CN-121106317-B - Unmanned mining vehicle driving force abnormality diagnosis method, device, equipment and medium

CN121106317BCN 121106317 BCN121106317 BCN 121106317BCN-121106317-B

Abstract

The disclosure relates to a method, a device, equipment and a medium for diagnosing driving force abnormality of an unmanned mining vehicle. The driving force abnormality diagnosis method for the unmanned mining vehicle comprises the steps of obtaining real-time target data and historical target data of the unmanned mining vehicle, calculating actual net acceleration and expected net acceleration based on the real-time target data and the historical target data, updating a count value under the condition that the actual net acceleration and the expected net acceleration meet the preset starting fault counter condition, and reporting a corresponding driving fault type fault code under the condition that the count value exceeds a preset safety threshold. According to the embodiment of the disclosure, the accuracy of driving force abnormal fault detection can be improved, the false alarm and missing report probability is greatly reduced, and the safety and reliability of the unmanned mine car during operation are effectively improved.

Inventors

ZHANG XUYUAN
LI JIAPENG
FAN CHUNHUI
WANG YANLIN
ZHOU DONGFENG
LIAO PEICHONG

Assignees

中铁十九局集团北京领航智途科技有限公司

Dates

Publication Date: 20260512
Application Date: 20250905

Claims (9)

1. The driving force abnormality diagnosis method for the unmanned mining vehicle is characterized by comprising the following steps of: acquiring real-time target data and historical target data of an unmanned mining vehicle; Calculating an actual net acceleration and a desired net acceleration based on the real-time target data and the historical target data; updating a count value under the condition that the actual net acceleration and the expected net acceleration meet the preset condition of starting a fault counter; reporting a corresponding driving fault type fault code under the condition that the count value exceeds a preset safety threshold value; The calculating the desired net acceleration based on the real-time target data and the historical target data comprises: index searching is carried out based on the real-time target data and the historical target data to obtain a speed index and an accelerator opening index, and boundary constraint is carried out on the speed index and the accelerator opening index; calculating a first weight and a second weight corresponding to the speed index and the accelerator opening index; and carrying out interpolation calculation by using a bilinear interpolation algorithm based on the speed index, the accelerator opening index, the first weight and the second weight to obtain the expected net acceleration.
2. The method of claim 1, wherein the real-time target data includes actual vehicle speed, actual acceleration/acceleration, road grade, brake command, throttle command, gear, park status.
3. The method of claim 1, wherein obtaining historical target data for the unmanned mining vehicle comprises: setting a sliding window with a preset length; And updating the cached throttle instruction and the road gradient in real time based on the sliding window to obtain historical target data of the unmanned mining vehicle.
4. The method of claim 1, wherein said calculating an actual net acceleration based on said real-time target data and said historical target data comprises: Calculating acceleration generated by rolling resistance and acceleration generated by ramp resistance according to the real-time target data and the historical target data; the actual net acceleration is calculated based on the acceleration due to the rolling resistance and the acceleration due to the ramp resistance.
5. The method according to claim 1, wherein updating the count value in the case where it is determined that the actual net acceleration and the expected net acceleration satisfy a preset start-up failure counter condition comprises: under the condition that the real-time target data meets the preset abnormal diagnosis condition, judging whether the actual net acceleration and the expected net acceleration meet the preset fault starting counter condition or not; And updating a count value under the condition that the actual net acceleration and the expected net acceleration meet the preset condition of starting a fault counter.
6. The method according to claim 1, wherein reporting the corresponding driving failure type failure code if the count value exceeds a preset safety threshold value, comprises: Reporting a fault sign as true under the condition that the count value exceeds a preset safety threshold value; and based on the true fault sign, reporting a corresponding driving fault type fault code according to a preset fault type definition rule.
7. An unmanned mining vehicle driving force abnormality diagnosis device, characterized by comprising: The data acquisition module is used for acquiring real-time target data and historical target data of the unmanned mining vehicle; a speed calculation module for calculating an actual net acceleration and an expected net acceleration based on the real-time target data and the historical target data; The numerical value updating module is used for updating the count value under the condition that the actual net acceleration and the expected net acceleration are judged to meet the preset condition of starting a fault counter; the fault reporting module is used for reporting a corresponding driving fault type fault code under the condition that the count value exceeds a preset safety threshold value; The calculating the desired net acceleration based on the real-time target data and the historical target data comprises: index searching is carried out based on the real-time target data and the historical target data to obtain a speed index and an accelerator opening index, and boundary constraint is carried out on the speed index and the accelerator opening index; calculating a first weight and a second weight corresponding to the speed index and the accelerator opening index; and carrying out interpolation calculation by using a bilinear interpolation algorithm based on the speed index, the accelerator opening index, the first weight and the second weight to obtain the expected net acceleration.
8. An unmanned mining vehicle driving force abnormality diagnosis apparatus, comprising: A processor; a memory for storing executable instructions; Wherein the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the unmanned mining vehicle driving force abnormality diagnosis method of any one of claims 1 to 6.
9. A non-transitory computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, causes the processor to implement the unmanned mining vehicle driving force abnormality diagnosis method according to any one of the preceding claims 1 to 6.

