Prediction system for performance degradation of automobile shock absorber

Abstract

The invention discloses a system for predicting performance degradation of an automobile shock absorber, and relates to the technical field of shock absorption, and the system comprises the steps: obtaining a historical monitoring record of a preset shock absorber, matching a record under a first historical node from a plurality of sets of records, carrying out the analysis according to a preset hardness strategy to obtain first historical hardness under the node, and carrying out the prediction of the performance degradation of the shock absorber. Analyzing the corresponding relation between the first historical node and the hardness to obtain the real-time hardness, and finally analyzing the deviation between the real-time hardness and the hardness reference to obtain the real-time performance attenuation index. The technical problem that in the prior art, a means for accurately predicting the performance attenuation of the shock absorber is lacked is solved, and the technical effects of accurately predicting the performance attenuation of the shock absorber of the automobile in real time and improving the driving safety of the automobile are achieved by taking the hardness as a key factor for representing the state of the shock absorber.

Description

Technical Field

[0001] The present application relates to the field of shock absorption technology, and in particular to a prediction system for automobile shock absorber performance attenuation. Background Art

[0002] In the automobile driving scene, the safety and comfort issues caused by the performance degradation of automobile shock absorbers are extremely prominent, and the contradiction between the need to accurately evaluate the state of shock absorbers and efficiently allocate maintenance resources is becoming more and more severe. Among them, the hardness of the shock absorber is a key indicator, and it is crucial to accurately reflect the performance status of the shock absorber. Traditional automobile shock absorber performance testing and evaluation are often relatively single and localized, relying only on manual experience and regular testing equipment, insufficient monitoring of long-term changes in shock absorber performance, and lack of in-depth analysis and utilization of historical monitoring data. In particular, the consideration of the important indicator of hardness is seriously missing, making it difficult to comprehensively and accurately evaluate the performance degradation of the shock absorber. There are unreasonable situations in resource allocation, resulting in some shock absorbers that are in urgent need of maintenance not being handled in time, while some shock absorbers in better condition may be overly concerned. The formulation of shock absorber maintenance plans is relatively simple and fixed, and cannot cope well with the ever-changing actual driving conditions of the car.

[0003] At present, relevant technologies lack the technical means to accurately predict the attenuation of shock absorber performance. Summary of the invention

[0004] The present application provides a prediction system for automobile shock absorber performance attenuation. The system obtains historical monitoring records of preset shock absorbers, matches records under a first historical node from multiple groups of records, obtains the first historical hardness under the node according to a predetermined hardness and softness strategy, and then analyzes the correspondence between the first historical node and the hardness and hardness to obtain the real-time hardness and hardness. Finally, the real-time performance attenuation index is obtained by analyzing the deviation between the real-time hardness and the hardness and hardness benchmark. This achieves the technical effect of accurately predicting the performance attenuation of automobile shock absorbers in real time and improving the safety of automobile driving by using hardness and softness as the key factors to characterize the state of the shock absorber.

[0005] The present application provides a prediction system for automobile shock absorber performance attenuation, including: A historical shock absorber monitoring record acquisition module, the historical shock absorber monitoring record acquisition module is used to acquire historical shock absorber monitoring records, and the historical shock absorber monitoring records include multiple groups of monitoring records of preset shock absorbers under multiple historical nodes; a first monitoring record matching module, the first monitoring record matching module is used to match the first monitoring record under the first historical node in the multiple groups of monitoring records, and the first historical node refers to any one of the multiple historical nodes; a first historical hardness acquisition module, the first historical hardness acquisition module is used to analyze the first monitoring record according to a predetermined hardness strategy to obtain the first historical hardness under the first historical node; a first correspondence analysis module, the first correspondence analysis module is used to analyze the first correspondence between the first historical node and the first historical hardness to obtain the real-time hardness of the preset shock absorber; a real-time performance attenuation index acquisition module, the real-time performance attenuation index acquisition module is used to analyze the real-time hardness deviation between the real-time hardness and the hardness benchmark to obtain the real-time performance attenuation index.

