Intelligent tire dynamic response adaptive monitoring method and system based on data analysis

Abstract

The present invention discloses an intelligent tire dynamic response adaptive monitoring method and system based on data analysis, which belongs to the field of tire targeted analysis technology. Based on sensors, monitor and record abnormal triggering behaviors of tire working conditions; synchronously collect data for abnormal feedback instructions; construct a tire targeted dynamic response matrix model to quantify and record the early warning triggering behaviors of sensors; based on the early warning triggering behaviors of sensors, construct a tire targeted solution analysis model to analyze the tire targeted coupling degree; based on the tire targeted coupling degree, construct a tire targeted sensitivity analysis model to analyze the tire targeted sensitivity; construct a tire targeted solution efficiency judgment model to judge the targeted solution efficiency tendency, generate a targeted area set, and regularly update and output the targeted area set; further, it can be based on the mutual correlation and coupling between the tire dynamic response and the tire state parameters to improve the accuracy and efficiency of the tire state parameter solution.

Description

Technical Field

[0001] The present invention relates to the technical field of tire targeted analysis, and in particular to an intelligent tire dynamic response adaptive monitoring method and system based on data analysis. Background Art

[0002] The research results in the field of tire targeted analysis have broad application prospects in tire design, production, and application. For example, in tire design, the tire design can be optimized and tire performance can be improved by studying the tire structure and side deviation characteristics. In tire production, the finite element method, model analysis and other technical means can be used to realize the digitalization and intelligence of the tire production process. In tire application, the adjustment of wheel alignment parameters can reduce tire wear and improve vehicle handling stability.

[0003] Since the sensitivity of tire state parameters to dynamic response parameters and their target areas under different working conditions is different, and there is a mutual correlation and coupling between the tire dynamic response and the tire state parameters, the difficulty of analyzing the tire targeted solution capability is increased, resulting in low accuracy and insufficient efficiency in the solution of tire state parameters in the existing technology. Summary of the invention

[0004] Purpose of the invention: In view of the deficiencies in the prior art, the present invention provides an intelligent tire dynamic response adaptive monitoring method and system based on data analysis to solve the problems mentioned in the above background technology.

[0005] Technical solution: An intelligent tire dynamic response adaptive monitoring method based on data analysis, the method comprising the following steps:

[0006] Step S100: compile a tire working condition requirement library, and based on the tire working condition requirement, generate a tire state perception log library, and monitor and record abnormal triggering behaviors of the tire working condition requirement based on an acceleration sensor, a strain sensor, and a speed sensor;

[0007] Step S200: Based on the abnormal triggering behavior, synchronous data collection is performed on the abnormal feedback instruction, and a first abnormal synchronous data cluster and a second abnormal synchronous data cluster are generated respectively;

[0008] Step S300: Based on the first abnormal synchronous data cluster and the second abnormal synchronous data cluster, a tire targeted dynamic response matrix model is constructed to quantify and record the early warning triggering behavior of the sensor; based on the early warning triggering behavior of the sensor, a tire targeted solution analysis model is constructed to analyze the tire targeted coupling degree;

[0009] Step S400: Based on the tire targeted coupling degree, a tire targeted sensitivity analysis model is constructed to analyze the tire targeted sensitivity; a tire targeted solution efficiency judgment model is constructed to judge the targeted solution efficiency tendency, and based on the judgment result, a targeted area set is generated, and the targeted area set is regularly updated and output.

