Mine car running state data supervision method and system for underground transportation

Abstract

The invention discloses a mine car running state data supervision method and system for underground transportation, and the method comprises the following steps: collecting mine car running state data of different dimensions based on a plurality of sensors, and carrying out the preprocessing of the mine car running state data, and obtaining a preprocessing result; analyzing the preprocessing result based on a data analysis model; comparing the analysis result information with set analysis condition information to obtain a data deviation rate; judging whether the data deviation rate is greater than or equal to a set deviation rate threshold value; if yes, early warning information is generated, and if not, the running state of the mine car continues to be monitored in real time; the mine operation state data is analyzed in real time by establishing the data analysis model, the abnormal condition of the mine car operation state data is judged according to the analysis result, so that an effective basis is provided for safe operation of the mine car, in addition, the abnormal condition in the mine car operation state data is early warned in real time, and the mine car operation safety is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data supervision, and in particular to a method and system for supervising the running status data of a mine car used for underground transportation. Background Art

[0002] The current society is facing challenges in mine operation and management. Traditional mine car operation and management methods have a series of problems, such as incomplete data collection, low management efficiency and untimely monitoring. Traditional methods mainly rely on manual operation and limited sensor data, resulting in inaccurate monitoring and management of mine car status, which is difficult to meet the needs of mine operations.

[0003] At present, there are many problems with the existing mine car operation management technology. Uneven data collection leads to incomplete monitoring of the mine car status. The inaccuracy and timeliness of sensor data make management inefficient. In addition, traditional data supervision methods often require a lot of manpower and time costs, and are inefficient in processing abnormal data and missing data. Summary of the invention

[0004] The purpose of the present invention is to propose a method for supervising the running status data of a mine car for underground transportation to solve the problem that the monitoring of the running status data of the mine car in the prior art is inaccurate and has poor timeliness, and cannot improve the monitoring efficiency.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a method for monitoring the running status data of a mine car for underground transportation, comprising the following steps: S1, collecting the mine car running status data of different dimensions based on multiple sensors, preprocessing the mine car running status data to obtain a preprocessing result; S2, analyzing the preprocessing results based on the data analysis model and outputting the analysis result information; S3, comparing the analysis result information with the set analysis condition information to obtain the data deviation rate; S4, determining whether the data deviation rate is greater than or equal to a set deviation rate threshold; S5, if it is greater than or equal to, the mine car operation status data is determined to be abnormal and a warning message is generated. If it is less than, the mine car operation status data is determined to be normal and the mine car operation status continues to be monitored in real time.

[0006] Furthermore, in step S1, the mine car operation status data of different dimensions are collected based on multiple sensors, and the mine car operation status data is preprocessed to obtain a preprocessing result, which specifically includes: S11, collecting the mine car running status data of different dimensions according to multiple sensors on the mine car, the multiple sensors including speed sensor, displacement sensor, direction angle sensor, attitude sensor, temperature sensor and pressure sensor; S12, fusing and processing the mine car operation status data of different dimensions to obtain fused data; S13, cleaning the fused data based on the cleaning conditions of the set rules to obtain cleaned data; S14, performing statistics on the cleaned fusion data based on the cleaned data to obtain a preprocessing result.

[0007] Furthermore, the method for constructing the data analysis model in step S2 is as follows: S21, based on big data, obtain historical mine car operation status data and historical analysis data to establish a training set; S22, selecting an initial model, inputting the training set into the initial model for iterative training, and obtaining a training result; S23, determining whether the training result has converged; S24, if converged, a data analysis model is generated; S25, if it does not converge, adjust the model parameters or optimize the training set to perform secondary training on the initial model until the training results converge.

[0008] Furthermore, the warning information is generated in step S5, specifically including: Get the mine car running status data; Obtain the normal operation data of the mine car in the expert database, and establish the operation safety interval value based on the normal operation data of the mine car in the expert database; Based on the operation safety interval value, the operation safety lower limit value and the operation safety upper limit value are obtained; Compare the mine car operation status data with the operation safety upper limit value and the operation safety lower limit value; If the mine car operation status data is less than the lower limit of operation safety, an early warning message is generated; If the mine car operating status data is greater than the operating safety upper limit, an early warning message is generated.