[0006] The prediction system for automobile shock absorber performance attenuation proposed in this application first obtains historical monitoring records of preset shock absorbers, matches records under the first historical node from multiple groups of records, obtains the first historical hardness under the node according to a predetermined hardness and softness strategy analysis, and then analyzes the correspondence between the first historical node and the hardness to obtain the real-time hardness. Finally, the real-time performance attenuation index is obtained by analyzing the deviation between the real-time hardness and the hardness benchmark, thereby achieving the technical effect of accurately predicting the performance attenuation of automobile shock absorbers in real time and improving the safety of automobile driving by taking hardness and softness as the key factors to characterize the state of shock absorbers. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0008] Figure 1 A schematic diagram of the structure of a system for predicting the attenuation of automobile shock absorber performance provided in an embodiment of the present application; Figure 2 This is a schematic diagram of the structure of the first historical hardness and softness acquisition module of the system for predicting the attenuation of automobile shock absorber performance provided in an embodiment of the present application.

[0009] Explanation of the accompanying drawings: historical shock absorber monitoring record acquisition module 10, first monitoring record matching module 20, first historical softness and hardness acquisition module 30, first corresponding relationship analysis module 40, real-time performance attenuation index acquisition module 50. DETAILED DESCRIPTION

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0011] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0012] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0013] The present application embodiment provides a prediction system for automobile shock absorber performance attenuation, such as Figure 1 As shown, the system comprises: The module 10 for acquiring historical shock absorber monitoring records is used to acquire historical shock absorber monitoring records, and the historical shock absorber monitoring records include multiple groups of monitoring records of preset shock absorbers at multiple historical nodes. Specifically, the module 10 for acquiring historical shock absorber monitoring records plays a key basic role in the automobile shock absorber performance attenuation prediction system. Collect multiple groups of monitoring records of preset shock absorbers at multiple historical nodes, and the data sources include data collected in real time by various sensors on the automobile under different driving conditions and data recorded during regular maintenance, repair or professional inspection of the automobile. The record content covers the physical parameters of the shock absorber itself, vehicle driving road condition information, vehicle load condition and driving speed and other information. Historical records provide a rich data basis for subsequent modules of the system, reflecting the changing trend of shock absorber performance over time, and are also of great significance to automobile maintenance and management decisions, and can assist in determining whether the shock absorber needs to be maintained or replaced in advance to ensure the safety and comfort of automobile driving.

[0014] The first monitoring record matching module 20 is used to match the first monitoring record under the first historical node in the multiple groups of monitoring records, and the first historical node refers to any one of the multiple historical nodes. Specifically, the first monitoring record matching module 20 plays a key screening role in the automobile shock absorber performance attenuation prediction system. From the multiple groups of monitoring records collected by the historical shock absorber monitoring record acquisition module, the first monitoring record under any one of the multiple historical nodes is matched. The first historical node can be selected according to specific needs or randomly, and the module is determined to search and match among many records based on information such as timestamps. The first monitoring record that is successfully matched contains various status information of the shock absorber at a specific moment and information related to vehicle driving, providing targeted data support for subsequent analysis and ensuring the accuracy and reliability of performance attenuation prediction.

[0015] The first historical hardness and softness acquisition module 30 is used to analyze the first monitoring record according to a predetermined hardness and softness strategy to obtain the first historical hardness and softness at the first historical node. Specifically, the first historical hardness and softness acquisition module 30 analyzes the first monitoring record according to the predetermined hardness and softness strategy, which is based on a large amount of experimental data, theoretical models and practical experience, and comprehensively considers various factors that affect the hardness and softness of the shock absorber. The first historical hardness and softness acquisition module 30 extracts specific parameters in the first monitoring record, such as the shock absorber pressure change range, displacement, vehicle speed and road condition flatness, etc., and performs comprehensive processing through a specific calculation formula or algorithm to determine the hardness and softness state of the shock absorber at the first historical node. The hardness and softness value is used as a quantitative representation to reflect the key performance indicators such as the elasticity and damping characteristics of the shock absorber. It is an important basic data for subsequent analysis and prediction, which can help understand the specific historical node state of the shock absorber, analyze the performance trend over time, and provide key clues for predicting performance attenuation.

[0016] In one possible implementation, Figure 2 As shown, the first historical hardness and softness acquisition module 30 includes: a predetermined characteristic index unit, which is used to store predetermined characteristic indexes in the predetermined hardness and softness strategy. Specifically, the predetermined characteristic indexes stored in the predetermined hardness and softness strategy are the basic settings of the entire analysis process. The predetermined characteristic indexes are determined after a lot of research and practice, and can reflect the key factors of the hardness and softness of the shock absorber, for example, including the range of variation of specific physical parameters of the shock absorber, specific indicators related to the driving conditions of the vehicle, etc. The predetermined characteristic indexes provide a clear direction and basis for subsequent analysis.