[0010] The specific implementation process of step S100 includes:

[0011] Step S101: Generate a tire operating condition requirement library based on the tire operating condition requirement, denoted as WR={wr q |q∈[1,Q]}, where wr q represents the qth tire operating condition requirement, Q represents the total number of types of tire operating condition requirements, the tire operating condition requirement is a tire performance index that the tire meets under different usage conditions, and the usage condition includes at least one of road conditions, climate conditions, and load;

[0012] Step S102: Establish a tire state perception log library, in which abnormal feedback instructions and warning coefficients of sensors are stored, wherein a sensor is used to monitor a tire state parameter; uniformly encode the sensors, and when the tire state parameter monitored by the i-th sensor exceeds the configured i-th sensor warning value, the abnormal feedback instruction required by the tire working condition is triggered, and the warning coefficient sensed by the i-th sensor when the abnormal feedback instruction required by the tire working condition is triggered is uploaded to the tire state perception log library, wherein the warning coefficient is the ratio of the difference between the tire state parameter and the warning value to the warning value.

[0013] The specific implementation process of step S200 includes:

[0014] Step S201: Based on the early warning triggering behavior of the sensor, synchronous data collection of abnormal feedback instructions is performed to form a first abnormal synchronous data cluster, recorded as FAD t ={EC i |i∈[1,I]}, where FAD t Indicates the first abnormal synchronization data cluster generated at the tth synchronization time, EC i It represents the warning coefficient uploaded by the i-th sensor, and I represents the maximum code number of the sensor;

[0015] Step S202: Based on the early warning triggering behavior of the sensor, a trigger tag of the abnormal feedback instruction is generated to form a second abnormal synchronization data cluster, which is recorded as SAD t ={WC(wr q )|q∈[1,Q]}, where SAD t represents the second abnormal synchronization data cluster generated at the tth synchronization time, WC(wr q) represents the tire working condition requirement wr q Corresponding to the generated trigger tag set, and WC(wr q )={S i |i∈[1,I]}, when the i-th sensor S i Trigger tire condition requirement wr q When an abnormal feedback instruction is given, the sensor is recorded in the trigger tag set WC (wr q )middle.

[0016] The specific implementation process of step S300 includes:

[0017] Step S301: construct a tire targeted dynamic response matrix model, in which the row number of the matrix corresponds to the type number of the tire working condition requirement, and the column number of the matrix corresponds to the code number of the sensor, and the matrix element corresponding to the qth row and the ith column in the matrix is ​​recorded as R qi In the second abnormal synchronization data cluster, capture trigger tag set WC (wr q ), and based on the trigger tag set WC(wr q ) i Corresponding to the code number i, in the first abnormal synchronous data cluster, pick sensor S i Corresponding warning coefficient EC i , and record it in the matrix element position corresponding to the qth row and the ith column in the matrix, then R qi =EC i ; Based on the synchronization number and the tire targeted dynamic response matrix model, the tire targeted dynamic response matrix corresponding to the t-th synchronization is recorded as X(t); the average value of the matrix elements in the q-th row of the tire targeted dynamic response matrix X(t) is obtained. If R qi If it is greater than or equal to the mean value, then R qi Set to 1, otherwise R qi Set to 0, so that the tire targeted dynamic response matrix X(t) is converted into a Boolean matrix containing only 0 or 1, denoted as X(t);

[0018] Step S302: Based on the Boolean matrix X(t), a tire targeted solution analysis model is constructed to calculate the tire targeted coupling degree. The specific calculation formula is as follows:

[0019]

[0020] Among them, CF(t) represents the coupling degree of the tire targeted dynamic response during the parameter coupling process between tire state parameters when the t-th synchronization is transferred to the t+1-th synchronization. It represents the Boolean matrix generated at the t+1th synchronization time. Represents a Boolean matrix With Boolean matrices The number of 1s contained in the intersection logic operation between Represents a Boolean matrix With Boolean matrices The number of 1s included in the logical union operation between them.

