WO2023108692A1 - 综采工作面智能控制系统、方法 - Google Patents

综采工作面智能控制系统、方法 Download PDF

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Publication number
WO2023108692A1
WO2023108692A1 PCT/CN2021/139794 CN2021139794W WO2023108692A1 WO 2023108692 A1 WO2023108692 A1 WO 2023108692A1 CN 2021139794 W CN2021139794 W CN 2021139794W WO 2023108692 A1 WO2023108692 A1 WO 2023108692A1
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WIPO (PCT)
Prior art keywords
intelligent control
control device
intelligent
chip module
video image
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PCT/CN2021/139794
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English (en)
French (fr)
Inventor
冯银辉
付振
李首滨
李森
韦文术
高思伟
刘清
姚钰鹏
任伟
Original Assignee
北京天玛智控科技股份有限公司
北京煤科天玛自动化科技有限公司
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Publication of WO2023108692A1 publication Critical patent/WO2023108692A1/zh

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    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21D—SHAFTS; TUNNELS; GALLERIES; LARGE UNDERGROUND CHAMBERS
    • E21D23/00—Mine roof supports for step- by- step movement, e.g. in combination with provisions for shifting of conveyors, mining machines, or guides therefor
    • E21D23/12—Control, e.g. using remote control
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
    • E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
    • E21F17/18—Special adaptations of signalling or alarm devices

Definitions

  • the disclosure relates to the technical field of intelligent control of coal mine production, in particular to an intelligent control system and method for a fully mechanized mining face.
  • coal mining production is realized by controlling the functions of coal shearer cutting coal, hydraulic support support, and scraper conveyor coal transportation.
  • a controller is provided on the hydraulic support, and the controller can receive signals from a remote controller, and then personnel can send control signals through the remote controller, so that the controller can control the support to adjust the working state.
  • the controller can receive signals from a remote controller, and then personnel can send control signals through the remote controller, so that the controller can control the support to adjust the working state.
  • the current method of visual remote intervention in coal mining requires staff to observe the actual operating conditions of the equipment on the working face through video monitoring in the monitoring center or on the ground, and then use the console to send corresponding control signals to realize the detection of abnormal conditions on the working face. deal with.
  • This method has problems such as incomplete viewing of video, large communication delay, reliance on manual observation, and low reliability, and also has great limitations.
  • the present disclosure aims to solve one of the technical problems in the related art at least to a certain extent.
  • the present disclosure proposes a working face intelligent control system, method and communication, which automatically adjusts the working status of hydraulic supports, coal shearers and other equipment on the basis of combining the actual working conditions of the working face, with high safety And high efficiency.
  • an intelligent control system for a fully mechanized mining face includes: at least one support, at least one intelligent control device arranged on the support, and a first manual integrated in the intelligent control device.
  • the first image acquisition device is configured to acquire a first video image within a first preset range in real time, and send the first video image to the first AI chip module; the first AI chip module, It is used to process the first video image in real time, identify the first video image according to the pre-trained deep learning model to obtain a first identification result, and send the first identification result to the intelligent control device; the intelligent control device, configured to control the bracket to perform a corresponding action according to the first recognition result sent by the first AI chip module.
  • the system also includes: an intelligent wireless gateway device connected to the intelligent control device, a second AI chip device integrated in the intelligent wireless gateway, and a second image acquisition device connected to the second AI chip device .
  • the second image acquisition device is configured to acquire a second video image within a second preset range in real time, and send the second video image to the second AI chip module; the second AI chip module, It is used to process the second video image in real time, identify the second video image according to the pre-trained deep learning model to obtain a second identification result, and send the second identification result to the intelligent control device; the intelligent control device, configured to control the bracket to perform a corresponding action according to the second identification result sent by the intelligent wireless gateway device.
  • the system also includes: a wireless communication device integrated in the intelligent wireless gateway, a handheld terminal device; the handheld terminal device is interactively connected with the intelligent control device through the wireless communication device, and/or the handheld The terminal device is connected with the intelligent wireless gateway device.
  • the handheld terminal device is used to read the data in the intelligent control device in real time and modify the system software parameters of the intelligent control device to adjust the bracket to perform corresponding actions.
  • the wireless communication device includes: at least one of the following: a WIFI communication unit; a 4G communication unit; and a 5G communication unit.
  • the system further includes: two adjacent intelligent control devices among the multiple intelligent control devices are connected by wire; and/or, any two intelligent control devices among the multiple intelligent control devices The devices are interactively connected through the wireless communication device of the intelligent wireless gateway device.
  • the system also includes: a sound pickup device; the sound pickup device is connected with the intelligent control device.
  • the sound pickup device is used to obtain environmental voiceprint information, and send the environmental voiceprint information to the second AI chip module; the second AI chip module is also used to identify The environmental characteristics of the working face, and send the environmental characteristics of the working face to the intelligent control device; the intelligent control device is used to receive the environmental characteristics of the working face, and control the execution of the support according to the environmental characteristics of the working face corresponding action.
  • the system also includes: a UWB communication unit integrated in the intelligent wireless gateway device.
  • the UWB communication unit is used to interact with the UWB positioning tag carried by the personnel to locate the personnel in real time, and send the personnel positioning information to the intelligent wireless gateway device, and then to the intelligent control device;
  • the intelligent control device is further configured to receive the personnel positioning information, and control the support to perform corresponding actions according to the personnel positioning information.
  • the system also includes: at least one wireless sensor detection device, a wireless sensor communication unit integrated in the intelligent wireless gateway device; the wireless sensor detection device communicates with the intelligent wireless gateway device through the wireless sensor communication unit Interactive connection.
  • the wireless sensor detection device is used to detect a specific feature, obtain the detection result of the specific feature, and send the detection result to the intelligent wireless gateway device, and then send it to the intelligent control device.
  • the intelligent control device is further configured to receive the detection result, and control the support to perform corresponding actions according to the detection result.
  • the intelligent wireless gateway device can be installed one for each hydraulic support, or can be installed for multiple hydraulic supports, and the video coverage can be expanded through an external video device, and the video image can be sent to the AI chip
  • the module senses the environment of the working face.
  • the system also includes: a sound amplifying device connected to the intelligent control device; the sound amplifying device is used to receive the sound signal sent by the intelligent control device, and convert the sound signal into voice information for broadcasting.
  • the system also includes: a warning device connected to the intelligent control device; the warning device cooperates with the intelligent control device to display a lock, so as to remind personnel to pay attention to safety.
  • the system also includes: a pressure sensor device and a travel sensor device respectively connected to the intelligent control device.
  • a bracket control method includes: acquiring a video image within a preset range in real time, and sending the video image to an AI chip module; The video image is processed, and the video image is recognized according to the pre-trained deep learning model to obtain a recognition result, and the recognition result is sent to the intelligent control device; the intelligent control device sends The identification result, and control the support to perform corresponding actions.
  • the method further includes: a hand-held terminal device is interactively connected to the intelligent control device through a wireless communication unit; the hand-held terminal device reads data in the intelligent control device in real time, and the The system software parameters of the intelligent control device are modified to control the support to perform corresponding actions.
  • the intelligent wireless gateway device of each hydraulic support Through the intelligent wireless gateway device of each hydraulic support, its integrated video acquisition module acquires video images, sends them to its integrated AI chip module, and processes the video images in real time. According to the pre-trained deep learning model, the video images are processed Identify, obtain the recognition result, and send the recognition result to the connected intelligent control device, and the intelligent control device can control the bracket to perform corresponding actions according to the recognition result, so as to automatically adjust the bracket. Therefore, the working face intelligent control system provided by the embodiments of the present disclosure can adjust the working state of the hydraulic support equipment on the spot and automatically in combination with the actual working conditions of the working face, which solves the problem of real-time control and visibility from all angles. It also reduces the workload of the operator to observe the video image, with high safety and high efficiency.
  • FIG. 1 is a structural diagram of an intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure
  • Fig. 2 is a structural diagram of an intelligent control device in a fully mechanized mining face intelligent control system provided by an embodiment of the present disclosure
  • Fig. 3 is a structural diagram of another intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure
  • Fig. 4 is a structural diagram of another intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure
  • Fig. 5 is a structural diagram of another intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure
  • Fig. 6 is a structural diagram of a wireless communication device in a fully mechanized mining face intelligent control system provided by an embodiment of the present disclosure
  • Fig. 7 is a structural diagram of another intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure.
  • Fig. 8 is a structural diagram of another intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure
  • Fig. 9 is a structural diagram of an intelligent wireless gateway device in a fully mechanized mining face intelligent control system provided by an embodiment of the present disclosure.
