Adaptive Adjustment Method and System for Braking Pressure of Underground Rack Rail Vehicle

Abstract

The present invention relates to the technical field of braking of rack and pinion vehicles, and particularly to a method and system for adaptively adjusting the braking pressure of underground rack and pinion vehicles, which can adaptively adjust the braking pressure according to different underground driving condition attributes. The method includes: constructing an influence matrix related to braking conditions; in the influence matrix related to braking conditions, different underground driving condition attributes respectively correspond to different theoretical attenuation amplitudes of braking performance; obtaining in real time the underground driving condition attributes corresponding to the braking action to be performed by the rack and pinion vehicle; taking the underground driving condition attributes obtained in real time as the target, traversing in the preset influence matrix related to braking conditions to obtain the theoretical attenuation amplitude of braking performance corresponding to the braking action to be performed; obtaining the braking performance score after the previous braking action, and combining with the theoretical attenuation amplitude of braking performance, calculating to obtain the predicted braking performance score after the braking action to be performed; and generating a braking pressure adjustment strategy corresponding to the braking action to be performed based on the predicted braking performance score after the braking action to be performed.

Description

Technical Field

[0001] The present invention relates to the technical field of braking of rack vehicles, and particularly to a method and system for adaptively adjusting the braking pressure of underground rack vehicles. Background Art

[0002] In modern mine exploitation operations, underground rack vehicles, as core transportation equipment, frequently shuttle through complex roadways, undertaking the heavy responsibility of material transfer and personnel transportation. The performance of their braking systems is directly related to the safety and efficiency of the entire mine operation. The underground working conditions are complex. For example, variable driving gradients, different driving speeds, frequent bends, and dynamic changes in vehicle load will all have a significant impact on the braking performance of rack vehicles. With the continuous expansion of the depth and scale of mine exploitation, the requirements for the braking systems of underground rack vehicles are also getting higher and higher.

[0003] The existing methods for adjusting the braking pressure of underground rack vehicles are relatively single, mostly using a fixed braking pressure mode. Whether the vehicle is unloaded or fully loaded, driving on a flat roadway or a steep slope, the braking pressure always remains unchanged. This results in that when the vehicle is fully loaded and going downhill, the fixed braking pressure is difficult to provide sufficient braking force, easily leading to vehicle out of control; while when driving unloaded or on a flat road, the excessive braking pressure will cause excessive wear of braking components and unnecessary consumption of energy.

[0004] Therefore, there is an urgent need for a method for adaptively adjusting the braking pressure of underground rack vehicles to solve the above problems. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a method and system for adaptively adjusting the braking pressure of underground rack vehicles, which can adaptively adjust the braking pressure according to different underground driving condition attributes.

[0006] In the first aspect, the present invention provides a method for adaptively adjusting the braking pressure of underground rack vehicles, and the method includes:

[0007] Construct an influence matrix related to braking conditions; in the influence matrix related to braking conditions, different underground driving condition attributes respectively correspond to different theoretical attenuation amplitudes of braking performance;

[0008] Obtain in real time the underground driving condition attributes corresponding to the braking action to be performed by the rack vehicle;

[0009] Taking the underground driving condition attributes obtained in real time as the target, traverse in the influence matrix related to braking conditions to obtain the theoretical attenuation amplitude of braking performance corresponding to the braking action to be performed;

[0010] Obtain the braking performance score after the previous braking action, and combine it with the theoretical attenuation amplitude of braking performance to calculate the predicted braking performance score after the braking action to be performed;

[0011] Generate a braking pressure adjustment strategy corresponding to the braking action to be performed based on the predicted braking performance score after the braking action to be performed.

[0012] Combined with the first aspect, in a possible design, construct an influence matrix related to the braking condition, including:

[0013] Collect the braking characteristic parameter set of the underground rack rail vehicle after each braking action and the corresponding underground driving condition attributes.

[0014] Use a preset braking performance evaluation model to quantitatively evaluate the braking characteristic parameter set, and obtain the braking performance score of the underground rack rail vehicle after each braking;

[0015] For each braking performance score, perform performance decay analysis with the previous and closest braking performance score to obtain the braking performance decay amplitude corresponding to the braking action of the underground rack rail vehicle;

[0016] Conduct a correlation analysis on the braking performance decay amplitude and the corresponding underground driving condition attributes, and construct an influence matrix related to the braking condition according to the analysis results.

[0017] Combined with the first aspect, in a possible design, the braking characteristic parameter set includes the brake cylinder pressure, brake pad wear, brake oil temperature, brake pipeline pressure, and braking response time.

[0018] Combined with the first aspect, in a possible design, the underground driving condition attributes include vehicle load, driving slope, driving speed, and curve curvature.

[0019] Combined with the first aspect, in a possible design, obtain the underground driving condition attributes corresponding to the braking action to be performed by the rack rail vehicle in real time, including:

[0020] According to the working condition change rate and data accuracy requirements, set the acquisition frequency for sensors at different positions respectively;

[0021] According to the set acquisition frequency, each sensor collects the working condition attribute data in real time;

[0022] Conduct a preliminary verification on the collected working condition attribute data, and eliminate abnormal data;

[0023] Convert the data after verification and processing into a unified format that can be recognized and processed.

[0024] Combined with the first aspect, in a possible design, with the underground driving condition attributes obtained in real time as the target, traverse in the influence matrix related to the braking condition to obtain the theoretical braking performance decay amplitude corresponding to the braking action to be performed, including:

[0025] Take the underground driving condition attribute as the target attribute for searching and matching in the braking condition related influence matrix;

[0026] Establish an index according to the range division of different underground driving condition attributes, and locate the matrix area that may be related to the target attribute according to the index;

[0027] In the located matrix area, compare the underground driving condition attribute corresponding to each element in the matrix with the target attribute one by one;

[0028] For each compared matrix element, evaluate the similarity between the underground driving condition attribute and the target attribute according to the preset similarity evaluation criteria; if the similarity reaches the preset threshold, it is considered that the theoretical attenuation amplitude of the braking performance corresponding to the matrix element may be related to the current braking action to be performed;

[0029] Find the matrix element with the highest similarity between the underground driving condition attribute and the target attribute, and determine the theoretical attenuation amplitude of the braking performance corresponding to this element as the theoretical attenuation amplitude of the braking performance corresponding to the braking action to be performed.

