Automatic ore drawing alignment system and method for draw shaft

Abstract

The invention discloses an automatic ore drawing alignment system and method for a draw shaft, and the system comprises a precise positioning module which is used for measuring distance information and determining the initial position coordinates of an electric locomotive; the data acquisition and preprocessing module is used for acquiring the output data and the related operation data of the electric locomotive and preprocessing the output data and the related operation data; the AI model processing module is used for an AI model, performing analysis processing on the preprocessed data, and then performing image acquisition and processing; the alignment control module is used for comparing the accurate position information, output by the AI visual model processing module, of the electric locomotive with a preset alignment target position and generating a control instruction; and the execution equipment is used for receiving the control instruction of the positioning control module and controlling the start and stop of the electric locomotive according to the control instruction. According to the invention, automatic alignment of the electric locomotive to the ore drawing machine is realized through data acquisition and model processing. The mine car alignment efficiency is improved, the alignment time is shortened, and the overall automatic ore drawing efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of metallurgical mining equipment control, and in particular to a chute automatic ore placing alignment system and method. Background Art

[0002] In the ore-laying operation of metallurgical mines, when the electric locomotive transports the ore to the chute for ore-laying operation, accurate alignment is the key link to ensure the smooth ore-laying and improve production efficiency. The traditional alignment method relies on manual operation, which is not only inefficient, but also easily affected by human factors, resulting in inaccurate alignment, which in turn affects the efficiency and safety of ore-laying. With the continuous advancement of science and technology, the development of UWB positioning technology and AI vision technology has made it possible to achieve automatic and precise alignment of electric locomotives. By integrating these advanced technologies into one system, the efficiency and accuracy of alignment can be effectively improved, manual intervention can be reduced, labor intensity can be reduced, and the automation level and overall benefits of mine production can be improved. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. To achieve the above purpose, a system and method for automatic ore placement in a chute is adopted to solve the problems raised in the above background technology.

[0004] An automatic ore placement alignment system for a chute, comprising a precise positioning module, a data acquisition and preprocessing module, an AI model processing module, an alignment control module, an execution device, and an electric locomotive;

[0005] The precise positioning module is used to measure the distance information between the electric locomotive and the base station and determine the preliminary position coordinates of the electric locomotive;

[0006] The data acquisition and preprocessing module is responsible for collecting the data output by the precise positioning module and the relevant operation data of the electric locomotive, and performing preprocessing;

[0007] The AI ​​model processing module is used to analyze and process the pre-processed data using an AI model based on deep learning, and then acquire and process the image in combination with the monitoring screen of the ore-drawing work area;

[0008] The alignment control module is used to combine the precise position information of the electric locomotive output by the AI ​​visual model processing module with the information output by the data acquisition and preprocessing module, compare it with the preset alignment target position, and generate a control instruction;

[0009] The execution device is used to receive the control instruction of the positioning control module and control the start and stop of the electric locomotive according to the control instruction.

[0010] As a further solution of the present invention: the precise positioning module includes a UWB tag arranged on the electric locomotive and a plurality of UWB base stations distributed in the mine tunnel.

[0011] As a further solution of the present invention: the execution device includes a vehicle-mounted controller arranged on the electric locomotive, and an operating console arranged on the ground end.

[0012] As a further solution of the present invention: the AI ​​model processing module includes a camera arranged in the lane, an image processing module, and a built-in deep learning model.

[0013] A technical solution on the other hand: a method for a chute automatic ore placement alignment system as described in any one of the above items, comprising the following steps:

[0014] Step S1, measuring the UWB tag signal on the electric locomotive through a UWB base station based on a pre-deployed precise positioning module, and calculating the distance information between the electric locomotive and the base station using parameters such as arrival time difference;

[0015] Step S2: using the data acquisition and preprocessing module to receive the data output by the precise positioning module and the relevant operation data of the electric locomotive and preprocessing them, and then sending the preprocessed data to the alignment control module;

[0016] Step S3: Based on the AI ​​model of deep learning, the AI ​​model processing module analyzes and processes the pre-processed data, and then acquires and processes the image in combination with the monitoring screen of the ore-drawing work area;

[0017] Step S4, the alignment control module combines the precise position information of the electric locomotive output by the AI ​​visual model processing module with the information output by the data acquisition and preprocessing module, compares it with the preset alignment target position, and generates a control instruction;

[0018] Step S5: When the execution device receives the control instruction of the positioning control module, it controls the start and stop of the electric locomotive according to the control instruction.