[0017] The first characteristic parameter set acquisition unit is used to traverse the predetermined characteristic indicators in the first monitoring record to obtain the first characteristic parameter set. Specifically, traversing the predetermined characteristic indicators in the first monitoring record reflects the screening and extraction of each data in the first monitoring record one by one. In this way, a data set corresponding to the predetermined characteristic indicators can be found, that is, the first characteristic parameter set. For example, if the predetermined characteristic indicators include specific pressure change ranges and displacement requirements, in the first monitoring record, pressure and displacement data that meet these requirements will be searched and combined into the first characteristic parameter set, providing a specific data basis for subsequent analysis.

[0018] The first feedback prediction value acquisition unit is used to use the first characteristic parameter set as input information of the soft and hard feedback prediction model to obtain the first feedback prediction value. Specifically, the first characteristic parameter set is used as the input information of the soft and hard feedback prediction model, and the model analyzes and predicts according to the input characteristic parameter set. Through the calculation of the model, the first feedback prediction value is obtained. The feedback prediction value is a preliminary prediction result of the soft and hardness of the shock absorber, and various factors in the first characteristic parameter set are comprehensively considered. For example, if the first characteristic parameter set contains a large pressure change and a specific displacement, the model will predict a corresponding soft and hard feedback value based on the parameters.

[0019] A feedback adjustment unit, the feedback adjustment unit is used to perform feedback adjustment on the hardness benchmark of the preset shock absorber according to the first feedback prediction value to obtain the first historical hardness. Specifically, the hardness benchmark of the preset shock absorber is feedback-adjusted according to the first feedback prediction value. The hardness benchmark is a reference value. By comparing and adjusting the first feedback prediction value with the hardness benchmark, a more accurate first historical hardness can be obtained. The initial reference value is corrected according to the actual situation, so that the final first historical hardness is more in line with the actual situation. For example, if the first feedback prediction value indicates that the shock absorber is harder than the hardness benchmark under the current situation, the hardness benchmark will be adjusted accordingly to obtain a more accurate first historical hardness.

[0020] In a possible implementation, the first characteristic parameter set acquisition unit further includes: a predetermined characteristic index composition subunit, and the predetermined characteristic index composition subunit is used for the predetermined characteristic index to include a predetermined hardening characteristic index and a predetermined softening characteristic index. Specifically, it is clarified that the predetermined characteristic index is composed of a predetermined hardening characteristic index and a predetermined softening characteristic index, which provides a specific classification direction for subsequent analysis, so that when analyzing the hardness of the shock absorber, the factors causing hardening and softening can be considered respectively.