[0009] Furthermore, in step S5, the operation status of the mine car is continuously monitored in real time, specifically including: Establish a collection time window, and calculate the time value of the collection time period based on the collection time window; Set the number of collection points, divide the time value into equal time segments based on the number of collection points, and obtain the corresponding collection time nodes; The running status of the mine car at each collection time node is obtained, and the running status data of the mine car at each collection time node is transmitted to the terminal.

[0010] Furthermore, the analysis result information is compared with the set analysis condition information to obtain the data deviation rate, which specifically includes: Obtain the depth information collected underground in the mine, segment the depth information based on the mine geology, and obtain multiple depth thresholds; Establishing analysis condition information corresponding to the mine depth based on multiple depth thresholds; Obtain the location information of the mine car, compare the location information of the mine car with the depth of the mine, and select corresponding analysis condition information according to the location information of the mine car; The analysis result information is compared with the corresponding analysis condition information to obtain the data deviation rate.

[0011] The present invention also provides a mine car operating status data monitoring system for underground transportation, comprising a processor, a memory and at least one program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program includes instructions for executing a mine car operating status data monitoring method for underground transportation as described in any one of the above items.

[0012] Due to the application of the above technical solution, the present invention has the following advantages compared with the prior art: The present invention establishes a data analysis model to perform real-time analysis on the mine operation status data, and judges the abnormal situation of the mine car operation status data according to the analysis results, thereby providing an effective basis for the safe operation of the mine car. In addition, real-time early warning is given for abnormal situations in the mine car operation status data to improve the safety of mine car operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram showing a flow chart of a method for monitoring data on the running status of a mine car used for underground transportation provided by an embodiment of the present invention; Figure 2 A flow chart of a method for preprocessing the running status data of a mine car for underground transportation provided by the embodiment is shown; Figure 3 A flow chart of a method for constructing a data analysis model for a method for supervising the operating status data of a mine car for underground transportation provided in this embodiment is shown. DETAILED DESCRIPTION

[0014] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0015] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0016] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0017] like Figure 1 As shown, an embodiment of the present invention provides a method for monitoring the running status data of a mine car for underground transportation, comprising the following steps: S1, collecting the mine car running status data of different dimensions based on multiple sensors, preprocessing the mine car running status data to obtain a preprocessing result; S2, analyzing the preprocessing results based on the data analysis model and outputting the analysis result information; S3, comparing the analysis result information with the set analysis condition information to obtain the data deviation rate; S4, determining whether the data deviation rate is greater than or equal to a set deviation rate threshold; S5, if it is greater than or equal to, the mine car operation status data is determined to be abnormal and a warning message is generated. If it is less than, the mine car operation status data is determined to be normal and the mine car operation status continues to be monitored in real time.

[0018] It should be noted that by acquiring the mine car operation status data at different latitudes in real time, the mine car operation status data is analyzed and monitored in real time, and abnormal mine car operation status is warned to improve the safety of mine car operation.

[0019] like Figure 2 As shown, according to an embodiment of the present invention, in step S1, the mine car running status data of different dimensions is collected based on multiple sensors, and the mine car running status data is preprocessed to obtain a preprocessing result, which specifically includes: S11, collecting the mine car running status data of different dimensions according to multiple sensors on the mine car, the multiple sensors including speed sensor, displacement sensor, direction angle sensor, attitude sensor, temperature sensor and pressure sensor; S12, fusing and processing the mine car operation status data of different dimensions to obtain fused data; S13, cleaning the fused data based on the cleaning conditions of the set rules to obtain cleaned data; S14, performing statistics on the cleaned fusion data based on the cleaned data to obtain a preprocessing result.

[0020] It should be noted that the redundancy of the mine car operating status data is reduced by fusing the mine car operating status data of different dimensions and cleaning the status data.

[0021] like Figure 3 As shown, according to an embodiment of the present invention, the method for constructing a data analysis model in step S2 is as follows: S21, based on big data, obtain historical mine car operation status data and historical analysis data to establish a training set; S22, selecting an initial model, inputting the training set into the initial model for iterative training, and obtaining a training result; S23, judging whether the training result has converged; S24, if converged, a data analysis model is generated; S25, if it does not converge, adjust the model parameters or optimize the training set to perform secondary training on the initial model until the training results converge.

[0022] It should be noted that the initial model is iteratively trained through historical mine car operation data and historical analysis data, and the model parameters are continuously adjusted during the training process to improve the output accuracy of the data analysis model.

