CN114422748B - A real-time control method and system for coal flow in working face based on video monitoring - Google Patents
A real-time control method and system for coal flow in working face based on video monitoring Download PDFInfo
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Abstract
本申请提出一种基于视频监测的工作面煤流量实时控制方法及系统，所述方法包括：通过设置在液压支架上的摄像仪实时采集工作面中刮板运输机预设范围内的图像信息；利用所述图像信息确定工作面刮板运输机的瞬时煤流量；将所述工作面刮板运输机的瞬时煤流量输入预先训练好的煤流负荷模型中，获取工作面中液压支架动作的控制指令值、采煤机的速度控制指令值和刮板运输机的速度控制指令值；基于所述指令值控制工作面中的液压支架动作、采煤机的速度和刮板运输机的速度进而对工作面煤流量进行实时控制。本发明提供的技术方案，可以动态监控煤流量信息进而对工作面煤流量进行协同控制，提高了煤流检测的精确度，保证工作面安全高效运行。
The present application proposes a method and system for real-time control of coal flow in a working face based on video monitoring, the method comprising: collecting image information within a preset range of a scraper conveyor in the working face in real time through a camera arranged on a hydraulic support; determining the instantaneous coal flow of the scraper conveyor in the working face using the image information; inputting the instantaneous coal flow of the scraper conveyor in the working face into a pre-trained coal flow load model, obtaining the control command value of the hydraulic support action in the working face, the speed control command value of the coal mining machine and the speed control command value of the scraper conveyor; based on the command value, controlling the hydraulic support action, the speed of the coal mining machine and the speed of the scraper conveyor in the working face, and thus controlling the coal flow of the working face in real time. The technical solution provided by the present invention can dynamically monitor the coal flow information and then coordinately control 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 working face coal flow real-time control method and system based on video monitoring.
Background
At present, in a comprehensive mechanized coal mining working face (simply referred to as a fully mechanized coal mining working face), coal mining production is realized by controlling functions of coal cutting of a coal mining machine, supporting of a hydraulic support, coal transportation of a scraper conveyor and the like.
In the related art, the coal flow monitor detects a frequency signal 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 utilizes a dynamic coal flow monitoring and weighing device to extract parameters of a coal mine transmission belt in real time and accurately measure the coal quantity through the weight of coal on the coal mine transmission belt and the speed of the coal mine transmission belt, or utilizes a scraper coal feeder coal quantity monitoring device to measure the instantaneous coal quantity of the coal for a boiler and measure the accumulated coal quantity. But cannot cooperatively control the speed of coal flow, and meanwhile, under complex geological conditions, the construction of intelligent working surfaces has more influencing factors, especially the deep mine is influenced by multiple factors such as high ground pressure, high temperature, high mine water corrosion environment, working surface inclination angle and the like, so that the working surface is difficult to advance, multiple operators are needed on the working surface, and the existing system and method have low adaptability and low safety.
The current method for controlling the coal flow rate requires that a worker observe the actual operation condition of working face equipment in a gateway monitoring center or the ground through a video monitoring method, and further uses a control console to send out corresponding control signals so as to realize the treatment of abnormal conditions of the working face. The method has the problems of incomplete video watching, large 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 working face coal flow based on video monitoring, which at least solve the technical problems that the coal flow speed cannot be cooperatively controlled and the coal flow detection precision is low in the related technology.
The embodiment of the first aspect of the application provides a real-time control method for working face coal flow based on video monitoring, which comprises the steps of 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, identifying coal flow information in the preset range of the scraper conveyor in the working face, secondly collecting coal flow information in each preset range in the working face by an upper computer in the working face, determining instantaneous coal flow of the scraper conveyor in the working face, inputting the instantaneous coal flow of the scraper conveyor in a pre-trained coal flow load model, acquiring a control command value of the hydraulic support action in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor, and finally controlling the hydraulic support action in the working face, the speed of the scraper conveyor and the speed of the scraper conveyor based on the command value of the hydraulic support action in the working face and the speed command value of the scraper conveyor, and further controlling the coal flow of the working face in real time, wherein the preset range of the scraper conveyor in the working face comprises the preset range of the hydraulic support and the coal flow in the preset range in the coal flow range.