  • Fig. 10 is a structural diagram of an intelligent wireless gateway device in another intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure
  • Fig. 11 is a structural diagram of an intelligent control device in a fully mechanized mining face intelligent control system provided by an embodiment of the present disclosure
  • Fig. 12 is a flow chart of an intelligent control method for a fully mechanized mining face provided by an embodiment of the present disclosure.
  • Fig. 1 is a structural diagram of an intelligent control system for a fully mechanized mining face provided by an embodiment of the present disclosure.
  • the working surface intelligent control system provided by the embodiment of the present disclosure includes: at least one support 1 , and an intelligent control device 2 arranged on the support.
  • the structure of the bracket 1 in FIG. 1 is only for illustration and is not intended to limit the present disclosure.
  • the bracket 1 may also be a bracket 1 with other structures.
  • the installation position of the intelligent control device 2 is only for illustration, not as a limitation to the present disclosure.
  • the intelligent control device 2 can also be provided at any other position on the bracket 1, or integrated in the structure of the bracket 1 , or arranged in other devices other than the structure of the bracket 1 fixedly connected with the bracket 1 , the present disclosure does not specifically limit this.
  • the system also includes: a first artificial intelligence AI chip module 21 integrated in the intelligent control device 2, a first image acquisition module connected to the first artificial intelligence AI chip module 21 device 22.
  • the first image acquisition device 22 is configured to acquire a first video image within a first preset range in real time, and send the first video image to the first AI chip module 21 .
  • the first AI chip module 21 is used to process the first video image in real time, recognize the first video image according to the pre-trained deep learning model to obtain the first recognition result, and send the first recognition result to the intelligent control device 2.
  • the intelligent control device 2 is configured to control the bracket 1 to perform corresponding actions according to the first identification result sent by the first AI chip module 21 .
  • the first image acquisition device 22 may be a camera, a monocular camera or other devices capable of acquiring images, which is not specifically limited in the present disclosure.
  • the monocular camera is mainly an RGB camera, which can quickly complete the acquisition with the monocular algorithm, and send high-quality images to the backend for recognition and comparison.
  • the first image acquisition device 22 is set at a specific position of the bracket to be able to acquire images within the first preset range, for example: the first image acquisition device 22 can be set at the position of the bracket column, or set at the bracket The base or other arbitrary positions, so that the first image acquisition device 22 can acquire images within a specific range such as coal walls, side panels, conveyor chutes, or surrounding environments.
  • the first AI chip module 21 may be, for example, an artificial intelligence chip, or a device integrated with an artificial intelligence processing program.
  • a pre-trained deep learning model is preset in the first AI chip module 21, which can recognize images, and can recognize different images for different training samples.
  • coal wall images are pre-selected as training samples, coal wall abnormal images in different situations are selected as training samples, and the deep learning model is trained to obtain a trained deep learning model, so that the trained
  • the deep learning model recognizes the real-time images acquired by the first image acquisition device 22, it can identify images that are the same as or similar to the sample coal wall images, so as to achieve the purpose of identifying coal wall anomalies.
  • the first identification result obtained by the first AI chip module 21 may be the identified abnormal type. action corresponding strategy, thus, after the intelligent control device 2 obtains the first recognition result sent by the first AI chip module 21, it can determine the corresponding action that needs to be controlled by the bracket 1 according to the preset corresponding strategy, and then control Stand 1 performs this action.
  • the first recognition result obtained by the first AI chip module 21 may be the corresponding action that needs to be controlled by the bracket.
  • the first AI chip module 21 is preset with an exception type and the corresponding strategy for the control bracket to execute the corresponding action.
  • the first AI chip module 21 acquires the video image, it recognizes the abnormal type of the video image, and then according to the abnormal type and the corresponding strategy for the control bracket to execute the corresponding action, generates the required control bracket 1 to execute Therefore, the first AI chip module 21 sends the first recognition result of the corresponding action that needs to be controlled by the bracket 1 to the intelligent control device 2, and the intelligent control device 2 according to the first recognition result,
  • the control bracket 1 performs corresponding actions.
  • the first image acquisition device 22 acquires the first video image within the first preset range in real time, and sends the first video image to the first AI chip module 21, and the first AI
  • the chip module 21 processes the first video image in real time, recognizes the first video image according to the pre-trained deep learning model, obtains the first recognition result, and sends the first recognition result to the intelligent control device 2, and the intelligent control device 2, according to the first recognition result, the bracket 1 may be controlled to perform corresponding actions, so as to automatically adjust the bracket 1 . Therefore, the intelligent control system of the fully mechanized mining face provided by the embodiment of the present disclosure can adaptively adjust the working state of the support 1 in combination with the actual working conditions of the fully mechanized mining face, with high safety and high efficiency.
  • the system also includes: an intelligent wireless gateway device 3 connected to the intelligent control device 2, a second AI chip module 31 integrated in the intelligent wireless gateway device 3, a second AI chip module 31 connected to the The second image acquisition device 32 .
  • the second image acquisition device 32 is used to acquire the second video image within the second preset range in real time, and sends the second video image to the second AI chip module 31;
  • the second video image is processed, and the second video image is recognized according to the pre-trained deep learning model to obtain a second recognition result, and the second recognition result is sent to the intelligent wireless gateway device 3 respectively.
  • the intelligent wireless gateway device 3 is configured to receive the second identification result and send the second identification result to the intelligent control device 2 .
  • the intelligent control device 2 is configured to control the bracket 1 to perform corresponding actions according to the second identification result sent by the intelligent wireless gateway device 3 .
  • the second image acquisition device 32 may be a camera, a monocular camera or other devices capable of acquiring images, which is not specifically limited in the present disclosure.
  • the monocular camera is mainly an RGB camera, which can quickly complete the acquisition with the monocular algorithm, and send high-quality images to the backend for recognition and comparison.
  • the second image acquisition device 32 is set at a specific position of the bracket to be able to acquire images within a second preset range, for example: the second image acquisition device 32 can be set at a position below the top beam of the bracket, or can It is installed on the top of the mine or any other position, so that the second image acquisition device 32 can acquire images within a specific range such as coal walls, side panels, conveyor chutes, or the surrounding environment.
  • the second AI chip module 31 may be an artificial intelligence chip, or a device integrated with an artificial intelligence processing program.
  • a pre-trained deep learning model is preset in the second AI chip module 31, which can recognize images, and can recognize different images for different training samples.
  • coal wall images are pre-selected as training samples, coal wall abnormal images in different situations are selected as training samples, and the deep learning model is trained to obtain a trained deep learning model, so that the trained
  • the deep learning model recognizes the real-time images acquired by the second image acquisition device 32 , it can identify images that are the same as or similar to the sample coal wall images, so as to achieve the purpose of identifying abnormal coal walls.
  • the second identification result obtained by the second AI chip module 31 may be the identified abnormal type.
  • the corresponding strategy of the action thus, after the intelligent control device 2 obtains the second identification result obtained from the second AI chip module 31 sent by the intelligent wireless gateway device 3, it can determine that it needs to control according to the preset corresponding strategy. The corresponding action performed by the stent 1, and then the stent 1 is controlled to perform the action.
  • the second recognition result acquired by the second AI chip module 31 may be the corresponding action that needs to be controlled by the bracket.
  • the second AI chip module 31 is preset with an exception type and the corresponding strategy for the control bracket to execute the corresponding action. After the second AI chip module 31 acquires the video image, it recognizes the abnormal type of the video image, and then according to the abnormal type and the corresponding strategy for the control bracket to execute the corresponding action, generates the corresponding strategy that needs to be controlled by the control bracket 1.
  • the second AI chip module 31 sends the second recognition result of the corresponding action that needs to be controlled by the bracket 1 to the smart wireless gateway device 3, and the smart wireless gateway device 3 sends the second recognition result
  • the information is sent to the intelligent control device 2, and the intelligent control device 2 controls the bracket 1 to perform corresponding actions according to the second identification result.
  • the second image acquisition device 32 acquires the second video image within the second preset range in real time, and sends the second video image to the second AI chip module 31, and the second AI The chip module 31 processes the second video image in real time, recognizes the second video image according to the pre-trained deep learning model, obtains the second recognition result, and sends the second recognition result to the smart wireless gateway device 3, the smart wireless The gateway device 3 sends the second identification result to the intelligent control device 2 , and the intelligent control device 2 can control the bracket 1 to perform corresponding actions according to the second identification result, so as to automatically adjust the bracket 1 . Therefore, the intelligent control system of the fully mechanized mining face provided by the embodiment of the present disclosure can adaptively adjust the working state of the support 1 in combination with the actual working conditions of the fully mechanized mining face, with high safety and high efficiency.