[0030] Combined with the first aspect, in a possible design, based on the predicted braking performance score after the braking action to be performed, generate a braking pressure adjustment strategy corresponding to the braking action to be performed, including:

[0031] Pre - formulate braking pressure adjustment strategies for different ranges of predicted braking performance scores to form a strategy library;

[0032] Compare the predicted braking performance score with the score intervals in the braking pressure adjustment strategy library;

[0033] Find the corresponding braking pressure adjustment strategy according to the interval where the predicted braking performance score is located;

[0034] According to the matched braking pressure adjustment strategy, combined with the current braking pressure value, calculate the braking pressure adjustment amount.

[0035] In the second aspect, the present application also provides an underground rack - pinion vehicle braking pressure adaptive adjustment system, and the system includes:

[0036] A matrix construction module for constructing a braking condition related influence matrix, in which different underground driving condition attributes respectively correspond to different theoretical attenuation amplitudes of braking performance;

[0037] A working condition attribute acquisition module for real - time acquiring the underground driving condition attribute corresponding to the braking action to be performed by the rack - pinion vehicle;

[0038] The attenuation amplitude acquisition module takes the underground driving condition attributes acquired in real time as the target, traverses the preset braking condition related influence matrix, and obtains the theoretical attenuation amplitude of the braking performance corresponding to the braking action to be performed;

[0039] The performance score calculation module is used to obtain the braking performance score after the last braking action, and calculate the predicted braking performance score after the braking action in combination with the theoretical attenuation amplitude of the braking performance;

[0040] The strategy generation module generates a brake pressure adjustment strategy corresponding to the braking action to be performed based on the brake performance prediction score after the braking action to be performed.

[0041] In conjunction with the second aspect, in one possible design, the matrix building module is further configured as follows:

[0042] Collecting the braking characteristic parameter set and the corresponding underground driving condition attributes of the underground rack rail vehicle after each braking action;

[0043] The preset braking performance evaluation model is used to quantitatively evaluate the braking characteristic parameter set to obtain the braking performance score of the underground rack rail vehicle after each braking;

[0044] For each braking performance score, a performance decay analysis is performed with the previous and most recent braking performance score to obtain the braking performance decay amplitude corresponding to the braking action of the underground rack rail vehicle;

[0045] The correlation between the braking performance attenuation amplitude and the corresponding underground driving condition attributes is analyzed, and the braking condition related influence matrix is constructed based on the analysis results.

[0046] In conjunction with the second aspect, in a possible design, the operating condition attribute acquisition module is further configured as follows:

[0047] According to the rate of change of working conditions and the requirements of data accuracy, set the collection frequency for sensors in different locations;

[0048] According to the set collection frequency, each sensor collects working condition attribute data in real time;

[0049] Conduct preliminary verification on the collected working condition attribute data and eliminate abnormal data;

[0050] Convert the verified and processed data into a unified format that can be recognized and processed.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] By constructing an influence matrix related to the braking condition, the correlation between the attributes of the underground driving condition and the theoretical attenuation amplitude of the braking performance is established, providing a comprehensive data framework for subsequent analysis; by obtaining the condition attributes in real time, closely fitting the actual operating state of the rack rail vehicle, ensuring that subsequent analysis and adjustment are based on the real scenario; by traversing the real-time condition attributes in the matrix to obtain the theoretical attenuation amplitude of the braking performance, realizing the accurate mapping between the condition and the change of the braking performance; by obtaining the previous braking performance score and calculating the predicted score in combination with the theoretical attenuation amplitude, considering the influence of the historical braking situation and the current condition on the braking performance, providing a dynamic and comprehensive perspective for the evaluation of the braking performance; by generating a braking pressure adjustment strategy based on the predicted score, realizing the accurate adaptive adjustment of the braking pressure.

[0053] In terms of accurately coping with complex working conditions, by constructing an influence matrix related to the braking condition and obtaining the condition attributes in real time to determine the theoretical attenuation amplitude, it can comprehensively and dynamically adapt to the complex and changeable underground working conditions, considering the influence of the historical state of the system on the current braking; in terms of optimizing the performance of the braking system, it can not only accurately adjust the braking pressure according to different working conditions to improve safety, but also avoid excessive wear of components and unnecessary consumption of energy, extend the life of components and save energy; in terms of improving the overall operation efficiency, the stable adjustment of the braking pressure ensures the stable operation of the rack rail vehicle, maintains the smooth transportation process, and can also adapt to the complex working condition requirements brought about by the expansion of the mine exploitation scale, improving the operation efficiency. Brief Description of the Drawings

[0054] Figure 1 is the flow chart of the present invention;

[0055] Figure 2 is the flow chart of constructing an influence matrix related to the braking condition in the embodiment;

[0056] Figure 3 is the structural diagram of the underground rack rail vehicle braking pressure adaptive regulation system. Detailed Embodiment

[0057] The present application will be described below with reference to the drawings in the present application.

[0058] As Figure 1 shown, the underground rack rail vehicle braking pressure adaptive regulation method of the present invention specifically includes the following steps:

[0059] Step S1, construct an influence matrix related to the braking condition; in the influence matrix related to the braking condition, different attributes of the underground driving condition respectively correspond to different theoretical attenuation amplitudes of the braking performance;

[0060] Step S2, obtain the attributes of the underground driving condition corresponding to the braking action to be performed by the rack rail vehicle in real time;

[0061] Step S3: Using the underground driving condition attributes obtained in real time as the target, traverse in the preset influence matrix related to braking conditions to obtain the theoretical attenuation amplitude of braking performance corresponding to the pending braking action;

[0062] Step S4: Obtain the braking performance score after the last braking action, and combine it with the theoretical attenuation amplitude of braking performance to calculate the predicted braking performance score after the pending braking action;

[0063] Step S5: Based on the predicted braking performance score after the pending braking action, generate a braking pressure adjustment strategy corresponding to the pending braking action.

[0064] In this embodiment, by constructing an influence matrix related to braking conditions, the relationship between underground driving condition attributes and the theoretical attenuation amplitude of braking performance is comprehensively sorted out, providing a data basis for subsequent adjustment; by obtaining condition attributes in real time, closely fitting the actual operating state of the vehicle, making the adjustment more targeted and timely; traversing in the matrix to obtain the theoretical attenuation amplitude of braking performance, and combining with historical scores to calculate predicted scores, taking into account condition changes and historical braking situations, improving the accuracy of braking performance evaluation; generating a braking pressure adjustment strategy based on the predicted score to achieve precise adaptive adjustment of braking pressure, which can not only provide sufficient braking force in dangerous conditions such as heavy load downhill to ensure driving safety, but also avoid excessive braking pressure during no-load or flat-road driving, reducing wear of braking components and energy consumption; this method significantly improves the safety, reliability and economy of the braking system of underground rack rail vehicles.