[0021] A characteristic information acquisition subunit, the characteristic information acquisition subunit is used to sequentially traverse the predetermined hardening characteristic index and the predetermined softening characteristic index in the first monitoring record to obtain first hardening characteristic information and first softening characteristic information respectively. Specifically, first consider the predetermined hardening characteristic index, such as oil oxidation or contamination. In the first monitoring record, if it is found that the oil-related parameters in the shock absorber show that the oil may have been oxidized or contaminated over time, such as changes in the chemical properties of the oil, increases in the impurity content, etc., it can be determined that there is a factor that causes the shock absorber to harden, thereby obtaining the oil oxidation or contamination part in the first hardening characteristic information. For the wear of internal parts, in the first monitoring record, it is possible to check the wear degree parameters of the shock absorber's internal piston, sealing ring and other parts, such as the size change of the parts, the surface roughness, etc., to determine whether there is a situation in which the shock absorber has hardened due to the wear of the internal parts, and then obtain the corresponding first hardening characteristic information. In terms of temperature changes, by monitoring the temperature of the shock absorber at different stages of use and the corresponding shock absorber performance changes Parameters. If it is found that the temperature rises and the oil viscosity increases after long-term use, determine the factor that causes the shock absorber to harden and include it in the first hardening characteristic information. In the case of changes in internal gas pressure, check the internal gas pressure parameters of the pneumatic shock absorber in the first monitoring record. If the pressure is too high and the damping increases, it indicates the existence of this hardening feature and add it to the first hardening characteristic information. In the case of improper adjustment, analyze the adjustment setting parameters of the adjustable shock absorber in the first monitoring record. If the shock absorber becomes hard due to improper setting, use it as part of the first hardening characteristic information. In the case of manufacturing defects, check the relevant information in the first monitoring record such as the production parameters and quality inspection records of the shock absorber to determine whether there are manufacturing defects that cause the shock absorber to harden. If so, include it in the first hardening characteristic information. Then consider the predetermined softening characteristic indicators, such as oil leakage.In the first monitoring record, if it is found that the flow rate, pressure and other parameters of the oil inside the shock absorber show that there is oil leakage, that is, the damping capacity is reduced, the factor that causes the shock absorber to soften is determined, and the oil leakage part in the first softening characteristic information is obtained. When internal parts are damaged, by checking the working state parameters of internal parts such as pistons and sealing rings in the first monitoring record, such as the sealing of parts, smoothness of movement, etc., it is determined whether there is internal parts damage that leads to poor oil flow and reduced damping, and then the corresponding first softening characteristic information is obtained. In terms of gas leakage, for inflatable shock absorbers, check the internal gas pressure and flow parameters in the first monitoring record. If gas leakage is found and the damping is reduced, it indicates the existence of this softening characteristic. , add it to the first softening characteristic information. When the temperature change causes the shock absorber to soften, by monitoring the performance parameters of the shock absorber and the change in oil viscosity at extremely low temperatures, if the oil viscosity decreases and the shock absorber feels soft, determine this factor and include it in the first softening characteristic information. In the case of improper adjustment, analyze the adjustment setting parameters of the adjustable shock absorber in the first monitoring record. If adjustment to a lower damping setting causes the shock absorber to soften, include it as part of the first softening characteristic information. In the case of wear, by checking the wear degree parameters of the internal parts of the shock absorber after long-term use in the first monitoring record, such as the amount of parts loss and the degree of performance degradation, determine whether the damping capacity has decreased and the shock absorber has softened due to wear. If so, include it in the first softening characteristic information.

[0022] The first characteristic parameter set constitutes a subunit, and the first characteristic parameter set constitutes a subunit for the first hardening characteristic information and the first softening characteristic information to constitute the first characteristic parameter set. Specifically, the first hardening characteristic information and the first softening characteristic information obtained through the above process are combined together to form a first characteristic parameter set, which integrates various specific factor information that causes the shock absorber to harden and soften, and provides a comprehensive data basis for further analysis of the softness and hardness of the shock absorber.

[0023] In a possible implementation, the first feedback prediction value acquisition unit further includes: a soft and hard feedback prediction model composition subunit, and the soft and hard feedback prediction model composition subunit is used for the soft and hard feedback prediction model to include a hardening feedback prediction channel and a softening feedback prediction channel. Specifically, it is clarified that the soft and hard feedback prediction model is composed of a hardening feedback prediction channel and a softening feedback prediction channel, which provides a structural basis for the subsequent analysis of the characteristic information that causes the shock absorber to become hard and soft.

[0024] The first hardening feedback prediction value acquisition subunit is used to analyze the first hardening characteristic information through the hardening feedback prediction channel to obtain a first hardening feedback prediction value. Specifically, the first hardening characteristic information is analyzed through the hardening feedback prediction channel. The hardening feedback prediction channel is an analysis module specifically for the hardening characteristics of the shock absorber. The hardening feedback prediction channel uses its internal algorithms and models to process various factors in the first hardening characteristic information. For example, if the first hardening characteristic information includes specific parameters corresponding to factors such as oil oxidation or contamination, internal parts wear, etc., the hardening feedback prediction channel will evaluate their influence on the hardening degree of the shock absorber based on these parameters, thereby obtaining a first hardening feedback prediction value, which represents a quantitative prediction of the hardening condition of the shock absorber.

[0025] The first softening feedback prediction value acquisition subunit is used to analyze the first softening characteristic information through the softening degree feedback prediction channel to obtain a first softening feedback prediction value. Specifically, the first softening characteristic information is analyzed through the softening degree feedback prediction channel, and the softening degree feedback prediction channel processes the parameters corresponding to factors such as oil leakage and internal parts damage in the first softening characteristic information according to the softening characteristics of the shock absorber, and obtains the first softening feedback prediction value by analyzing the relationship between the parameters and the softening degree of the shock absorber, which quantifies the softening condition of the shock absorber.

