force of the axle is appropriately increased to optimize the wear uniformity.

[0117] In actual applications, the braking force of each wheel is dynamically distributed through the electronic brake system (EBS) to ensure the consistency of the braking performance of each wheel and improve the braking performance and safety of the vehicle. The EBS system monitors the driving state of the vehicle (such as speed, load, road conditions, etc.) in real time. According to the real-time monitoring data and the remaining life prediction value, the EBS system dynamically adjusts the distribution of the braking force of each wheel.

[0118] In an example, a digital twin model of the brake system and a finite element analysis model are established. The digital twin model of the brake system is used to simulate different braking force distribution schemes in real time, to find the optimal braking force distribution scheme, to improve the braking performance and safety of the vehicle. The finite element analysis model is used to predict the microstructure evolution of the friction material, so as to judge the service life in advance and avoid brake failure caused by excessive wear of the friction material.

[0119] In this embodiment, the clamping force of each axle brake caliper is dynamically adjusted through the hydraulic system according to the remaining life prediction value and the wear rate of each friction plate, to balance the wear of the multiple axle brakes, and the braking force of each wheel is dynamically distributed through the electronic brake system, which prolongs the overall service life of the brake and improves the safety and reliability of the brake system.

[0120] In addition, in one possible implementation, the brake wear monitoring device further includes: a calculation module configured to determine the estimated remaining driving distance of the vehicle according to the current thickness and the wear rate of each friction plate. a display module configured to display the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle on a center console large screen and a vehicle instrument panel in a driver's cabin; an alarm module configured to perform hierarchical alarm prompting according to the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle.

[0121] The estimated remaining driving distance refers to the distance that the vehicle can continue to travel before the friction plates are replaced, which is calculated according to the remaining life prediction value and the wear rate of each friction plate.

[0122] Specifically, the estimated remaining driving distance of the vehicle is calculated according to the current thickness and the wear rate of each friction plate. In one example, the ratio of the current thickness to the wear rate of each friction plate is calculated to obtain the estimated remaining driving distance corresponding to each friction plate. The minimum value among the estimated remaining driving distances corresponding to all the friction plates is taken as the estimated remaining driving distance of the vehicle.

[0123] Further, the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle are displayed on the center console large screen and the vehicle instrument panel in the driver's cabin. In one example, the brake wear monitoring device transmits the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle to the center console large screen and the vehicle instrument panel in the driver's cabin through a CAN bus, and the center console large screen and the vehicle instrument panel visually display the remaining life prediction value of each friction plate, the wear rate of each friction plate, and the estimated remaining driving distance of the vehicle.

[0124] Further, different levels of alarm prompts are automatically issued according to the remaining life prediction value, the wear rate, and the estimated remaining driving distance of each friction plate. For example, different alarm value ranges can be set, and the level of the current alarm prompt is determined according to the alarm value range to which the remaining life prediction value, the wear rate, and the estimated remaining driving distance of each friction plate belong, and the alarm of the level is performed. For example, different levels of alarms can be realized through different alarm modes, such as audible and visual alarms, alarm light constant on, voice prompts, etc.

[0125] In this embodiment, the estimated remaining driving distance of the vehicle is determined according to the remaining life prediction value and the wear rate of each friction plate, and these information are displayed on the center console large screen and the vehicle instrument panel in the driver's cabin, and hierarchical alarm prompting is performed, which intuitively and quantitatively displays the braking state, improves the decision-making efficiency of the driver, reduces the driving risk caused by excessive wear, and improves the safety and reliability of the braking system.

[0126] In addition, in a possible implementation, the brake wear monitoring method further includes: If the current temperature of the brake disc is greater than the temperature threshold, starting the auxiliary heat dissipation device and / or limiting the continuous braking duration.

[0127] In a commercial vehicle braking system, the temperature management of the brake disc is a key safety feature. If the temperature of the brake disc exceeds the temperature threshold, it may cause a decrease in braking efficiency (thermal decay), deformation or damage of the brake disc. Therefore, measures need to be taken to control the temperature of the brake disc to ensure the safety and reliability of the braking system.

[0128] The auxiliary heat dissipation device is an additional cooling system for reducing the temperature of the brake disc. The auxiliary heat dissipation device quickly reduces the temperature of the brake disc through additional cooling measures such as fans, cooling liquid injection, etc., thereby avoiding the decrease in braking efficiency caused by high temperature.