Description

Unmanned mining vehicle driving force abnormality diagnosis method, device, equipment and medium Technical Field The disclosure relates to the technical field of mine automatic driving, in particular to a method, a device, equipment and a medium for diagnosing driving force abnormality of an unmanned mining vehicle. Background Based on the severe operation conditions of most mining areas with high altitudes and extremely cold areas in the unmanned application field of mines, the long-time operation of the mining areas in the environment not only has great challenges on the physical functions of drivers, but also has extremely high requirements on driving technologies. Therefore, the pressure for better improving the working efficiency of mineral exploitation and effectively reducing the labor cost is provided. The market demand of unmanned mining dump trucks with high safety, high efficiency and high reliability is increasing. Because unmanned mining dump trucks often operate for a long time under working conditions such as high dust, high altitude, high humidity, large load impact and the like, a driving system (such as a motor, a gearbox and a transmission shaft) can bear extreme stress for a long time, and fatigue failure of components is accelerated. According to researches, the fault of the driving system accounts for more than 40% of the shutdown reasons of the mining vehicle, and the accurate diagnosis can reduce 30% of unplanned shutdown. In addition, mine digitization is realized by predicting faults through real-time data analysis, so that safety accidents caused by expansion of accident chains are avoided. Disclosure of Invention In order to solve the technical problems, the disclosure provides a driving force abnormality diagnosis method, device, equipment and medium for an unmanned mining vehicle. In a first aspect, the present disclosure provides a driving force abnormality diagnosis method for an unmanned mining vehicle, including: acquiring real-time target data and historical target data of an unmanned mining vehicle; Calculating an actual net acceleration and a desired net acceleration based on the real-time target data and the historical target data; updating a count value under the condition that the actual net acceleration and the expected net acceleration meet the preset condition of starting a fault counter; And reporting a corresponding driving fault type fault code under the condition that the count value exceeds a preset safety threshold value. In a second aspect, the present disclosure provides an unmanned mining vehicle driving force abnormality diagnosis apparatus, comprising: The data acquisition module is used for acquiring real-time target data and historical target data of the unmanned mining vehicle; a speed calculation module for calculating an actual net acceleration and an expected net acceleration based on the real-time target data and the historical target data; The numerical value updating module is used for updating the count value under the condition that the actual net acceleration and the expected net acceleration are judged to meet the preset condition of starting a fault counter; And the fault reporting module is used for reporting a corresponding driving fault type fault code under the condition that the count value exceeds a preset safety threshold value. In a third aspect, the present disclosure provides an unmanned mining vehicle driving force abnormality diagnosis apparatus, comprising: A processor; a memory for storing executable instructions; The processor is used for reading the executable instructions from the memory and executing the executable instructions to realize the unmanned mining vehicle driving force abnormality diagnosis method of the first aspect. In a fourth aspect, the present disclosure provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement the unmanned mining vehicle driving force abnormality diagnosis method of the first aspect. Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages: According to the driving force abnormality diagnosis method for the unmanned mining vehicle, real-time target data and historical target data of the unmanned mining vehicle can be obtained, then actual net acceleration and expected net acceleration are calculated based on the real-time target data and the historical target data, then a count value is updated under the condition that the actual net acceleration and the expected net acceleration meet the preset starting fault counter condition is judged, and finally a corresponding driving fault type fault code is reported under the condition that the count value exceeds a preset safety threshold. Therefore, diagnosis can be timely and accurately made when the driving system is abnormal, the accuracy of driving force abnormal fault detection is improved, t