  • the system also includes: a handheld terminal device 4 .
  • the handheld terminal device 4 shown in FIG. 4 is only for illustration, and is not intended to limit the present disclosure.
  • the handheld terminal device 4 may be: a mobile phone terminal, a tablet computer, or a developed handheld terminal device with certain functions.
  • the handheld terminal device 4 may also be a computer, a palmtop computer, etc., which is not specifically limited in the present disclosure.
  • the system further includes: a wireless communication device 33 integrated in the intelligent wireless gateway device 3 .
  • the handheld terminal device 4 is interactively connected with the intelligent control device 2 through the wireless communication device 33 integrated in the intelligent wireless gateway device 3 .
  • the handheld terminal device 4 is used to read the data in the intelligent control device 2 in real time and modify the system software parameters of the intelligent control device 2 to control the bracket 1 to perform corresponding actions.
  • the handheld terminal device 4 is interactively connected with the intelligent control module 11 through the wireless communication device 33 integrated in the intelligent wireless gateway device 3, and the handheld terminal device 4 can read the data of the intelligent control device 2 in real time, for example: System software parameters, support control parameters and the like in the intelligent control device 2.
  • the hand-held terminal device 4 can be interactively connected with the intelligent control module 11 through the wireless communication device 33 integrated in the intelligent wireless gateway device 3, and engineers and technicians can use the hand-held terminal device 4 to remotely monitor or adjust the intelligent control module.
  • the system software parameters in the device 2 are used to control the support 1 to perform corresponding actions and adjust the posture of the support 1, so that engineers and technicians can remotely control the support, with high safety and high efficiency.
  • the wireless communication device 33 includes at least one of the following: a WIFI communication unit 331 ; a 4G communication unit 332 ; and a 5G communication unit 333 .
  • the wireless communication unit 33 can receive the wireless signal sent by the handheld terminal device 4 and send the wireless signal to the handheld terminal device 4.
  • the wireless communication unit 33 can be a WIFI communication unit 331, a 4G communication unit 332 and a 5G communication unit At least one of 333.
  • the wireless communication unit 33 may include a WIFI communication unit 331, or a 4G communication unit 332, or a 5G communication unit 333, or a WIFI communication unit 331 and a 4G communication unit 332, or a WIFI communication unit 331 and a 5G communication unit 333 , or a 4G communication unit 332 and a 5G communication unit 333 , or a WIFI communication unit 331 , a 4G communication unit 332 and a 5G communication unit 333 .
  • the wireless communication unit 33 includes a WIFI communication unit 331 and a 4G communication unit 332, or a WIFI communication unit 331 and a 5G communication unit 333, or a 4G communication unit 332 and a 5G communication unit 333, or a WIFI communication unit 331 and a 4G communication unit 332
  • the WIFI communication unit 331, the 4G communication unit 332 and the 5G communication unit 333 are mutually redundant. one to connect.
  • the wireless communication unit 33 includes a WIFI communication unit 331 and a 4G communication unit 332, the WIFI communication unit 331 and the 4G communication unit 332 are mutually redundant, and the handheld terminal device 4 communicates with the intelligent control device through the wireless communication unit 33 2 interaction, if the connection fails using the WIFI communication unit 331, the 4G communication unit 332 can be used for interactive connection with the intelligent control device 2.
  • the wireless communication unit 33 includes at least one of the WIFI communication unit 331, the 4G communication unit 332 and the 5G communication unit 333, and the WIFI communication unit 331, the 4G communication unit 332 and the 5G communication unit 333 are mutually redundant, Multiple connection methods can be provided for the interactive connection between the handheld terminal device 4 and the intelligent control device 2, so as to avoid only one interactive connection method. After the failure of the interactive connection method, the handheld terminal device 4 cannot be interactively connected with the intelligent control device 2 , so that the hand-held terminal device 4 and the intelligent control device 2 can be interactively connected in various ways to avoid interaction failure.
  • the system includes: two adjacent intelligent control devices 2 among the plurality of intelligent control devices 2 are connected by wire; and/or, any two intelligent control devices among the plurality of intelligent control devices 2 2.
  • any two adjacent intelligent control devices 2 provided by multiple supports 1 are connected in a wired manner to realize support cluster control.
  • any two intelligent control devices 2 in the plurality of intelligent control devices 2 are interactively connected through the wireless communication device 33 of the intelligent wireless gateway device 3, so that any two intelligent control devices 2 in the plurality of intelligent control devices 2 can be wirelessly connected to each other.
  • the way of interactive connection can also realize the control of the bracket cluster.
  • the information transmission between the two intelligent control devices 2 may be transmitted in a wired or wireless manner, so that the stability and efficiency of system information transmission can be improved.
  • the information transmission between two intelligent control devices 2 can only be done in a wired or wireless way, and the wired and wireless ways cannot be used at the same time.
  • the information transmission between two intelligent control devices 2 is transmitted in a wired way. There is a redundant relationship with wireless transmission to avoid signal transmission failure or confusion.
  • the system also includes: a sound pickup device 23 connected to the intelligent control device 2 .
  • the sound pickup device 23 is used to obtain the environmental voiceprint information, and sends the environmental voiceprint information to the first AI chip module 21; the first AI chip module 21 is also used to identify the environmental characteristics of the working face according to the environmental voiceprint information, and The environmental characteristics of the working face are sent to the intelligent control device 2; the intelligent control device 2 is used to receive the environmental characteristics of the working face, and control the support 1 to perform corresponding actions according to the environmental characteristics of the working face.
  • the sound pickup device 23 can obtain the voiceprint information in the environment, for example: the sound pickup device 23 can be a sound pickup; or other devices or equipment capable of collecting the voiceprint information in the environment, those skilled in the art can choose to meet the above requirements as needed Any device, which is not specifically limited in the present disclosure.
  • the first AI chip module 21 receives the environmental voiceprint information obtained by the sound pickup device 23. It can be understood that the environmental voiceprint information may include the voiceprint information of people speaking, and may also include the sound of broken coal and rocks. , including other sounds. In the embodiment of the present disclosure, after the first AI chip module 21 acquires the environmental voiceprint information, it recognizes the environmental voiceprint information, and can recognize the environmental characteristics of the fully mechanized mining face and/or the voice information of personnel, etc. .
  • the first AI chip module 21 can identify the environmental voiceprint information related to the operation of the fully mechanized mining face, obtain the environmental characteristics of the working face, and send the environmental characteristics of the working face to the intelligent control device 2, and then the intelligent control device 2 According to the environmental characteristics of the working face and the corresponding strategy of the preset environmental characteristics of the working face and the corresponding actions of the support 1, the support 1 is controlled to perform the corresponding actions, so that the information obtained from various aspects can be integrated, combined with the actual working conditions of the working face, on-site And automatically adjust the working status of the bracket 1 and other equipment accordingly, which solves the problems of real-time control and full viewing from all angles, and also reduces the workload of engineering and technical personnel to observe video images, with high safety and high efficiency.
  • the system further includes: a UWB communication unit 34 integrated in the intelligent wireless gateway device 3 .
  • UWB communication unit 34 is used for interacting with the UWB positioning tag carried by the personnel, so as to locate the personnel in real time, and send the personnel positioning information to the intelligent wireless gateway device 3; the intelligent wireless gateway The device 3 is also used to send the personnel location information to the intelligent control device 2 .
  • the intelligent control device 2 is also used to receive personnel positioning information, and control the bracket 1 to perform corresponding actions according to the personnel information.
  • the personnel when the personnel enter the underground operation, they carry UWB positioning tags.
  • the UWB communication unit 34 interacts with the UWB positioning tags carried by the personnel to realize real-time positioning of the personnel's position.
  • the personnel positioning information is transmitted to the intelligent control device 2, and the intelligent control device 2 controls the bracket 1 to perform corresponding actions according to the personnel positioning information, so as to improve the protection of personnel safety.
  • the system further includes: at least one wireless sensor unit 35 , and a wireless sensor access module 36 integrated in the intelligent wireless gateway device 3 .
  • the wireless sensor unit 35 is arranged at a specific position of the bracket 1 to detect specific features of the bracket 1 , and is interactively connected with the intelligent wireless gateway device 3 through the wireless sensor access module 36 .
  • the wireless sensor unit 35 is interactively connected with the intelligent wireless gateway device 3 through the wireless sensor access module 36 in the intelligent wireless gateway device 3; the wireless sensor unit 35 is used to detect specific features, obtain the detection results of specific features and send the detection results to The intelligent wireless gateway device 3; the intelligent wireless gateway device 3 is also used to receive the detection result and send the detection result to the intelligent control device 2; the intelligent control device 2 is also used to receive the detection result and control the bracket 1 to execute according to the detection result corresponding action.