[0019] As a further solution of the present invention: the precise positioning module adopts a multilateral positioning algorithm to determine the preliminary position coordinates of the electric locomotive according to the distance information.

[0020] As a further solution of the present invention: the AI ​​model processing module receives the video image from the camera and transmits the video picture to the image processing module; the image processing module sends the adjusted video picture to the deep learning model, and finally outputs the target detection result.

[0021] As a further solution of the present invention: the alignment control module analyzes whether the car body position is aligned with the chute outlet position according to the output target detection result, calculates and gives a braking instruction, and reduces the locomotive alignment time.

[0022] Compared with the prior art, the present invention has the following technical effects:

[0023] The above technical solution integrates UWB positioning, data collection preprocessing, AI model processing, alignment control and execution equipment. The electric locomotive is initially positioned through the precise positioning module. After data collection preprocessing, the AI ​​model is used in combination with the monitoring screen to analyze the precise position of the electric locomotive. The alignment control module generates control instructions by comparing the preset target position. The execution equipment controls the start and stop of the electric locomotive to achieve automatic alignment. Beneficial effects: The system improves the automation level of ore discharge in the chute, ensures the precise alignment of the electric locomotive, reduces manual intervention, and improves work efficiency and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings:

[0025] Figure 1 A schematic diagram of the structure of the alignment system of the embodiment disclosed in the present application;

[0026] Figure 2 This is a flowchart of the steps of the alignment system of the embodiment disclosed in this application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Please refer to Figure 1 In an embodiment of the present invention, a chute automatic ore placement alignment system includes a precise positioning module, a data acquisition and preprocessing module, an AI model processing module, an alignment control module, an execution device, and an electric locomotive;

[0029] Precise positioning module, used to measure the distance between the electric locomotive and the base station and determine the preliminary position coordinates of the electric locomotive;

[0030] In this embodiment, the precise positioning module includes a UWB tag installed on the electric locomotive and a plurality of UWB base stations distributed in the mine tunnel.

[0031] In this embodiment, UWB equipment selection and installation select UWB positioning equipment suitable for the harsh environment of the mine, which is required to have the characteristics of high protection level, strong anti-interference ability and high precision. The UWB tag should be small and light, easy to install on the electric locomotive, and have good battery life and signal transmission stability. The base station should have a large coverage range and high positioning accuracy, and be able to adapt to the complex terrain and electromagnetic environment of the mine. Select a suitable location on the electric locomotive to install the UWB tag to ensure that the signal transmission of the tag is not blocked and can communicate stably with the base station. In the mine tunnel, according to the pre-designed base station layout plan, use professional installation tools and fixtures to install the UWB base station on the tunnel wall or other suitable locations. Ensure that the base station is firmly installed, accurately positioned, and well grounded to improve the stability and anti-interference ability of the equipment.

[0032] The data acquisition and preprocessing module is responsible for collecting the data output by the precise positioning module and the relevant operation data of the electric locomotive, and performing preprocessing;

[0033] Specifically, the data acquisition and preprocessing module transmits the data such as the speed, braking time, and working condition of the electric locomotive to the data processing model. After processing the data, the data processing model sends the data such as the braking coefficient and the braking coefficient to the alignment control module. The data processing model is set on the working condition machine.

[0034] The AI ​​model processing module is used to analyze and process the pre-processed data using an AI model based on deep learning, and then acquire and process the images in combination with the monitoring screen of the ore-drawing work area;

[0035] In this embodiment, the AI ​​model processing module includes a camera set in the alley, an image processing module, and a built-in deep learning model.

[0036] The alignment control module is used to combine the precise position information of the electric locomotive output by the AI ​​visual model processing module with the information output by the data acquisition and preprocessing module, compare it with the preset alignment target position, and generate control instructions;

[0037] The execution device is used to receive the control instructions of the positioning control module and control the start and stop of the electric locomotive according to the control instructions.

[0038] In this embodiment, the execution device includes a vehicle-mounted controller and a chute installed on the electric locomotive, and an operation console installed on the ground. Specifically, the operation console receives the control instructions of the alignment control module and then forwards them to the vehicle-mounted controller, which controls the start and stop of the electric locomotive according to the execution instructions;

[0039] In this embodiment, the camera selection and installation selects a high-definition, wide dynamic range camera with good low-light performance and dust and water resistance to adapt to the complex lighting and environmental conditions of the ore-laying work area. According to the actual layout and monitoring requirements of the ore-laying work area, the installation location and number of cameras are determined to ensure that the ore-laying machine, the electric locomotive driving area and other key parts can be fully covered.

