Intelligent detection method for plate body mass of excavator track shoe

Abstract

The application discloses a method for intelligently detecting the quality of a plate body of a crawler plate of an excavator, and relates to the technical field of mechanical quality detection. The method comprises the following steps: based on a vibration acceleration signal, a time-frequency ridge line feature reflecting the dynamic characteristics of the local structure of the plate body is constructed, and a resonance frequency band associated with the bending and tensile principal strain directions of the plate body is selected according to a work load spectrum; the gradient distribution change of a surface temperature signal is synchronously analyzed, the energy fluctuation in the resonance frequency band is combined, the abnormal temperature rise area of the plate body caused by cyclic plastic deformation and internal friction heat generation is identified, and a mapping relationship between the spatial position of the abnormal temperature rise area, the energy attenuation rate of the time-frequency ridge line feature and a preset crack propagation dynamics model is established; the application accurately captures the weak feature signal related to the early micro-cracks of the plate body, realizes the accurate positioning of the initial micro-cracks and the quantitative determination of the expansion tendency, and effectively meets the needs of early warning and accurate detection of the quality of the plate body.

Description

Technical Field

[0001] This invention relates to the field of mechanical quality inspection technology, and in particular to an intelligent inspection method for the quality of excavator track shoes. Background Technology

[0002] As a core load-bearing and moving component of excavators, track shoes endure multiple forces such as cyclic loads and frictional impacts under complex working conditions. These track shoes are prone to developing microcracks due to stress concentration and material fatigue. These initial microcracks are tiny and inconspicuous; if not identified promptly and accurately, they can rapidly propagate under continuous working loads, eventually leading to track shoe fracture and failure. This not only affects the excavator's normal operating efficiency but may also cause safety accidents. Therefore, efficient and accurate inspection of track shoe quality is crucial.

[0003] Existing track plate quality inspection technologies have significant limitations in detecting initial microcracks, as they struggle to effectively capture the weak characteristic signals associated with microcracks. Since signals such as vibration and temperature changes during track plate operation are easily affected by factors such as operating condition fluctuations and environmental interference, existing methods fail to fully clarify the intrinsic relationship between these signals and the initiation and propagation of microcracks. They cannot accurately distinguish between signal anomalies caused by normal operating condition fluctuations and those caused by microcracks, nor can they quantify the propagation tendency of microcracks. This results in insufficient accuracy and limited reference value of the inspection results, failing to meet the practical application needs for early warning and accurate assessment of track plate quality. Summary of the Invention

[0004] This invention provides an intelligent detection method for the quality of excavator track pads to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides an intelligent detection method for the quality of excavator track shoes, comprising:

[0006] S1. Obtain the multi-source time-series monitoring signal set of the target track plate under the working load spectrum. The multi-source time-series monitoring signal set includes vibration acceleration signal and surface temperature signal deployed at preset measuring points on the plate.

[0007] S2. Based on the vibration acceleration signal, construct the time-frequency ridge line characteristics that reflect the dynamic characteristics of the local structure of the plate, and screen the resonant frequency bands that are related to the bending and tensile principal strain directions of the plate according to the working load spectrum.

[0008] S3. Simultaneously analyze the gradient distribution changes of the surface temperature signal, and combine them with the energy fluctuations within the resonant frequency band to identify the abnormal temperature rise area of ​​the plate caused by cyclic plastic deformation and internal frictional heat generation.

[0009] S4. Establish the mapping relationship between the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge characteristics, and the preset crack propagation dynamics model, and generate the quantitative evaluation results of the initial microcrack location and propagation tendency value of the plate.

[0010] S5. Based on the initial microcrack location and propagation tendency value in the quantitative evaluation results, generate a plate health status detection report.

[0011] Preferably, the setting of the preset measuring points on the plate includes:

[0012] Based on the plate's geometry and working load spectrum, key areas prone to stress concentration are identified, and these key areas are obtained.

[0013] Within the critical area, the initial installation position is obtained by cross-selecting the installation position of the measuring point based on the location of the maximum strain gradient on the plate surface and the location of the vibration mode node.

[0014] Based on the propagation and attenuation relationship between vibration and temperature signals in the plate, the relative spacing and orientation of the sensors at the initial installation positions are adjusted to obtain an optimized layout of the preset measurement points on the plate.

[0015] Preferably, the construction of time-frequency ridge features reflecting the dynamic characteristics of the local structure of the plate based on vibration acceleration signals includes:

[0016] The vibration acceleration signal is transformed by time and frequency to obtain the time and frequency energy distribution of the vibration acceleration signal;

[0017] In time-frequency energy distribution, based on the continuity of energy distribution, the evolution path of the frequency of the energy concentration area over time is traced to obtain the initial ridge line;

[0018] By combining the known dynamic response mode of the plate under the working load spectrum, the frequency value of the initial ridge line is trend-fitted to obtain the time-frequency ridge line characteristics that reflect the local structural dynamic characteristics of the plate.

[0019] Preferably, the step of screening the resonant frequency bands associated with the principal strain directions of plate bending and tension based on the working load spectrum includes:

[0020] By analyzing the working load spectrum, typical load components corresponding to bending and tensile deformation of the plate are separated, and typical load time series are obtained.

[0021] By mapping the time phase of a typical load time series to the frequency change phase of the time-frequency ridge feature, a time synchronization relationship between load excitation and plate frequency response is established.

[0022] Based on the time synchronization relationship, the fluctuation period of the instantaneous frequency of each frequency band and the change period of the typical load components in the time-frequency ridge characteristics are analyzed; the frequency bands with stable period correspondence are identified as resonant frequency bands.

[0023] Preferably, the synchronous analysis of the gradient distribution change of the surface temperature signal includes:

[0024] Based on surface temperature signals deployed at different preset measurement points, a temperature field reflecting the spatial distribution of temperature on the plate surface is constructed.

[0025] The temperature field over a continuous time series is analyzed, and the rate of change of the temperature difference between adjacent spatial points on the plate surface over time is calculated to obtain the gradient distribution change.

[0026] From the gradient distribution changes, regional features are extracted where the temperature change rate exceeds the change rate caused by the background heat conduction process of the plate, thus obtaining candidate anomalous temperature regions.