[0129] The continuous braking duration limit refers to limiting the number of times or duration of continuous braking of the vehicle within a certain period of time. By limiting continuous braking, the heat accumulation of the brake disc is reduced to prevent the temperature from being too high, so as to ensure that the braking system operates within a safe temperature range and avoid brake failure caused by overheating.

[0130] In this embodiment, if the current temperature of the brake disc is greater than the temperature threshold, the auxiliary heat dissipation device is started and / or the continuous braking duration is limited, which can effectively control the temperature of the brake disc and ensure the safety and reliability of the braking system.

[0131] In addition, in a possible implementation, the brake wear monitoring device further includes: The preprocessing module is configured to preprocess the current wear data of the vehicle, and the preprocessing includes at least one of data cleaning, data denoising, data completion, data standardization, and feature extraction.

[0132] In this embodiment, after obtaining the current wear data of the vehicle, the current wear data of the vehicle is preprocessed, which can effectively ensure the accuracy and reliability of the current wear data, provide reliable support for subsequent brake wear monitoring, and improve the accuracy and reliability of brake wear monitoring.

[0133] In addition, in a possible implementation, the brake wear monitoring device further includes: The setting module is configured to set the current thickness of the friction plate to the initial thickness after replacing the friction plate.

[0134] In this embodiment, after replacing the friction plate, the current thickness of the friction plate is set as the initial thickness, without manual calibration, so as to ensure that the system can accurately monitor and predict the wear condition of the new friction plate, optimize the brake force distribution, improve the system reliability, optimize the maintenance plan, reduce the maintenance cost, and improve the safety and reliability of the brake system.

[0135] In addition, in a possible implementation, the brake wear monitoring device further comprises an inversion module, and the inversion module is configured to: collect vibration signals and noise signals between the friction plate and the brake disc; analyze the frequency spectrum characteristics of the vibration signals and the noise signals by vibration acoustics to invert the wear state of each friction plate.

[0136] During actual braking, friction between the friction plate and the brake disc will generate vibration and noise. The vibration signals and the noise signals contain rich information reflecting the wear condition of the brake. By installing vibration sensors and acoustic sensors on the vehicle, the vibration and noise signals can be collected in real time, and spectrum analysis can be performed to determine the wear state of each friction plate.

[0137] The brake wear monitoring device provided in this embodiment collects the current wear data of the vehicle by the collection module, and the current wear data of the vehicle includes the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure, and the current rotating speed of each wheel, that is, the present application comprehensively considers multiple parameters related to the wear of the brake to achieve comprehensive brake wear monitoring. Further, the prediction module inputs the current wear data of the vehicle and the pre-stored historical wear data into the pre-trained residual life prediction model to obtain the residual life prediction value of each friction plate output by the residual life prediction model, so as to achieve accurate and reliable brake wear monitoring and avoid brake failure due to excessive wear. Therefore, the scheme of this embodiment improves the accuracy and reliability of brake wear monitoring, and further improves the safety and reliability of the vehicle.

[0138] Figure 3 is a structural schematic diagram of an electronic device provided by the present application, as Figure 3As shown, the electronic device can include a processor 310, a communications interface 320, a memory 330, and a communications bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other through the communications bus 340. The processor 310 can invoke the logical instructions in the memory 330 to execute the brake wear monitoring method, which includes: collecting current wear data of the vehicle, the current wear data of the vehicle including the current thickness of each friction plate, the current temperature of the brake disc, the current brake pressure, and the current rotational speed of each wheel; inputting the current wear data of the vehicle and the pre-stored historical wear data into a remaining life prediction model to obtain the remaining life prediction value and the wear rate of each friction plate output by the remaining life prediction model; wherein the remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, and the training set includes multiple training data, each training data including historical wear data of the vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

[0139] In addition, the logical instructions in the memory 330 described above can be implemented in the form of a software functional unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0140] In another aspect, the present application also provides a computer program product, which comprises a computer program stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to perform the brake wear monitoring method provided by the above-mentioned methods, which comprises: collecting current wear data of a vehicle, wherein the current wear data of the vehicle comprises current thickness of each friction plate, current temperature of a brake disc, current brake pressure, and current rotation speed of each wheel; inputting the current wear data of the vehicle and pre-stored historical wear data into a remaining life prediction model to obtain a remaining life prediction value and a wear rate of each friction plate output by the remaining life prediction model; wherein the remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, and the training set comprises a plurality of training data, and each training data comprises historical wear data of a vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

