CN114422748A - Real-time control method and system for coal flow of working face based on video monitoring - Google Patents
Real-time control method and system for coal flow of working face based on video monitoring Download PDFInfo
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Abstract
The application provides a method and a system for controlling coal flow of a working face in real time based on video monitoring, wherein the method comprises the following steps: acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support; determining an instantaneous coal flow rate of the face scraper conveyor using the image information; inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor; and controlling the action of a hydraulic support in the working face, the speed of a coal mining machine and the speed of a scraper conveyor based on the instruction value so as to control the coal flow of the working face in real time. The technical scheme provided by the invention can dynamically monitor the coal flow information to further carry out cooperative control on the coal flow of the working face, thereby improving the accuracy of coal flow detection and ensuring safe and efficient operation of the working face.
Description
Technical Field
The application relates to the technical field of coal flow control, in particular to a method and a system for controlling coal flow of a working face in real time based on video monitoring.
Background
At present, in a coal mine comprehensive mechanized coal mining working face (a fully mechanized coal mining working face for short), coal mining production is realized by controlling the functions of a coal cutter, hydraulic support, scraper conveyor coal conveying and the like.
In the related technology, the coal flow monitor detects frequency signals generated by friction through band-pass filtering, and is widely applied to a coal feeder and used for measuring the flow of materials in a closed pipeline or a blanking hopper; or the parameters of the coal mine conveying belt are extracted in real time by using the dynamic coal flow monitoring and weighing device, and the coal quantity is accurately measured according to the weight of coal on the coal mine conveying belt and the speed of the coal mine conveying belt; or measuring the instantaneous coal quantity and the accumulated coal quantity of the coal used by the boiler by utilizing a coal quantity monitoring device of the scraper coal feeder. However, the speed of coal flow cannot be cooperatively controlled, and meanwhile, the influence factors of intelligent working faces constructed under complex geological conditions are more, especially, deep mines are influenced by multiple factors such as high ground pressure, high temperature, high mine water corrosion environment and working face inclination angle, so that the working faces are difficult to propel, multiple operators are needed for the working faces, and the existing system and method are low in adaptability and safety.
The current method for controlling the coal flow speed requires a worker to observe the actual operation condition of the working face equipment in a crossheading monitoring center or the ground through a video monitoring method, and then uses a control console to send out a corresponding control signal, so as to realize the processing of the abnormal condition of the working face. The method has the problems of incomplete video viewing, long communication delay, dependence on manual observation, low reliability and the like, and has great limitation.
Disclosure of Invention
The application provides a real-time control method and a real-time control system for coal flow of a working face based on video monitoring, which are used for at least solving the technical problems that the speed of coal flow cannot be cooperatively controlled and the detection precision of the coal flow is not high in the related technology.
An embodiment of a first aspect of the present application provides a method for controlling coal flow of a working face in real time based on video monitoring, including: firstly, acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support; inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face; secondly, collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face; inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor; finally, controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time; wherein, the coal flow information of scraper conveyor within the scope of predetermineeing in the working face includes: coal flow in a preset range, the existence of large coal blocks, time and the number of the corresponding hydraulic support in the preset range.
The embodiment of the second aspect of the present application provides a real-time control system for coal flow of a working face based on video monitoring, including: the intelligent wireless gateway is integrated with an artificial intelligent AI chip device; at least one rotatable camera is arranged in the intelligent wireless gateway and used for collecting images in a preset range of the scraper conveyer in a working face; the artificial intelligence AI chip device is used for receiving the image collected by the rotatable camera and identifying the coal flow information in the preset range of the scraper conveyor in the working face based on the collected image; and the upper computer is used for receiving the coal flow information in the identified preset range of the scraper conveyor in the working face, generating a control instruction based on the coal flow information, and controlling the action of a hydraulic support in the working face, the speed of a coal mining machine and the speed of the scraper conveyor so as to control the coal flow of the working face in real time.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
in summary, the present application provides a method and a system for real-time controlling coal flow of a working face based on video monitoring, including: acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support; inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face; collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face; inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor; and controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time. The technical scheme provided by the invention can dynamically monitor the coal flow information to further carry out cooperative control on the coal flow of the working face, thereby improving the accuracy of coal flow detection and ensuring safe and efficient operation of the working face.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a method for controlling coal flow of a working face in real time based on video monitoring according to an embodiment of the present application;
FIG. 2 is a block diagram of a real-time control system for coal flow of a working face based on video monitoring according to an embodiment of the present application;
fig. 3 is a block diagram of an intelligent wireless gateway provided according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
In the working face coal flow real-time control method and system based on video monitoring, image information in a preset range of a scraper conveyor in a working face is collected in real time through a camera arranged on a hydraulic support; inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face; collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face; inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor; and controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time. Therefore, the real-time control method and the real-time control system for the coal flow of the working face based on video monitoring can dynamically monitor the coal flow information to further perform cooperative control on the coal flow of the working face, improve the accuracy of coal flow detection and ensure safe and efficient operation of the working face.