[0021] The specific implementation process of step S400 includes:

[0022] Step S401: Based on the tire targeting coupling degree, a tire targeting sensitivity analysis model is constructed to calculate the tire targeting sensitivity. The specific calculation formula is as follows:

[0023]

[0024] Where CS(t) represents the tire targeting sensitivity at the tth synchronization time, α and β represent the variance and mean of the tire targeting coupling degree, respectively;

[0025] Based on tire pressure, tire vibration and tire wear, a tire targeting sensitivity threshold is preset. If the tire targeting sensitivity is greater than or equal to the tire targeting sensitivity threshold, the Boolean matrix is ​​traced back. and Boolean matrices And if the matrix element R qi Corresponding to the Boolean matrix With Boolean matrices If the intersection logic operation is 1, then for the matrix element R qi Marking, and based on the matrix element R qi The corresponding row number q and column number i capture the trigger tag set WC (wr q ) in the sensor S i , generate a capture label, denoted as F{S i |[WC(wr q )∈SAD t ]}=1;

[0026] Step S402: Under the synchronization subdomain T, and t∈T, construct a tire targeting solution efficiency judgment model to judge the sensor S i The targeted solution efficiency tendency under different tire working conditions is determined by the following formula:

[0027]

[0028] Among them, EV[S i |wr q ] indicates sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q The tendency degree, EV[S i |wr q+1] indicates sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q+1 degree of inclination;

[0029] If the judgment formula is satisfied, it means that the sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q ; Get the tire working condition requirements wr q All sensors of the target region set are generated, denoted as RC(wr q )={S i |i∈[1,I]}, the targeted region set is updated and output regularly.

[0030] A system for realizing an intelligent tire dynamic response adaptive monitoring method based on data analysis, comprising: a data monitoring module, a data intelligent integration module, a targeted coupling analysis module and a targeted sensitivity analysis module, wherein each module is connected in turn via wireless signals;

[0031] The data monitoring module is used to compile a tire working condition requirement library, and based on the tire working condition requirements, generate a tire state perception log library, and monitor and record abnormal triggering behaviors of tire working condition requirements based on sensors;

[0032] The data intelligent integration module performs synchronous data collection on the abnormal feedback instruction based on the abnormal triggering behavior, and generates a first abnormal synchronous data cluster and a second abnormal synchronous data cluster respectively;

[0033] The targeted coupling analysis module constructs a tire targeted dynamic response matrix model based on the first abnormal synchronous data cluster and the second abnormal synchronous data cluster, quantifies and records the early warning triggering behavior of the sensor; constructs a tire targeted solution analysis model based on the early warning triggering behavior of the sensor, and analyzes the tire targeted coupling degree;

[0034] The targeted sensitivity analysis module constructs a tire targeted sensitivity analysis model based on the tire targeted coupling degree to analyze the tire targeted sensitivity; constructs a tire targeted solution efficiency judgment model to judge the targeted solution efficiency tendency, generates a targeted area set based on the judgment result, and regularly updates and outputs the targeted area set.

[0035] Beneficial effects: In the intelligent tire dynamic response adaptive monitoring system and method based on data analysis provided by the present invention, sensors are used to monitor and record abnormal triggering behaviors of tire working conditions; synchronous data collection is performed on abnormal feedback instructions; a tire targeted dynamic response matrix model is constructed to quantify and record the early warning triggering behaviors of sensors; based on the early warning triggering behaviors of sensors, a tire targeted solution analysis model is constructed to analyze the tire targeted coupling degree; based on the tire targeted coupling degree, a tire targeted sensitivity analysis model is constructed to analyze the tire targeted sensitivity; a tire targeted solution efficiency judgment model is constructed to judge the targeted solution efficiency tendency, generate a targeted area set, and regularly update and output the targeted area set; furthermore, based on the correlation and coupling between the tire dynamic response and the tire state parameters, the accuracy and efficiency of the tire state parameter solution can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0037] Figure 1 It is a schematic diagram of the steps of the intelligent tire dynamic response adaptive monitoring method based on data analysis of the present invention.

[0038] Figure 2 The present invention shows a schematic diagram of the structure of each sub-region in a plane after the tire deformation zone is expanded.