  • At least one wireless sensor unit 35 includes, for example, one or more of an altitude sensor, a pressure sensor, an inclination sensor, and a stroke sensor. It can be understood that different wireless sensor units 35 detect different features and are set at different positions, and can be placed at specific positions that can accurately detect specific features, and those skilled in the art can set as required.
  • At least one wireless sensor unit 35 includes: a height measuring sensor; the height measuring sensor is arranged under the top beam of the support 1 for detecting the height of the top beam of the support 1 .
  • At least one wireless sensor unit 35 includes: a pressure sensor, which is arranged at the position of the support pole of the bracket 1 to detect the pressure on the bracket 1 .
  • wireless sensor unit 35 is only for illustration, and sensors with various functions can also be provided as required to detect specific features.
  • At least one wireless sensor unit 35 generates a signal carrying environmental data from the detection result, and sends it to the smart wireless gateway device 3 through the wireless sensor access module 36, and the smart wireless gateway device 3 sends the detection result to the smart wireless gateway device 3.
  • the control device 2 so that the intelligent control device 2 can obtain the data of the detection result of the measured specific feature, and further control the bracket 1 to perform corresponding actions according to the detection result.
  • the system also includes: a sound amplifying device 24 ; the sound amplifying device 24 is connected with the intelligent control device 2 .
  • the sound amplifying device 24 is used for receiving the sound signal sent by the intelligent control device 2, converting the sound signal into voice information for broadcasting and sending.
  • the sound amplifying device 24 can send out sound messages, for example: the sound amplifying device 24 can be: a loudspeaker, a horn, etc.
  • the sound amplification device 24 in the embodiment of the present disclosure receives the sound signal sent by the intelligent control device 2, and converts the sound signal into voice information for broadcast transmission; For notification signals, announcement message signals, or playing music signals or news signals during breaks, etc., the above-mentioned sound signals are converted into voice information for broadcasting and transmission, so that relevant information can be obtained and personnel exchanges can be carried out.
  • the system also includes: a warning device 25 ; the warning device 25 is connected with the intelligent control device 2 .
  • the warning device 25 is used for receiving the warning signal sent by the intelligent control device 2, and giving a warning according to the warning signal.
  • the warning device 25 cooperates with the intelligent control device 2 to display a lock, so as to remind personnel to pay attention to safety.
  • the warning device 25 is, for example, a two-color lamp, an indicator light, and the like.
  • the intelligent control device 2 can issue warning information through the warning device 25, for example: when the warning device 25 is a two-color light, the intelligent control device 2 controls the two-color light to perform a locked display to display different Color, to inform underground personnel of different information, to remind personnel to pay attention to safety.
  • the warning device 25 can be arranged under the top beam of the support 1 so that personnel can see the warning device 25 intuitively.
  • the system further includes: a pressure sensor device 26 and a stroke sensor device 27 respectively connected to the intelligent control device 2 .
  • the pressure sensor device 26 and the stroke sensor device 27 are connected with the intelligent control device 2 in a wired manner, and are used to detect different features, and send the detection results of different features to the intelligent control device 2 .
  • the pressure sensor device 26 can be set at the position of the supporting rod of the bracket 1 to detect the pressure on the bracket 1; the stroke sensor device 27 can be set at the position of the pushing rod to detect the stroke of the pushing rod.
  • the present disclosure also proposes an intelligent control method for a fully mechanized mining face.
  • Fig. 12 is a flow chart of an intelligent control method for a fully mechanized mining face provided by an embodiment of the present disclosure.
  • the intelligent control method for fully mechanized mining face includes but not limited to the following steps:
  • S1 Acquire the video image within the preset range in real time, and send the video image to the AI chip module.
  • the AI chip module processes the video image in real time, and according to the pre-trained deep learning model, recognizes the video image to obtain the recognition result, and sends the recognition result to the intelligent control device.
  • the intelligent control device controls the bracket to perform corresponding actions according to the recognition result sent by the AI chip module.
  • the method further includes: the hand-held terminal device interacts with the intelligent control device through a wireless communication device; the hand-held terminal device modifies the system software parameters of the intelligent control device by reading the data in the intelligent control device in real time , to control the bracket to perform corresponding actions.
  • the bracket control method provided by the embodiments of the present disclosure obtains video images within a preset range in real time, and sends the video images to the AI chip module; the AI chip module processes the video images in real time, and according to the pre-trained deep learning model, The video image is recognized to obtain the recognition result, and the recognition result is sent to the intelligent control device; the intelligent control device controls the bracket to perform corresponding actions according to the recognition result sent by the AI chip module. Therefore, the intelligent control method of the working face provided by the embodiment of the present disclosure can adjust the working state of the hydraulic support equipment on the spot and automatically in combination with the actual working conditions of the working face, which solves the problems of real-time control and visibility from all angles. It also reduces the workload of the operator to observe the video image, with high safety and high efficiency.
  • description with reference to the terms “one embodiment,” “some embodiments,” “example,” “exemplary embodiment,” etc. means that a specific feature, structure, material, described in connection with the embodiment or example Or features are included in at least one embodiment or example of the present disclosure.
  • the schematic representations of the above terms are not necessarily directed to the same embodiment or example.
  • the described specific features, structures, materials or characteristics may be combined in any suitable manner in any one or more embodiments or examples.
  • those skilled in the art can combine and combine different embodiments or examples and features of different embodiments or examples described in this specification without conflicting with each other.
  • first and second are used for descriptive purposes only, and cannot be interpreted as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features.
  • the features defined as “first” and “second” may explicitly or implicitly include at least one of these features.
  • “plurality” means at least two, such as two, three, etc., unless otherwise specifically defined.
  • a "computer-readable medium” may be any device that can contain, store, communicate, propagate or transmit a program for use in or in conjunction with an instruction execution system, device or device.
  • computer-readable media include the following: electrical connection with one or more wires (electronic device), portable computer disk case (magnetic device), random access memory (RAM), Read Only Memory (ROM), Erasable and Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM).
  • the computer-readable medium may even be paper or other suitable medium on which the program can be printed, as it may be possible, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or other suitable processing if necessary.
  • the program is processed electronically and stored in computer memory.
  • various parts of the present disclosure may be implemented in hardware, software, firmware or a combination thereof.
  • various steps or methods may be implemented by software or firmware stored in memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware as in another embodiment, it can be implemented by any one or a combination of the following techniques known in the art: a discrete Logic circuits, ASICs with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing module, each unit may exist separately physically, or two or more units may be integrated into one module.
  • the above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules. If the integrated modules are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium.
  • the storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, and the like.