[0040] Equip the electric locomotive with an advanced onboard controller that can accurately receive and execute instructions from the alignment console and precisely control the electric locomotive's actuators. Ensure that the onboard controller is compatible with the electric locomotive's electrical system, is securely installed, and has reliable connections. Select appropriate communication equipment, such as wireless bridges, industrial Ethernet switches, etc., to achieve data transmission between various modules of the system. According to the actual environment and communication distance of the mine, reasonably configure the parameters of the communication equipment to ensure the stability and real-time performance of data transmission.

[0041] The electric locomotive can obtain UWB positioning information, locomotive specific working conditions and other information during operation, upload it to the operating console, and output the relevant data to the alignment control module after processing through the data acquisition and preprocessing module. This module should have a multi-source data interface, be able to communicate with different types of hardware devices, collect data according to the predetermined sampling frequency and data format, and perform real-time caching and preprocessing.

[0042] In terms of preprocessing functions, a data cleaning algorithm is implemented to remove outliers and noise interference. A data fusion algorithm is used to integrate and associate data from different sensors to form a unified data format. At the same time, a data format conversion function is implemented to convert the preprocessed data into a format suitable for the input of the AI ​​visual model processing module. The data acquisition and preprocessing software runs on an industrial computer to ensure the real-time and efficient data processing.

[0043] AI visual model processing software is developed based on the deep learning framework. The software is responsible for loading and running pre-trained AI visual models, and analyzing and processing the data and images sent by the camera. In the design of the software architecture, a modular design concept is adopted to encapsulate functional modules such as image preprocessing, feature extraction, target detection, and data analysis fusion for easy maintenance and upgrading. The inference calculation process of the model is optimized to improve the processing speed and efficiency to meet real-time requirements.

[0044] To realize the core functions of the alignment control module, the software receives the precise position information of the electric locomotive sent by the AI ​​vision model processing module, combines it with the braking coefficient and other data uploaded by the data acquisition and preprocessing module, and compares and analyzes it with the preset alignment target position, and generates corresponding control instructions according to the preset control strategy.

[0045] The software should have a good human-computer interaction interface, which can display the locomotive's position information, alignment status, system operating parameters, and monitoring screen in real time. The operator can perform parameter settings, manual intervention, and fault diagnosis through the interface.

[0046] The communication between the alignment control software and the operating console and vehicle controller should be stable and reliable to ensure the accurate transmission and execution of control instructions. At the same time, it has emergency handling functions, and can switch to manual control mode or take corresponding safety measures in time when abnormal situations occur.

[0047] System Integration and DeploymentIntegrate data acquisition and preprocessing software, AI visual model processing software and alignment control software to build a complete alignment control system for automatic ore placement in the chute. During the integration process, ensure that the data interface specifications between various software modules are unified and data transmission is unimpeded.

[0048] The entire software system is deployed on an industrial computer or server, and reasonable resource allocation and optimization are performed. According to the actual network environment of the mine, the network parameters are configured to ensure that the system can run stably under different network conditions. At the same time, the system is fully tested and debugged, including functional testing, performance testing, compatibility testing, and security testing, to ensure that the system can meet the requirements of actual production.

[0049] Another technical solution: Figure 2 As shown, the figure is a flowchart of the steps of the alignment system; a method of an automatic ore placement alignment system for a chute including any of the above items comprises the following steps:

[0050] Step S1, measuring the UWB tag signal on the electric locomotive through a UWB base station based on a pre-deployed precise positioning module, and calculating the distance information between the electric locomotive and the base station using parameters such as arrival time difference;

[0051] Step S2: using the data acquisition and preprocessing module to receive the data output by the precise positioning module and the relevant operation data of the electric locomotive and preprocessing them, and then sending the preprocessed data to the alignment control module;

[0052] Step S3: Based on the AI ​​model of deep learning, the AI ​​model processing module analyzes and processes the pre-processed data, and then acquires and processes the image in combination with the monitoring screen of the ore-drawing work area;

[0053] Step S4, the alignment control module combines the precise position information of the electric locomotive output by the AI ​​visual model processing module with the information output by the data acquisition and preprocessing module, compares it with the preset alignment target position, and generates a control instruction;

[0054] Step S5: When the execution device receives the control instruction of the positioning control module, it controls the start and stop of the electric locomotive according to the control instruction.

[0055] In the specific implementation steps, the precise positioning module adopts a multilateral positioning algorithm to determine the preliminary position coordinates of the electric locomotive based on the distance information.