[0027] Preferably, the identification of abnormal temperature rise regions in the plate caused by cyclic plastic deformation and internal frictional heating, based on energy fluctuations within the resonant frequency band, includes:

[0028] Obtain the time series of energy fluctuations within the same time period in the resonant frequency band;

[0029] By mapping the time phase of candidate anomalous temperature regions to the change phase of energy fluctuation time series, the temporal correspondence and intensity ratio between the change of candidate anomalous temperature regions and energy fluctuation time series are analyzed to obtain the thermal-vibration coupling correlation.

[0030] Based on the thermal-vibration coupling relationship, sub-regions in the candidate abnormal temperature region where the change in temperature has a stable intensity ratio with the energy fluctuation time series are identified as abnormal temperature rise regions of the plate.

[0031] Preferably, the crack propagation dynamics model is constructed through the following steps:

[0032] Based on fatigue test data of the same material as the plate under working load spectrum, the constitutive relationship between crack propagation rate and stress intensity factor range was determined.

[0033] In the constitutive relation, a damping attenuation coefficient related to vibration energy dissipation is introduced as a correction term to establish a two-dimensional parameter space with the stress intensity factor range and the damping attenuation coefficient as coordinates, and the boundary between the stable crack propagation region and the unstable crack propagation region is delineated in this space.

[0034] By integrating the two-dimensional parameter space and boundary, a criterion system for quantitatively evaluating the crack propagation tendency is constructed, resulting in a crack propagation dynamics model.

[0035] Preferably, the mapping relationship between establishing the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge characteristics, and the preset crack propagation dynamics model includes:

[0036] For the abnormal temperature rise region, based on its spatial location and the principal stress trajectory of the plate under the working load spectrum, the potential crack initiation direction and local stress concentration factor are determined, and the local stress state parameters are obtained.

[0037] The amplitude of the time-frequency ridge feature within the resonant frequency band is fitted over time, and the percentage decrease in amplitude per unit time is calculated to obtain the energy decay rate.

[0038] Based on the local stress state parameters and energy decay rate, a feature point characterizing the current plate state is determined in the parameter space defined by the crack propagation dynamics model.

[0039] Based on the relative relationship between the position of feature points in the parameter space and the boundary of the crack stable propagation region defined by the model, the tendency of the abnormal temperature rise region to develop into a macroscopic crack is quantified, and the mapping relationship is obtained.

[0040] Preferably, the quantitative evaluation results of the initial microcrack location and propagation tendency value of the generated plate include:

[0041] From the abnormal temperature rise region, the region with the highest degree of overlap between its spatial location and the potential crack initiation direction indicated by the local stress state parameter is selected as the initial microcrack location.

[0042] Obtain the crack propagation tendency value quantified by the mapping relationship corresponding to the initial microcrack location;

[0043] The crack propagation tendency value is dynamically corrected based on the energy decay rate to obtain the corrected propagation tendency value.

[0044] The initial microcrack location is combined with the corrected propagation tendency value to form a quantitative evaluation result.

[0045] Preferably, the step of generating a plate health status detection report based on the initial microcrack location and propagation tendency value in the quantitative evaluation results includes:

[0046] The urgency level of maintenance action is determined based on the magnitude of the propagation tendency value and the local stress state parameters at the location of the initial microcrack.

[0047] Based on the correlation between energy decay rate and thermal-vibration coupling, maintenance strategy suggestions are generated for the initial microcrack location;

[0048] The spatial coordinates of the initial microcrack location, the propagation tendency value, the urgency level of maintenance actions, and maintenance strategy recommendations are structurally integrated to generate a plate health status detection report.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. By acquiring multi-source time-series monitoring signals of vibration acceleration and surface temperature, time-frequency ridge features are constructed and resonant frequency bands associated with the principal strain directions of plate bending and tension are screened. Simultaneously, the changes in temperature gradient distribution and energy fluctuations in resonant frequency bands are analyzed to identify abnormal temperature rise regions. Finally, combined with the crack propagation dynamics model, quantitative evaluation results of the initial microcrack location and propagation tendency are generated. This can accurately capture weak characteristic signals related to early microcracks in the plate, realize the accurate location of the initial microcrack and the quantitative determination of the propagation tendency, and effectively meet the needs of early warning and accurate detection of plate quality.

[0051] 2. The optimized layout of the pre-set measurement points on the plate ensures the effectiveness and reliability of the acquisition of multi-source monitoring signals. The crack propagation dynamics model is corrected by introducing the damping attenuation coefficient related to vibration energy dissipation. Combined with the mapping relationship between the spatial location of the abnormal temperature rise area and the energy attenuation rate of the time-frequency ridge, the accuracy and adaptability of the quantitative evaluation results are further improved. Attached Figure Description

[0052] Figure 1 This is a flowchart illustrating an intelligent detection method for the quality of excavator track pads according to an embodiment of the present invention.

[0053] Figure 2 This is a flowchart illustrating a method for determining an abnormal temperature rise region according to an embodiment of the present invention.

[0054] Figure 3 This is a flowchart illustrating a method for determining a crack propagation dynamics model according to an embodiment of the present invention.

[0055] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0056] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0057] This application provides an intelligent detection method for the quality of excavator track pads. The executing entity of this intelligent detection method for excavator track pad quality includes, but is not limited to, at least one of the electronic devices that can be configured to execute the method provided in this application, such as a server and a terminal. In other words, the intelligent detection method for excavator track pad quality can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0058] Example 1, referring to Figure 1 The diagram shown is a flowchart illustrating an intelligent detection method for the quality of excavator track shoes according to an embodiment of the present invention. In this embodiment, the intelligent detection method for the quality of excavator track shoes includes:

[0059] S1. Obtain the multi-source time-series monitoring signal set of the target track plate under the working load spectrum. The multi-source time-series monitoring signal set includes vibration acceleration signal and surface temperature signal deployed at preset measuring points on the plate.

[0060] S2. Based on the vibration acceleration signal, construct the time-frequency ridge line characteristics that reflect the dynamic characteristics of the local structure of the plate, and screen the resonant frequency bands that are related to the bending and tensile principal strain directions of the plate according to the working load spectrum.

[0061] S3. Simultaneously analyze the gradient distribution changes of the surface temperature signal, and combine them with the energy fluctuations within the resonant frequency band to identify the abnormal temperature rise area of ​​the plate caused by cyclic plastic deformation and internal frictional heat generation.

[0062] S4. Establish the mapping relationship between the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge characteristics, and the preset crack propagation dynamics model, and generate the quantitative evaluation results of the initial microcrack location and propagation tendency value of the plate.

