Stall protection arresting cable system for mining trackless rubber-tyred vehicle

Abstract

The invention relates to the technical field of stall stopping, in particular to a stall protection arresting cable system for a mining trackless rubber-tyred vehicle, which comprises a data acquisition module used for acquiring environmental data and vehicle state data of a roadway where the mining trackless rubber-tyred vehicle is located according to a set acquisition frequency; the data processing module is used for performing feature extraction on the environment data and the vehicle state data to obtain a stall risk environment feature set and a vehicle state feature set; the data analysis module is used for carrying out stall analysis on the stall risk environment feature set and the vehicle state feature set or the vehicle state feature set, and determining an optimal arrester wire adjusting parameter based on a stall analysis result after determining that the stall risk exists; and the execution module is used for executing the stopping action on the mining trackless rubber-tyred vehicle according to the optimal stopping wire adjusting parameters. The mine production efficiency and the life safety of personnel can be effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of stall prevention, and in particular to a stall protection cable system for a mine-used trackless rubber-tyred vehicle. Background Art

[0002] In mine exploitation operations, mine-used trackless rubber-tyred vehicles, as key transportation equipment, undertake important tasks such as material transportation and personnel conveyance. The safety of their operation is directly related to the efficiency of mine production and the lives of personnel. However, in the complex mine roadway environment, mine-used trackless rubber-tyred vehicles face many risk factors that may cause stalling.

[0003] The road conditions in mine roadways are complex and changeable, with situations such as undulating slopes and slippery road surfaces. These environmental factors will significantly affect the driving stability and braking performance of the vehicle. At the same time, the vehicle's own state also plays a key role in whether the vehicle can drive stably. Once a mine-used trackless rubber-tyred vehicle stalls, it may cause serious accidents such as vehicle out of control, collision with the roadway wall, and collision with other equipment or personnel, resulting in huge economic losses and even endangering the lives of personnel.

[0004] At present, the existing stall protection cable system for mine-used trackless rubber-tyred vehicles only relies on vehicle speed parameters for judgment, without comprehensively considering the influence of environmental parameters such as roadway slope and friction coefficient on the vehicle's dynamic characteristics, resulting in a lag in risk warning. At the same time, it lacks the ability of dynamic adjustment and is difficult to match the optimal cable blocking strength according to the actual stall degree, making it difficult to take timely and effective targeted protection measures when the vehicle is about to stall and unable to ensure the safety of mine transportation to the greatest extent. Summary of the Invention

[0005] The present invention provides a stall protection cable system for a mine-used trackless rubber-tyred vehicle that can effectively ensure the efficiency of mine production and the lives of personnel, and can effectively solve the problems in the background art.

[0006] To achieve the above object, the present invention provides a stall protection cable system for a mine-used trackless rubber-tyred vehicle, including: A data acquisition module for collecting environmental data and vehicle state data of the roadway where the mine-used trackless rubber-tyred vehicle is located according to a set acquisition frequency; A data processing module for respectively extracting features from the environmental data and the vehicle state data to obtain a stall risk environmental feature set and a vehicle state feature set; A data analysis module for performing stall analysis on the stall risk environmental feature set and the vehicle state feature set, or the vehicle state feature set, and determining the best cable adjustment parameters based on the stall analysis result after confirming the existence of a stall risk; An execution module, configured to perform a blocking action on a mine trackless rubber-tyred vehicle according to the optimal cable arresting parameter.

[0007] In a possible design, the data analysis module is further configured to: Perform a stall risk assessment on the vehicle state feature set to obtain a first stall risk score; Compare the first stall risk score with a preset stall risk threshold; In response to the first stall risk score not exceeding the preset stall risk threshold, input the stall risk environment feature set into a stall environment impact analysis model to obtain a stall environment impact factor; Based on the stall environment impact factor, perform an environmental impact correction on the first stall risk score to obtain a second stall risk score; In response to the first stall risk score or the second stall risk score exceeding the preset stall risk threshold, calculate the degree of stall risk abnormality exceeding the preset stall risk threshold; Based on the degree of stall risk abnormality, optimize within a preset mapping space of cable arresting parameters to determine the optimal cable arresting parameter.

[0008] In a possible design, the execution module at least includes a cable arrester, a buffer device, and a brake; The execution module controls the tension of the cable arrester through the buffer device according to the optimal cable arresting parameter to absorb the kinetic energy of the vehicle. The cable arrester is used to block the mine trackless rubber-tyred vehicle, and the brake is used to lock the cable arrester.

[0009] In a possible design, the environmental data includes roadway gradient, road surface friction coefficient, dust concentration, humidity, and temperature.

[0010] In a possible design, the vehicle state data includes vehicle driving speed, acceleration, brake wear degree, brake pressure, and tire rotation speed.

[0011] In a possible design, the basis for setting the acquisition frequency includes vehicle motion state, roadway environment characteristics, system response requirements, hardware performance, and data processing capabilities.