[0026] The absolute value summing subunit is used to take the absolute value of the first hardening feedback prediction value and the first softening feedback prediction value as the first feedback prediction value. Specifically, the absolute value of the first hardening feedback prediction value and the first softening feedback prediction value are taken and added, in order to comprehensively consider the hardening and softening conditions of the shock absorber, and obtain a first feedback prediction value that can reflect the overall trend of the hardness change of the shock absorber. By taking the absolute value, it is possible to avoid the positive and negative values ​​from offsetting each other, and ensure that the effects of hardening and softening can be reflected in this value.

[0027] A hardening feedback prediction channel supervised learning subunit, wherein the hardening feedback prediction channel is an intelligent model obtained by supervised learning of a first training data group, wherein the first training data group includes training hardening feature information and training hardening feedback value of a training shock absorber, wherein the training hardening feedback value refers to the ratio of the first training hardness to the training hardness benchmark corresponding to the training shock absorber. Specifically, the hardening feedback prediction channel is an intelligent model obtained by supervised learning of the first training data group, wherein the first training data group includes training hardening feature information and training hardening feedback value of a training shock absorber, wherein the training hardening feedback value is the ratio of the first training hardness to the training hardness benchmark corresponding to the training shock absorber, and the ratio reflects the degree of hardening of the training shock absorber relative to the benchmark. During the supervised learning process, the model continuously adjusts its own parameters according to the training hardening feature information and the corresponding training hardening feedback value to improve the accuracy of the prediction of the hardening of the shock absorber.

[0028] A supervised learning subunit for the softening feedback prediction channel, wherein the softening feedback prediction channel is an intelligent model obtained by supervised learning of the second training data group, wherein the second training data group includes the training softening characteristic information and the training softening feedback value of the training shock absorber, and the training softening feedback value refers to the ratio of the second training softness and hardness to the training softness and hardness benchmark. Specifically, the softening feedback prediction channel is also an intelligent model obtained by supervised learning of the second training data group, wherein the second training data group includes the training softening characteristic information and the training softening feedback value of the training shock absorber, and the training softening feedback value is the ratio of the second training softness and hardness to the training softness and hardness benchmark, which reflects the softening degree of the training shock absorber relative to the benchmark. Through supervised learning, the softening feedback prediction channel continuously optimizes itself in order to more accurately predict the softening of the shock absorber.

[0029] The first correspondence analysis module 40 is used to analyze the first correspondence between the first historical node and the first historical softness and hardness to obtain the real-time softness and hardness of the preset shock absorber. Specifically, the first correspondence analysis module 40 takes the correspondence between the first historical node and the first historical softness and hardness as the analysis object. Regression analysis, trend analysis and other methods are used to fit the data points to determine the functional relationship between time and hardness, while considering the impact of vehicle driving state (such as high-speed driving, sudden braking, sharp turns, etc.) and road condition changes (such as flat roads, bumpy roads, mountain roads, etc.) on hardness, and finally calculate the real-time softness and hardness of the preset shock absorber, providing key data for the subsequent evaluation of shock absorber performance attenuation.

[0030] In a possible implementation, the first correspondence analysis module 40 includes: a regression fitting unit, the regression fitting unit is used to perform polynomial regression fitting on the first corresponding scatter plot obtained according to the first correspondence to obtain a first fitting formula. Specifically, the first corresponding scatter plot can be obtained according to the first correspondence between the first historical node and the first historical soft and hard values. The scatter plot displays the soft and hard data under different historical nodes in the form of points on a two-dimensional plane, wherein the horizontal axis usually represents time or historical nodes, and the vertical axis represents the soft and hard values. The scatter plot is processed using a polynomial regression fitting method. Polynomial regression fitting is a mathematical method that finds a suitable polynomial function to get as close to these scattered points as possible, and determines the degree and coefficient of the polynomial according to the distribution of the scatter points, so that the fitted function can best reflect the trend of the data, and obtain the first fitting formula, which can predict the corresponding soft and hard values ​​according to the input historical node values.

[0031] A real-time hardness and softness acquisition unit is used to obtain the real-time hardness and softness at the real-time node based on the first fitting formula. Specifically, the real-time hardness and softness at the real-time node is obtained based on the first fitting formula. After the current real-time node (which can be the current time point or a specific operating state point) is determined, the value of this real-time node is substituted into the first fitting formula. Through the calculation of the first fitting formula, the predicted hardness and softness value of the shock absorber at this real-time node is obtained, that is, the real-time hardness and softness. The real-time hardness and softness is a quantitative estimation of the current state of the shock absorber, which provides an important data basis for subsequent performance attenuation analysis and decision-making.