[0063] S5. Based on the initial microcrack location and propagation tendency value in the quantitative evaluation results, generate a plate health status detection report.

[0064] In this embodiment, the setting of preset measuring points on the plate includes:

[0065] Based on the plate's geometry and working load spectrum, key areas prone to stress concentration are identified, and these key areas are obtained.

[0066] Within the critical area, the initial installation position is obtained by cross-selecting the installation position of the measuring point based on the location of the maximum strain gradient on the plate surface and the location of the vibration mode node.

[0067] Based on the propagation and attenuation relationship between vibration and temperature signals in the plate, the relative spacing and orientation of the sensors at the initial installation positions are adjusted to obtain an optimized layout of the preset measurement points on the plate.

[0068] In practice, a comprehensive analysis of the plate's geometry is first conducted to clarify the shape characteristics and connection relationships of each part of the plate, with a focus on the parts where the geometry changes abruptly. Then, the load type and load transfer path corresponding to the working load spectrum are associated with the plate's geometry. By analyzing the load transfer process in each part of the plate, the parts that bear large loads and have abrupt changes in geometry are identified. These parts are the key areas where stress concentration is likely to occur.

[0069] Furthermore, stress distribution analysis was performed on the key areas, and strain changes were checked point by point along different directions on the plate surface to determine the location with the most drastic strain gradient among adjacent positions. Then, periodic excitation was applied to the plate, and the vibration response at each location in the key areas was observed to determine the location of the vibration mode node where the vibration amplitude was always zero.

[0070] The location information of the maximum strain gradient point and the vibration mode node position are then superimposed and compared, and the position that is near the maximum strain gradient point and avoids the vibration mode node is selected as the initial installation position.

[0071] Furthermore, standard vibration signals and standard temperature signals were applied to different locations on the plate, and the corresponding signal amplitudes were collected at different distances and in different directions to clarify the attenuation law of vibration signals and temperature signals as the propagation distance increases and the propagation direction changes.

[0072] Finally, based on the attenuation law, the distance between the sensors at the initial installation position is adjusted to ensure that the signals collected by adjacent sensors will not be excessively attenuated due to excessive distance or redundant due to excessive distance. At the same time, the installation direction of the sensors is adjusted so that the sensor signal acquisition surface is facing the main direction of signal propagation, thereby obtaining the optimized layout of the preset measurement points on the board.

[0073] It should be noted that those skilled in the art can also arrange the points based on experience or evenly. Of course, the solution presented here is a preferred method. By cross-screening the geometric structure, load spectrum, strain gradient, and vibration mode nodes, and optimizing the layout in combination with the signal propagation attenuation law, it can accurately locate the key monitoring area, avoid redundant measurement points, ensure the effectiveness and reliability of the acquired signal, and balance detection accuracy and efficiency.

[0074] In this embodiment, based on the vibration acceleration signal, a time-frequency ridge feature reflecting the dynamic characteristics of the local structure of the plate is constructed, including:

[0075] The vibration acceleration signal is transformed by time and frequency to obtain the time and frequency energy distribution of the vibration acceleration signal;

[0076] In time-frequency energy distribution, based on the continuity of energy distribution, the evolution path of the frequency of the energy concentration area over time is traced to obtain the initial ridge line;

[0077] By combining the known dynamic response mode of the plate under the working load spectrum, the frequency value of the initial ridge line is trend-fitted to obtain the time-frequency ridge line characteristics that reflect the local structural dynamic characteristics of the plate.

[0078] In practice, a wavelet basis that fits the frequency range of the vibration acceleration signal is selected. The wavelet basis is then convolved with the vibration acceleration signal point by point according to different time shifts and frequency scaling ratios. Each time point and frequency point will yield a corresponding energy value. The energy values ​​corresponding to all time points and frequency points are arranged sequentially according to the time dimension and frequency dimension to form the time-frequency energy distribution of the vibration acceleration signal.

[0079] Furthermore, in the time-frequency energy distribution, an energy concentration region with a significantly higher energy value than the surrounding area is identified. Starting from the time starting position of this energy concentration region, the frequency point with the highest energy value at each moment is selected along the direction of time progression. These frequency points selected moment by moment are connected sequentially in time order to form the evolution path of the frequency of the energy concentration region over time, thus obtaining the initial ridge line.

[0080] Finally, the known dynamic response mode of the plate refers to the inherent law of the local structural vibration frequency of the plate changing with the load under working load. First, the frequency values ​​corresponding to each moment on the initial ridge line are extracted. With time as the horizontal axis and frequency value as the vertical axis, these frequency values ​​are sorted out. The fitted curve is compared with the initial ridge line by linear fitting. The discrete frequency points in the initial ridge line caused by signal noise are corrected to obtain the time-frequency ridge line characteristics that reflect the local structural dynamic characteristics of the plate.

[0081] In this embodiment, the resonant frequency bands related to the principal strain directions of plate bending and tension are screened based on the working load spectrum, including:

[0082] By analyzing the working load spectrum, typical load components corresponding to bending and tensile deformation of the plate are separated, and typical load time series are obtained.

[0083] By mapping the time phase of a typical load time series to the frequency change phase of the time-frequency ridge feature, a time synchronization relationship between load excitation and plate frequency response is established.

[0084] Based on the time synchronization relationship, the fluctuation period of the instantaneous frequency of each frequency band and the change period of the typical load components in the time-frequency ridge characteristics are analyzed; the frequency bands with stable period correspondence are identified as resonant frequency bands.

[0085] Among them, there exists a stable periodic correspondence through the correlation coefficient. The quantitative determination is performed using the following formula:

[0086] ;

[0087] In the formula, The Pearson correlation coefficient represents the relationship between load and frequency response; express The instantaneous frequency value of the time band; This represents the average instantaneous frequency over the analysis period. express The amplitude of the typical load component at any given time; This represents the average value of typical load components over the analysis period; This represents the number of sampling points within the analysis period. When... When the value exceeds a preset threshold, it is determined that a stable periodic correspondence exists.

[0088] In practice, the direction and form of action of various loads in the working load spectrum are first clarified, and loads that can cause bending deformation and tensile deformation of the plate are distinguished. Through time series extraction, the amplitude data of these two types of loads changing with time are extracted in chronological order to form typical load time series corresponding to bending deformation of the plate and typical load time series corresponding to tensile deformation of the plate.