[0012] In a possible design, the calculation formula for the first stall risk score is: S1 = k1V + k2A + k3W + k4P + k5R Among them, S1 represents the first stall risk score, V represents the vehicle driving speed, k1 represents the weight of the vehicle driving speed, A represents the acceleration, k2 represents the weight of the acceleration, W represents the braking wear degree, k3 represents the weight of the braking wear degree, P represents the brake pressure, k4 represents the weight of the brake pressure, R represents the tire rotation speed, and k5 represents the weight of the tire rotation speed.

[0013] In a possible design, the influencing factors for setting the preset stall risk threshold include vehicle self - factors, roadway environment factors, operation requirement factors, and historical data factors.

[0014] In a possible design, the method for constructing the stall environment impact analysis model includes: Collect historical data of the mine - used trackless rubber - tired vehicle driving in the mine roadway, including environmental data and vehicle status data; Select a machine - learning model as the basic architecture of the stall environment impact analysis model, and the machine - learning model includes multiple linear regression, decision tree, random forest, and neural network; Use the historical data to train the model, and improve the prediction performance of the model by adjusting the model parameters and optimizing the algorithm; After the model training is completed, input the stall risk environment feature set into the model to obtain the stall environment impact factors.

[0015] In a possible design, the formula for calculating the stall risk abnormality degree exceeding the preset stall risk threshold is: Among them, D represents the stall risk abnormality degree, S1 represents the first stall risk score, and T represents the preset stall risk threshold.

[0016] Through the technical solution of the present invention, the following technical effects can be achieved: Through the data acquisition module, the system can collect the environmental data and vehicle status data of the roadway where the mine trackless rubber-tyred vehicle is located in real time and comprehensively, providing a rich and accurate data basis for subsequent stall analysis; the data processing module extracts the features of the collected environmental data and vehicle status data to form a stall risk environmental feature set and a vehicle status feature set; it helps to extract the most critical information for stall risk judgment from complex and changeable data, improving the accuracy and efficiency of the analysis; the data analysis module not only considers the vehicle status features, but also comprehensively considers the influence of environmental parameters such as roadway gradient and friction coefficient on the vehicle dynamics characteristics to conduct a more comprehensive and in-depth stall analysis; it can more accurately identify potential stall risks and determine the optimal adjustment parameters of the arresting cable based on the analysis results, avoiding the limitations of single-parameter judgment; the system can dynamically adjust the adjustment parameters of the arresting cable according to the actual stall degree to ensure that targeted protective measures can be taken in a timely and effective manner when the vehicle is about to stall; it improves the flexibility and adaptability of the system and can better cope with the complex and changeable mine roadway environment; through comprehensive analysis and dynamic adjustment, the system can issue an early warning before or at the initial stage of the stall risk and take corresponding arresting measures; the early warning and timely response mechanism can minimize the occurrence of stall accidents to ensure the safety of mine transportation; the entire system realizes the intelligence and automation of data acquisition, processing, analysis and execution, reducing the possibility of human intervention and misjudgment; it not only improves the reliability and stability of the system, but also reduces the operation difficulty and cost; The system combines environmental data with vehicle status data to conduct a comprehensive analysis of stall risks, and can more accurately capture the multiple factors that lead to stalls; the comprehensive and integrated analysis enables the system to detect potential stall risks in advance, thereby greatly enhancing the accuracy and timeliness of early warning; the system has dynamic adjustment capabilities and can dynamically adjust the adjustment parameters of the blocking cable according to the real-time stall analysis results; it can match the optimal blocking strength according to the actual stall degree, thereby minimizing interference with vehicle operation while ensuring safety, allowing the system to maintain a high degree of flexibility and reliability in the complex and changeable mine tunnel environment; through comprehensive data analysis and dynamic adjustment, the system can issue a warning signal in time when the vehicle is about to stall, and immediately perform blocking actions; the early warning and effective protection mechanism can It can minimize the occurrence of stall accidents and ensure the safety of mine transportation. At the same time, because the system can be adjusted intelligently according to the actual stall degree, it can reduce unnecessary blocking actions while ensuring safety and improve transportation efficiency. The entire system realizes the intelligence and automation of data collection, processing, analysis and execution, reducing the possibility of human intervention and misjudgment. This not only improves the reliability and stability of the system, but also reduces the difficulty and cost of operation. At the same time, the improvement of the intelligence level of the system also provides strong support for the intelligent management of mine transportation. The system design is scalable and upgradeable, and can expand functions and upgrade performance with the continuous development of mine tunnel environment and vehicle technology. This means that the system can continue to adapt to new safety requirements and technical challenges and maintain its long-term effectiveness and advancement. To sum up, the stall protection arresting cable system for rubber-tyred trackless vehicles mentioned above, through the comprehensive use of various modules, has produced an overall logical effect of comprehensiveness and integration, dynamic adaptability and intelligent adjustment, early warning and effective protection, improved intelligence and automation level, as well as scalability and upgradeability, which can more effectively ensure the efficiency of mine production and the safety of personnel's lives. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is a schematic diagram of the structure of the stall protection arresting cable system for mining trackless rubber-tyred vehicles; Figure 2 This is a structural diagram of the data analysis module. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0020] The present application will be described below with reference to the accompanying drawings in the present application.