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Abstract

本公开提出一种综采工作面智能控制系统和方法，系统包括：至少一个支架，设置在支架上的智能控制装置、集成在智能控制装置中的第一人工智能AI芯片模块、与第一人工智能AI芯片模块相连的第一图像采集装置；第一图像采集装置实时获取第一预设范围内的第一视频图像发送至第一AI芯片模块；第一AI芯片模块实时根据预先训练的深度学习模型，对第一视频图像进行识别发送第一识别结果至智能控制装置；智能控制装置根据第一识别结果，控制支架执行相应动作。由此，能够结合工作面的实际工况，就地并且自动对液压支架设备的工作状态进行相应调整，解决了控制的实时性、各角度看得全等问题，也减轻操作员观察视频图像的工作量，安全性高且效率高。

Description

综采工作面智能控制系统、方法
相关申请的交叉引用
本公开基于申请号为202111550115.4、申请日为2021年12月17日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本公开作为参考。
技术领域
本公开涉及煤矿生产智能化控制技术领域，尤其涉及一种综采工作面智能控制系统和方法。
背景技术
目前，煤矿综合机械化采煤工作面中(简称：综采工作面)，通过控制采煤机割煤、液压支架支护、刮板运输机运煤等功能，实现煤炭开采生产。
相关技术中，液压支架上设置控制器，控制器能够接收遥控器的信号，进而人员可以通过遥控器发出控制信号，以使控制器控制支架进行工作状态调整。但是在复杂地质条件下建设智能化工作面影响因素较多，尤其是深部矿井受高地压、高温和高矿井水腐蚀环境及工作面倾斜角等多重因素影响，造成工作面推进困难，工作面需要多名作业人员，现有系统和方法适应性不高、安全性低。
当前可视化远程干预采煤方法，需要工作人员在顺槽监控中心或地面通过视频监控的方法，观察工作面设备的实际运行工况，进而使用控制台发出相应的控制信号，实现工作面异常情况的处理。该方法存在视频看不全、通讯延时大、依赖人工观察、可靠性不高等问题，也存在很大的局限性。
随着人工智能、工业互联网、大数据、5G、边缘计算等新兴技术的发展，应用新技术构建低延时、大容量、高可靠的控制系统，可以进一步提升智能化水平，实现安全、绿色、高效开采。
发明内容
本公开旨在至少在一定程度上解决相关技术中的技术问题之一。
为此，本公开提出一种工作面智能控制系统、方法和通信，在结合工作面的实际工况的基础上，自动对液压支架、采煤机等设备的工作状态进行相应调整，安全性高且效率高。
第一方面，提出一种综采工作面智能控制系统，所述系统，包括：至少一个支架、设置在所述支架上的至少一个智能控制装置、集成在所述智能控制装置中的第一人工智能AI芯片装置、与所述第一AI芯片装置相连的第一图像采集装置。
所述第一图像采集装置，用于实时获取第一预设范围内的第一视频图像，并 将所述第一视频图像发送至所述第一AI芯片模块；所述第一AI芯片模块，用于实时对所述第一视频图像进行处理，根据预先训练的深度学习模型，对所述第一视频图像进行识别获取第一识别结果，并将所述第一识别结果发送至所述智能控制装置；所述智能控制装置，用于根据所述第一AI芯片模块发送的所述第一识别结果，控制所述支架执行相应动作。
所述系统，还包括：与所述智能控制装置相连的智能无线网关装置、集成在所述智能无线网关中的第二AI芯片装置、与所述第二AI芯片装置相连的第二图像采集装置。
所述第二图像采集装置，用于实时获取第二预设范围内的第二视频图像，并将所述第二视频图像发送至所述第二AI芯片模块；所述第二AI芯片模块，用于实时对所述第二视频图像进行处理，根据预先训练的深度学习模型，对所述第二视频图像进行识别获取第二识别结果，并将所述第二识别结果发送至所述智能控制装置；所述智能控制装置，用于根据所述智能无线网关装置发送的所述第二识别结果，控制所述支架执行相应动作。
所述系统，还包括：集成在所述智能无线网关中的无线通信装置、手持终端装置；所述手持终端装置通过所述无线通信装置与所述智能控制装置交互连接，和/或所述手持终端装置与所述智能无线网关装置相连接。
所述手持终端装置，用于通过实时读取所述智能控制装置中的数据，以及对所述智能控制装置的系统软件参数进行修改，以调整所述支架执行相应动作。
其中，所述无线通信装置，包括：以下至少一者：WIFI通信单元；4G通信单元；5G通信单元。
所述系统，还包括：多个所述智能控制装置中相邻的两个所述智能控制装置通过有线方式相连接；和/或，多个所述智能控制装置中任两个所述智能控制装置通过所述智能无线网关装置的所述无线通讯装置交互连接。
所述系统，还包括：拾音装置；所述拾音装置与所述智能控制装置相连。
所述拾音装置，用于获取环境声纹信息，发送所述环境声纹信息至所述第二AI芯片模块；所述第二AI芯片模块，还用于根据所述环境声纹信息，识别工作面环境特征，并将所述工作面环境特征发送至所述智能控制装置；所述智能控制装置，用于接收所述工作面环境特征，并根据所述工作面环境特征控制所述支架执行相应动作。
所述系统，还包括：集成在所述智能无线网关装置中的UWB通信单元。
所述UWB通信单元，用于与人员携带的UWB定位标签进行交互，以对人员进行实时定位，并将人员定位信息发送至所述智能无线网关装置，进而发送至所述的智能控制装置；所述智能控制装置，还用于接收所述人员定位信息，并根据所述人员定位信息控制所述支架执行相应动作。
所述系统，还包括：至少一个无线传感检测装置、集成在所述智能无线网关 装置中的无线传感器通信单元；所述无线传感器检测装置通过所述无线传感器通信单元与所述智能无线网关装置交互连接。
所述无线传感器检测装置，用于检测特定特征，获取所述特定特征的检测结果并将所述检测结果发送至所述智能无线网关装置，进而发送至所述的智能控制装置。所述智能控制装置，还用于接收所述检测结果，并根据所述检测结果控制所述支架执行相应动作。
在一些实施例中，所述智能无线网关装置，可以每个液压支架安装1个，也可以多个液压支架共享安装1个，通过外接的视频装置扩展视频覆盖范围，将视频图像发送给AI芯片模块，对工作面环境进行感知。
所述系统，还包括：与所述智能控制装置相连的扩音装置；扩音装置，用于接收所述智能控制装置发送的声音信号，将所述声音信号转化为语音信息进行广播发送。
所述系统，还包括：与所述智能控制装置相连的示警装置；所述示警装置与所述智能控制装置配合进行闭锁显示，以提醒人员注意安全。
所述系统，还包括：分别与所述智能控制装置相连的压力传感器装置和行程传感器装置。
本公开第二方面，提出一种支架控制方法，所述方法，包括：实时获取预设范围内的视频图像，并将所述视频图像发送至AI芯片模块；所述AI芯片模块实时对所述视频图像进行处理，根据预先训练的深度学习模型，对所述视频图像进行识别获取识别结果，并将所述识别结果发送至所述智能控制装置；所述智能控制装置根据所述AI芯片模块发送的所述识别结果，控制所述支架执行相应动作。
在一些实施例中，所述方法，还包括：手持终端装置通过无线通信单元与所述智能控制装置交互连接；所述手持终端装置通过实时读取所述智能控制装置中的数据，对所述智能控制装置的系统软件参数进行修改，以控制所述支架执行相应动作。
本公开实施例所提供的技术方案，可以包含如下的有益效果：
通过每个液压支架的智能无线网关装置，其集成的视频采集模块获取视频图像，发送至其所集成的AI芯片模块，实时对视频图像进行处理，根据预先训练的深度学习模型，对视频图像进行识别，并获取识别结果，将识别结果发送至相连的智能控制装置，智能控制装置则可以根据识别结果，控制支架执行相应动作，以对支架进行自动调整。由此，本公开实施例提供的工作面智能控制系统，能够结合工作面的实际工况，就地并且自动对液压支架设备的工作状态进行相应调整，解决了控制的实时性、各角度看得全等问题，也减轻操作员观察视频图像的工作量，安全性高且效率高。
附图说明
为了更清楚地说明本申请实施例或背景技术中的技术方案，下面将对本申请实施例或背景技术中所需要使用的附图进行说明。
图1为本公开实施例提供的一种综采工作面智能控制系统的结构图；
图2为本公开实施例提供的一种综采工作面智能控制系统中的智能控制装置的结构图；
图3为本公开实施例提供的另一种综采工作面智能控制系统的结构图；
图4为本公开实施例提供的又一种综采工作面智能控制系统的结构图；
图5为本公开实施例提供的又一种综采工作面智能控制系统的结构图；
图6为本公开实施例提供的一种综采工作面智能控制系统中无线通信装置的结构图；
图7为本公开实施例提供的又一种综采工作面智能控制系统的结构图；
图8为本公开实施例提供的又一种综采工作面智能控制系统的结构图；
图9为本公开实施例提供的一种综采工作面智能控制系统中智能无线网关装置的结构图；
图10为本公开实施例提供的另一种综采工作面智能控制系统中智能无线网关装置的结构图；
图11为本公开实施例提供的一种综采工作面智能控制系统中智能控制装置的结构图；
图12为本公开实施例提供的一种综采工作面智能控制方法的流程图。
具体实施方式