[0089] Furthermore, the time references for the typical load time series and the time-frequency ridge feature are first unified to ensure that their time start points and time intervals are completely consistent. Then, the time phase of the typical load time series and the frequency change phase of the time-frequency ridge feature are matched moment by moment. The typical load amplitude and the frequency value of the time-frequency ridge feature corresponding to each time phase are recorded to establish the time synchronization relationship between the load excitation and the plate frequency response.

[0090] Furthermore, frequency bands with stable periodic correspondences are identified as resonant frequency bands. First, the instantaneous frequency values ​​of each frequency band at each moment during the analysis period are extracted from the time-frequency ridge features. Then, the time interval between the periodic fluctuations of the instantaneous frequency of each frequency band is counted, which is the fluctuation period.

[0091] Simultaneously, the amplitude of typical load components at each moment during the analysis period is extracted, the time interval of periodic changes in typical load components is statistically analyzed (i.e., the change period), and then the Pearson correlation coefficient is used to quantify and determine whether there is a stable periodic correspondence between the two.

[0092] Specifically, when calculating the Pearson correlation coefficient, The frequency band to be analyzed is derived from the time-frequency ridge features. The instantaneous frequency value at time 1. This refers to all frequency bands to be analyzed. Moment Add them together and divide by the number of sampling points within the analysis period. The obtained mean, Derived from typical load time series The load amplitude at that moment This refers to all of the typical load time series. Moment Add and then divide The obtained mean, It is the total number of vibration acceleration signals and load signals collected at fixed sampling intervals within the analysis period.

[0093] Specifically, first calculate each time and The difference, then calculate each time and The difference is calculated by multiplying the two differences at corresponding times and summing them to obtain the numerator. All differences are then calculated separately. time and Sum of squares of differences, all time and The sum of squares of the differences is multiplied, and the square root of the product of the two sums of squares is taken to obtain the denominator. The correlation coefficient is then obtained by dividing the numerator by the denominator. .

[0094] Specifically, the Pearson correlation coefficient is used to measure the degree of linear correlation between typical load components and instantaneous frequency changes in the frequency band. The more synchronous the changes of the two are, the closer the absolute value of the coefficient is to 1, and vice versa.

[0095] It should be noted that the preset threshold can be determined through multiple sets of plate load and frequency response experiments under different working conditions. Multiple sets of different working load conditions are selected, and typical load time series and time-frequency ridge characteristics are collected for each set of conditions. The data for each set are then calculated. Simultaneously observe whether the frequency band corresponding to each set of data is actually related to the principal strain direction of the plate bending or tension, and group the most actually related sets. The minimum absolute value is used as the preset threshold.

[0096] It should also be noted that those skilled in the art can directly perform Fourier transform on the vibration acceleration signal to extract steady-state frequency features, or decompose the signal into multiple intrinsic mode components through empirical mode decomposition, and then extract the frequency trajectory of each component as features.

[0097] Of course, regarding the selection of resonant frequency bands, the natural frequencies corresponding to the bending and stretching of the plate can be calibrated through offline frequency sweep experiments and directly used as the target resonant frequency bands; or, based on engineering experience, the resonant frequency band ranges corresponding to common faults of excavator track plates can be matched.

[0098] This solution provides an optimal approach that, through time-frequency transformation, energy ridge tracking, and dynamic response mode correction, can accurately characterize the time-varying dynamic characteristics of local structures. Combined with load phase synchronization and correlation coefficient quantification, it achieves a precise correlation between the resonant frequency band and actual working conditions and strain types, balancing the dynamic nature of the features with the objectivity of the selection process.

[0099] Example 2, as Figure 2 This is a flowchart illustrating a method for determining an abnormal temperature rise region according to an embodiment of the present invention.

[0100] In this embodiment, the synchronous analysis of the gradient distribution change of the surface temperature signal includes:

[0101] Based on surface temperature signals deployed at different preset measurement points, a temperature field reflecting the spatial distribution of temperature on the plate surface is constructed.

[0102] The temperature field over a continuous time series is analyzed, and the rate of change of the temperature difference between adjacent spatial points on the plate surface over time is calculated to obtain the gradient distribution change.

[0103] From the gradient distribution changes, regional features are extracted where the temperature change rate exceeds the change rate caused by the background heat conduction process of the plate, thus obtaining candidate anomalous temperature regions.

[0104] In practice, the surface temperature signals of all preset measuring points are collected at the same time. A two-dimensional spatial coordinate system is established based on the geometric coordinates of the plate, and the temperature value of each preset measuring point is mapped to its specific position in the two-dimensional spatial coordinate system.

[0105] Then, spatial interpolation is used to fill the temperature blank area between adjacent preset measuring points. During the interpolation process, the temperature value of the blank area is determined according to the changing trend of the temperature values ​​of adjacent measuring points, so that the filled temperature data can continuously cover the entire plate surface, and finally form a temperature field with corresponding temperature values ​​at all positions on the plate surface at each moment.

[0106] Furthermore, temperature fields corresponding to multiple consecutive time points are selected and arranged in chronological order to form a set of temperature fields in a continuous time sequence. For the temperature field at each time point, adjacent spatial points are selected on the surface of the plate, and the temperature difference between each pair of adjacent spatial points is calculated.

[0107] Then, select two adjacent time points, calculate the change in the temperature difference between the same pair of adjacent spatial points at these two time points, and divide the change by the time interval between the two time points to obtain the rate of change of the temperature difference between the pair of adjacent spatial points over time.

[0108] By traversing all adjacent spatial points on the plate surface and all adjacent moments in the continuous time series using the above method, the rate of change of temperature difference at all locations at different times is obtained. These rates of change are then organized according to spatial location and time order to form a gradient distribution.

[0109] Furthermore, the temperature change rate caused by the background heat conduction process of the plate is determined. By collecting the surface temperature signal of the plate when it is not under working load, the temperature change rate under no-load condition is obtained by calculating the temperature difference over time as described above. This change rate is the change rate caused by the background heat conduction process.

[0110] Finally, the temperature change rate at each location in the gradient distribution change is compared with the background heat conduction change rate. All spatial locations with a temperature change rate greater than the background heat conduction change rate are extracted. These locations are divided according to spatial continuity. Adjacent locations that both meet the conditions are grouped into one region. Features such as the spatial range and peak temperature change rate of each region are extracted to obtain candidate abnormal temperature regions.