[0021] As Figure 1 shown, the present invention provides a stall protection blocking cable system for a mine trackless rubber-tyred vehicle, which specifically includes the following modules; A data acquisition module, configured to acquire the environmental data and vehicle state data of the roadway where the mine trackless rubber-tyred vehicle is located according to the set acquisition frequency; A data processing module, configured to respectively extract features from the environmental data and the vehicle state data to obtain a stall risk environmental feature set and a vehicle state feature set; A data analysis module, which performs stall analysis on the stall risk environmental feature set and the vehicle state feature set, or the vehicle state feature set, and determines the optimal blocking cable adjustment parameters based on the stall analysis result after confirming the existence of a stall risk; An execution module, configured to perform a blocking action on the mine trackless rubber-tyred vehicle according to the optimal blocking cable adjustment parameters.

[0022] In this embodiment, the system can collect the environmental data and vehicle status data of the roadway where the mine trackless rubber-tyred vehicle is located in real time and comprehensively through the data acquisition module, providing a rich and accurate data basis for subsequent stall analysis. The data processing module extracts features from the collected environmental data and vehicle status data to form a stall risk environmental feature set and a vehicle status feature set, which helps to extract the most critical information for stall risk judgment from complex and variable data, improving the accuracy and efficiency of analysis. The data analysis module not only considers the vehicle status features, but also comprehensively considers the influence of environmental parameters such as roadway slope and friction coefficient on the vehicle dynamics characteristics to conduct a more comprehensive and in-depth stall analysis. It can more accurately identify potential stall risks and determine the optimal adjustment parameters of the blocking cable based on the analysis results, avoiding the limitations of single-parameter judgment. The system can dynamically adjust the adjustment parameters of the blocking cable according to the actual stall degree to ensure that targeted protective measures can be taken in a timely and effective manner when the vehicle is about to stall, improving the flexibility and adaptability of the system and enabling it to better cope with the complex and variable mine roadway environment. Through comprehensive analysis and dynamic adjustment, the system can issue an early warning before or at the initial stage of the stall risk and take corresponding blocking measures. The early warning and timely response mechanism can minimize the occurrence of stall accidents to the greatest extent and ensure the safety of mine transportation. The entire system realizes the intelligence and automation of data collection, processing, analysis and execution, reducing the possibility of human intervention and misjudgment, not only improving the reliability and stability of the system, but also reducing the operation difficulty and cost. The system combines environmental data with vehicle status data to conduct a comprehensive analysis of stall risks, and can more accurately capture the multiple factors that lead to stalls; the comprehensive and integrated analysis enables the system to detect potential stall risks in advance, thereby greatly enhancing the accuracy and timeliness of early warning; the system has dynamic adjustment capabilities and can dynamically adjust the adjustment parameters of the blocking cable according to the real-time stall analysis results; it can match the optimal blocking strength according to the actual stall degree, thereby minimizing interference with vehicle operation while ensuring safety, allowing the system to maintain a high degree of flexibility and reliability in the complex and changeable mine tunnel environment; through comprehensive data analysis and dynamic adjustment, the system can issue a warning signal in time when the vehicle is about to stall, and immediately perform blocking actions; the early warning and effective protection mechanism can It can minimize the occurrence of stall accidents and ensure the safety of mine transportation. At the same time, because the system can be adjusted intelligently according to the actual stall degree, it can reduce unnecessary blocking actions while ensuring safety and improve transportation efficiency. The entire system realizes the intelligence and automation of data collection, processing, analysis and execution, reducing the possibility of human intervention and misjudgment. This not only improves the reliability and stability of the system, but also reduces the difficulty and cost of operation. At the same time, the improvement of the intelligence level of the system also provides strong support for the intelligent management of mine transportation. The system design is scalable and upgradeable, and can expand functions and upgrade performance with the continuous development of mine tunnel environment and vehicle technology. This means that the system can continue to adapt to new safety requirements and technical challenges and maintain its long-term effectiveness and advancement. To sum up, the stall protection arresting cable system for rubber-tyred trackless vehicles mentioned above, through the comprehensive use of various modules, has produced an overall logical effect of comprehensiveness and integration, dynamic adaptability and intelligent adjustment, early warning and effective protection, improved intelligence and automation level, as well as scalability and upgradeability, which can more effectively ensure the efficiency of mine production and the safety of personnel's lives.