[0039] Figure 3 It is a sensitivity mean distribution curve diagram of the force sensitive response variable of the crown area of ​​the present invention.

[0040] Figure 4 It is a sensitivity mean distribution curve diagram of the force sensitive response variable of the sidewall area of ​​the present invention.

[0041] Figure 5 It is a structural schematic diagram of the intelligent tire dynamic response adaptive monitoring system based on data analysis of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] In the description of the present invention, it is necessary to understand that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0044] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0045] The method for adaptively monitoring dynamic response of intelligent tires based on data analysis comprises the following steps:

[0046] First, the tire deformation area is expanded into a plane and divided into the following parts along the lateral and circumferential directions: Figure 2 There are 21 small areas shown, where L and R represent the left and right areas of the tire respectively.

[0047] like Figure 1 As shown, step S100: compile a tire working condition requirement library, and based on the tire working condition requirement, generate a tire state perception log library, and monitor and record abnormal triggering behaviors of the tire working condition requirement based on an acceleration sensor, a strain sensor, and a speed sensor;

[0048] The specific implementation process includes:

[0049] Step S101: Generate a tire operating condition requirement library based on the tire operating condition requirement, denoted as WR={wr q |q∈[1,Q]}, where wr q represents the qth tire operating condition requirement, Q represents the total number of types of tire operating condition requirements, the tire operating condition requirement is a tire performance index that the tire meets under different usage conditions, and the usage condition includes at least one of road conditions, climate conditions, and load;

[0050] Step S102: Establish a tire state perception log library, in which abnormal feedback instructions and warning coefficients of sensors are stored, wherein a sensor is used to monitor a tire state parameter; uniformly encode the sensors, and when the tire state parameter monitored by the i-th sensor exceeds the configured i-th sensor warning value, the abnormal feedback instruction required by the tire working condition is triggered, and the warning coefficient sensed by the i-th sensor when the abnormal feedback instruction required by the tire working condition is triggered is uploaded to the tire state perception log library, wherein the warning coefficient is the ratio of the difference between the tire state parameter and the warning value to the warning value.

[0051] Step S200: Based on the abnormal triggering behavior, synchronous data collection is performed on the abnormal feedback instruction, and a first abnormal synchronous data cluster and a second abnormal synchronous data cluster are generated respectively;

[0052] The specific implementation process includes:

[0053] Step S201: Based on the early warning triggering behavior of the sensor, synchronous data collection of abnormal feedback instructions is performed to form a first abnormal synchronous data cluster, recorded as FAD t ={EC i |i∈[1,I]}, where FAD t Indicates the first abnormal synchronization data cluster generated at the tth synchronization time, EC i It represents the warning coefficient uploaded by the i-th sensor, and I represents the maximum code number of the sensor;

[0054] Step S202: Based on the early warning triggering behavior of the sensor, a trigger tag of the abnormal feedback instruction is generated to form a second abnormal synchronization data cluster, which is recorded as SAD t ={WC(wr q )|q∈[1,Q]}, where SAD t represents the second abnormal synchronization data cluster generated at the tth synchronization time, WC(wr q ) represents the tire working condition requirement wr q Corresponding to the generated trigger tag set, and WC(wr q )={S i |i∈[1,I]}, when the i-th sensor S i Trigger tire condition requirement wr q When an abnormal feedback instruction is given, the sensor is recorded in the trigger tag set WC (wr q )middle.