[0111] In this embodiment, by combining energy fluctuations within the resonant frequency band, the abnormal temperature rise region of the plate caused by cyclic plastic deformation and internal frictional heat generation is identified, including:

[0112] Obtain the time series of energy fluctuations within the same time period in the resonant frequency band;

[0113] By mapping the time phase of candidate anomalous temperature regions to the change phase of energy fluctuation time series, the temporal correspondence and intensity ratio between the change of candidate anomalous temperature regions and energy fluctuation time series are analyzed to obtain the thermal-vibration coupling correlation.

[0114] Based on the thermal-vibration coupling relationship, sub-regions in the candidate abnormal temperature region where the change in temperature has a stable intensity ratio with the energy fluctuation time series are identified as abnormal temperature rise regions of the plate.

[0115] Among them, the stability strength ratio relationship is obtained through the coupling coefficient. Linear quantization, its calculation formula is:

[0116] ;

[0117] In the formula, Indicates the thermal-vibration coupling coefficient; and These represent the maximum and root mean square values ​​of the temperature change rate of the candidate abnormal temperature sub-regions during the analysis period, respectively. and These represent the maximum amplitude and root mean square value of the energy fluctuation time series within the same time period, respectively.

[0118] when When the strength remains stable within a predetermined reasonable range, it is determined that a stable intensity ratio exists.

[0119] In practice, the energy value corresponding to each time point in the analysis period is extracted from the previously screened resonant frequency band. During the extraction process, the total energy at each time point is obtained by calculating the superposition of the energy of all frequency components in the resonant frequency band. These total energies are then arranged in chronological order within the analysis period to form an energy fluctuation time series with time as the horizontal axis and energy value as the vertical axis.

[0120] Furthermore, we first unify the time reference of the candidate abnormal temperature region and the energy fluctuation time series to ensure that the starting point and time interval of the two are completely consistent. Then, we observe the changes in the temperature change rate of the candidate abnormal temperature region and the changes in the energy value of the energy fluctuation time series at each time step, record the time points when the peak and trough values ​​of the two occur, and determine whether these characteristic time points overlap or have a fixed time lag relationship to determine the time correspondence.

[0121] Simultaneously, the ratio of the temperature change rate amplitude of the candidate abnormal temperature region to the energy amplitude of the energy fluctuation time series at the same moment is calculated. The change of this ratio over time is observed to determine the intensity ratio relationship. The thermal-vibration coupling correlation is obtained by combining the time correspondence relationship and the intensity ratio relationship.

[0122] Furthermore, the candidate anomalous temperature region is subdivided into multiple sub-regions, and the thermal-vibration coupling coefficient is calculated for each sub-region. This coefficient reflects the degree of coupling matching between the intensity of temperature change in the sub-region and the intensity of energy fluctuation in the resonant frequency band. The larger the value, the stronger the correlation between the two.

[0123] It should be noted that the preset reasonable range can be determined through multiple sets of normal working condition experiments. For example, multiple sets of normal working conditions without cyclic plastic deformation and internal frictional heat generation of the plate can be selected, and data can be collected from different sub-regions under each set of conditions. , and the corresponding resonant frequency band and Calculate each set of data Statistics of these The distribution range is determined and used as a pre-defined reasonable range.

[0124] When a certain sub-region If the temperature remains within the preset reasonable range and there are no obvious sudden changes during the analysis period, it is determined that there is a stable strength ratio relationship, and this sub-region is the abnormal temperature rise region of the plate.

[0125] It should be emphasized that those skilled in the art can also pre-set the upper limit of the plate surface temperature and directly determine the area where the measured temperature exceeds the threshold as an abnormal temperature rise area.

[0126] Alternatively, temperature field distribution data under normal working conditions of the plate can be obtained through finite element simulation. The measured temperature field and the simulation data can be compared point by point, and areas where the difference exceeds the set range are judged as abnormal.

[0127] Alternatively, without combining temperature signals, the region where energy fluctuations exceed the reference value can be identified as an abnormal temperature rise region simply by monitoring the amplitude of energy fluctuations within the resonant frequency band.

[0128] This solution presents a preferred implementation method, which establishes and quantifies the thermal-vibration coupling relationship by synchronously analyzing the changes in temperature gradient distribution and the energy fluctuations in the resonant frequency band. This method can accurately locate abnormal areas caused by cyclic plastic deformation and internal frictional heat generation, taking into account both the real-time nature and accuracy of the determination.

[0129] Example 3, as Figure 3 This is a flowchart illustrating a method for determining a crack propagation dynamics model according to an embodiment of the present invention.

[0130] In this embodiment, the crack propagation dynamics model is constructed through the following steps:

[0131] Based on fatigue test data of the same material as the plate under working load spectrum, the constitutive relationship between crack propagation rate and stress intensity factor range was determined.

[0132] In the constitutive relation, a damping attenuation coefficient related to vibration energy dissipation is introduced as a correction term to establish a two-dimensional parameter space with the stress intensity factor range and the damping attenuation coefficient as coordinates, and the boundary between the stable crack propagation region and the unstable crack propagation region is delineated in this space.

[0133] By integrating the two-dimensional parameter space and boundary, a criterion system for quantitatively evaluating the crack propagation tendency is constructed, resulting in a crack propagation dynamics model.

[0134] In practice, a standard fatigue specimen is first prepared using a material that is completely consistent with the material and processing technology of the plate. The specimen is then placed in a fatigue testing device and subjected to a load that is exactly the same as the working load spectrum type and variation law of the plate.

[0135] During the experiment, the initiation and propagation of cracks on the sample surface were continuously observed, and the crack length at different test moments was recorded in real time. The crack propagation rate at different stages was calculated by the ratio of the change in crack length to the change in time.

[0136] Simultaneously, stress analysis was used to determine the range of stress intensity factor at the crack tip of the specimen at each moment. All experimental data were organized with the range of stress intensity factor as the horizontal axis and the crack propagation rate as the vertical axis to clarify the intrinsic relationship between the two and obtain the constitutive relationship between crack propagation rate and stress intensity factor range.

[0137] Furthermore, the damping attenuation coefficient is obtained through vibration tests on samples of the same material. The sample is subjected to vibration excitation at a fixed frequency, and the attenuation process of the vibration amplitude over time is recorded. The damping attenuation coefficient is calculated by the ratio of the vibration amplitude attenuation to the initial amplitude. This coefficient directly reflects the degree of energy dissipation of the material vibration.