[0056] In the specific implementation steps, the AI ​​model processing module receives the video image from the camera and transmits the video screen to the image processing module; the image processing module sends the adjusted video screen to the deep learning model and finally outputs the target detection result.

[0057] Specifically, it includes a camera in the tunnel, an image processing module and a deep learning model, wherein the image processing module and the deep learning model are set in an alignment box underground as the algorithm part;

[0058] The camera in the tunnel is installed on the tunnel wall, and the angle can fully see the chute and the locomotive car body. The camera transmits the video image to the image processing module; the image processing module adjusts the image and sends the adjusted video image to a mature deep learning model, which outputs the target detection results including the front position of the car body, the position of the chute exit, and the rear position of the locomotive.

[0059] In the specific implementation steps, the alignment control module analyzes whether the car body position is aligned with the chute outlet position based on the output target detection results. In the aligned moving operation, the braking coefficient and braking coefficient of each car are different. During the loading process, the braking coefficient is also changing. Therefore, the time when the start and braking control instructions are issued is calculated by the alignment control module to give the braking instruction, thereby reducing the locomotive alignment time.

[0060] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents, and all should be included within the scope of protection of the present invention.

Claims

1. A chute automatic ore placement system, characterized in that: It includes precise positioning module, data acquisition and preprocessing module, AI model processing module, alignment control module, execution equipment, and electric locomotive; The precise positioning module is used to measure the distance information between the electric locomotive and the base station and determine the preliminary position coordinates of the electric locomotive; The data acquisition and preprocessing module is responsible for collecting the data output by the precise positioning module and the relevant operation data of the electric locomotive, and performing preprocessing; The AI ​​model processing module is used to analyze and process the pre-processed data using an AI model based on deep learning, and then acquire and process the image in combination with the monitoring screen of the ore-drawing work area; The alignment control module is used to combine the precise position information of the electric locomotive output by the AI ​​visual model processing module with the information output by the data acquisition and preprocessing module, compare it with the preset alignment target position, and generate a control instruction; The execution device is used to receive the control instruction of the positioning control module and control the start and stop of the electric locomotive according to the control instruction.

2. According to claim 1, a chute automatic ore placement alignment system is characterized in that: The precise positioning module includes a UWB tag arranged on the electric locomotive and a plurality of UWB base stations distributed in the mine tunnel.

3. The automatic ore placement alignment system for a chute according to claim 1, characterized in that: The execution device includes a vehicle-mounted controller arranged on the electric locomotive and an operating console arranged on the ground end.

4. The automatic ore placement alignment system for a chute according to claim 3 is characterized in that: The AI ​​model processing module includes a camera arranged in the lane, an image processing module, and a built-in deep learning model.

5. A method comprising a chute automatic ore placement alignment system as claimed in any one of claims 1 to 4, characterized in that: The following steps are involved: Step S1, measuring the UWB tag signal on the electric locomotive through a UWB base station based on a pre-deployed precise positioning module, and calculating the distance information between the electric locomotive and the base station using parameters such as arrival time difference; Step S2: using the data acquisition and preprocessing module to receive the data output by the precise positioning module and the relevant operation data of the electric locomotive and preprocess them, and then sending the preprocessed data to the alignment control module; Step S3: Based on the AI ​​model of deep learning, the AI ​​model processing module analyzes and processes the pre-processed data, and then acquires and processes the image in combination with the monitoring screen of the ore-drawing work area; Step S4, the alignment control module combines the precise position information of the electric locomotive output by the AI ​​visual model processing module with the information output by the data acquisition and preprocessing module, compares it with the preset alignment target position, and generates a control instruction; Step S5: When the execution device receives the control instruction of the positioning control module, it controls the start and stop of the electric locomotive according to the control instruction.

6. A method for an automatic ore placement alignment system for a chute according to claim 5, characterized in that: The precise positioning module adopts a multilateral positioning algorithm to determine the preliminary position coordinates of the electric locomotive according to the distance information.

7. The method of the automatic ore placement alignment system of a chute according to claim 5, characterized in that: The AI ​​model processing module receives the video image from the camera and transmits the video image to the image processing module; the image processing module sends the adjusted video image to the deep learning model and finally outputs the target detection result.

8. The method of the automatic ore placement alignment system of a chute according to claim 7, characterized in that: The alignment control module analyzes whether the car body position is aligned with the chute outlet position according to the output target detection result, calculates and gives a braking command, and reduces the locomotive alignment time.

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