下面详细描述本公开的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本公开，而不能理解为对本公开的限制。
下面参考附图描述本公开实施例的综采工作面智能控制系统、方法。
图1为本公开实施例所提供的一种综采工作面智能控制系统的结构图。
如图1所示，本公开实施例提供的工作面智能控制系统，包括：至少一个支架1，设置在支架上的智能控制装置2。
需要说明的是，图1中支架1的结构仅作为示意，并不作为对本公开的限制，本公开实施例中，支架1还可以为其他结构的支架1。智能控制装置2的设置位置也仅作为示意，并不作为对本公开的限制，本公开实施例中，智能控制装置2还可以设置在支架1上的其他任何位置，或集成在支架1的结构中，或设置于与支架1固定连接的支架1结构之外的其他装置中，本公开对此不作具体限制。
如图2所示，本公开实施例中，该系统，还包括：集成在智能控制装置2 中的第一人工智能AI芯片模块21、与第一人工智能AI芯片模块21相连的第一图像采集装置22。
第一图像采集装置22，用于实时获取第一预设范围内的第一视频图像，并将第一视频图像发送至第一AI芯片模块21。第一AI芯片模块21，用于实时对第一视频图像进行处理，根据预先训练的深度学习模型，对第一视频图像进行识别获取第一识别结果，并将第一识别结果发送至智能控制装置2。智能控制装置2，用于根据第一AI芯片模块21发送的第一识别结果，控制支架1执行相应动作。
其中，第一图像采集装置22可以为摄像头、单目摄像头或者其他可以采集图像的设备，本公开对此不作具体限制。单目摄像头主要是RGB摄像头，配合单目算法可快速完成采集，将高质量的图像输送给后端进行识别比对。
本公开实施例中，第一图像采集装置22设置在支架特定位置，以能够获取第一预设范围内的图像，例如：第一图像采集装置22可以设置在支架立柱的位置，或者设置在支架底座或者其他任意位置，以使第一图像采集装置22能够获取煤壁、护帮板、运输机溜槽或者周边环境等特定范围内的图像。
可以理解的是，第一AI芯片模块21，例如：可以为人工智能芯片，或者集成人工智能处理程序的设备。本公开实施例中，第一AI芯片模块21中预先设置有预先训练好的深度学习模型，能够对图像进行识别，针对不同的训练样本，可以识别不同的图像。
示例性实施例中，本公开实施例中预先选择煤壁图像作为训练样本，选取不同情形的煤壁异常图像作为训练样本，对深度学习模型进行训练得到训练好的深度学习模型，从而训练好的深度学习模型在后续第一图像采集装置22获取的实时图像进行识别时，可以识别出与样本煤壁图像相同或者类似的图像，以达到识别煤壁异常的目的。
示例性实施例中，本公开实施例中，第一AI芯片模块21获取的第一识别结果可以为识别出的异常类型，此时，智能控制装置2中预先设置有异常类型和控制支架执行相应动作的对应策略，由此，智能控制装置2在获取到第一AI芯片模块21发送的第一识别结果之后，可以根据该预先设置的对应策略，确定需要控制支架1执行的相应动作，进而控制支架1执行该动作。
另一示例性实施例中，本公开实施例中，第一AI芯片模块21获取的第一识别结果可以为需要控制支架执行的相应动作，此时，第一AI芯片模块21中预先设置有异常类型和控制支架执行相应动作的对应策略，第一AI芯片模块21获取到视频图像之后，识别视频图像的异常类型，进而根据异常类型和控制支架执行相应动作的对应策略，生成需要控制支架1执行的相应动作的第一识别结果，由此，第一AI芯片模块21将需要控制支架1执行的相应动作的第一识别结果发送至智能控制装置2，智能控制装置2根据该第一识别结果，控制支架1执行相应 动作。
本公开实施例提供的工作面智能控制系统，第一图像采集装置22实时获取第一预设范围内的第一视频图像，并将第一视频图像发送至第一AI芯片模块21，第一AI芯片模块21实时对第一视频图像进行处理，根据预先训练的深度学习模型，对第一视频图像进行识别，并获取第一识别结果，将第一识别结果发送至智能控制装置2，智能控制装置2则可以根据第一识别结果，控制支架1执行相应动作，以对支架1进行自动调整。由此，本公开实施例提供的综采工作面智能控制系统，能够结合综采工作面的实际工况，自适应对支架1的工作状态进行相应调整，安全性高且效率高。
如图3所示，该系统，还包括：与智能控制装置2相连的智能无线网关装置3、集成在智能无线网关装置3中的第二AI芯片模块31、与第二AI芯片模块31相连的第二图像采集装置32。
第二图像采集装置32，用于实时获取第二预设范围内的第二视频图像，并将第二视频图像发送至第二AI芯片模块31；第二AI芯片模块31，用于实时对第二视频图像进行处理，根据预先训练的深度学习模型，对第二视频图像进行识别获取第二识别结果，并将第二识别结果分别发送至智能无线网关装置3。智能无线网关装置3，用于接收第二识别结果，并将第二识别结果发送至智能控制装置2。智能控制装置2，用于根据智能无线网关装置3发送的第二识别结果，控制支架1执行相应动作。
其中，第二图像采集装置32可以为摄像头、单目摄像头或者其他可以采集图像的设备，本公开对此不作具体限制。单目摄像头主要是RGB摄像头，配合单目算法可快速完成采集，将高质量的图像输送给后端进行识别比对。
本公开实施例中，第二图像采集装置32设置在支架特定位置，以能够获取第二预设范围内的图像，例如：第二图像采集装置32可以设置在支架顶梁下方的位置，或者可以设置在矿井顶部或者其他任意位置，以使第二图像采集装置32能够获取煤壁、护帮板、运输机溜槽或者周边环境等特定范围内的图像。
可以理解的是，第二AI芯片模块31，例如：可以为人工智能芯片，或者集成人工智能处理程序的设备。本公开实施例中，第二AI芯片模块31中预先设置有预先训练好的深度学习模型，能够对图像进行识别，针对不同的训练样本，可以识别不同的图像。
示例性实施例中，本公开实施例中预先选择煤壁图像作为训练样本，选取不同情形的煤壁异常图像作为训练样本，对深度学习模型进行训练得到训练好的深度学习模型，从而训练好的深度学习模型在后续第二图像采集装置32获取的实时图像进行识别时，可以识别出与样本煤壁图像相同或者类似的图像，以达到识别煤壁异常的目的。
示例性实施例中，本公开实施例中，第二AI芯片模块31获取的第二识别结 果可以为识别出的异常类型，此时，智能控制装置2中预先设置有异常类型和控制支架执行相应动作的对应策略，由此，智能控制装置2在获取到智能无线网关装置3发送的从第二AI芯片模块31处获取的第二识别结果之后，可以根据该预先设置的对应策略，确定需要控制支架1执行的相应动作，进而控制支架1执行该动作。
另一示例性实施例中，本公开实施例中，第二AI芯片模块31获取的第二识别结果可以为需要控制支架执行的相应动作，此时，第二AI芯片模块31中预先设置有异常类型和控制支架执行相应动作的对应策略，第二AI芯片模块31获取到视频图像之后，识别视频图像的异常类型，进而根据异常类型和控制支架执行相应动作的对应策略，生成需要控制支架1执行的相应动作的第二识别结果，由此，第二AI芯片模块31将需要控制支架1执行的相应动作的第二识别结果发送至智能无线网关装置3，智能无线网关装置3将第二识别结果发送至智能控制装置2，智能控制装置2根据该第二识别结果，控制支架1执行相应动作。
本公开实施例提供的工作面智能控制系统，第二图像采集装置32实时获取第二预设范围内的第二视频图像，并将第二视频图像发送至第二AI芯片模块31，第二AI芯片模块31实时对第二视频图像进行处理，根据预先训练的深度学习模型，对第二视频图像进行识别，并获取第二识别结果，将第二识别结果发送至智能无线网关装置3，智能无线网关装置3将第二识别结果发送至智能控制装置2，智能控制装置2则可以根据第二识别结果，控制支架1执行相应动作，以对支架1进行自动调整。由此，本公开实施例提供的综采工作面智能控制系统，能够结合综采工作面的实际工况，自适应对支架1的工作状态进行相应调整，安全性高且效率高。
如图4所示，该系统，还包括：手持终端装置4。
需要说明的是，图4中所示出的手持终端装置4仅作为示意，不作为对本公开的限制。手持终端装置4可以为：手机终端、平板电脑或者开发的具有一定功能的手持终端装置等。手持终端装置4还可以为计算机、掌上电脑等，本公开对此不作具体限制。
如图5所示，该系统，还包括：集成在智能无线网关装置3中的无线通信装置33。
手持终端装置4通过集成在智能无线网关装置3中的无线通信装置33与智能控制装置2交互连接。
手持终端装置4，用于通过实时读取智能控制装置2中的数据，以及对智能控制装置2的系统软件参数进行修改，以控制支架1执行相应动作。
本公开实施例中，手持终端装置4以通过集成在智能无线网关装置3中的无线通信装置33与智能控制模块11交互连接，手持终端装置4可以实时读取智能控制装置2的数据，例如：智能控制装置2中的系统软件参数、支架控制参数等 等。
在实际使用过程中，手持终端装置4能够通过集成在智能无线网关装置3中的无线通信装置33与智能控制模块11交互连接，工程技术人员可以通过使用手持终端装置4远程监控，或者调节智能控制装置2中的系统软件参数，以控制支架1执行相应的动作，调整支架1的姿态，以使工程技术人员可以远程操控支架，安全性高且效率高。
如图6所示，无线通信装置33，包括以下至少一者：WIFI通信单元331；4G通信单元332；5G通信单元333。