[0138] Furthermore, the damping attenuation coefficient is incorporated as a correction term into the previously obtained constitutive relation to correct the influence of vibration energy dissipation on the crack propagation rate. A two-dimensional parameter space is constructed with the stress intensity factor range as the horizontal axis and the damping attenuation coefficient as the vertical axis.

[0139] Then, select multiple sets of fatigue test data of the same material under different load levels, record the stress intensity factor range and damping attenuation coefficient corresponding to the transition of crack from stable to unstable propagation in each set of data, mark these critical state parameter combinations as coordinate points in two-dimensional parameter space, and connect all the marked points in sequence to form a continuous curve, which is the boundary between the stable crack propagation region and the unstable crack propagation region.

[0140] Finally, the constructed two-dimensional parameter space is integrated with the defined stable-unstable propagation boundary, clarifying that one side of the boundary in the two-dimensional parameter space is the stable crack propagation region and the other side is the unstable crack propagation region. At the same time, the variation law of crack propagation rate in different regions is defined, forming a criterion system that can quantitatively evaluate the crack propagation tendency value based on the stress intensity factor range and damping attenuation coefficient. This criterion system is the crack propagation dynamics model.

[0141] It should be noted that the proposed solution for constructing the crack propagation dynamics model is a preferred implementation method. Those skilled in the art can also use industry-standard empirical formulas for crack propagation without combining material fatigue test data or introducing correction terms related to vibration energy dissipation; or they can directly generate the crack propagation dynamics model by simulating the crack initiation and propagation process of the plate under ideal load using finite element software.

[0142] Overall, this scheme determines the constitutive relation based on real fatigue test data of the same material, introduces a damping attenuation coefficient to correct the influence of vibration energy dissipation, and constructs a two-dimensional parameter space and propagation boundary that can accurately reflect the stable / unstable propagation state of cracks under actual working conditions, making the model more accurate and applicable.

[0143] In this embodiment, the mapping relationship between the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge characteristics, and the preset crack propagation dynamics model is established, including:

[0144] For the abnormal temperature rise region, based on its spatial location and the principal stress trajectory of the plate under the working load spectrum, the potential crack initiation direction and local stress concentration factor are determined, and the local stress state parameters are obtained.

[0145] The amplitude of the time-frequency ridge feature within the resonant frequency band is fitted over time, and the percentage decrease in amplitude per unit time is calculated to obtain the energy decay rate.

[0146] Based on the local stress state parameters and energy decay rate, a feature point characterizing the current plate state is determined in the parameter space defined by the crack propagation dynamics model.

[0147] Based on the relative relationship between the position of feature points in the parameter space and the boundary of the crack stable propagation region defined by the model, the tendency of the abnormal temperature rise region to develop into a macroscopic crack is quantified, and the mapping relationship is obtained.

[0148] In practice, the principal stress trajectory under the working load spectrum is first obtained through stress analysis of the plate structure. The transmission path and distribution law of the working load inside the plate are analyzed to determine the direction and magnitude of the principal stress in each region of the plate and form a principal stress trajectory diagram. The spatial location of the abnormal temperature rise region is matched with the principal stress trajectory diagram to determine the direction of the principal stress at the location of the region. The direction of potential crack initiation is perpendicular to the direction of the principal stress.

[0149] Simultaneously, the geometry and surrounding structure of the abnormal temperature rise region are analyzed, and the stress magnitude of this region is compared with that of other uniform stress regions of the plate. The local stress concentration factor of this region is calculated, and the potential crack initiation direction and the local stress concentration factor are integrated to form a local stress state parameter.

[0150] Furthermore, amplitude data corresponding to all moments within the resonance band are extracted from the time-frequency ridge features. These amplitude data are organized in chronological order, and the fitting curve is aligned with the trend of amplitude data using a linear fitting method. The variation law of amplitude over time is determined based on the fitting curve. Two different time points are selected, and the amplitude decrease between these two time points is calculated. The decrease is divided by the time interval between the two time points to obtain the average amplitude decrease rate.

[0151] Then, the ratio of the average amplitude decrease rate to the amplitude at the beginning of the time period is calculated to obtain the proportion of amplitude decrease per unit time, which is the energy decay rate.

[0152] Furthermore, the local stress concentration factor in the local stress state parameters is converted into the corresponding stress intensity factor range. This conversion is based on the mechanical properties of the plate material and the local stress distribution law. The converted stress intensity factor range is used as the horizontal axis coordinate, and the previously calculated energy decay rate is converted into the damping decay coefficient as the vertical axis coordinate. The position point corresponding to this set of horizontal and vertical coordinate axes is found in the two-dimensional parameter space of the crack propagation dynamics model. This position point is the characteristic point representing the current plate state.

[0153] Furthermore, the relative position of the feature point to the boundary of the stable crack propagation region is determined, and the distance from the feature point to the boundary is calculated. If the feature point is located within the stable propagation region, the distance is positive; if it is located within the unstable propagation region, the distance is negative.

[0154] Finally, the tendency of the abnormal temperature rise region to develop into a macroscopic crack is quantified based on the magnitude of the distance and the positive or negative direction. The closer to the boundary, the higher the tendency. When the distance is negative, the tendency is higher than when the distance is positive. The correspondence between the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge feature, and the location of the feature point and the tendency of crack propagation in the crack propagation dynamics model is established. This correspondence is the required mapping relationship.

[0155] In this embodiment, the quantitative evaluation results of the initial microcrack location and propagation tendency value of the generated plate include:

[0156] From the abnormal temperature rise region, the region with the highest degree of overlap between its spatial location and the potential crack initiation direction indicated by the local stress state parameter is selected as the initial microcrack location.

[0157] Obtain the crack propagation tendency value quantified by the mapping relationship corresponding to the initial microcrack location;

[0158] The crack propagation tendency value is dynamically corrected based on the energy decay rate to obtain the corrected propagation tendency value.

[0159] The initial microcrack location is combined with the corrected propagation tendency value to form a quantitative evaluation result.

[0160] In practice, first, the potential crack initiation direction indicated by the local stress state parameter is determined, then the spatial extension direction of each sub-region within the abnormal temperature rise area is analyzed, and the overlap between the extension direction of each sub-region and the potential crack initiation direction is calculated. The overlap is determined by the angle between the two directions. The smaller the angle, the higher the overlap. The sub-region with the smallest angle and the highest overlap is selected, and this sub-region is the location of the initial microcrack.