[0065] In some embodiments of the present invention, for step S1, as Figure 2 shown, constructing an influence matrix related to braking conditions includes:

[0066] Step S11: Collect the braking characteristic parameter set and the corresponding underground driving condition attributes of the underground rack rail vehicle after each braking action;

[0067] Step S12: Use a preset braking performance evaluation model to quantitatively evaluate the braking characteristic parameter set to obtain the braking performance score of the underground rack rail vehicle after each braking;

[0068] Step S13: For each braking performance score, perform performance attenuation analysis with the previous and nearest braking performance score to obtain the braking performance attenuation amplitude corresponding to the braking action of the underground rack rail vehicle;

[0069] Step S14: Analyze the correlation between the braking performance attenuation amplitude and the corresponding underground driving condition attributes, and construct an influence matrix related to braking conditions according to the analysis results.

[0070] Specifically, step S11 aims to collect key state parameters reflecting the situation of the rack rail vehicle during braking and external condition conditions during vehicle driving, where the braking characteristic parameter set includes:

[0071] a) Brake cylinder pressure: The brake cylinder pressure directly reflects the magnitude of the force applied during braking. By installing a pressure sensor on the brake cylinder, the pressure changes inside the brake cylinder during the braking process are monitored in real time. After each braking action, this pressure value is recorded to facilitate subsequent analysis of the working state and braking effect of the braking system;

[0072] b) Brake pad wear: The degree of wear of the brake pads is related to the reliability and service life of the braking system. A wear sensor is used to obtain the wear amount of the brake pads. After each braking, the thickness change of the brake pads is measured by the sensor to obtain the wear amount data of the brake pads;

[0073] c) Brake oil temperature: Heat is generated during the braking process, causing the brake oil temperature to rise. Excessive oil temperature will affect the performance and stability of the braking system. A temperature sensor is installed in the brake oil circuit to monitor the change of the brake oil temperature in real time. After each braking, the value of the brake oil temperature is recorded to analyze the heat dissipation situation and working state of the braking system;

[0074] d) Brake pipeline pressure: The brake pipeline is responsible for transmitting the brake fluid and transferring the pressure of the brake cylinder to each braking component; A pressure sensor is installed in the brake pipeline to monitor the pressure change inside the brake pipeline in real time; After each braking action, the brake pipeline pressure value is recorded for evaluating the sealing performance of the brake pipeline and the transmission situation of the brake fluid;

[0075] e) Brake response time: The brake response time refers to the time interval from when the driver issues a braking command to when the braking system starts to generate braking force. By installing a time sensor in the control circuit of the brake, the brake response time is accurately measured. After each braking, this time data is recorded to analyze the response speed and sensitivity of the braking system.

[0076] Furthermore, the underground driving condition attributes include:

[0077] f) Vehicle load: By installing a weighing sensor on the chassis or suspension system of the underground rack rail vehicle, the vehicle load is measured in real time. During each braking, the vehicle load data is recorded to facilitate subsequent analysis of the braking performance changes under different load conditions;

[0078] g) Driving slope: The slope of the underground roadway changes greatly, which has a significant impact on the braking performance. By installing a slope sensor or using an inertial measurement unit (IMU) to measure the driving slope of the vehicle, the current driving slope data is recorded during each braking, providing a basis for analyzing the influence of the slope on the braking performance;

[0079] h) Travel speed: By installing speed sensors on the wheels or drive shafts of the rack vehicle, the travel speed of the vehicle is monitored in real time. Each time braking occurs, the travel speed data before braking is recorded to facilitate subsequent analysis of braking performance at different speeds;

[0080] i) Bend curvature: There are many bends in the underground roadway, and the bend curvature will affect the stability of the vehicle during braking; The bend curvature is measured by installing angle sensors or using on-vehicle cameras combined with image recognition technology. Each time braking occurs, the curvature data of the bend where the vehicle is located is recorded for analyzing the influence of the bend on braking performance.

[0081] Through the above methods, a set of braking characteristic parameters and the corresponding underground driving condition attributes of the underground rack vehicle after each braking action are comprehensively collected, providing a rich and accurate data basis for constructing an influence matrix related to braking conditions subsequently.

[0082] Step S12 concretizes the complex braking performance, enabling different braking situations to have quantifiable and comparable criteria. The quantitative evaluation method is as follows:

[0083] Step S121: Input the set of braking characteristic parameters after each braking collected into a preset braking performance evaluation model; The set of braking characteristic parameters serves as the input variable of the braking performance evaluation model, providing a data basis for the braking performance evaluation model to evaluate braking performance; For example, the magnitude of the brake cylinder pressure reflects the power output during braking. A lower brake cylinder pressure may mean insufficient braking force; Excessive wear of the brake pads may lead to a decline in braking effect, etc. Each parameter reflects the working state of the braking system from different aspects;

[0084] Step S122: Analyze and calculate the input braking characteristic parameters according to the internal set algorithms and weight coefficients of the braking performance evaluation model; Methods such as weighted average, analytic hierarchy process, neural network, etc. are used to comprehensively evaluate each parameter; For example, higher weights are assigned to parameters such as brake cylinder pressure and brake pipeline pressure that directly affect the magnitude of braking force, while parameters such as brake pad wear and brake oil temperature, although they will not immediately cause braking failure, will have an important impact on braking performance in the long run, so appropriate weights are assigned; Through these algorithms and weights, the model integrates and operates each parameter to obtain a value that can comprehensively reflect braking performance.

[0085] Step S123: After the operation and processing by the model, a specific value is output, which is the braking performance score of the underground rack rail vehicle after each braking. The braking performance score can intuitively reflect the performance status of the braking system of the rack rail vehicle during this braking. The range and criteria of the score are determined according to actual requirements and experience when establishing the model. For example, a score range of 0 - 100 can be set. The higher the score, the better the braking performance. A score below 60 indicates that there are certain problems with the braking performance and inspections and maintenance are required, etc.

[0086] In the above way, with the comprehensively collected braking characteristic parameter set as the input, and using the preset braking performance evaluation model to quantitatively evaluate the braking characteristic parameter set, the complex working state of the braking system can be transformed into an intuitive braking performance score, providing data support for subsequent analysis of the braking performance attenuation amplitude and construction of the influence matrix related to braking conditions, etc.