[0032] A real-time performance attenuation index acquisition module 50 is used to analyze the real-time hardness deviation between the real-time hardness and the hardness benchmark to obtain a real-time performance attenuation index. Specifically, the real-time performance attenuation index acquisition module 50 is used to determine the degree of real-time performance attenuation of the shock absorber. With the hardness benchmark as a reference, the hardness benchmark can be a standard value in a brand new state or an average hardness value of a large number of normal shock absorbers. By comparing the real-time hardness of the preset shock absorber with the hardness benchmark, the real-time hardness deviation is calculated, which reflects the current degree of deviation of the shock absorber from the benchmark state. Then, the real-time hardness deviation is deeply analyzed, and the usage time, mileage, working environment and other factors are comprehensively considered, and it is converted into a real-time performance attenuation index using specific algorithms and models, which provides an important basis for judging whether the shock absorber needs maintenance, replacement or adjustment.

[0033] In a possible implementation, the real-time performance attenuation index acquisition module 50 further includes: a difference calculation unit, the difference calculation unit is used to record the difference between the real-time hardness and the hardness reference as the real-time hardness deviation. Specifically, first, the task of the difference calculation unit is to determine the difference between the real-time hardness and the hardness reference. The hardness reference, as a reference value, represents the hardness of the shock absorber in an ideal state. The real-time hardness is the actual hardness of the shock absorber at the current moment obtained through the previous analysis. The difference obtained by subtracting the two is recorded as the real-time hardness deviation. The deviation value reflects the degree of deviation between the current state of the shock absorber and the ideal state, and is the basic data for subsequent analysis.

[0034] The first performance index extraction unit is used to extract the first performance index from the predetermined shock absorber performance index, and the first performance index has a first correlation coefficient. Specifically, the first performance index extraction unit extracts the first performance index from the predetermined shock absorber performance index, and the predetermined performance index is predetermined and used to evaluate multiple aspects of the shock absorber performance. The first performance index has a first correlation coefficient, which means that it has a certain correlation with the performance attenuation of the shock absorber. By extracting this specific performance index, the relationship between it and the softness and hardness deviation can be further analyzed.

[0035] The first performance attenuation index weighted calculation unit is used to weight the first correlation coefficient and the normalized real-time soft and hard deviation to obtain the first performance attenuation index. Specifically, after obtaining the first performance index and the real-time soft and hard deviation, the first performance attenuation index weighted calculation unit performs weighted calculation. First, the real-time soft and hard deviation is normalized so that it is within a specific range for better calculation and comparison. The first correlation coefficient and the normalized real-time soft and hard deviation are weighted. The purpose of weighting is to give different weights according to the importance of the two, so as to obtain a comprehensive first performance attenuation index. The index reflects the attenuation degree of the shock absorber under this performance index.

[0036] A comparison and analysis unit, the comparison and analysis unit is used to compare and analyze the first performance attenuation index to obtain the real-time performance attenuation index. Specifically, finally, the comparison and analysis unit compares and analyzes the first performance attenuation index, compares the first performance attenuation index obtained under different conditions, or compares it with other relevant indicators. Through the comparison and analysis, the performance attenuation of the shock absorber under different conditions can be determined, thereby obtaining a more accurate real-time performance attenuation index. The index can comprehensively reflect the real-time performance attenuation degree of the shock absorber, and provide an important basis for judging the state of the shock absorber and taking corresponding maintenance measures.

[0037] In a possible implementation, the comparative analysis unit further includes: a descending arrangement subunit, which is used to arrange the first performance attenuation index in descending order to obtain a performance attenuation sequence. Specifically, the descending arrangement subunit processes the first performance attenuation index, which is calculated through the previous steps and reflects the attenuation degree of the shock absorber under different performance indicators. Arranging the index in descending order means sorting it in order from large to small, in order to better identify the performance indicator with the most serious attenuation. By arranging in descending order, the difference in the attenuation degree of each performance indicator can be clearly seen, which provides an orderly data basis for the subsequent extraction of the first performance attenuation coefficient.