[0023] In some embodiments of the present invention, for the data acquisition module: The environmental data include roadway slope, road friction coefficient, dust concentration, humidity and temperature; Tunnel slope: The high-precision tilt sensor measures the slope changes of the tunnel where the mine car is located in real time; the high-precision tilt sensor can capture tiny slope fluctuations and provide key environmental parameters for the system; Road surface friction coefficient: using a friction coefficient measuring device, which includes a small test wheel, to evaluate the friction performance of the current road surface through the contact between the test wheel and the road surface; Dust concentration: dust sensors monitor the air quality in the lanes; high dust concentrations can affect the vehicle’s braking performance and vision, increasing the risk of stalling; Humidity and temperature: Use temperature and humidity sensors to record the environmental conditions in the roadway in real time; changes in humidity and temperature will affect the friction coefficient of the road surface, the mechanical properties of the vehicle, and the stability of the electrical system; The vehicle status data includes vehicle speed, acceleration, brake wear, brake pressure and tire speed; Vehicle speed: The speed of the mine car is measured in real time by installing a speed sensor on the wheel or drive shaft; Acceleration: Use acceleration sensors to monitor changes in vehicle acceleration, including longitudinal and lateral acceleration; acceleration data helps identify dynamic behaviors such as sudden acceleration, deceleration, or turning, as well as potential instability; Brake wear: Evaluate the effectiveness of braking performance by monitoring the wear of brake system components, including brake discs and brake pads; Brake pressure: Use pressure sensors to monitor pressure changes in the brake system to reflect the driver's braking force and the response speed of the brake system. Tire speed: The speed sensor installed on the wheel measures the speed of each tire to detect abnormal conditions such as tire slippage and locking; The acquisition frequency is set based on: Vehicle motion status: If the vehicle speed changes frequently and with large amplitude, a higher acquisition frequency is required to timely capture the instantaneous change in speed and accurately determine whether the vehicle has a tendency to stall. Rapid changes in acceleration are also an important indicator for determining the risk of vehicle stalling. For vehicles with fast acceleration changes, a higher acquisition frequency can better monitor the real-time acceleration situation. When the vehicle is in conditions where the acceleration changes significantly, such as starting, braking or climbing, the acquisition frequency needs to be increased to a level that can accurately capture every acceleration change. Laneway environmental characteristics: When the laneway has large slope fluctuations and the road conditions are complex, such as mud and water accumulation, the vehicle's driving stability and braking performance will be significantly affected, and the risk of vehicle stalling will increase. In order to fully understand the vehicle's status in such a complex environment, it is necessary to increase the acquisition frequency to ensure that the vehicle's status changes under different road conditions can be obtained in a timely manner. Environmental parameters such as dust concentration, humidity and temperature, if they change rapidly, will also affect the vehicle's operating status and stall risk. When the ventilation system is turned on or off, the dust concentration and humidity will change rapidly. At this time, the acquisition frequency needs to be increased accordingly to reflect the impact of these changes on the vehicle in a timely manner. System response requirements: To achieve timely and effective stall warnings and interceptions, the acquisition frequency should be high enough to ensure the shortest time interval between the appearance of stall signs in the vehicle and the execution of the interception action; to react within an extremely short time when the vehicle is about to stall, the data acquisition frequency needs to match the overall response time requirements of the system to ensure that the system can initiate the interception action at the optimal time; if the system is to accurately match the interception intensity according to the actual stall degree, accurate and real-time data support is required; a higher acquisition frequency can provide the system with more continuous and accurate data, enabling the system to analyze the stall situation more precisely and thus achieve more refined dynamic adjustment; Hardware performance: Different types of sensors have their respective upper limits of sampling frequency and accuracy; when setting the acquisition frequency, the performance limitations of the sensors should be fully considered to ensure that the acquired data is both accurate and meets the system requirements, setting the acquisition frequency within the range allowed by the sensor performance while taking into account the system's requirements for data accuracy and real-time performance; Data processing capacity: The acquired data needs to be transmitted to the data processing module for processing. If the data transmission bandwidth is limited or the computing speed of the data processing unit is slow, too high an acquisition frequency may lead to data transmission delays or untimely processing, resulting in data loss or system jamming; therefore, the acquisition frequency should be reasonably set according to the data transmission and processing capabilities of the hardware.

[0024] In this embodiment, through high-precision tilt sensors, friction coefficient measurement devices, dust sensors, temperature and humidity sensors, and various vehicle state sensors, the system can comprehensively and real-time collect key data on the roadway environment and vehicle state; ensuring that the system can capture various subtle changes that affect the driving stability of the vehicle, providing accurate and timely data support for subsequent stall analysis and blocking actions; the setting of the acquisition frequency fully considers multiple factors such as the vehicle motion state, roadway environment characteristics, system response requirements, as well as hardware performance and data processing capabilities; enabling the system to dynamically adjust the acquisition frequency according to the actual situation, thereby optimizing system performance and resource utilization while ensuring data quality; high-precision data acquisition and real-time analysis enable the system to react within a very short time when the vehicle shows signs of stalling, not only improving the system's early warning ability but also ensuring the timeliness and effectiveness of the blocking action, thus greatly reducing the safety risks caused by vehicle stalling; when setting the acquisition frequency, the system fully considers the performance limitations of the sensors and the computing speed of the data processing unit, ensuring the collaborative optimization of data acquisition and processing; not only improving the stability and reliability of the system but also reducing the overall power consumption and cost of the system; by real-time collecting and analyzing roadway environment and vehicle state data, the system can provide data-driven decision support for decision-makers; helping mine managers better understand the operating state of the vehicle and the roadway environment, thereby formulating more scientific and reasonable safety management measures and emergency plans; in summary, this module not only improves the accuracy and real-time performance of the stall protection blocking cable system for mine trackless rubber-tyred vehicles but also enhances the flexibility and adaptability of the system.