[0087] Step S13 precisely presents the dynamic changes in braking performance by comparing and analyzing each braking performance score with the previous nearest score. The specific content is as follows:

[0088] Step S131: For each obtained braking performance score, find its previous and nearest braking performance score as the comparison object; analyze the changes in braking performance during two adjacent braking processes. Since adjacent braking processes have strong relevance in terms of time and working conditions, they can more accurately reflect the real-time change trend of braking performance.

[0089] Step S132: Numerically compare the current braking performance score with the selected previous nearest braking performance score and calculate the difference between the two. For example, if the current braking performance score is 85 points and the previous nearest braking performance score is 90 points, then the difference is 85 - 90 = -5 points. The difference initially reflects whether the braking performance has improved or declined and the approximate degree of change.

[0090] Step S133: Analyze the reason for the difference in combination with the braking characteristic parameter set and the corresponding underground driving condition attributes. For example, if it is found that the wear amount of the brake pads increases significantly during this braking, and at the same time the driving slope is large and the vehicle load is heavy, then it can be speculated that the decline in braking performance may be due to the increased load and slope causing the brake pads to wear more severely, thus affecting the braking performance.

[0091] Step S134: Comprehensively consider the above various factors, conduct a comprehensive assessment of the attenuation of braking performance, and finally determine a value that can accurately reflect the degree of attenuation of braking performance, that is, the braking performance attenuation amplitude; the braking performance attenuation amplitude is not just a simple score difference, but a more accurate measure of the actual change degree of braking performance after comprehensively considering various influencing factors; for example, although the score difference is 5 points, considering the special working conditions of this braking and the change of braking characteristic parameters, after comprehensive analysis, it is determined that the braking performance attenuation amplitude is 8%. 8% can more accurately reflect the performance change of the braking system between these two brakings, providing more valuable data support for subsequent work such as constructing the influence matrix related to braking conditions.

[0092] In the above way, select adjacent scores for comparison, utilize their strong correlation in time and working conditions to accurately present the real-time change trend of braking performance, and provide an intuitive basis for the state monitoring of the braking system; calculating the score difference can initially judge the rise and fall and change degree of braking performance, with simple and intuitive operation and quick positioning of performance fluctuations; combine the braking characteristic parameters and the analysis of the reasons for the difference in the underground driving working condition attributes to deeply explore the internal factors of performance changes and provide clues for fault diagnosis and performance optimization; comprehensively evaluate and determine the braking performance attenuation amplitude, get rid of the limitation of simple numerical difference, comprehensively consider various influencing factors, and obtain a more accurate measurement value, providing high-quality data for subsequent work such as constructing the influence matrix related to braking conditions, and helping the scientific management and safe operation of the underground rack rail vehicle braking system.

[0093] Step S14 reveals the association between the braking performance attenuation amplitude and the underground driving working condition attributes through correlation analysis, and the specific content is as follows:

[0094] Step S141: Sort out the obtained braking performance attenuation amplitude data and the corresponding underground driving working condition attribute data; the underground driving working condition attributes include information such as vehicle load, driving slope, driving speed, and curve curvature, ensuring that these data are accurate, complete, and in one-to-one correspondence;

[0095] Step S142: Select a suitable correlation analysis method to conduct correlation analysis. For example, the Pearson correlation coefficient analysis method can be used to measure the linear correlation degree between the braking performance attenuation amplitude and each underground driving condition attribute. Other more complex analysis methods, such as multiple linear regression analysis, can also be used to consider the comprehensive influence of the interaction between multiple condition attributes on the braking performance attenuation amplitude. For the attribute of the braking performance attenuation amplitude and vehicle load, the correlation coefficient between the two is obtained through analysis and calculation. For example, if the calculated correlation coefficient is 0.7, it indicates that there is a strong positive correlation between the braking performance attenuation amplitude and vehicle load, that is, the greater the vehicle load, the greater the possible braking performance attenuation amplitude. Similarly, correlation analysis is separately conducted on other condition attributes such as driving slope, driving speed, and curve curvature with the braking performance attenuation amplitude to obtain corresponding analysis results such as correlation coefficients or regression equations to clarify their mutual relationships.

[0096] Step S143: Construct a relevant influence matrix for braking conditions according to the results of the correlation analysis. The rows and columns of the matrix can respectively correspond to different underground driving condition attributes and ranges of braking performance attenuation amplitudes. In the matrix, the relationship between each condition attribute and the braking performance attenuation amplitude is represented in the form of numerical values or symbols. For example, if there is a strong correlation between vehicle load and a certain range of braking performance attenuation amplitudes, a relatively large numerical value or a specific symbol, such as "++", is marked at the corresponding position in the matrix. If the correlation between the two is weak, a smaller numerical value or symbol, such as "+", or "±", is marked. For other condition attributes such as driving slope, driving speed, and curve curvature, they are also marked in the matrix in the same way, thus forming a relevant influence matrix for braking conditions that comprehensively reflects the relationship between the braking performance attenuation amplitude and underground driving condition attributes. The relevant influence matrix for braking conditions can intuitively display the change trend of braking performance under different conditions and provide an important reference basis for adjusting the braking pressure according to real-time conditions later.

[0097] In the above way, the data of the braking performance attenuation amplitude and underground driving condition attributes are sorted out to ensure accurate and complete correspondence of the data, laying a solid foundation for subsequent analysis; a suitable analysis method is selected to comprehensively consider the linear and comprehensive relationships between each condition attribute and the braking performance attenuation amplitude, and accurately reveal their internal connections; the relevant influence matrix for braking conditions constructed according to the analysis results clearly presents the change trend of braking performance under different conditions in an intuitive row-column representation form, providing a key reference for accurately adjusting the braking pressure of the underground rack railway vehicle according to real-time conditions, improving the adaptability and safety of the braking system to complex conditions, and ensuring the efficient development of mine operations.

[0098] In some embodiments of the present invention, step S2 relies on sensors with reasonable selection and precise deployment to provide real-time data support for subsequent precise regulation. The specific implementation steps are as follows:

[0099] Step S21: Set the acquisition frequency for sensors at different positions according to the working condition change rate and data accuracy requirements; for working condition parameters with rapid changes, such as driving speed and curve curvature changes, set a higher acquisition frequency, for example, set the acquisition frequency of the corresponding sensor to 100 Hz; for working condition parameters with relatively slow changes, such as vehicle load and driving slope, set a relatively low acquisition frequency, for example, set the acquisition frequency of the corresponding sensor to 10 Hz.