[0038] The first performance attenuation coefficient extraction subunit is used to take the first performance attenuation coefficient of the first performance in the performance attenuation sequence as the real-time performance attenuation index. Specifically, according to the principle of the wooden barrel, the performance with the most serious attenuation is the shortest board of the shock absorber performance, which can represent the performance attenuation of the entire shock absorber. After the performance attenuation sequence is obtained by arranging in descending order, the first performance attenuation coefficient extraction subunit selects the first performance attenuation coefficient of the first performance from this sequence. The coefficient corresponds to the performance index with the greatest attenuation degree, which is used as the real-time performance attenuation index. Because when evaluating the overall performance attenuation of the shock absorber, the weakest link often plays a decisive role. By extracting the first performance attenuation coefficient, the actual performance attenuation of the shock absorber can be more accurately reflected, which provides a key evaluation indicator for judging whether the shock absorber needs maintenance, replacement or adjustment.

[0039] In a possible implementation, the first performance indicator extraction unit further includes: a predetermined shock absorber performance indicator composition subunit, and the predetermined shock absorber performance indicator composition subunit is used for the predetermined shock absorber performance indicators including damping effect, handling stability and tire grip. Specifically, the predetermined shock absorber performance index composition sub-unit clarifies that the predetermined shock absorber performance indicators include damping effect, handling stability and tire grip. Damping effect is the key indicator. By measuring parameters such as the damping force size and change speed of the shock absorber under different working conditions, a good damping effect can make the vehicle run more smoothly. Handling stability affects the vehicle's posture when turning, accelerating and braking. By measuring parameters such as roll, pitch and yaw of the vehicle under various driving conditions, a shock absorber with good performance can improve handling confidence. Tire grip is closely related to shock absorber performance. The working state of the shock absorber affects the contact between the tire and the ground. Factors such as the shock absorber's load distribution on the tire and the change in friction under different road conditions are considered during the evaluation. When the shock absorber performance decreases, it may cause uneven contact between the tire and the ground and reduce grip. The indicators provide a specific direction and basis for the subsequent analysis of shock absorber performance attenuation, and can more comprehensively and accurately evaluate the shock absorber performance status.

[0040] The embodiment of the present application obtains historical monitoring records of preset shock absorbers, matches records under the first historical node from multiple groups of records, obtains the first historical hardness under the node according to a predetermined hardness and softness strategy analysis, and then analyzes the correspondence between the first historical node and the hardness and hardness to obtain the real-time hardness and hardness. Finally, the real-time performance attenuation index is obtained by analyzing the deviation between the real-time hardness and the hardness and hardness benchmark, thereby achieving the technical effect of accurately predicting the performance attenuation of the automobile shock absorber in real time and improving the safety of automobile driving by taking the hardness and softness as the key factor to characterize the state of the shock absorber.

[0041] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0042] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A prediction system for automobile shock absorber performance attenuation, characterized in that: include: A historical shock absorber monitoring record acquisition module, the historical shock absorber monitoring record acquisition module is used to acquire historical shock absorber monitoring records, the historical shock absorber monitoring records include multiple groups of monitoring records of preset shock absorbers at multiple historical nodes; A first monitoring record matching module, the first monitoring record matching module is used to match a first monitoring record under a first historical node in the multiple groups of monitoring records, the first historical node being any one of the multiple historical nodes; A first historical softness and hardness acquisition module, the first historical softness and hardness acquisition module is used to analyze the first monitoring record according to a predetermined softness and hardness strategy to obtain the first historical softness and hardness at the first historical node; A first correspondence analysis module, the first correspondence analysis module is used to analyze the first correspondence between the first historical node and the first historical softness and hardness to obtain the real-time softness and hardness of the preset shock absorber; A real-time performance attenuation index acquisition module is used to analyze the real-time hardness deviation between the real-time softness and the hardness benchmark to obtain a real-time performance attenuation index.

2. The prediction system for automobile shock absorber performance attenuation according to claim 1, characterized in that: The first historical softness and hardness acquisition module includes: A predetermined characteristic indicator unit, wherein the predetermined characteristic indicator unit is used to store predetermined characteristic indicators in the predetermined soft and hard strategy; A first characteristic parameter set acquisition unit, the first characteristic parameter set acquisition unit is used to traverse the predetermined characteristic indicator in the first monitoring record to obtain a first characteristic parameter set; a first feedback prediction value acquisition unit, the first feedback prediction value acquisition unit being configured to use the first feature parameter set as input information of a soft and hard feedback prediction model to obtain a first feedback prediction value; A feedback adjustment unit is used to perform feedback adjustment on the softness and hardness benchmark of the preset shock absorber according to the first feedback prediction value to obtain the first historical softness and hardness.