[0055] Step S300: Based on the first abnormal synchronous data cluster and the second abnormal synchronous data cluster, a tire targeted dynamic response matrix model is constructed to quantify and record the early warning triggering behavior of the sensor; based on the early warning triggering behavior of the sensor, a tire targeted solution analysis model is constructed to analyze the tire targeted coupling degree;

[0056] The specific implementation process includes:

[0057] Step S301: construct a tire targeted dynamic response matrix model, in which the row number of the matrix corresponds to the type number of the tire working condition requirement, and the column number of the matrix corresponds to the code number of the sensor, and the matrix element corresponding to the qth row and the ith column in the matrix is ​​recorded as R qi In the second abnormal synchronization data cluster, capture trigger tag set WC (wr q ), and based on the trigger tag set WC(wr q ) i Corresponding to the code number i, in the first abnormal synchronous data cluster, pick sensor S i Corresponding warning coefficient EC i , and record it in the matrix element position corresponding to the qth row and the ith column in the matrix, then R qi =EC i ; Based on the synchronization number and the tire targeted dynamic response matrix model, the tire targeted dynamic response matrix corresponding to the t-th synchronization is recorded as X(t); the average value of the matrix elements in the q-th row of the tire targeted dynamic response matrix X(t) is obtained. If R qi If it is greater than or equal to the mean value, then R qi Set to 1, otherwise R qi Set to 0, so that the tire targeted dynamic response matrix X(t) is converted into a Boolean matrix containing only 0 or 1, denoted as

[0058] Step S302: Based on Boolean matrix Construct a tire targeted solution analysis model and calculate the tire targeted coupling degree. The specific calculation formula is as follows:

[0059]

[0060] Among them, CF(t) represents the coupling degree of the tire targeted dynamic response during the parameter coupling process between tire state parameters when the t-th synchronization is transferred to the t+1-th synchronization. It represents the Boolean matrix generated at the t+1th synchronization time. Represents a Boolean matrix With Boolean matrices The number of 1s contained in the intersection logic operation between Represents a Boolean matrix With Boolean matrices The number of 1s included in the logical union operation between them.

[0061] Step S400: Based on the tire targeted coupling degree, a tire targeted sensitivity analysis model is constructed to analyze the tire targeted sensitivity; a tire targeted solution efficiency judgment model is constructed to judge the targeted solution efficiency tendency, and based on the judgment result, a targeted area set is generated, and the targeted area set is regularly updated and output;

[0062] The specific implementation process includes:

[0063] Step S401: Based on the tire targeting coupling degree, a tire targeting sensitivity analysis model is constructed to calculate the tire targeting sensitivity. The specific calculation formula is as follows:

[0064]

[0065] Where CS(t) represents the tire targeting sensitivity at the tth synchronization time, α and β represent the variance and mean of the tire targeting coupling degree, respectively;

[0066] Based on tire pressure, tire vibration and tire wear, a tire targeting sensitivity threshold is preset. In this application, a targeting sensitivity mean above 0.8 is considered to indicate that the output response has high sensitivity to the input, a targeting sensitivity mean between 0.6 and 0.8 is considered to indicate high sensitivity, and a targeting sensitivity mean below 0.6 is considered to indicate low sensitivity. If the tire targeting sensitivity is greater than or equal to the tire targeting sensitivity threshold, the Boolean matrix is ​​traced back. and Boolean matrices And if the matrix element R qi Corresponding to the Boolean matrix With Boolean matrices If the intersection logic operation is 1, then for the matrix element R qi Marking, and based on the matrix element R qi The corresponding row number q and column number i capture the trigger tag set WC (wr q ) in the sensor S i , generate a capture label, denoted as F{S i |[WC(wr q )∈SAD t ]}=1;

[0067] Step S402: Under the synchronization subdomain T, and t∈T, construct a tire targeting solution efficiency judgment model to judge the sensor S i The targeted solution efficiency tendency under different tire working conditions is determined by the following formula:

[0068]

[0069] Among them, EV[S i |wr q ] indicates sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q The tendency degree, EV[S i |wr q+1 ] indicates sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q+1 degree of inclination;

[0070] If the judgment formula is satisfied, it means that the sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q ; Get the tire working condition requirements wr q All sensors of the target region set are generated, denoted as RC(wr q )={S i |i∈[1,I]}, the targeted region set is updated and output regularly.