[0025] In some embodiments of the present invention, for the data processing module: Extract features from the environmental data, including: From the collected roadway terrain data, calculate the slope values at different positions of the roadway through mathematical algorithms; in order to more accurately reflect the impact of the slope on the vehicle, it is also necessary to smooth the slope data to remove some noise caused by measurement errors and other factors, obtaining continuous and stable slope feature data; Considering the influence of different road surface materials and humidity and other factors on the friction coefficient, comprehensively analyze the collected road surface friction coefficient and extract the road surface friction coefficient features; Calculate the average dust concentration, peak dust concentration, etc. within a certain period of time to characterize the dust condition in the roadway; conduct time series analysis on the dust concentration data to observe its change trend, providing a basis for judging the ventilation condition in the roadway, etc.; Humidity and temperature feature extraction: Normalize the humidity and temperature data so that it has the same dimension and value range as other environmental feature data, facilitating subsequent analysis and comparison; at the same time, analyze features such as the change rate of humidity and temperature to reflect the dynamic change of the environment; Fuse the extracted environmental features to obtain a set of stall risk environmental features; Extract features from the vehicle state data, including: Denoise the vehicle driving speed data to remove abnormal fluctuations caused by factors such as electromagnetic interference; then, calculate eigenvalue such as average speed and instantaneous speed according to different time intervals to comprehensively reflect the driving speed state of the vehicle; analyze the change trend of the speed to judge whether the vehicle is in an accelerating, decelerating or constant speed driving state; Filter the acceleration data to remove noise and interference; the acceleration features not only include the acceleration of the vehicle in the straight driving direction, but may also include information such as lateral acceleration to reflect the dynamic characteristics of the vehicle during operations such as turning and braking; By measuring data such as the thickness change of the brake pads and the pressure change of the brake fluid, and combining the working principle of the braking system, establish the relationship between the braking wear degree and these parameters, so as to extract the braking wear degree features; Amplify, filter and other processes on the brake pressure data to ensure the accuracy and reliability of the data; then, analyze features such as the magnitude, change trend of the brake pressure and the pressure distribution under different braking conditions to judge whether the working state of the braking system is normal and whether the braking performance of the vehicle meets the requirements; After digitizing the tire rotation speed data, calculate eigenvalue such as the average rotation speed and rotation speed difference of the tire; the tire rotation speed difference can reflect whether the vehicle has abnormal conditions such as deviation and skidding, while the average rotation speed is closely related to the driving speed of the vehicle; Fuse the extracted vehicle state features to obtain a set of vehicle state features.

[0026] In this embodiment, through preprocessing operations such as denoising and filtering on the original data, abnormal fluctuations and noise caused by factors such as measurement errors and electromagnetic interference are effectively removed, improving the accuracy and reliability of the data; through normalizing the humidity and temperature data, and appropriate processing of other feature data, different features have the same dimension and value range, enhancing the comparability and analyzability between features; by extracting key features and fusing them to form a set of stall risk environmental features and a set of vehicle state features, the system can more quickly identify potential stall risks and make timely and effective blocking actions accordingly; greatly improving the response speed and accuracy of the system, contributing to maximizing the safety of mine transportation; the results of feature extraction not only provide a basis for judging the stall risk, but also make it possible for the system to dynamically adjust the blocking intensity according to the actual stall degree; enabling the system to take targeted protection measures according to different situations, further improving the flexibility and practicality of the system; this step helps to improve the overall performance and safety of the system.