[0141] In another aspect, the present application also provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program can be executed by a processor to implement the brake wear monitoring method provided by the above-mentioned methods, which comprises: collecting current wear data of a vehicle, wherein the current wear data of the vehicle comprises current thickness of each friction plate, current temperature of a brake disc, current brake pressure, and current rotation speed of each wheel; inputting the current wear data of the vehicle and pre-stored historical wear data into a remaining life prediction model to obtain a remaining life prediction value and a wear rate of each friction plate output by the remaining life prediction model; wherein the remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, and the training set comprises a plurality of training data, and each training data comprises historical wear data of a vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

[0142] The device embodiments described above are only schematic, wherein the units shown as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0143] Those skilled in the art can clearly understand the technical solutions of the various embodiments from the above description of the embodiments, and the various embodiments can be implemented by means of software with the necessary general hardware platforms, and of course, can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, and the like, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0144] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features therein; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A brake wear monitoring method, characterized by, The method comprises the following steps: obtaining current wear data of the vehicle, the current wear data of the vehicle comprising current thickness of each friction plate, current temperature of the brake disc, current brake pressure, and current rotating speed of each wheel; inputting the current wear data of the vehicle and the pre-stored historical wear data into a residual life prediction model to obtain residual life prediction values and wear rates of each friction plate output by the residual life prediction model; wherein the residual life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, the training set comprising a plurality of training data, each training data comprising historical wear data of the vehicle, residual life reference values of each friction plate, and wear rate reference values of each friction plate.

2. The brake wear monitoring method according to claim 1, characterized by, After obtaining the residual life prediction values and wear rates of each friction plate output by the residual life prediction model, the method further comprises: According to the residual life prediction values and wear rates of each friction plate, dynamically adjusting the clamping force of each axle brake caliper through the hydraulic system to balance the wear of the plurality of axle brakes, and dynamically distributing the braking force of each wheel through the electronic braking system.

3. The brake wear monitoring method according to claim 1, characterized by, After obtaining the residual life prediction values and wear rates of each friction plate output by the residual life prediction model, the method further comprises: determining the estimated remaining driving distance of the vehicle according to the current thickness and wear rate of each friction plate; displaying the residual life prediction values of each friction plate, the wear rates of each friction plate, and the estimated remaining driving distance of the vehicle on the central large screen in the cab and the vehicle instrument panel; According to the residual life prediction values of each friction plate, the wear rates of each friction plate, and the estimated remaining driving distance of the vehicle, performing hierarchical alarm prompting.

4. The brake wear monitoring method according to claim 1, characterized by, The method further comprises: acquiring the current thickness of each friction plate through a non-contact displacement sensor; acquiring the current temperature of the brake disc through a temperature sensor; acquiring the current brake pressure through a pressure sensor; acquiring the current rotating speed of each wheel through a speed sensor.

5. The brake wear monitoring method according to claim 1, characterized by, The method further comprises: if the current temperature of the brake disc is greater than a temperature threshold, starting an auxiliary heat dissipation device and / or limiting the continuous braking time.

6. The brake wear monitoring method according to any one of claims 1 to 5, characterized in that, Before inputting the current wear data of the vehicle and the pre-stored historical wear data into the residual life prediction model, the method further comprises: preprocessing the current wear data of the vehicle, the preprocessing comprising at least one of the following: data cleaning, data denoising, data completion, data standardization, and feature extraction.

7. A brake wear monitoring device, characterized by The method comprises the following steps: an acquisition module configured to acquire current wear data of the vehicle, the current wear data of the vehicle comprising current thickness of each friction plate, current temperature of the brake disc, current brake pressure, and current rotating speed of each wheel; A prediction module is configured to input the current wear data of the vehicle and the pre-stored historical wear data into a remaining life prediction model to obtain a remaining life prediction value and a wear rate of each friction plate output by the remaining life prediction model; wherein the remaining life prediction model is constructed based on a neural network and is a model obtained by pre-training based on a training set, and the training set includes a plurality of training data, and each training data includes historical wear data of a vehicle, a remaining life reference value of each friction plate, and a wear rate reference value of each friction plate.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor implements the brake wear monitoring method according to any one of claims 1-6 when executing the computer program. 9.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the brake wear monitoring method according to any one of claims 1-6.

10. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the brake wear monitoring method according to any one of claims 1-6. The computer program, when executed by the processor, implements the brake wear monitoring method according to any one of claims 1-6.

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