[0071] Through the above method, it can be concluded that under different working conditions, when the tire is affected by at least one of the road conditions, climate conditions and load conditions, the change in the tire is reflected in the change of the three-dimensional force of the tire, including vertical force, longitudinal force and lateral force. The distribution of sensitive response variables of the three-dimensional force in each area of ​​the tire is as follows:

[0072] Distribution table of sensitive response variables of three-axis forces in various areas of the tire

[0073]

[0074] The force-sensitive response variables of the crown region include:

[0075] Vertical force sensitive response variables - radial acceleration A1, circumferential acceleration A2, radial displacement U1, circumferential displacement U2 and circumferential strain LE2;

[0076] Longitudinal force sensitive response variable – circumferential displacement U2;

[0077] The sidewall area force-sensitive response variables include:

[0078] Vertical force sensitive response variables – circumferential acceleration A2, lateral acceleration A3, lateral displacement U3 and radial strain LE1;

[0079] Longitudinal force sensitive response variables - radial acceleration A1, circumferential displacement U2;

[0080] Lateral force sensitive response variables - lateral acceleration A3, lateral displacement U3.

[0081] The distribution of the tire triaxial force sensitive response variables on the crown and sidewall are as follows: Figure 3 and Figure 4 As shown in the figure, the ordinate is the targeted sensitivity mean of the sensitive response variable during the entire tire contact process, from area A before contact, area B after contact, and area C after contact. The abscissa is the crown and sidewall positions, with the crown center point G0 and the sidewall starting point G2 as zero points respectively.

[0082] It can be concluded that: for the estimation of the tire vertical force and longitudinal force, the corresponding sensor is installed at the center of the crown; for the simultaneous estimation of the tire vertical force, longitudinal force and lateral force, the position near the center of the sidewall is selected as the installation position of the sensor, that is, 24 to 35 mm away from the starting point G2 of the sidewall.

[0083] like Figure 5 As shown, the system for realizing the intelligent tire dynamic response adaptive monitoring method based on data analysis includes: a data monitoring module, a data intelligent integration module, a targeted coupling analysis module and a targeted sensitive analysis module, and each module is connected in turn through wireless signals;

[0084] The data monitoring module is used to compile a tire working condition requirement library, and based on the tire working condition requirements, generate a tire state perception log library, and monitor and record abnormal triggering behaviors of tire working condition requirements based on sensors;

[0085] The data intelligent integration module performs synchronous data collection on the abnormal feedback instruction based on the abnormal triggering behavior, and generates a first abnormal synchronous data cluster and a second abnormal synchronous data cluster respectively;

[0086] The targeted coupling analysis module constructs a tire targeted dynamic response matrix model based on the first abnormal synchronous data cluster and the second abnormal synchronous data cluster, quantifies and records the early warning triggering behavior of the sensor; constructs a tire targeted solution analysis model based on the early warning triggering behavior of the sensor, and analyzes the tire targeted coupling degree;

[0087] The targeted sensitivity analysis module constructs a tire targeted sensitivity analysis model based on the tire targeted coupling degree to analyze the tire targeted sensitivity; constructs a tire targeted solution efficiency judgment model to judge the targeted solution efficiency tendency, generates a targeted area set based on the judgment result, and regularly updates and outputs the targeted area set.

[0088] It can be seen from the formula that the tire targeted sensitivity analysis model is based on the calculation of tire targeted coupling degree. The key lies in using statistical methods to quantitatively analyze the response characteristics of the tire under different working conditions.