The following describes a working face coal flow real-time control method and system based on video monitoring according to an embodiment of the present application with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for controlling coal flow of a working face in real time based on video monitoring according to an embodiment of the present application, where as shown in fig. 1, the method includes:
step 101: acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support;
step 102: inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face;
in an embodiment of the present disclosure, a training process of a coal flow identification model includes: and selecting images corresponding to the scraper conveyer in the working face at the historical moment and coal flow information corresponding to the images as training samples, and training the deep learning model to obtain a trained coal flow identification model.
Wherein, the coal flow information of scraper conveyor within the scope of predetermineeing in the working face includes: coal flow in a preset range, the existence of large coal blocks, time and the number of the corresponding hydraulic support in the preset range.
It should be noted that when the large coal blocks are identified to be present in the preset range of the scraper conveyor in the working face, the operation of the coal mining machine and the scraper conveyor is stopped, and manual processing is called.
After the identified information is reported to the upper computer, the display screen of the upper computer 3 displays that the large coal blocks are on the next few shelves, and a worker is prompted to process the large coal blocks.
Step 103: collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face;
in the disclosed embodiment, the instantaneous coal flow X at time t of the face scraper conveyor is determined as followst：
In the formula, xi,tAnd N is the total number of the hydraulic supports in the working face.
Step 104: inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor;
in the disclosed embodiment, before inputting the instantaneous coal flow of the face scraper conveyor into the pre-trained coal flow load model, the method comprises the following steps:
step 4-1: judging whether the coal flow state to which the instantaneous coal flow of the working face scraper conveyor belongs at the current moment is the same as the coal flow state to which the instantaneous coal flow of the working face scraper conveyor belongs at the last moment;
step 4-2, if the coal flow state of the instant coal flow at the current moment is different from the coal flow state of the instant coal flow at the last moment, entering step 3, otherwise, returning to step 1;
step 4-3: and inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of the hydraulic support in the working face, a speed control instruction value of the coal mining machine and a speed control instruction value of the scraper conveyor.
Wherein the coal flow state comprises: overload condition, full condition, excess condition, moderate condition, low condition, and low condition.
Specifically, when the coal flow rate of the scraper conveyor is greater than the rated transport capacity of the scraper conveyor, the coal flow rate is in an overload state.
When the coal flow of the scraper conveyor is less than or equal to the rated transportation capacity of the scraper conveyor and more than eighty percent of the rated transportation capacity of the scraper conveyor, the coal flow is in a full-load state.
When the coal flow of the scraper conveyor is less than or equal to eighty percent of the rated transportation capacity of the scraper conveyor and greater than sixty percent of the rated transportation capacity of the scraper conveyor, the coal flow is in an excessive state.
When the coal flow of the scraper conveyor is less than or equal to sixty percent of the rated transportation capacity of the scraper conveyor and is more than forty percent of the rated transportation capacity of the scraper conveyor, the coal flow is in a moderate state.
When the coal flow rate of the scraper conveyor is less than or equal to forty percent of the rated transportation capacity of the scraper conveyor and is greater than twenty percent of the rated transportation capacity of the scraper conveyor, the coal flow rate is in a small state.
When the coal flow of the scraper conveyor is less than or equal to twenty percent of the rated transport capacity of the scraper conveyor, the coal flow is in an extremely small state.
In an embodiment of the present disclosure, the training process of the coal flow load model includes: instantaneous coal flow at the historical moment of the scraper conveyor of the working face and a control instruction corresponding to the instantaneous coal flow are selected as training samples, and an empirical model of multiple linear regression is trained to obtain a trained coal flow load model.
Step 105: and controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time.
In the embodiment of the disclosure, the actions of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled according to the instruction value of the actions of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor, so that the coal flow of the working face is controlled in real time, the coal flow of the working face can be cooperatively controlled, the coal flow detection accuracy is improved, and the safe and efficient operation of the working face is ensured.