[0023] According to an embodiment of the present invention, generating warning information in step S5 specifically includes: Get the mine car running status data; Obtain the normal operation data of the mine car in the expert database, and establish the operation safety interval value based on the normal operation data of the mine car in the expert database; Based on the operation safety interval value, the operation safety lower limit value and the operation safety upper limit value are obtained; Compare the mine car operation status data with the operation safety upper limit value and the operation safety lower limit value; If the mine car operation status data is less than the lower limit of operation safety, an early warning message is generated; If the mine car operating status data is greater than the operating safety upper limit, an early warning message is generated.

[0024] According to an embodiment of the present invention, the operation status of the mining vehicle is continuously monitored in real time in step S5, which specifically includes: Establish a collection time window, and calculate the time value of the collection time period based on the collection time window; Set the number of collection points, divide the time value into equal time segments based on the number of collection points, and obtain the corresponding collection time nodes; The running status of the mine car at each collection time node is obtained, and the running status data of the mine car at each collection time node is transmitted to the terminal.

[0025] According to an embodiment of the present invention, the analysis result information is compared with the set analysis condition information to obtain the data deviation rate, which specifically includes: Obtain the depth information collected underground in the mine, segment the depth information based on the mine geology, and obtain multiple depth thresholds; Establishing analysis condition information corresponding to the mine depth based on multiple depth thresholds; Obtain the location information of the mine car, compare the location information of the mine car with the depth of the mine, and select corresponding analysis condition information according to the location information of the mine car; The analysis result information is compared with the corresponding analysis condition information to obtain the data deviation rate.

[0026] The present invention also provides a mine car operating status data monitoring system for underground transportation, comprising a processor, a memory and at least one program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program includes instructions for executing any of the mine car operating status data monitoring methods for underground transportation as described above.

[0027] In summary, the present invention establishes a data analysis model to conduct real-time analysis of the mine operation status data, and judges the abnormal situation of the mine car operation status data according to the analysis results, thereby providing an effective basis for the safe operation of the mine car. In addition, real-time warning is given for abnormal situations in the mine car operation status data to improve the safety of mine car operation.

[0028] This embodiment also provides a mine car operating status data monitoring system for underground transportation, including a processor, a memory and at least one program, the program is stored in the memory and is configured to be executed by the processor, the program includes instructions for executing any of the above-mentioned mine car operating status data monitoring methods for underground transportation.

[0029] Those skilled in the art will appreciate that, for ease of description, the example in which both the memory and the processor are provided with one is used for description. In an actual terminal or server, there may be multiple processors and memories. The memory may also be referred to as a storage medium or a storage device, etc., which is not limited in the embodiments of the present application.

[0030] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor may also be a general-purpose microprocessor, graphics processing unit (GPU), or one or more integrated circuits for executing related programs to implement the functions required to be executed in the embodiments of the present application.

[0031] The processor can also be an integrated circuit chip with signal processing capabilities. In the implementation process, the various steps of the present application can be completed by the integrated logic circuit of the hardware in the processor or the instructions in the form of software. The above-mentioned processor can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to be executed, or a combination of hardware and software modules in the decoding processor to be executed. The software module can be located in a random access memory, a flash memory and a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register and other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and combines its hardware to complete the functions required to be performed by the unit included in the method, device and storage medium of the embodiment of the present application.

[0032] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache.

[0033] By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM).

[0034] The memory may also be a read-only optical disc (Compact Disc Read-Only Memory, CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory may be independent and connected to the processor via a bus. The memory may also be integrated with the processor, and the memory may store a program. When the program stored in the memory is executed by the processor, the processor is used to execute the various steps of the determination method in the above-mentioned embodiment of the present application.

[0035] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) is integrated into the processor. It should be noted that the memory described herein is intended to include but is not limited to these and any other suitable types of memory.

[0036] It should be understood that the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0037] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory, and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0038] Those skilled in the art will appreciate that the various illustrative logical blocks (ILBs) and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0039] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a program product of computer programming. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a processor, all or part of the processes or functions according to the embodiments of the present application are generated. The computer may be a general-purpose computer, a computer network, or other programmable device.

[0040] This embodiment also provides a computer-readable storage medium, which stores a computer program. The computer program enables a computer to execute to implement the above-mentioned method for supervising the operating status data of a mine car used for underground transportation.