[0089] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0090] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent tire dynamic response adaptive monitoring method based on data analysis, characterized in that: The method comprises the following steps: Step S100: compile a tire working condition requirement library, and based on the tire working condition requirement, generate a tire state perception log library, and monitor and record abnormal triggering behaviors of the tire working condition requirement based on an acceleration sensor, a strain sensor, and a speed sensor; Step S200: Based on the abnormal triggering behavior, synchronous data collection is performed on the abnormal feedback instruction, and a first abnormal synchronous data cluster and a second abnormal synchronous data cluster are generated respectively; Step S300: Based on the first abnormal synchronous data cluster and the second abnormal synchronous data cluster, a tire targeted dynamic response matrix model is constructed to quantify and record the early warning triggering behavior of the sensor; based on the early warning triggering behavior of the sensor, a tire targeted solution analysis model is constructed to analyze the tire targeted coupling degree; Step S400: Based on the tire targeted coupling degree, a tire targeted sensitivity analysis model is constructed to analyze the tire targeted sensitivity; a tire targeted solution efficiency judgment model is constructed to judge the targeted solution efficiency tendency, and based on the judgment result, a targeted area set is generated, and the targeted area set is regularly updated and output; The specific implementation process of step S300 includes: Step S301: construct a tire targeted dynamic response matrix model, in which the row number of the matrix corresponds to the type number of the tire working condition requirement, and the column number of the matrix corresponds to the code number of the sensor, and the matrix element corresponding to the qth row and the ith column in the matrix is ​​recorded as R qi In the second abnormal synchronization data cluster, capture trigger tag set WC (wr q ), and based on the trigger tag set WC(wr q ) i Corresponding to the code number i, in the first abnormal synchronous data cluster, pick sensor S i Corresponding warning coefficient EC i , and record it in the matrix element position corresponding to the qth row and the ith column in the matrix, then R qi =EC i ; Based on the synchronization number and the tire targeted dynamic response matrix model, the tire targeted dynamic response matrix corresponding to the t-th synchronization is recorded as X(t); the average value of the matrix elements in the q-th row of the tire targeted dynamic response matrix X(t) is obtained. If R qi If it is greater than or equal to the mean value, then R qi Set to 1, otherwise R qi Set to 0, so that the tire targeted dynamic response matrix X(t) is converted into a Boolean matrix containing only 0 or 1, denoted as Step S302: Based on Boolean matrix Construct a tire targeted solution analysis model and calculate the tire targeted coupling degree. The specific calculation formula is as follows: Among them, CF(t) represents the coupling degree of the tire targeted dynamic response during the parameter coupling process between tire state parameters when the t-th synchronization is transferred to the t+1-th synchronization. It represents the Boolean matrix generated at the t+1th synchronization time. Represents a Boolean matrix With Boolean matrices The number of 1s contained in the intersection logic operation between Represents a Boolean matrix With Boolean matrices The number of 1s contained in the logical operation of the union between them; The specific implementation process of step S400 includes: Step S401: Based on the tire targeting coupling degree, a tire targeting sensitivity analysis model is constructed to calculate the tire targeting sensitivity. The specific calculation formula is as follows: Where CS(t) represents the tire targeting sensitivity at the tth synchronization time, α and β represent the variance and mean of the tire targeting coupling degree, respectively; Based on tire pressure, tire vibration and tire wear, a tire targeting sensitivity threshold is preset. If the tire targeting sensitivity is greater than or equal to the tire targeting sensitivity threshold, the Boolean matrix is ​​traced back. and Boolean matrices And if the matrix element R qi Corresponding to the Boolean matrix With Boolean matrices If the intersection logic operation is 1, then for the matrix element R qi Marking, and based on the matrix element R qi The corresponding row number q and column number i capture the trigger tag set WC (wr q ) in the sensor S i , generate a capture label, denoted as F{S i |[WC(wr q )∈SAD t ]}=1; Step S402: Under the synchronization subdomain T, and t∈T, construct a tire targeting solution efficiency judgment model to judge the sensor S i The targeted solution efficiency tendency under different tire working conditions is determined by the following formula: Among them, EV[S i |wr q ] indicates sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q The tendency degree, EV[S i |wr q+1 ] indicates sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q+1 degree of inclination; If the judgment formula is satisfied, it means that the sensor S i The targeted solution efficiency tends to the tire working condition requirements wr q ; Get the tire working condition requirements wr q All sensors of the target region set are generated, denoted as RC(wr q )={S i |i∈[1,I]}, the targeted region set is updated and output regularly.