本公开实施例中，无线通信单元33能够接收手持终端装置4发送的无线信号，并向手持终端装置4发送无线信号，无线通信单元33可以为WIFI通信单元331、4G通信单元332和5G通信单元333中的至少一者。
示例性实施例中，无线通信单元33可以包括WIFI通信单元331，或者4G通信单元332，或者5G通信单元333，或者WIFI通信单元331和4G通信单元332，或者WIFI通信单元331和5G通信单元333，或者4G通信单元332和5G通信单元333，或者WIFI通信单元331、4G通信单元332和5G通信单元333。
其中，在无线通信单元33包括WIFI通信单元331和4G通信单元332，或者WIFI通信单元331和5G通信单元333，或者4G通信单元332和5G通信单元333，或者WIFI通信单元331、4G通信单元332和5G通信单元333的情况下，WIFI通信单元331、4G通信单元332和5G通信单元333三者之间互为冗余，也即，在其中之一失效或者连接失败的情况下，可以通过另一个进行连接。
示例性实施例中，在无线通信单元33包括WIFI通信单元331和4G通信单元332，WIFI通信单元331和4G通信单元332互为冗余，在手持终端装置4通过无线通信单元33与智能控制装置2交互时，若使用WIFI通信单元331连接失败后，可以通过4G通信单元332与智能控制装置2交互连接。
本公开实施例中，无线通信单元33包括WIFI通信单元331、4G通信单元332和5G通信单元333中的至少一者，WIFI通信单元331、4G通信单元332和5G通信单元333互为冗余，能够为手持终端装置4和智能控制装置2交互连接提供多种连接方式，以避免仅有一种交互连接方式，在该一种交互连接方式失败后，手持终端装置4无法与智能控制装置2交互连接，从而能够实现手持终端装置4与智能控制装置2能够通过多种方式交互连接，避免交互失败。
如图7所示，该系统，包括：多个智能控制装置2中相邻的两个智能控制装置2通过有线方式相连接；和/或，多个智能控制装置2中任两个智能控制装置2通过智能无线网关装置3的无线通讯装置33交互连接。
本公开实施例中，在整个综采工作面中，多个支架1设置的多个智能控制装置2任意相邻的两个智能控制装置2之间通过有线的方式相连，可实现支架集群控制。
并且，多个智能控制装置2中任两个智能控制装置2通过智能无线网关装置3的无线通讯装置33交互连接，可实现多个智能控制装置2中任两个智能控制装置2之间通过无线的方式交互相连，同样可实现支架集群控制。
本公开实施例中，两个智能控制装置2之间信息传递可通过有线的方式传递或者无线的方式传递，从而能够提高系统信息传输的稳定性和效率。
需要说明的是，在两个智能控制装置2之间信息传递只能通过有线的方式，或者无线的方式，不能同时使用有线方式和无线方式，两个智能控制装置2之间信息传递有线方式传递和无线方式传递存在冗余的关系，避免出现信号传递失败或者混乱。
如图8所示，该系统，还包括：与智能控制装置2相连的拾音装置23。
拾音装置23，用于获取环境声纹信息，发送环境声纹信息至第一AI芯片模块21；第一AI芯片模块21，还用于根据环境声纹信息，识别工作面环境特征，并将工作面环境特征发送至智能控制装置2；智能控制装置2，用于接收工作面环境特征，并根据工作面环境特征控制支架1执行相应动作。
其中，拾音装置23可以获取环境中的声纹信息，例如：拾音装置23可以为拾音器；或者其他能够采集环境中声纹信息的装置或设备，本领域技术人员可以根据需要选择满足上述要求的任意装置，本公开对此不作具体限制。
本公开实施例中，第一AI芯片模块21接收拾音装置23获取的环境声纹信息，可以理解的是，环境声纹信息可能包括人员讲话的声纹信息，也可能包括煤岩破碎的声音，还包括其他声音，本公开实施例中第一AI芯片模块21在获取到环境声纹信息之后，对环境声纹信息进行识别，能够识别出综采工作面环境特征和/或人员语音信息等。
本公开实施例中，第一AI芯片模块21可以识别与综采工作面作业相关的环境声纹信息，获得工作面环境特征，将工作面环境特征发送至智能控制装置2，进而，智能控制装置2根据工作面环境特征与预设的工作面环境特征与支架1执行相应动作的对应策略，控制支架1执行相应动作，从而能够综合多方面获取的信息，结合工作面的实际工况，就地并且自动对支架1等设备的工作状态进行相应调整，解决了控制的实时性、各角度看得全等问题，也减轻工程技术人员观察视频图像的工作量，安全性高且效率高。
如图9所示，该系统，还包括：集成在智能无线网关装置3中的UWB通信单元34。
其中，(ultra wide band，超带宽)UWB通信单元34，用于与人员携带的UWB定位标签进行交互，以对人员进行实时定位，并将人员定位信息发送至智能无线网关装置3；智能无线网关装置3，还用于将人员定位信息发送至智能控制装置2。智能控制装置2，还用于接收人员定位信息，并根据人员信息控制支架1执行相应动作。
本公开实施例中，人员在进入井下作业时，携带有UWB定位标签，在人员作业的过程中，通过UWB通信单元34与人员携带的UWB定位标签进行交互，实现对人员的位置进行实时定位，并将人员定位信息传输至智能控制装置2，智能控制装置2根据人员定位信息控制支架1执行相应动作，以对人员安全提高保障。
如图10所示，该系统，还包括：至少一个无线传感器单元35、集成在智能无线网关装置3中的无线传感器接入模块36。
其中，无线传感器单元35设置在支架1的特定位置处，以对支架1的特定特征进行检测，并通过无线传感器接入模块36与智能无线网关装置3交互连接。
无线传感器单元35通过智能无线网关装置3中的无线传感器接入模块36与智能无线网关装置3交互连接；无线传感器单元35，用于检测特定特征，获取特定特征的检测结果并将检测结果发送至智能无线网关装置3；智能无线网关装置3，还用于接收检测结果，并将检测结果发送至智能控制装置2；智能控制装置2，还用于接收检测结果，并根据检测结果控制支架1执行相应动作。
本公开实施例中，至少一个无线传感器单元35，包括：例如测高传感器、压力传感器、倾角传感器、行程传感器中的一个或多个。可以理解的是，不同无线传感器单元35其检测不同的特征，设置的位置也不相同，可以放置在能够准确检测特定特征的特定位置，本领域技术人员可以根据需要进行设置。
示例性实施例中，至少一个无线传感器单元35包括：测高传感器；测高传感器设置在支架1顶梁下方，用于检测支架1顶梁的高度。
示例性实施例中，至少一个无线传感器单元35包括：压力传感器，压力传感器设置在支架1支撑杆的位置，以检测支架1承受的压力。
可以理解的是，上述无线传感器单元35的示例仅作为示意，还可以根据需要设置多种功能的传感器，以检测特定的特征。
本公开实施例中，至少一个无线传感器单元35将检测的结果，生成携带环境数据的信号，通过无线传感器接入模块36发送至智能无线网关装置3，智能无线网关装置3将检测结果发送至智能控制装置2，从而智能控制装置2可以获取到所测量的特定特征的检测结果的数据，进一步的根据检测结果控制支架1执行相应动作。
如图11所示，该系统，还包括：扩音装置24；扩音装置24与智能控制装置2相连。
扩音装置24，用于接收智能控制装置2发送的的声音信号，将声音信号转化为语音信息进行广播发送。
扩音装置24可以向外发出声音消息，例如：扩音装置24可以为：扩音器、喇叭等。
本公开实施例中的扩音装置24接收智能控制装置2发送的的声音信号，将 声音信号转化为语音信息进行广播发送；其中，声音信号，例如：工程技术人员交流的声音信号、临时广播的通知信号、公告消息信号、或者休息时间播放音乐信号或者新闻信号等，将上述声音信号转化为语音信息进行广播发送，从而可以获取相关的信息，进行人员交流。
请再次参见图11，该系统，还包括：示警装置25；示警装置25与智能控制装置2相连。
示警装置25，用于接收智能控制装置2发送的示警信号，并根据示警信号进行示警。
本公开实施例中，示警装置25与智能控制装置2配合进行闭锁显示，以提醒人员注意安全。
其中，示警装置25，例如：双色灯、指示灯等。
可以理解的是，本公开实施例中智能控制装置2可以通过示警装置25以发出示警信息，例如：在示警装置25为双色灯时，智能控制装置2控制双色灯进行闭锁显示，以显示不同的颜色，告知井下人员不同信息，以提醒人员注意安全。示警装置25可以设置在支架1顶梁的下方，以使人员能够直观的看到示警装置25。
请再次参见图10，该系统，还包括：分别与智能控制装置2相连的压力传感器装置26和行程传感器装置27。
其中，压力传感器装置26和行程传感器装置27与智能控制装置2有线方式连接，用于检测不同的特征，并将不同特征的检测结果发送至智能控制装置2。
示例性的，压力传感器装置26可以设置在支架1支撑杆的位置，以检测支架1承受的压力；行程传感器装置27设置在推移杆的位置，以检测推移杆的行程。
需要说明的是，上述压力传感器装置26和行程传感器装置27的设置位置及其检测的特征仅作为示意，其还可以设置在其他位置，以测量其他特征，本公开实施例对此不作具体限制。
为了实现上述实施例，本公开还提出一种的综采工作面智能控制方法。