[0100] Step S22: Each sensor collects working condition attribute data in real time according to the established frequency; after the sensor converts the collected physical quantity into an electrical signal, it transmits it.

[0101] Step S23: Conduct a preliminary verification on the collected working condition attribute data to eliminate abnormal data; use a data filtering algorithm, such as median filtering, to process the signal output by the sensor, and remove the spike noise and abnormal values caused by factors such as electromagnetic interference. For example, for driving speed data, if the speed value collected at a certain moment far exceeds the normal driving speed range of the vehicle, replace it with a reasonable value through the median filtering algorithm.

[0102] Step S24: Convert the verified and processed data into a unified format that can be recognized and processed; for example, uniformly convert the analog or digital data output by different sensors into a binary coding format to prepare for subsequent query in the influence matrix related to the braking condition and braking performance analysis.

[0103] In this embodiment, by setting the acquisition frequency according to the working condition change rate and data accuracy requirements, precise control of working condition parameters with different change characteristics is achieved. High-frequency acquisition is set for rapidly changing working condition parameters to ensure data real-time, and low-frequency acquisition is set for slowly changing working condition parameters to reduce the data processing burden while taking into account data quality and efficiency; the real-time acquisition and transmission of sensors ensure that the system can timely obtain vehicle operation status information and provide immediate data for braking pressure regulation; using an algorithm to verify data effectively eliminates abnormal values, improves data accuracy, and avoids misjudgment caused by incorrect data; unifying the data format eliminates format differences, facilitates identification and processing, and improves the scientificity and reliability of braking pressure adaptive regulation.

[0104] The sensors include a weighing sensor, an acceleration sensor, a rotational speed sensor, and an angle sensor. Specifically:

[0105] a) Load cell: Installed at the key load-bearing parts of the rack vehicle chassis; for example, a resistance strain gauge type load cell is used, which converts the pressure generated by the vehicle load into an electrical signal output through the principle of pressure strain.

[0106] b) Acceleration sensor: Installed on the longitudinal center line of the rack vehicle, near the vehicle's center of gravity; for example, a biaxial acceleration sensor is used, which precisely calculates the vehicle's driving slope by detecting the components of gravitational acceleration in different axial directions.

[0107] c) Rotation speed sensor: Installed near the drive wheel of the rack vehicle; for example, an electromagnetic induction type rotation speed sensor is used. When the wheel rotates, the sensing element of the sensor cuts the magnetic field lines, generating a pulse signal proportional to the wheel rotation speed. By measuring the number of pulses per unit time and combining with the wheel circumference, the vehicle's driving speed can be precisely calculated.

[0108] d) Angle sensor: Installed on the steering mechanism of the rack vehicle; for example, a potentiometer type angle sensor is used. As the steering mechanism rotates, the resistance value of the sensor changes, outputting a voltage signal proportional to the steering angle. By monitoring the change rate and duration of the steering angle, and combining parameters such as the vehicle wheelbase, the curve curvature is calculated using geometric algorithms, providing information on the driving conditions of the vehicle on the curve for the braking system.

[0109] In some embodiments of the present invention, step S3 traverses the real-time underground driving condition attributes in a preset matrix to accurately match the theoretical attenuation amplitude of the braking performance corresponding to the braking action to be performed. The specific implementation is as follows:

[0110] Step S31: Use the underground driving condition attributes as the target attributes for searching and matching in the braking condition related influence matrix; that is, the vehicle load, driving slope, driving speed, and curve curvature information, which reflect the actual operating conditions of the rack vehicle when braking is to be performed currently.

[0111] Step S32: Establish an index according to the range division of different condition attributes, and locate the matrix area that may be related to the target attributes according to the index; for example, according to the numerical range of the vehicle load, quickly determine the corresponding row or column range in the matrix to narrow the search space.

[0112] Step S33: In the initially located matrix area, compare the underground driving condition attributes corresponding to each element in the matrix with the target attributes one by one; by comparing specific values such as the vehicle load, driving slope, driving speed, and curve curvature, judge the similarity between them; for example, calculate the difference between the target driving speed and the driving speed corresponding to each element in the matrix, or use more complex similarity calculation methods (such as Euclidean distance, cosine similarity, etc.) to measure the similarity of the overall condition attributes.

[0113] Step S34: For each compared matrix element, determine its similarity to the target downhole driving condition attribute according to a preset similarity evaluation criterion; if the similarity reaches a certain threshold, it is considered that the theoretical attenuation amplitude of the braking performance corresponding to the matrix element may be related to the current braking action to be performed;

[0114] Step S35: After traversing the matrix area and evaluating the similarity of all elements, find the matrix element with the highest similarity to the target downhole driving condition attribute, and determine the theoretical attenuation amplitude of the braking performance corresponding to this element as the theoretical attenuation amplitude of the braking performance corresponding to the braking action to be performed; the theoretical attenuation amplitude of the braking performance reflects the possible attenuation degree of the braking performance predicted based on historical data and analysis under the current downhole driving condition, and provides an important basis for calculating the predicted score of the braking performance after the braking action to be performed.

[0115] In this embodiment, through the operation of step S3 above, the real-time downhole driving condition attribute is clearly used as the search target, closely conforming to the actual operating conditions of the rack rail vehicle, providing a direction for subsequent operations; by establishing an index to locate the relevant matrix area, the search range is reduced, the search efficiency is improved, and computing resources are saved; by using a method of comparing one by one and complex similarity calculation, the similarity degree of the condition attributes is comprehensively measured to ensure the accuracy of the evaluation; determining the similarity according to the preset standard can accurately screen out the theoretical attenuation amplitude of the braking performance related to the current braking action to be performed; finding the attenuation amplitude corresponding to the element with the highest similarity provides a reliable basis for calculating the predicted score of the braking performance, enabling the entire braking pressure adaptive adjustment mechanism to better adapt to complex conditions and ensure the safe and efficient operation of the downhole rack rail vehicle based on an accurate prediction of the braking performance change.

[0116] In some embodiments of the present invention, step S4 accurately calculates the predicted score of the braking performance after the braking action to be performed by combining the previous braking performance score and the current theoretical attenuation amplitude of the braking performance, providing core data support for formulating a reasonable braking pressure adjustment strategy in the future. The specific implementation is as follows:

[0117] Step S41: Obtain the braking performance score after the previous braking action; query and extract from the storage device the braking performance score recorded after the previous braking action ended. The score is obtained by quantitatively evaluating the set of braking characteristic parameters after the previous braking action through a preset braking performance evaluation model, reflecting the comprehensive performance state of the braking system of the rack rail vehicle during the previous braking; for example, after the previous braking action, the braking performance score obtained through evaluation by the braking performance evaluation model is 80 points.