Firstly, acquiring images in a preset range of a scraper conveyor in a working face in real time by using a rotatable camera, inputting the acquired images into a pre-trained coal flow identification model, and identifying coal flow information; secondly, uploading the coal flow information to an upper computer, and determining the instantaneous coal flow of a scraper conveyor in a working face by the upper computer based on the coal flow information; and then judging whether the determined instantaneous coal flow is the same as the coal flow state to which the instantaneous coal flow belongs at the previous moment, if so, generating a control instruction based on the instantaneous coal flow, controlling the action of a hydraulic support in a working face, the speed of a coal mining machine and the speed of a scraper conveyor to further control the coal flow of the working face in real time, and if so, not controlling and continuing to identify the coal flow. The scheme that this embodiment provided can be handled the realization on the spot to the image of gathering and carry out real-time detection discernment to coal flow to can carry out cooperative control to the working face coal flow, improve the accuracy that the coal flow detected, guarantee the safe high-efficient operation of working face.
In summary, the present application provides a method and a system for real-time controlling coal flow of a working face based on video monitoring, including: acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support; inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face; collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face; inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor; and controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time. The technical scheme provided by the invention can dynamically monitor the coal flow information to further carry out cooperative control on the coal flow of the working face, thereby improving the accuracy of coal flow detection and ensuring safe and efficient operation of the working face.
Fig. 2 is a block diagram of a real-time control system for coal flow of a working surface based on video monitoring according to an embodiment of the present application, and as shown in fig. 2, the system may include: the hydraulic support comprises at least one hydraulic support 1, at least one intelligent wireless gateway 2 and at least one upper computer 3, wherein the intelligent wireless gateway 2 is arranged below a top beam of the hydraulic support, and an artificial intelligent AI chip device 4 is integrated in the intelligent wireless gateway 2.
It should be noted that fig. 2 shows a hydraulic support 1, at least one intelligent wireless gateway 2 disposed below a top beam of the hydraulic support, and at least one upper computer 3, and fig. 2 is only for illustration and is not intended to limit the embodiment of the present application.
As shown in fig. 3, in the embodiment of the present disclosure, the system further includes a rotatable camera 21 disposed in the intelligent wireless gateway 2, where the rotatable camera 21 is configured to acquire an image in a preset range of the scraper conveyor in the working plane in real time, and send the acquired image to the artificial intelligence AI chip device 4. The artificial intelligence AI chip device 4 is used for receiving the images collected by the rotatable camera 21, processing the images in real time, identifying the images according to a pre-trained coal flow identification model, identifying coal flow information in a preset range of the scraper conveyor in a working face, and sending the identified coal flow information to the upper computer 3. And the upper computer 3 is used for receiving the coal flow information in the preset range of the scraper conveyor in the identified working face, determining the instantaneous coal flow of the scraper conveyor in the working face based on the coal flow information, judging whether the determined instantaneous coal flow is the same as the coal flow state of the instantaneous coal flow at the last moment, if so, generating a control instruction based on the instantaneous coal flow, controlling the action of a hydraulic support in the working face, the speed of a coal mining machine and the speed of the scraper conveyor to further control the coal flow of the working face in real time, and if so, not controlling and continuing to identify the coal flow. The scheme that this embodiment provided uses artificial intelligence AI chip device 4 to carry out the on-the-spot processing to the image information that rotatable appearance 21 gathered of making a video recording, realizes the real-time detection discernment of coal flow to can carry out cooperative control to the working face coal flow, improve the accuracy that the coal flows and detect, guarantee the safe high-efficient operation of working face.
Wherein, the coal flow information of scraper conveyor within the scope of predetermineeing in the working face includes: coal flow in a preset range, the existence of large coal blocks, time and the number of the corresponding hydraulic support in the preset range.
In the embodiment of the present disclosure, the rotatable camera 21 may be a camera, a monocular camera, or other devices capable of collecting images, which is not specifically limited by the present disclosure. The monocular camera is mainly an RGB camera, can rapidly complete acquisition by matching with a monocular algorithm, and transmits high-quality images to the rear end for identification and comparison.
In the embodiment of the present disclosure, the rotatable camera 21 is disposed at a specific position of the hydraulic mount 1 to be able to acquire an image within a preset range.
It should be noted that, when the coal flow identification model identifies that large coal blocks appear in the preset range of the scraper conveyor in the working face, the identified information is reported to the upper computer, and manual processing is called.