图12为本公开实施例提供的一种综采工作面智能控制方法的流程图。
具体的，如图12所示，本公开实施例提供的综采工作面智能控制方法，包括但不限于如下步骤：
S1：实时获取预设范围内的视频图像，并将视频图像发送至AI芯片模块。
S2：AI芯片模块实时对视频图像进行处理，根据预先训练的深度学习模型，对视频图像进行识别获取识别结果，并将识别结果发送至智能控制装置。
S3：智能控制装置根据AI芯片模块发送的识别结果，控制支架执行相应动作。
在一些实施例中，该方法，还包括：手持终端装置通过无线通信装置与智能 控制装置交互连接；手持终端装置通过实时读取智能控制装置中的数据，对智能控制装置的系统软件参数进行修改，以控制支架执行相应动作。
关于上述实施例中的支架控制方法，其中各个步骤执行操作的具体方式已经在有关该工作面智能控制系统的实施例中进行了详细描述，此处不再赘述。
本公开实施例提供的支架控制方法，通过实时获取预设范围内的视频图像，并将视频图像发送至AI芯片模块；AI芯片模块实时对视频图像进行处理，根据预先训练的深度学习模型，对视频图像进行识别获取识别结果，并将识别结果发送至智能控制装置；智能控制装置根据AI芯片模块发送的识别结果，控制支架执行相应动作。由此，本公开实施例提供的工作面智能控制方法，能够结合工作面的实际工况，就地并且自动对液压支架设备的工作状态进行相应调整，解决了控制的实时性、各角度看得全等问题，也减轻操作员观察视频图像的工作量，安全性高且效率高。
应该理解，可以使用上面所示的各种形式的流程，重新排序、增加或删除步骤。例如，本发申请中记载的各步骤可以并行地执行也可以顺序地执行也可以不同的次序执行，只要能够实现本公开公开的技术方案所期望的结果，本文在此不进行限制。
上述具体实施方式，并不构成对本公开保护范围的限制。本领域技术人员应该明白的是，根据设计要求和其他因素，可以进行各种修改、组合、子组合和替代。任何在本公开的精神和原则之内所作的修改、等同替换和改进等，均应包含在本公开保护范围之内。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“示例性实施例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本公开的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本公开的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现定制逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本公开的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本公开的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本公开的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。如，如果用硬件来实现和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本公开各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (13)

  1. 一种综采工作面智能控制系统，其特征在于，所述系统，包括：至少一个支架，设置在所述支架上的智能控制装置、集成在所述智能控制装置中的第一人工智能AI芯片模块、与所述第一人工智能AI芯片模块相连的第一图像采集装置；
    所述第一图像采集装置，用于实时获取第一预设范围内的第一视频图像，并将所述第一视频图像发送至所述第一AI芯片模块；
    所述第一AI芯片模块，用于实时对所述第一视频图像进行处理，根据预先训练的深度学习模型，对所述第一视频图像进行识别获取第一识别结果，并将所述第一识别结果发送至所述智能控制装置；
    所述智能控制装置，用于根据所述第一AI芯片模块发送的所述第一识别结果，控制所述支架执行相应动作。
  2. 根据权利要求1所述的系统，其特征在于，所述系统，还包括：与所述智能控制装置相连的智能无线网关装置、集成在所述智能无线网关装置中的第二AI芯片模块、与所述第二AI芯片模块相连的第二图像采集装置；
    所述第二图像采集装置，用于实时获取第二预设范围内的第二视频图像，并将所述第二视频图像发送至所述第二AI芯片模块；
    所述第二AI芯片模块，用于实时对所述第二视频图像进行处理，根据预先训练的深度学习模型，对所述第二视频图像进行识别获取第二识别结果，并将所述第二识别结果发送至所述智能控制装置；
    所述智能控制装置，用于根据所述智能无线网关装置发送的所述第二识别结果，控制所述支架执行相应动作。
  3. 根据权利要求2所述的系统，其特征在于，所述系统，还包括：手持终端装置、集成在所述智能无线网关装置中的无线通信装置；
    所述手持终端装置通过集成在所述智能无线网关装置中的所述无线通信装置与所述智能控制装置交互连接，和/或所述手持终端装置与所述智能无线网关装置相连接；
    所述手持终端装置，用于通过实时读取所述智能控制装置中的数据，对所述智能控制装置的系统软件参数进行修改，以调整所述支架执行相应动作。
  4. 根据权利要求3所述的系统，其特征在于，所述无线通信装置，包括以下至少一者：
    WIFI通信单元；
    4G通信单元；
    5G通信单元。
  5. 根据权利要求3或4所述的系统，其特征在于，所述系统，包括：
    多个所述智能控制装置中相邻的两个所述智能控制装置通过有线方式相连接；
    和/或，
    多个所述智能控制装置中任两个所述智能控制装置通过所述智能无线网关装置的所述无线通讯装置交互连接。
  6. 根据权利要求3所述的系统，其特征在于，所述系统，还包括：拾音装置；所述拾音装置与所述智能控制装置相连；
    所述拾音装置，用于获取环境声纹信息，发送所述环境声纹信息至所述第一AI芯片模块；
    所述第一AI芯片模块，还用于根据所述环境声纹信息，识别工作面环境特征，并将所述工作面环境特征发送至所述智能控制装置；
    所述智能控制装置，用于接收所述工作面环境特征，并根据所述工作面环境特征控制所述支架执行相应动作。
  7. 根据权利要求2所述的系统，其特征在于，所述系统，还包括：集成在所述智能无线网关装置中的UWB通信单元；
    所述UWB通信单元，用于与人员携带的UWB定位标签进行交互，以对人员进行实时定位，并将人员定位信息发送至所述智能无线网关装置，进而发送至所述的智能控制装置；
    所述智能控制装置，还用于接收所述人员定位信息，并根据所述人员定位信息控制所述支架执行相应动作。
  8. 根据权利要求2所述的系统，其特征在于，所述系统，还包括：至少一个无线传感器单元、集成在所述智能无线网关装置中的无线传感器接入模块；
    所述无线传感器单元通过所述无线传感器接入模块与所述智能无线网关装置交互连接；
    所述无线传感器单元，用于检测特定特征，获取所述特定特征的检测结果并将所述检测结果发送至所述智能无线网关装置，进而发送至所述的智能控制装置；
    所述智能控制装置，还用于接收所述检测结果，并根据所述检测结果控制所述支架执行相应动作。
  9. 根据权利要求1所述的系统，其特征在于，所述系统，还包括：与所述智能控制装置相连的扩音装置；
    扩音装置，用于接收所述智能控制装置发送的声音信号，将所述声音信号转化为语音信息进行广播发送。
  10. 根据权利要求1所述的系统，其特征在于，所述系统，还包括：与所述智能控制装置相连的示警装置；所述示警装置与所述智能控制装置配合进行闭锁显示，以提醒人员注意安全。
  11. 根据权利要求1所述的系统，其特征在于，所述系统，还包括：分别与所述智能控制装置相连的压力传感器装置和行程传感器装置。
  12. 一种综采工作面智能控制方法，其特征在于，所述方法，包括：
    实时获取预设范围内的视频图像，并将所述视频图像发送至AI芯片模块；
    所述AI芯片模块实时对所述视频图像进行处理，根据预先训练的深度学习模型，对所述视频图像进行识别获取识别结果，并将所述识别结果发送至所述智能控制装置；
    所述智能控制装置根据所述AI芯片模块发送的所述识别结果，控制支架执行相应动作。
  13. 根据权利要求12所述的方法，其特征在于，所述方法，还包括：
    手持终端装置通过无线通信单元与所述智能控制装置交互连接；
    所述手持终端装置通过实时读取所述智能控制装置中的数据，对所述智能控制装置的系统软件参数进行修改，以调整所述支架执行相应动作。
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CN112855241A (zh) * 2021-01-29 2021-05-28 辽宁瑞华实业集团高新科技有限公司 液压支架控制装置及方法

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