[0118] Step S42: Determine the theoretical attenuation amplitude of braking performance; the theoretical attenuation amplitude of braking performance is obtained by traversing in a preset influence matrix related to braking conditions with the attributes of the underground driving conditions obtained in real time as the target, where different attributes of underground driving conditions correspond to different theoretical attenuation amplitudes of braking performance; for example, under the current real-time working conditions, by matching in the matrix, it is determined that the corresponding theoretical attenuation amplitude of braking performance is 10%, which means that under the current working conditions, the braking performance will theoretically attenuate by 10%.

[0119] Step S43: Calculate the predicted braking performance score after the upcoming braking action based on the obtained braking performance score after the last braking action and the determined theoretical attenuation amplitude of braking performance; a common calculation method is to calculate according to a certain formula. For example: the predicted braking performance score after the upcoming braking action = the braking performance score after the last braking action × (1 - the theoretical attenuation amplitude of braking performance). Taking the data in the above example, if the braking performance score after the last braking is 80 points and the theoretical attenuation amplitude of braking performance is 10%, then the predicted braking performance score after the upcoming braking action = 80×(1 - 0.1) = 72 points. The predicted score of 72 points reflects the braking performance level expected after this braking action under the current working conditions considering the theoretical attenuation of braking performance.

[0120] Step S44: Conduct a rationality check on the calculated predicted braking performance score; compare the braking performance scores under similar working conditions in historical data, or make a comprehensive judgment in combination with the actual operating state of the current vehicle (such as whether there is a braking system fault warning, etc.). If it is found that there may be a large deviation between the predicted score and the actual situation, the data sources in the calculation process will be further checked (such as the accuracy of the braking performance score after the last braking, the rationality of the theoretical attenuation amplitude of braking performance, etc.), and corresponding adjustments will be made as needed to ensure that the finally obtained predicted braking performance score can truly reflect the braking performance situation after this upcoming braking action.

[0121] In this embodiment, through the operations of Step S4 above, the braking performance score after the last braking is obtained. This score, through quantitative evaluation, can truly reflect the comprehensive performance of the braking system last time and provides a historical data basis for this calculation; by traversing in the preset matrix to determine the theoretical attenuation amplitude of braking performance, it is closely related to the real-time working conditions, making the prediction fit the actual operating state; using a scientific formula to calculate the predicted braking performance score clearly and intuitively presents the expected braking performance level under the current working conditions; conducting a rationality check on the predicted score, making a comprehensive judgment in combination with historical data and the actual operating state of the vehicle, promptly checking for data deviations, and adjusting the calculation process to ensure that the score truly reflects the braking performance after this upcoming braking action, providing a solid and reliable data support for formulating accurate and effective braking pressure adjustment strategies later, and effectively ensuring the safe and stable operation of the underground rack rail vehicle braking.

[0122] In some embodiments of the present invention, step S5 can dynamically adjust the braking pressure according to the prediction results of the braking performance of the rack vehicle under real-time working conditions, ensuring that the braking system can maintain a stable and efficient working state under different working conditions. The specific implementation is as follows:

[0123] Step S51: Establish a braking pressure adjustment strategy library; in advance, according to a large amount of experimental data, theoretical analysis, and actual operation experience, a series of detailed braking pressure adjustment strategies are formulated for different ranges of braking performance prediction scores to form a strategy library; for example, the braking performance prediction scores are divided into multiple intervals. If the score is in the range of 0-40 points, it represents extremely poor braking performance, and a strategy of significantly increasing the braking pressure and issuing an alarm is set; if the score is in the range of 40-60 points, it represents poor braking performance, and a strategy of appropriately increasing the braking pressure and giving a system check prompt is set; if the score is in the range of 60-80 points, it represents general braking performance, and a strategy of maintaining the current braking pressure and continuously monitoring is set; if the score is in the range of 80-100 points, it represents good braking performance, and a strategy of appropriately reducing the braking pressure to save energy is set; the above strategies not only consider the braking performance, but also comprehensively consider various factors such as the actual operation safety of the underground rack vehicle, the wear condition of the braking components, and energy consumption;

[0124] Step S52: Compare the calculated braking performance prediction score after the braking action with the score intervals in the braking pressure adjustment strategy library; according to the interval where the score is located, find the corresponding braking pressure adjustment strategy; for example, if the calculated braking performance prediction score is 50 points, by searching the strategy library, it is determined that it is in the interval of 40-60 points, so the strategy of "appropriately increasing the braking pressure and giving a system check prompt" is matched;

[0125] Step S53: Based on the matched braking pressure adjustment strategy and combined with the current braking pressure value, calculate the braking pressure adjustment amount; for example, if the strategy is to appropriately increase the braking pressure, according to factors such as the distance between the score and the interval boundary, the current load of the vehicle, and the driving slope, calculate the value of the braking pressure to be increased through a specific formula. For example, for every 1-point score difference, increase the braking pressure by a certain proportion (such as 1%); if the strategy involves other operations, such as issuing an alarm or giving a system check prompt, the corresponding operation parameters also need to be clarified, such as the level of the alarm, the content and method of the prompt, etc.;

[0126] Step S54: Generate a corresponding braking pressure adjustment control instruction according to the calculated braking pressure adjustment amount; the instruction includes the direction of braking pressure adjustment (increase or decrease), the specific value of the adjustment, the time requirement for execution, and other relevant operation information (such as alarm triggering, etc.); for example, the generated instruction may be "within the next 5 seconds, increase the braking pressure by 10% and at the same time issue a second-level alarm;

[0127] Step S55: After the actuator receives the instruction, it performs corresponding operations according to the instruction requirements to achieve the adjustment of the braking pressure and other related operations. The actuator includes, but is not limited to, a brake pump, a brake valve, etc.;

[0128] Step S56: Verify whether the actually adjusted pressure meets the expectation. If there is a deviation, make corresponding adjustments. Each sensor monitors the actual change of the braking pressure in real time. After the braking pressure adjustment actuator executes the instruction, compare the actual braking pressure value with the adjustment target required in the instruction. If it is found that there is a deviation between the actual braking pressure and the target pressure, and the deviation exceeds a certain allowable range, then adjust the braking pressure adjustment strategy according to the magnitude and direction of the deviation, regenerate and send a new adjustment instruction to ensure that the braking pressure can be accurately adjusted to the expected target value, realizing the precise control of the braking pressure.