Specifically, when the coal flow identification model identifies that the large coal blocks appear in the preset range of the scraper conveyor in the working face, the identified information is reported to the upper computer, and then the large coal blocks are displayed on the display screen of the upper computer 3 to prompt workers to process the large coal blocks.
In an embodiment of the present disclosure, the coal flow state includes: overload condition, full condition, excess condition, moderate condition, low condition, and low condition.
Specifically, when the coal flow rate of the scraper conveyor is greater than the rated transport capacity of the scraper conveyor, the coal flow rate is in an overload state.
When the coal flow of the scraper conveyor is less than or equal to the rated transportation capacity of the scraper conveyor and more than eighty percent of the rated transportation capacity of the scraper conveyor, the coal flow is in a full-load state.
When the coal flow of the scraper conveyor is less than or equal to eighty percent of the rated transportation capacity of the scraper conveyor and greater than sixty percent of the rated transportation capacity of the scraper conveyor, the coal flow is in an excessive state.
When the coal flow of the scraper conveyor is less than or equal to sixty percent of the rated transportation capacity of the scraper conveyor and is more than forty percent of the rated transportation capacity of the scraper conveyor, the coal flow is in a moderate state.
When the coal flow rate of the scraper conveyor is less than or equal to forty percent of the rated transportation capacity of the scraper conveyor and is greater than twenty percent of the rated transportation capacity of the scraper conveyor, the coal flow rate is in a small state.
When the coal flow of the scraper conveyor is less than or equal to twenty percent of the rated transport capacity of the scraper conveyor, the coal flow is in an extremely small state.
It is understood that the artificial intelligence AI chip device 4, for example: the device can be an artificial intelligence chip or a device integrating an artificial intelligence processing program. In the embodiment of the present disclosure, the artificial intelligence AI chip device 4 is preset with a pre-trained coal flow recognition model, so as to recognize images, and recognize different images according to different training samples.
In the embodiment of the disclosure, the upper computer is preset with a pre-trained coal flow load model, and can output control instruction values, and the control instruction values can be output according to different training samples.
In an exemplary embodiment, in the embodiment of the disclosure, an image corresponding to a scraper conveyor at a historical time in a working face and coal flow information corresponding to the image are pre-selected as training samples, and a deep learning model is trained to obtain a trained coal flow identification model. When the real-time image acquired by the rotatable camera 21 is identified subsequently, the image which is the same as or similar to the sample image can be identified, so that the purpose of identifying the coal flow information is achieved.
In an exemplary embodiment, in the embodiment of the disclosure, an instantaneous coal flow at a historical moment of a face scraper conveyor and a control instruction corresponding to the instantaneous coal flow are pre-selected as training samples, and an empirical model of multiple linear regression is trained to obtain a trained coal flow load model. When the instantaneous coal flow is input into the model by the subsequent upper computer 3, the control instruction value is correspondingly output so as to achieve the purpose of controlling the coal flow of the working face in real time.
In the exemplary embodiment, the rotatable camera 21 is used to capture images in real time within a preset range of the scraper conveyor in the working plane and to send the captured images to the artificial intelligence AI chip device 4. The artificial intelligence AI chip device 4 receives the images collected by the rotatable camera 21, processes the images in real time, identifies the images according to a pre-trained coal flow identification model, identifies coal flow information in a preset range of the scraper conveyor in a working face, and sends the identified coal flow information to the upper computer 3. And the upper computer 3 receives the coal flow information in the preset range of the scraper conveyor in the identified working face, determines the instantaneous coal flow of the scraper conveyor in the working face based on the coal flow information, judges whether the determined instantaneous coal flow is the same as the coal flow state of the instantaneous coal flow at the last moment, generates a control instruction based on the instantaneous coal flow if the determined instantaneous coal flow is different from the coal flow state of the instantaneous coal flow at the last moment, controls the action of a hydraulic support in the working face, the speed of a coal mining machine and the speed of the scraper conveyor so as to control the coal flow of the working face in real time, and does not control and continues to identify the coal flow if the determined instantaneous coal flow is the same. The scheme that this embodiment provided uses artificial intelligence AI chip device 4 to carry out the on-the-spot processing to the image information that rotatable appearance 21 gathered of making a video recording, realizes the real-time detection discernment of coal flow to can carry out cooperative control to the working face coal flow, improve the accuracy that the coal flows and detect, guarantee the safe high-efficient operation of working face.