[0041] It should be noted that computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber) or wireless (e.g., infrared, wireless, microwave, etc.) means, or can be transmitted from one website, computer, server or data center to a mobile phone processor by wired means. Computer-readable storage media can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. Available media can be magnetic media (e.g., floppy disk, hard disk), optical media (e.g., DVD), or semiconductor media (e.g., solid-state hard disk), etc.

[0042] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring the running status data of a mine car used for underground transportation, characterized in that: The following steps are involved: S1, collecting the mine car running status data of different dimensions based on multiple sensors, preprocessing the mine car running status data to obtain a preprocessing result; S2, analyzing the preprocessing results based on the data analysis model and outputting the analysis result information; S3, comparing the analysis result information with the set analysis condition information to obtain the data deviation rate; S4, determining whether the data deviation rate is greater than or equal to a set deviation rate threshold; S5, if it is greater than or equal to, the mine car operation status data is determined to be abnormal and a warning message is generated. If it is less than, the mine car operation status data is determined to be normal and the mine car operation status continues to be monitored in real time.

2. The method for monitoring the running status data of a mine car for underground transportation according to claim 1, characterized in that: In step S1, the mine car operation status data of different dimensions are collected based on multiple sensors, and the mine car operation status data is preprocessed to obtain a preprocessing result, which specifically includes: S11, collecting the mine car running status data of different dimensions according to multiple sensors on the mine car, the multiple sensors including speed sensor, displacement sensor, direction angle sensor, attitude sensor, temperature sensor and pressure sensor; S12, fusing and processing the mine car operation status data of different dimensions to obtain fused data; S13, cleaning the fused data based on the cleaning conditions of the set rules to obtain cleaned data; S14, performing statistics on the cleaned fusion data based on the cleaned data to obtain a preprocessing result.

3. The method for monitoring the running status data of a mine car for underground transportation according to claim 2, characterized in that: The method for constructing the data analysis model in step S2 is as follows: S21, based on big data, obtain historical mine car operation status data and historical analysis data to establish a training set; S22, selecting an initial model, inputting the training set into the initial model for iterative training, and obtaining a training result; S23, determining whether the training result has converged; S24, if converged, a data analysis model is generated; S25, if it does not converge, adjust the model parameters or optimize the training set to perform secondary training on the initial model until the training results converge.

4. The method for monitoring the running status data of a mine car for underground transportation according to claim 3, characterized in that: Step S5 generates warning information, which specifically includes: Get the mine car running status data; Obtain the normal operation data of the mine car in the expert database, and establish the operation safety interval value based on the normal operation data of the mine car in the expert database; Based on the operation safety interval value, the operation safety lower limit value and the operation safety upper limit value are obtained; Compare the mine car operation status data with the operation safety upper limit value and the operation safety lower limit value; If the mine car operation status data is less than the lower limit of operation safety, an early warning message is generated; If the mine car operating status data is greater than the operating safety upper limit, an early warning message is generated.

5. The method for monitoring the running status data of a mine car for underground transportation according to claim 1, characterized in that: In step S5, the operation status of the mine car is continuously monitored in real time, which specifically includes: Establish a collection time window, and calculate the time value of the collection time period based on the collection time window; Set the number of collection points, divide the time value into equal time segments based on the number of collection points, and obtain the corresponding collection time nodes; The running status of the mine car at each collection time node is obtained, and the running status data of the mine car at each collection time node is transmitted to the terminal.

6. The method for monitoring the running status data of a mine car for underground transportation according to claim 1, characterized in that: Compare the analysis result information with the set analysis condition information to obtain the data deviation rate, including: Obtain the depth information collected underground in the mine, segment the depth information based on the mine geology, and obtain multiple depth thresholds; Establishing analysis condition information corresponding to the mine depth based on multiple depth thresholds; Obtain the location information of the mine car, compare the location information of the mine car with the depth of the mine, and select corresponding analysis condition information according to the location information of the mine car; The analysis result information is compared with the corresponding analysis condition information to obtain the data deviation rate.

7. A mine car operation status data monitoring system for underground transportation, characterized in that: It comprises a processor, a memory and at least one program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program comprises instructions for executing the method for supervising the operating status data of a mine car for underground transportation as described in any one of claims 1-6.

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