[0129] In this embodiment, through the operations of step S5 above, a braking pressure adjustment strategy library is established. Combining experimental data, theoretical analysis and practical experience, comprehensive and scientific strategies are formulated for different braking performance prediction score intervals, fully considering multiple aspects such as operation safety, component wear and energy consumption; comparing the prediction score with the strategy library can quickly match the accurate strategy, and then calculate the adjustment amount in combination with the current braking pressure value, generate a control instruction containing detailed operation information, and let the actuator execute accurately; verify the adjusted pressure in real time. Once the deviation exceeds the allowable range, adjust the strategy and instruction in time to realize the precise control of the braking pressure, ensure that the braking system always maintains stable and efficient operation under complex and changeable working conditions, and improve the safety and economy of the underground rack railway vehicle operation.

[0130] In some solutions, multiple embodiments of the present application can be combined and the combined solution can be implemented. Optionally, some operations in the processes of the method embodiments are optionally combined, and / or the order of some operations is optionally changed. And, the execution order between the steps of each process is only exemplary and does not constitute a limitation on the execution order between the steps. The steps can also be in other execution orders. It is not intended to indicate that the execution order is the only order in which these operations can be executed. Those of ordinary skill in the art will think of various ways to reorder the operations described herein. In addition, it should be noted that the process details involved in a certain embodiment herein are also applicable to other embodiments in a similar manner, or different embodiments can be combined and used.

[0131] In addition, some steps in the method embodiments can be equivalently replaced with other possible steps. Or, some steps in the method embodiments can be optional and can be deleted in some usage scenarios. Or, other possible steps can be added to the method embodiments.

[0132] Moreover, each method embodiment can be implemented independently or in combination.

[0133] As Figure 3 shown, the present invention also provides an adaptive adjustment system for the braking pressure of an underground rack rail vehicle, which specifically includes the following modules;

[0134] A matrix construction module for constructing an influence matrix related to the braking condition. In the influence matrix related to the braking condition, different underground driving condition attributes respectively correspond to different theoretical attenuation amplitudes of braking performance;

[0135] A condition attribute acquisition module for acquiring in real time the underground driving condition attributes corresponding to the braking action to be performed by the rack rail vehicle;

[0136] An attenuation amplitude acquisition module, taking the underground driving condition attributes acquired in real time as the target, traversing in the preset influence matrix related to the braking condition, and obtaining the theoretical attenuation amplitude of braking performance corresponding to the braking action to be performed;

[0137] A performance score calculation module for obtaining the braking performance score after the last braking action, and calculating the predicted braking performance score after the braking action to be performed in combination with the theoretical attenuation amplitude of braking performance;

[0138] A strategy generation module for generating a braking pressure adjustment strategy corresponding to the braking action to be performed based on the predicted braking performance score after the braking action to be performed.

[0139] In this embodiment, the matrix construction module sorts out the relationship between the condition attributes and the braking performance attenuation amplitude, providing data support for subsequent analysis; the condition attribute acquisition module collects data in real time to ensure that the system can be adjusted according to the actual working conditions; the attenuation amplitude acquisition module accurately matches the braking performance attenuation amplitude under the current working condition by traversing the matrix, providing a basis for performance evaluation; the performance score calculation module calculates the predicted score after the braking action to be performed by combining the historical score and the theoretical attenuation amplitude, comprehensively considering the change of braking performance; the strategy generation module generates an adjustment strategy based on the predicted score to achieve precise control of the braking pressure; each module works together to adjust the braking pressure in real time according to the complex underground working conditions, ensuring driving safety, avoiding excessive wear of braking components and energy waste, and improving the safety, reliability and economy of the braking system of the underground rack rail vehicle.

[0140] In a specific implementation, as an embodiment, the matrix construction module is further configured to:

[0141] Collect the braking characteristic parameter set and the corresponding underground driving condition attributes after each braking action of the underground rack rail vehicle.

[0142] Quantitatively evaluate the braking characteristic parameter set by using a preset braking performance evaluation model to obtain the braking performance score of the underground rack rail vehicle after each braking;

[0143] For each braking performance score, a performance decay analysis is performed with the previous and most recent braking performance score to obtain the braking performance decay amplitude corresponding to the braking action of the underground rack rail vehicle;

[0144] A correlation analysis is performed on the braking performance attenuation amplitude and the corresponding underground driving condition attributes, and a braking condition related influence matrix is constructed according to the analysis results.

[0145] The matrix construction module constructs a braking condition-related influence matrix by collecting, analyzing and processing the braking characteristic parameters and underground driving condition attributes, providing data support for the entire underground rack vehicle brake pressure adaptive adjustment system, so that the system can accurately predict the attenuation of braking performance based on the real-time underground driving condition attributes, thereby achieving precise adjustment of braking pressure, ensuring driving safety, and improving the reliability and economy of the braking system.

[0146] In a specific implementation, as an embodiment, the operating condition attribute acquisition module is further configured to:

[0147] According to the rate of change of working conditions and the data accuracy requirements, set the collection frequency for sensors in different locations;

[0148] According to the set collection frequency, each sensor collects working condition attribute data in real time;

[0149] Performing preliminary verification on the collected working condition attribute data and eliminating abnormal data;

[0150] Convert the verified and processed data into a unified format that can be recognized and processed.

[0151] The working condition attribute acquisition module provides real-time, accurate and reliable underground driving condition attribute data for the underground rack rail vehicle brake pressure adaptive adjustment system by reasonably setting the sensor acquisition frequency, accurately collecting data, strictly verifying data and unifying the data format. The system can accurately adjust the brake pressure according to the actual working conditions, thereby ensuring driving safety, avoiding excessive wear of brake components and energy waste, and improving the safety, reliability and economy of the underground rack rail vehicle braking system.

[0152] This embodiment divides the functional modules according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0153] The various variations and specific embodiments of the underground rack rail vehicle braking pressure adaptive regulation method in the foregoing Embodiment 1 are equally applicable to the underground rack rail vehicle braking pressure adaptive regulation system of this embodiment. Through the foregoing detailed description of the underground rack rail vehicle braking pressure adaptive regulation method, those skilled in the art can clearly know the implementation method of the underground rack rail vehicle braking pressure adaptive regulation system in this embodiment. Therefore, for the sake of brevity of the specification, it will not be elaborated herein.