2. The method for adaptively monitoring dynamic response of intelligent tires based on data analysis according to claim 1, characterized in that: The specific implementation process of step S100 includes: Step S101: Generate a tire operating condition requirement library based on the tire operating condition requirement, denoted as WR={wr q |q∈[1,Q]}, where wr q represents the qth tire operating condition requirement, Q represents the total number of types of tire operating condition requirements, the tire operating condition requirement is a tire performance index that the tire meets under different usage conditions, and the usage condition includes at least one of road conditions, climate conditions, and load; Step S102: Establish a tire state perception log library, in which abnormal feedback instructions and warning coefficients of sensors are stored, wherein a sensor is used to monitor a tire state parameter; uniformly encode the sensors, and when the tire state parameter monitored by the i-th sensor exceeds the configured i-th sensor warning value, the abnormal feedback instruction required by the tire working condition is triggered, and the warning coefficient sensed by the i-th sensor when the abnormal feedback instruction required by the tire working condition is triggered is uploaded to the tire state perception log library, wherein the warning coefficient is the ratio of the difference between the tire state parameter and the warning value to the warning value.

3. The method for adaptively monitoring dynamic response of intelligent tires based on data analysis according to claim 2, characterized in that: The specific implementation process of step S200 includes: Step S201: Based on the early warning triggering behavior of the sensor, synchronous data collection of abnormal feedback instructions is performed to form a first abnormal synchronous data cluster, recorded as FAD t ={EC i |i∈[1,I]}, where FAD t Indicates the first abnormal synchronization data cluster generated at the tth synchronization time, EC i It represents the warning coefficient uploaded by the i-th sensor, and I represents the maximum code number of the sensor; Step S202: Based on the early warning triggering behavior of the sensor, a trigger tag of the abnormal feedback instruction is generated to form a second abnormal synchronization data cluster, which is recorded as SAD t ={WC(wr q )|q∈[1,Q]}, where SAD t represents the second abnormal synchronization data cluster generated at the tth synchronization time, WC(wr q ) represents the tire working condition requirement wr q Corresponding to the generated trigger tag set, and WC(wr q )={S i |i∈[1,I]}, when the i-th sensor S i Trigger tire condition requirement wr q When an abnormal feedback instruction is given, the sensor is recorded in the trigger tag set WC (wr q )middle.

4. The system of the intelligent tire dynamic response adaptive monitoring method based on data analysis according to any one of claims 1 to 3, characterized in that: include: The data monitoring module, the data intelligent integration module, the targeted coupling analysis module and the targeted sensitivity analysis module are connected in sequence through wireless signals; The data monitoring module is used to compile a tire working condition requirement library, and based on the tire working condition requirements, generate a tire state perception log library, and monitor and record abnormal triggering behaviors of tire working condition requirements based on sensors; The data intelligent integration module performs synchronous data collection on the abnormal feedback instruction based on the abnormal triggering behavior, and generates a first abnormal synchronous data cluster and a second abnormal synchronous data cluster respectively; The targeted coupling analysis module constructs a tire targeted dynamic response matrix model based on the first abnormal synchronous data cluster and the second abnormal synchronous data cluster, and quantifies and records the early warning triggering behavior of the sensor; Based on the early warning triggering behavior of the sensor, a tire targeted solution analysis model is constructed to analyze the tire targeted coupling degree; The targeted sensitivity analysis module constructs a tire targeted sensitivity analysis model based on the tire targeted coupling degree to analyze the tire targeted sensitivity; constructs a tire targeted solution efficiency judgment model to judge the targeted solution efficiency tendency, generates a targeted area set based on the judgment result, and regularly updates and outputs the targeted area set.

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