[0161] Furthermore, based on the established mapping relationship, the spatial location information corresponding to the initial microcrack location and the energy decay rate corresponding to that location are found. By matching these two pieces of information in the mapping relationship, the corresponding crack propagation tendency quantification value is obtained. This quantification value is the crack propagation tendency value corresponding to the initial microcrack location.

[0162] Furthermore, the correlation between energy decay rate and crack propagation was analyzed. The faster the energy decay rate, the higher the degree of damage to the local structure of the plate and the greater the possibility of crack propagation. According to this rule, when the energy decay rate increases, the corresponding crack propagation tendency value is increased by a fixed proportion, and when the energy decay rate decreases, it is decreased by the same proportion. In this way, the initially obtained crack propagation tendency value is dynamically adjusted to obtain the corrected propagation tendency value.

[0163] Finally, the spatial range and coordinate information of the determined initial microcrack location are integrated with the quantitative data of the corrected propagation tendency value to form a complete evaluation data set containing location information and propagation tendency quantitative data. This data set is the quantitative evaluation result of the initial microcrack location and propagation tendency value of the plate.

[0164] It should be emphasized that those skilled in the art can determine the location of the initial microcrack solely based on the magnitude of the temperature gradient in the abnormal temperature rise area. The area with the largest temperature gradient can be directly used as the location of microcrack initiation, and the propagation tendency level can be empirically classified based on the magnitude of the temperature gradient.

[0165] Alternatively, accelerated fatigue failure tests can be conducted on track plates of the same specifications, and standard data on crack initiation location and propagation rate can be recorded. The measured abnormal temperature rise area and vibration energy data can be manually compared with the standard data to provide an evaluation result.

[0166] In general, the present invention provides a preferred embodiment, which establishes a mapping relationship between thermal-vibration dual parameters and crack propagation dynamics model, and combines stress state parameters and energy attenuation characteristics to achieve accurate quantification of microcrack location and propagation tendency. The evaluation results are more in line with actual working conditions and have dynamic correction capabilities.

[0167] In this embodiment, based on the initial microcrack location and propagation tendency value in the quantitative evaluation results, a plate health status detection report is generated, including:

[0168] The urgency level of maintenance action is determined based on the magnitude of the propagation tendency value and the local stress state parameters at the location of the initial microcrack.

[0169] Based on the correlation between energy decay rate and thermal-vibration coupling, maintenance strategy suggestions are generated for the initial microcrack location;

[0170] The spatial coordinates of the initial microcrack location, the propagation tendency value, the urgency level of maintenance actions, and maintenance strategy recommendations are structurally integrated to generate a plate health status detection report.

[0171] In practice, the magnitude of the propagation tendency value is first divided into different levels. Then, the local stress concentration factor and potential crack initiation direction in the local stress state parameters at the initial microcrack location are combined to determine whether the stress at that location is above the fatigue limit of the plate material.

[0172] When the propagation tendency value is at a high level and the local stress concentration factor is large, while the potential crack initiation direction is perpendicular to the principal stress direction of the plate, the maintenance urgency level is determined to be the highest level. When the propagation tendency value is at a low level and the local stress concentration factor is small, while the potential crack initiation direction deviates from the principal stress direction of the plate, the maintenance urgency level is determined to be the lowest level. In other cases, the intermediate level is determined according to the combination of the propagation tendency value and the local stress state parameter, thereby determining the urgency level of the maintenance action.

[0173] Furthermore, the rate of energy decay was analyzed. The faster the energy decay rate, the more severe the local structural damage to the plate. Combined with the tightness of the thermal-vibration coupling relationship, the tighter the coupling relationship, the stronger the correlation between abnormal temperature rise and resonant energy fluctuation, that is, the clearer the cause of crack initiation.

[0174] When the energy decay rate is fast and the thermal-vibration coupling relationship is tight, it is recommended to immediately stop the machine, grind and repair the initial microcrack location, and carry out comprehensive flaw detection. When the energy decay rate is slow and the thermal-vibration coupling relationship is loose, it is recommended to shorten the detection cycle, strengthen real-time monitoring of the location, and record its status changes, so as to generate maintenance strategy recommendations for the initial microcrack location.

[0175] Furthermore, the spatial coordinates of the initial microcrack locations were analyzed to clarify their specific orientation on the plate, and then the quantitative data of the propagation tendency value and the urgency level of the maintenance action were analyzed.

[0176] Finally, complete the corresponding maintenance strategy recommendations, and arrange all the information in the order of basic information of the tested object, analysis of test results, and maintenance recommendations to form a complete and logically clear structured document, which is the board health status test report.

[0177] In summary, this solution uses multi-dimensional data linkage, combines expansion tendency values ​​and local stress states to classify urgency levels, and formulates precise maintenance strategies based on energy decay rate and thermal-vibration coupling correlation. The generated structured report is logically clear and well-founded, and can directly guide actual maintenance actions.

[0178] In the several embodiments provided by this invention, it should be understood that the disclosed methods can be implemented in other ways.

[0179] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0180] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, and technology that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0181] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent detection method for the quality of excavator track shoes, characterized in that, The method includes: S1. Obtain the multi-source time-series monitoring signal set of the target track plate under the working load spectrum. The multi-source time-series monitoring signal set includes vibration acceleration signal and surface temperature signal deployed at preset measuring points on the plate. S2. Based on the vibration acceleration signal, construct the time-frequency ridge line characteristics that reflect the dynamic characteristics of the local structure of the plate, and screen the resonant frequency bands that are related to the bending and tensile principal strain directions of the plate according to the working load spectrum. S3. Simultaneously analyze the gradient distribution changes of the surface temperature signal, and combine them with the energy fluctuations within the resonant frequency band to identify the abnormal temperature rise area of ​​the plate caused by cyclic plastic deformation and internal frictional heat generation. S4. Establish the mapping relationship between the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge characteristics, and the preset crack propagation dynamics model, and generate the quantitative evaluation results of the initial microcrack location and propagation tendency value of the plate. S5. Based on the initial microcrack location and propagation tendency value in the quantitative evaluation results, generate a plate health status detection report.