3. The prediction system for automobile shock absorber performance attenuation according to claim 2, characterized in that: The first feature parameter set acquisition unit includes: A predetermined characteristic index composition subunit, wherein the predetermined characteristic index composition subunit is used for the predetermined characteristic index including a predetermined hardening characteristic index and a predetermined softening characteristic index; a characteristic information acquisition subunit, the characteristic information acquisition subunit being used to sequentially traverse the predetermined hardening characteristic index and the predetermined softening characteristic index in the first monitoring record to obtain first hardening characteristic information and first softening characteristic information respectively; The first characteristic parameter set constitutes a subunit, and the first characteristic parameter set constitutes a subunit for constituting the first characteristic parameter set with the first hardening characteristic information and the first softening characteristic information.

4. The prediction system for automobile shock absorber performance attenuation according to claim 3, characterized in that: The first feedback prediction value acquisition unit includes: A soft and hard feedback prediction model composition subunit, wherein the soft and hard feedback prediction model composition subunit is used for the soft and hard feedback prediction model to include a hardening degree feedback prediction channel and a softening degree feedback prediction channel; a first hardening feedback prediction value acquisition subunit, the first hardening feedback prediction value acquisition subunit being used to analyze the first hardening characteristic information through the hardening degree feedback prediction channel to obtain a first hardening feedback prediction value; a first softening feedback prediction value acquisition subunit, the first softening feedback prediction value acquisition subunit being used to analyze the first softening characteristic information through the softening degree feedback prediction channel to obtain a first softening feedback prediction value; an absolute value adding subunit, the absolute value adding subunit being used to obtain the absolute value of the first hardening feedback prediction value and the first softening feedback prediction value as the first feedback prediction value; A hardening feedback prediction channel supervised learning subunit, wherein the hardening feedback prediction channel is an intelligent model obtained by supervised learning of a first training data group, wherein the first training data group includes training hardening feature information and a training hardening feedback value of a training shock absorber, and the training hardening feedback value refers to the ratio of the first training softness and hardness to a training softness and hardness benchmark corresponding to the training shock absorber; A softening feedback prediction channel supervised learning subunit, wherein the softening feedback prediction channel is an intelligent model obtained by supervised learning of a second training data group, wherein the second training data group includes training softening characteristic information and training softening feedback value of the training shock absorber, and the training softening feedback value refers to the ratio of the second training softness and hardness to the training softness and hardness benchmark.

5. The prediction system for automobile shock absorber performance attenuation according to claim 1, characterized in that: The first correspondence analysis module includes: A regression fitting unit, wherein the regression fitting unit is used to perform polynomial regression fitting on the first corresponding scatter plot obtained according to the first corresponding relationship to obtain a first fitting formula; A real-time softness and hardness acquisition unit is used to obtain the real-time softness and hardness at a real-time node based on the first fitting formula.

6. The prediction system for automobile shock absorber performance attenuation according to claim 1, characterized in that: The real-time performance decay index acquisition module includes: A difference calculation unit, the difference calculation unit is used to record the difference between the real-time soft and hardness and the soft and hardness reference as the real-time soft and hardness deviation; A first performance index extraction unit, the first performance index extraction unit is used to extract a first performance index from the predetermined shock absorber performance indexes, the first performance index having an identifier of a first correlation coefficient; A first performance decay index weighted calculation unit, the first performance decay index weighted calculation unit is used to weight the first correlation coefficient and the normalized real-time soft and hard deviation to obtain a first performance decay index; A comparison and analysis unit, wherein the comparison and analysis unit is used to compare and analyze the first performance degradation index to obtain the real-time performance degradation index.

7. The prediction system for automobile shock absorber performance attenuation according to claim 6, characterized in that: The comparison and analysis unit comprises: A descending order arrangement subunit, the descending order arrangement subunit is used to arrange the first performance decay index in descending order to obtain a performance decay sequence; The first performance decay coefficient extraction subunit is used to take the first performance decay coefficient of the first performance in the performance decay sequence as the real-time performance decay index.

8. The prediction system for automobile shock absorber performance attenuation according to claim 6, characterized in that: The first performance indicator extraction unit includes: The predetermined shock absorber performance index composition subunit is used for the predetermined shock absorber performance index including damping effect, handling stability and tire grip.

Images