[0154] The foregoing is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for adaptively adjusting the braking pressure of an underground rack rail vehicle, characterized in that, The method includes: Constructing an influence matrix related to the braking condition; in the influence matrix related to the braking condition, different underground driving condition attributes respectively correspond to different theoretical attenuation amplitudes of braking performance; Obtaining in real time the underground driving condition attributes corresponding to the braking action to be performed by the rack pinion vehicle; Taking the underground driving condition attributes obtained in real time as the target, traversing in the influence matrix related to the braking condition, and obtaining the theoretical attenuation amplitude of braking performance corresponding to the braking action to be performed; Obtaining the braking performance score after the previous braking action, and combining with the theoretical attenuation amplitude of braking performance, calculating the predicted braking performance score after the braking action to be performed; Generating a braking pressure adjustment strategy corresponding to the braking action to be performed based on the predicted braking performance score after the braking action to be performed; Constructing an influence matrix related to the braking condition, including: Collecting the braking characteristic parameter set and the corresponding underground driving condition attributes after each braking action of the underground rack pinion vehicle; Quantitatively evaluating the braking characteristic parameter set by using a preset braking performance evaluation model, and obtaining the braking performance score of the underground rack pinion vehicle after each braking; For each braking performance score, numerically comparing the current braking performance score with the selected previous nearest braking performance score, and calculating the difference between the two; Comprehensively evaluating the difference in combination with the braking characteristic parameter set and the corresponding underground driving condition attributes to obtain the braking performance attenuation amplitude; Performing a correlation analysis on the braking performance attenuation amplitude and the corresponding underground driving condition attributes, and constructing an influence matrix related to the braking condition according to the analysis result.

2. The method for adaptively adjusting the braking pressure of the underground rack rail vehicle according to claim 1, characterized in that, The braking characteristic parameter set includes braking cylinder pressure, brake pad wear, brake oil temperature, brake pipeline pressure, and braking response time.

3. The method for adaptively adjusting the braking pressure of the underground rack vehicle according to claim 1, wherein, The underground driving condition attributes include vehicle load, driving slope, driving speed, and curve curvature.

4. The underground toothed rail vehicle braking pressure adaptive adjustment method according to any one of claims 1-3, characterized in that, Obtaining in real time the underground driving condition attributes corresponding to the braking action to be performed by the rack pinion vehicle, including: Setting the acquisition frequency for sensors at different positions respectively according to the working condition change rate and data accuracy requirements; According to the set acquisition frequency, each sensor acquires the working condition attribute data in real time; Performing a preliminary verification on the acquired working condition attribute data, and removing abnormal data; Converting the data after verification and processing into a unified format that can be recognized and processed.

5. The underground rack rail vehicle braking pressure adaptive regulation method according to any one of claims 1-3, characterized in that Taking the underground driving condition attributes obtained in real time as the target, traversing in the influence matrix related to the braking condition, and obtaining the theoretical attenuation amplitude of braking performance corresponding to the braking action to be performed, including: Taking the underground driving condition attributes as the target attributes for searching and matching in the influence matrix related to the braking condition; Establishing an index according to the range division of different underground driving condition attributes, and positioning the matrix area related to the target attributes according to the index; In the positioned matrix area, comparing each element in the matrix with the target attributes one by one for the corresponding underground driving condition attributes; For each compared matrix element, the similarity between the underground driving condition attribute and the target attribute is evaluated according to a preset similarity evaluation standard; if the similarity reaches a preset threshold, it is considered that the theoretical attenuation amplitude of the braking performance corresponding to the matrix element is related to the current braking action to be performed; Find the matrix element with the highest similarity between the underground driving condition attribute and the target attribute, and determine the theoretical attenuation amplitude of the braking performance corresponding to the element as the theoretical attenuation amplitude of the braking performance corresponding to the braking action to be performed.

6. The underground rack vehicle braking pressure adaptive adjustment method according to any one of claims 1-3, characterized in that, Based on the braking performance prediction score after the braking action to be performed, a braking pressure adjustment strategy corresponding to the braking action to be performed is generated, including: Predict and score the braking performance in different ranges in advance, formulate brake pressure adjustment strategies, and form a strategy library; Comparing the braking performance prediction score with the score interval in the brake pressure regulation strategy library; Finding a corresponding brake pressure adjustment strategy according to the interval of the brake performance prediction score; The brake pressure adjustment amount is calculated based on the matched brake pressure adjustment strategy and the current brake pressure value.

7. An underground rack rail vehicle braking pressure adaptive regulation system, characterized in that, The system is applied to the method for adaptively adjusting the braking pressure of an underground rack vehicle according to claim 1, and the system comprises: A matrix construction module is used to construct a braking condition-related influence matrix, in which different underground driving condition attributes correspond to different theoretical attenuation amplitudes of braking performance; A working condition attribute acquisition module, used to obtain the underground driving working condition attributes corresponding to the braking action of the rack rail vehicle in real time; The attenuation amplitude acquisition module takes the underground driving condition attributes acquired in real time as the target, traverses the preset braking condition related influence matrix, and obtains the theoretical attenuation amplitude of the braking performance corresponding to the braking action to be performed; The performance score calculation module is used to obtain the braking performance score after the last braking action, and calculate the predicted braking performance score after the braking action in combination with the theoretical attenuation amplitude of the braking performance; The strategy generation module generates a brake pressure adjustment strategy corresponding to the braking action to be performed based on the brake performance prediction score after the braking action to be performed.

8. The downhole rack rail vehicle braking pressure adaptive regulation system according to claim 7, wherein, The matrix building module is further configured to: Collecting the braking characteristic parameter set and the corresponding underground driving condition attributes of the underground rack rail vehicle after each braking action; The braking characteristic parameter set is quantitatively evaluated using a preset braking performance evaluation model to obtain a braking performance score of the underground rack rail vehicle after each braking; For each braking performance score, a performance decay analysis is performed with the previous and most recent braking performance score to obtain the braking performance decay amplitude corresponding to the braking action of the underground rack rail vehicle; A correlation analysis is performed on the braking performance attenuation amplitude and the corresponding underground driving condition attributes, and a braking condition related influence matrix is constructed according to the analysis results.

9. The downhole rack railway vehicle braking pressure adaptive regulation system according to any one of claims 7 and 8, characterized in that, The operating condition attribute acquisition module is further configured to: According to the rate of change of working conditions and the data accuracy requirements, set the collection frequency for sensors in different locations; According to the set collection frequency, each sensor collects working condition attribute data in real time; Performing preliminary verification on the collected working condition attribute data and eliminating abnormal data; Convert the data after verification and processing into a unified format that can be recognized and processed.

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