2. The intelligent detection method for the quality of excavator track shoes as described in claim 1, characterized in that, The setting of the preset measuring points on the plate includes: Based on the plate's geometry and working load spectrum, key areas prone to stress concentration are identified, and these key areas are obtained. Within the critical area, the initial installation position is obtained by cross-selecting the installation position of the measuring point based on the location of the maximum strain gradient on the plate surface and the location of the vibration mode node. Based on the propagation and attenuation relationship between vibration and temperature signals in the plate, the relative spacing and orientation of the sensors at the initial installation positions are adjusted to obtain an optimized layout of the preset measurement points on the plate.

3. The intelligent detection method for the quality of excavator track shoes as described in claim 1, characterized in that, The construction of time-frequency ridge features reflecting the dynamic characteristics of the local structure of the plate based on vibration acceleration signals includes: The vibration acceleration signal is transformed by time and frequency to obtain the time and frequency energy distribution of the vibration acceleration signal; In time-frequency energy distribution, based on the continuity of energy distribution, the evolution path of the frequency of the energy concentration area over time is traced to obtain the initial ridge line; By combining the known dynamic response mode of the plate under the working load spectrum, the frequency value of the initial ridge line is trend-fitted to obtain the time-frequency ridge line characteristics that reflect the local structural dynamic characteristics of the plate.

4. The intelligent detection method for the quality of excavator track shoes as described in claim 3, characterized in that, The method of screening resonant frequency bands related to the principal strain directions of plate bending and tension based on the working load spectrum includes: By analyzing the working load spectrum, typical load components corresponding to bending and tensile deformation of the plate are separated, and typical load time series are obtained. By mapping the time phase of a typical load time series to the frequency change phase of the time-frequency ridge feature, a time synchronization relationship between load excitation and plate frequency response is established. Based on the time synchronization relationship, the fluctuation period of the instantaneous frequency of each frequency band and the change period of the typical load components in the time-frequency ridge characteristics are analyzed; the frequency bands with stable period correspondence are identified as resonant frequency bands.

5. The intelligent detection method for the quality of excavator track shoes as described in claim 4, characterized in that, The synchronous analysis of the gradient distribution change of the surface temperature signal includes: Based on surface temperature signals deployed at different preset measurement points, a temperature field reflecting the spatial distribution of temperature on the plate surface is constructed. The temperature field over a continuous time series is analyzed, and the rate of change of the temperature difference between adjacent spatial points on the plate surface over time is calculated to obtain the gradient distribution change. From the gradient distribution changes, regional features are extracted where the temperature change rate exceeds the change rate caused by the background heat conduction process of the plate, thus obtaining candidate anomalous temperature regions.

6. The intelligent detection method for the quality of excavator track shoes as described in claim 5, characterized in that, The method of identifying abnormal temperature rise regions in the plate caused by cyclic plastic deformation and internal frictional heating by combining energy fluctuations within the resonant frequency band includes: Obtain the time series of energy fluctuations within the same time period in the resonant frequency band; By mapping the time phase of candidate anomalous temperature regions to the change phase of energy fluctuation time series, the temporal correspondence and intensity ratio between the change of candidate anomalous temperature regions and energy fluctuation time series are analyzed to obtain the thermal-vibration coupling correlation. Based on the thermal-vibration coupling relationship, sub-regions in the candidate abnormal temperature region where the change in temperature has a stable intensity ratio with the energy fluctuation time series are identified as abnormal temperature rise regions of the plate.

7. The intelligent detection method for the quality of excavator track shoes as described in claim 6, characterized in that, The crack propagation dynamics model is constructed through the following steps: Based on fatigue test data of the same material as the plate under working load spectrum, the constitutive relationship between crack propagation rate and stress intensity factor range was determined. In the constitutive relation, a damping attenuation coefficient related to vibration energy dissipation is introduced as a correction term to establish a two-dimensional parameter space with the stress intensity factor range and the damping attenuation coefficient as coordinates, and the boundary between the stable crack propagation region and the unstable crack propagation region is delineated in this space. By integrating the two-dimensional parameter space and boundary, a criterion system for quantitatively evaluating the crack propagation tendency is constructed, resulting in a crack propagation dynamics model.

8. The intelligent detection method for the quality of excavator track shoes as described in claim 7, characterized in that, The mapping relationship between establishing the spatial location of the abnormal temperature rise region, the energy decay rate of the time-frequency ridge characteristics, and the preset crack propagation dynamics model includes: For the abnormal temperature rise region, based on its spatial location and the principal stress trajectory of the plate under the working load spectrum, the potential crack initiation direction and local stress concentration factor are determined, and the local stress state parameters are obtained. The amplitude of the time-frequency ridge feature within the resonant frequency band is fitted over time, and the percentage decrease in amplitude per unit time is calculated to obtain the energy decay rate. Based on the local stress state parameters and energy decay rate, a feature point characterizing the current plate state is determined in the parameter space defined by the crack propagation dynamics model. Based on the relative relationship between the position of feature points in the parameter space and the boundary of the crack stable propagation region defined by the model, the tendency of the abnormal temperature rise region to develop into a macroscopic crack is quantified, and the mapping relationship is obtained.

9. The intelligent detection method for the quality of excavator track shoes as described in claim 8, characterized in that, The quantitative evaluation results of the initial microcrack location and propagation tendency of the generated plate include: From the abnormal temperature rise region, the region with the highest degree of overlap between its spatial location and the potential crack initiation direction indicated by the local stress state parameter is selected as the initial microcrack location. Obtain the crack propagation tendency value quantified by the mapping relationship corresponding to the initial microcrack location; The crack propagation tendency value is dynamically corrected based on the energy decay rate to obtain the corrected propagation tendency value. The initial microcrack location is combined with the corrected propagation tendency value to form a quantitative evaluation result.

10. The intelligent detection method for the quality of excavator track shoes as described in claim 6, characterized in that, Based on the initial microcrack location and propagation tendency value from the quantitative assessment results, a plate health status detection report is generated, including: The urgency level of maintenance action is determined based on the magnitude of the propagation tendency value and the local stress state parameters at the location of the initial microcrack. Based on the correlation between energy decay rate and thermal-vibration coupling, maintenance strategy suggestions are generated for the initial microcrack location; The spatial coordinates of the initial microcrack location, the propagation tendency value, the urgency level of maintenance actions, and maintenance strategy recommendations are structurally integrated to generate a plate health status detection report.

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