[0027] In some embodiments of the present invention, for the data analysis module: Analyze the vehicle state feature set to calculate the first stall risk score; use a machine learning algorithm to construct a stall risk assessment model; use historical data to train a decision tree model, taking vehicle state features such as vehicle driving speed, acceleration, brake wear degree, brake pressure, and tire rotation speed as inputs, and whether stalling as the output; after training, the model can calculate a corresponding stall risk score according to the input vehicle state feature set, that is, the first stall risk score; different vehicle state features have different degrees of influence on the stall risk, so corresponding weights need to be assigned to each feature; Compare the calculated first stall risk score with a preset stall risk threshold; if the first stall risk score does not exceed the preset stall risk threshold, input the stall risk environment feature set into the stall environment impact analysis model to obtain the stall environment impact factor Based on the stall environment impact factor, perform environmental impact correction on the first stall risk score to obtain the second stall risk score; In response to the first stall risk score or the second stall risk score exceeding the preset stall risk threshold, calculate the degree of stall risk abnormality exceeding the preset stall risk threshold; Based on the degree of stall risk abnormality, optimize in the preset arresting cable adjustment parameter mapping space to determine the optimal arresting cable adjustment parameter; The calculation formula for the first stall risk score is: S1 = k1V + k2A + k3W + k4P + k5R Where, S1 represents the first stall risk score, V represents the vehicle driving speed, k1 represents the weight of the vehicle driving speed, A represents the acceleration, k2 represents the weight of the acceleration, W represents the brake wear degree, k3 represents the weight of the brake wear degree, P represents the brake pressure, k4 represents the weight of the brake pressure, R represents the tire rotation speed, and k5 represents the weight of the tire rotation speed; The influencing factors for setting the preset stall risk threshold include: Vehicle own factors: Different types of mine explosion-proof trackless rubber-tired vehicles have different performance parameters and stall characteristics; the power performance, braking performance, suspension system, etc. of the vehicle will all affect its stall risk; vehicles with better performance have higher stall risk thresholds; Roadway environment factors: The roadway slope is an important factor affecting vehicle driving stability and braking performance; the greater the slope, the higher the risk of vehicle stalling, so the stall risk threshold should be correspondingly reduced; situations such as wet, muddy or dusty road surfaces will reduce the road surface friction coefficient and increase the risk of vehicle stalling; therefore, in these cases, the stall risk threshold should also be correspondingly reduced; Operational requirements: Different transport tasks have different requirements for vehicle speed and stability. Emergency transport tasks require higher speeds, but also increase the risk of stalling. Therefore, the stall risk threshold should be adjusted according to the specific task. When setting the stall risk threshold, safety factors need to be fully considered to ensure that transport operations are carried out within a controllable risk range. Historical data factor: By analyzing the data of historical stall events, we can understand the stall characteristics and risk levels of vehicles under different conditions, thus providing a reference for setting the stall risk threshold; The method for constructing the stall environment impact analysis model comprises: Collect a large amount of historical data of mining trackless rubber-tyred vehicles driving in mine tunnels, including environmental data and vehicle status data; clean and pre-process the collected data, remove outliers and missing values, and ensure the accuracy and completeness of the data; extract features closely related to stall risk from environmental data and vehicle status data to form a stall risk environmental feature set and a vehicle status feature set; According to the complexity of the problem and the characteristics of the data, a machine learning model is selected as the basic architecture of the stall environmental impact analysis model, and the machine learning model includes multiple linear regression, decision tree, random forest and neural network; Use historical data to train the model and improve the model's predictive performance by adjusting model parameters and optimizing algorithms; Use methods such as cross-validation to evaluate the generalization ability of the model to ensure that the model can maintain good prediction results on different data sets; After the model training is completed, the stall risk environment feature set is input into the model to obtain the stall environment influencing factors; The formula for calculating the abnormal degree of stall risk exceeding the preset stall risk threshold is: Wherein, D represents the abnormal degree of stall risk, S1 represents the first stall risk score, and T represents the preset stall risk threshold; The method for constructing the preset barrier cable adjustment parameter mapping space includes: Obtain arrester cable adjustment parameters, where the arrester cable adjustment parameters include the arrester cable tension, the buffering coefficient of the buffer device, and the braking time of the brake; the magnitude of the arrester cable tension is directly related to the arresting effect of the arrester cable on the stalled vehicle; it is necessary to determine the tension range according to factors such as the weight, speed, and stall risk degree of the vehicle; the buffering coefficient of the buffer device determines the buffering effect, and the buffer device is used to relieve the impact force on the vehicle and the arrester cable during the arresting process. It is necessary to determine different ranges of buffering coefficient values according to the possible stall state of the vehicle and the roadway environment, etc.; the length of the braking time of the brake affects whether the arrester cable can play a role in time and the stability of the arrest. The brake is used to lock the arrester cable; a reasonable braking time range should be set in combination with the vehicle motion state and the working characteristics of the arrester cable; Obtain influencing factors, where the influencing factors include vehicle state factors and environmental factors; the vehicle state factors include the vehicle driving speed, acceleration, brake wear degree, brake pressure, and tire rotation speed; the environmental factors include roadway slope, road surface friction coefficient, dust concentration, humidity, and temperature; Based on theories such as vehicle dynamics and tribology, combined with experimental data and on-site experience, establish a mathematical relationship model between the arrester cable adjustment parameters and the vehicle state characteristics and environmental characteristics, and determine the parameters of the model so that the model can accurately reflect the mapping relationship between various factors; Formulate specific mapping rules for the arrester cable adjustment parameters; Take all possible combinations of vehicle state characteristics and environmental characteristics as the input space, take the corresponding combinations of arrester cable adjustment parameters as the output space, and establish a mapping relationship between the two through the mapping rules to construct a preset mapping space for the arrester cable adjustment parameters.

[0028] In this embodiment, by using a machine learning algorithm to construct a stall risk assessment model and training the model in combination with historical data, the system can accurately calculate the first stall risk score according to the vehicle state feature set. The system not only considers vehicle state features, but also introduces a stall risk environment feature set, and modifies the environmental impact on the first stall risk score through a stall environment impact analysis model to obtain the second stall risk score, enabling the system to dynamically adjust according to the stall risk characteristics under different roadway environmental conditions, improving the accuracy and practicality of risk assessment. Based on the abnormal degree of stall risk, optimize within the preset mapping space of arrester cable adjustment parameters to determine the optimal arrester cable adjustment parameters, realizing intelligent parameter adjustment, being able to match the optimal blocking intensity according to the actual stall risk degree, and ensuring the pertinence and effectiveness of protective measures. When setting the preset stall risk threshold and constructing the mapping space of arrester cable adjustment parameters, fully consider the influences of various factors such as vehicle own factors, roadway environmental factors, operation requirement factors, and historical data factors, making the system more in line with the actual needs of mine exploitation operations and improving the applicability and reliability of the system. Through the collaborative work of the data acquisition module, data processing module, and data analysis module, the system realizes the efficient processing and analysis of the vehicle state feature set and environmental data, enabling the system to monitor and evaluate the stall risk in real time and take corresponding protective measures in a timely manner, ensuring the safety and efficiency of mine transportation. In summary, the data analysis module of the stall protection arrester cable system for mine trackless rubber-tired vehicles described in this step and its related construction methods improve the accuracy of risk assessment, enhance environmental adaptability, realize intelligent parameter adjustment, consider comprehensive factors, improve data processing efficiency, and enhance scalability and maintainability.