In summary, the present application provides a method and a system for real-time controlling coal flow of a working face based on video monitoring, including: acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support; inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face; collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face; inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor; and controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time. The technical scheme provided by the invention can dynamically monitor the coal flow information to further carry out cooperative control on the coal flow of the working face, thereby improving the accuracy of coal flow detection and ensuring safe and efficient operation of the working face.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A real-time control method for coal flow of a working face based on video monitoring is characterized by comprising the following steps:
acquiring image information in a preset range of a scraper conveyor in a working face in real time through a camera arranged on a hydraulic support;
inputting the image information into a pre-trained coal flow identification model, and identifying coal flow information in a preset range of a scraper conveyor in a working face;
collecting coal flow information in each preset range in the working face by using an upper computer in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face;
inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of a hydraulic support in the working face, a speed control instruction value of a coal mining machine and a speed control instruction value of the scraper conveyor;
controlling the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor based on the action instruction value of the hydraulic support in the working face, the instruction value of the coal mining machine and the speed instruction value of the scraper conveyor so as to control the coal flow of the working face in real time;
wherein, the coal flow information of scraper conveyor within the scope of predetermineeing in the working face includes: coal flow in a preset range, the existence of large coal blocks, time and the number of the corresponding hydraulic support in the preset range.
2. The method of claim 1, wherein the image information is input into a pre-trained coal flow identification model, and when a large coal block within a preset range of the face is identified, the shearer and the face conveyor are stopped and manual processing is called.
3. The method of claim 1, wherein determining the instantaneous coal flow rate of the face scraper conveyor by collecting coal flow rate information in each predetermined range of the face using an upper computer in the face comprises:
the instantaneous coal flow X at time t of the face scraper conveyor is determined as followst：
In the formula, xi,tAnd N is the total number of the hydraulic supports in the working face.
4. The method of claim 1, wherein inputting the instantaneous coal flow of the face scraper conveyor into a pre-trained coal flow load model, obtaining control command values for hydraulic carriage action in the face, shearer speed control command values, and scraper conveyor speed control command values, further comprises:
step 1: judging whether the coal flow state to which the instantaneous coal flow of the working face scraper conveyor belongs at the current moment is the same as the coal flow state to which the instantaneous coal flow of the working face scraper conveyor belongs at the last moment;
step 2, if the coal flow state of the instant coal flow at the current moment is different from the coal flow state of the instant coal flow at the last moment, entering step 3, otherwise, returning to step 1;
and step 3: and inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and acquiring a control instruction value of the action of the hydraulic support in the working face, a speed control instruction value of the coal mining machine and a speed control instruction value of the scraper conveyor.
5. The method of claim 4, wherein the coal flow conditions comprise: overload condition, full condition, excess condition, moderate condition, low condition, and low condition.
6. A real-time control system for coal flow of a working face based on video monitoring is characterized by comprising: the intelligent wireless gateway is integrated with an artificial intelligent AI chip device;
a rotatable camera is arranged in the intelligent wireless gateway and used for acquiring images in a preset range of the scraper conveyor in a working face;
the artificial intelligence AI chip device is used for receiving the image collected by the rotatable camera and identifying the coal flow information in the preset range of the scraper conveyor in the working face based on the collected image;
and the upper computer is used for receiving the coal flow information in the identified preset range of the scraper conveyor in the working face, generating a control instruction based on the coal flow information, and controlling the action of a hydraulic support in the working face, the speed of a coal mining machine and the speed of the scraper conveyor so as to control the coal flow of the working face in real time.
7. The system of claim 6, wherein the artificial intelligence AI chip device is provided with a pre-trained coal flow identification model for identifying coal flow information within a preset range of the scraper conveyor in the working face according to real-time image information acquired by the camera within the preset range of the scraper conveyor in the working face.
8. The system of claim 7, wherein when the presence of large pieces of coal within a predetermined range of the face is identified, the identified information is reported to an upper computer and a human is called for processing.
9. The system of claim 6, wherein the upper computer is provided with a pre-trained coal flow load model for determining the control command value of the hydraulic support action in the working face, the speed control command value of the shearer and the speed control command value of the scraper conveyor according to the instantaneous coal flow of the scraper conveyor of the working face.
10. The system of claim 9, wherein the instantaneous coal flow of the face scraper conveyor is determined based on the coal flow information collected by the upper computer for each predetermined range in the face.
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| CN117010845B (en) * | 2023-06-29 | 2024-04-05 | 天地科技股份有限公司北京技术研究分公司 | Coal mine mining, transporting and storing integrated collaborative management method and device |
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