[0029] In some embodiments of the present invention, for the execution module: The execution module at least includes an arrester cable, a buffer device, and a brake; Arrester cable: As a component that directly blocks the mine trackless rubber-tired vehicle, when the system determines that the vehicle has a stall risk and determines the optimal arrester cable adjustment parameters, the arrester cable will be adjusted to a suitable state, horizontally placed on the vehicle driving path, and prevent the vehicle from continuing to run out of control and move forward through its own strength and tension, thereby avoiding serious accidents such as the vehicle colliding with the roadway wall, other equipment, or personnel. Buffer device: Its function is to control the tension of the arrester cable to absorb the kinetic energy of the vehicle. During the process of blocking the vehicle, the buffer device can accurately adjust the tension of the arrester cable according to the optimal arrester cable adjustment parameters. When the vehicle impacts the arrester cable, the buffer device can make the tension of the arrester cable gradually increase, avoid excessive instantaneous tension from causing too much impact on the vehicle and the personnel on the vehicle, and effectively convert the kinetic energy of the vehicle into other forms of energy, so that the vehicle decelerates smoothly until it stops. Brake: mainly used to lock the arresting cable; after the buffer device absorbs the kinetic energy of the vehicle and the vehicle stops, the brake will come into play, locking the arresting cable in the current state, preventing the vehicle from moving again due to possible subsequent situations, ensuring that the vehicle is in a safe stationary state, and guaranteeing the safety of the mine operation environment; When the mine trackless rubber-tyred vehicle is traveling in the roadway, the data acquisition module will collect the environmental data and vehicle status data of the roadway in real time and transmit them to the data processing module for feature extraction; the data analysis module will then conduct a stall risk assessment based on the extracted feature set and determine the optimal arresting cable adjustment parameters; Once the data analysis module confirms the existence of a stall risk and determines the optimal arresting cable adjustment parameters, the execution module will start working; first, the buffer device adjusts its working state according to the adjustment parameters to prepare for absorbing the kinetic energy of the vehicle; then, the arresting cable quickly unfolds to arrest the vehicle; during the arresting process, the buffer device continuously absorbs the kinetic energy of the vehicle until the vehicle stops moving; finally, the brake locks the arresting cable to ensure the arresting effect; During the execution of the arresting action, the system will also monitor in real time parameters such as the tension of the arresting cable, the working state of the buffer device, and the dynamic response of the vehicle; once an abnormal situation is detected, the system will immediately issue an alarm and take corresponding safety measures to ensure the safety of personnel and vehicles; In this embodiment, by placing the arresting cable horizontally across the vehicle's travel path, it can directly prevent the mine trackless rubber-tyred vehicle from continuing to run out of control when stalling, avoiding collisions between the vehicle and the roadway wall, other equipment, or personnel, thus significantly reducing the probability of serious accidents, guaranteeing the safety of personnel's lives and mine equipment, and reducing the huge economic losses that may be caused by accidents; the buffer device can gradually increase the tension of the arresting cable, avoiding excessive impact on the vehicle and the personnel on the vehicle caused by instantaneously excessive tension, and while achieving the arresting purpose, maximizing the safety of the personnel in the vehicle and the integrity of the vehicle, reducing secondary injuries that may be caused by strong arresting; after the vehicle stops, the brake can lock the arresting cable in the current state, preventing the vehicle from moving again due to possible subsequent situations, further ensuring that the vehicle is in a safe stationary state, guaranteeing the overall safety of the mine operation environment, and avoiding potential secondary risks; the execution module can work precisely according to the optimal arresting cable adjustment parameters determined by the data analysis module, and the buffer device, arresting cable, and brake cooperate with each other. From preparing to absorb kinetic energy to implementing the arrest and then locking the arresting cable, the whole process proceeds in an orderly manner, ensuring the efficiency and accuracy of arresting the stalled vehicle, reflecting the intelligence and automation of the system; the system monitors in real time parameters such as the tension of the arresting cable, the working state of the buffer device, and the dynamic response of the vehicle during the execution of the arresting action, and can immediately issue an alarm and take corresponding safety measures once an abnormality is detected, enhancing the reliability and stability of the system, improving the ability to respond to emergencies, and ensuring the safety and controllability of the entire arresting process.

[0030] 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 each embodiment are optionally combined, and / or the order of some operations is optionally changed. Moreover, the execution order between the steps of each process is merely exemplary and does not constitute a limitation on the execution order between the steps. There can also be other execution orders between the steps. It is not intended to indicate that the described 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. Additionally, it should be noted that the process details involved in a certain embodiment herein are equally applicable to other embodiments in a similar manner, or different embodiments can be used in combination.

[0031] In addition, certain steps in the above embodiments can be equivalently replaced with other possible steps. Or, certain steps in the above embodiments can be optional and can be deleted in some usage scenarios. Or, other possible steps can be added to the above embodiments. Moreover, each of the above embodiments can be implemented independently or in combination.

[0032] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A stall protection arresting cable system for a mining trackless rubber-tyred vehicle, characterized in that: include: A data acquisition module is used to collect environmental data and vehicle status data of the lane where the mining trackless rubber-tyred vehicle is located according to a set acquisition frequency; A data processing module, used for extracting features from the environmental data and the vehicle status data respectively, to obtain a stall risk environmental feature set and a vehicle status feature set; a data analysis module, performing a stall analysis on the stall risk environment feature set and the vehicle state feature set, or the vehicle state feature set, and determining an optimal arresting cable adjustment parameter based on the stall analysis result after confirming that there is a stall risk; The execution module is used to execute the blocking action on the mining trackless rubber-tyred vehicle according to the optimal blocking cable adjustment parameters.

2. The stall protection arresting cable system for a trackless rubber-tyred mining vehicle according to claim 1 is characterized in that: The data analysis module is further configured to: Performing a stall risk assessment on the vehicle state feature set to obtain a first stall risk score; comparing the first stall risk score with a preset stall risk threshold; In response to the first stall risk score not exceeding a preset stall risk threshold, inputting the stall risk environment feature set into a stall environment impact analysis model to obtain a stall environment impact factor; Based on the stall environment influence factor, performing environmental influence correction on the first stall risk score to obtain a second stall risk score; In response to the first stall risk score or the second stall risk score exceeding a preset stall risk threshold, calculating a stall risk abnormality degree exceeding the preset stall risk threshold; Based on the abnormal degree of stall risk, an optimum is sought in a preset arresting cable adjustment parameter mapping space to determine the optimal arresting cable adjustment parameter.

3. The stall protection arresting cable system for a mining trackless rubber-tyred vehicle according to any one of claims 1 and 2, characterized in that: The execution module at least includes an arresting cable, a buffer device and a brake; The execution module controls the tension of the arresting cable through a buffer device to absorb the vehicle kinetic energy according to the optimal arresting cable adjustment parameters. The arresting cable is used to block the mining trackless rubber-tyred vehicle, and the brake is used to lock the arresting cable.

4. The stall protection arresting cable system for a trackless rubber-tyred mining vehicle according to claim 3 is characterized in that: The environmental data include roadway slope, road surface friction coefficient, dust concentration, humidity and temperature.

5. The stall protection arresting cable system for a trackless rubber-tyred mining vehicle according to claim 4 is characterized in that: The vehicle status data includes vehicle speed, acceleration, brake wear, brake pressure and tire speed.

6. The stall protection arresting cable system for a trackless rubber-tyred mining vehicle according to claim 1 is characterized in that: The acquisition frequency is set based on vehicle motion status, lane environment characteristics, system response requirements, hardware performance, and data processing capabilities.

7. The stall protection arresting cable system for a trackless rubber-tyred mining vehicle according to claim 2 is characterized in that: The calculation formula of the first stall risk score is: S1=k1V+ k2A+ k3W+ k4P+ k5R Among them, S1 represents the first stall risk score, V represents the vehicle speed, k1 represents the weight of the vehicle speed, A represents the acceleration, k2 represents the weight of the acceleration, W represents the degree of brake wear, k3 represents the weight of the degree of brake wear, P represents the brake pressure, k4 represents the weight of the brake pressure, R represents the tire speed, and k5 represents the weight of the tire speed.

8. The stall protection arresting cable system for a trackless rubber-tyred mining vehicle according to claim 2 is characterized in that: The factors affecting the setting of the preset stall risk threshold include vehicle factors, road environment factors, operation requirement factors and historical data factors.

9. The stall protection arresting cable system for a mining trackless rubber-tyred vehicle according to claim 2 is characterized in that: The method for constructing the stall environment impact analysis model comprises: Collect historical data of mining trackless rubber-tyred vehicles driving in mine tunnels, including environmental data and vehicle status data; Selecting a machine learning model as the basic architecture of the stall environment impact analysis model, wherein the machine learning model includes multiple linear regression, decision tree, random forest and neural network; Use historical data to train the model and improve the model's predictive performance by adjusting model parameters and optimizing algorithms; After the model training is completed, the stall risk environment feature set is input into the model to obtain the stall environment influencing factors.

10. The stall protection arresting cable system for a rubber-tyred trackless vehicle for mining use according to claim 2, characterized in that: The formula for calculating the abnormal degree of stall risk exceeding the preset stall risk threshold is: Wherein, D represents the abnormal degree of stall risk, S1 represents the first stall risk score, and T represents the preset stall risk threshold.

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