The embodiment of the second aspect of the application provides a real-time control system for working face coal flow based on video monitoring, which comprises at least one hydraulic support, at least one intelligent wireless gateway and at least one upper computer, wherein the at least one intelligent wireless gateway is arranged below a top beam of the hydraulic support, an artificial intelligent AI chip device is integrated in the intelligent wireless gateway, at least one rotatable camera is arranged in the intelligent wireless gateway and is used for collecting images in a preset range of a scraper conveyor in a working face, the artificial intelligent AI chip device is used for receiving the images collected by the rotatable camera and identifying coal flow information in the preset range of the scraper conveyor in the working face based on the collected images, and the upper computer is used for receiving the coal flow information in the preset range of the scraper conveyor in the identified working face, generating control instructions based on the coal flow information, 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 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 application provides a real-time control method and a real-time control system for working face coal flow based on video monitoring, wherein image information in a preset range of a scraper conveyor in a working face is acquired in real time through a camera arranged on a hydraulic support, the image information is input into a pre-trained coal flow identification model, coal flow information in the preset range of the scraper conveyor in the working face is identified, an upper computer in the working face is used for collecting the coal flow information in each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor in the working face, the instantaneous coal flow of the scraper conveyor in the working face is input into a pre-trained coal flow load model, a control command value of the hydraulic support action in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor are acquired, the hydraulic support action in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled based on the command value of the hydraulic support action in the working face, the command value of the scraper conveyor and the speed command value of the scraper conveyor, and then the real-time control is carried out on the working face coal flow. According to the technical scheme provided by the application, the coal flow information can be dynamically monitored so as to cooperatively control the coal flow of the working face, the accuracy of coal flow detection is improved, and the safe and efficient operation of the working face is ensured.
Additional aspects and advantages of the 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 application.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flow chart of a method for real-time control of working face coal flow based on video monitoring according to an embodiment of the application;
FIG. 2 is a block diagram of a real-time control system for working face coal flow based on video monitoring according to an embodiment of the application;
Fig. 3 is a block diagram of an intelligent wireless gateway according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The real-time control method and system for the working face coal flow based on video monitoring are characterized in that image information in a preset range of a scraper conveyor in a working face is acquired in real time through a camera arranged on a hydraulic support, the image information is input into a pre-trained coal flow identification model, coal flow information in the preset range of the scraper conveyor in the working face is identified, an upper computer in the working face is used for collecting coal flow information in each preset range in the working face to determine the instantaneous coal flow of the working face scraper conveyor, the instantaneous coal flow of the working face scraper conveyor is input into a pre-trained coal flow load model, a control command value of the action of the hydraulic support in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor are obtained, the hydraulic support action in the working face, the speed of the coal mining machine and the speed command value of the scraper conveyor are controlled based on the command value of the action of the hydraulic support in the working face, and the speed command value of the scraper conveyor, and the speed of the working face coal is further controlled in real time. Therefore, the working face coal flow real-time control method and system based on video monitoring provided by the embodiment of the disclosure can dynamically monitor the coal flow information so as to cooperatively control the working face coal flow, improve the accuracy of coal flow detection and ensure the safe and efficient operation of the working face.
The following describes a working face coal flow real-time control method and a working face coal flow real-time control system based on video monitoring according to an embodiment of the application with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for controlling a coal flow rate of a working surface in real time based on video monitoring according to an embodiment of the present application, as shown in fig. 1, the method includes:
step 101, acquiring image information in a preset range of a scraper conveyor in a working surface in real time through a camera arranged on a hydraulic support;
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 the embodiment of the disclosure, the training process of the coal flow recognition model comprises the steps of selecting images corresponding to historical moments of a scraper conveyor in a working face and coal flow information corresponding to the images as training samples, and training a deep learning model to obtain a trained coal flow recognition model.
The coal flow information in the preset range of the scraper conveyor in the working face comprises coal flow in the preset range, whether massive coal exists or not, time and frame numbers of corresponding hydraulic supports in the preset range.
When the large coal is recognized to appear in the preset range of the scraper conveyor in the working face, the working 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 the number of frames of the large coal blocks, and prompts workers 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 an embodiment of the present disclosure, the instantaneous coal flow X t at time t of the face scraper conveyor is determined as follows:
In the formula, x i,t is the instantaneous coal flow at the moment t shot by a camera on the ith hydraulic support, and N is the total number of the hydraulic supports in the working surface.
104, Inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and obtaining a control command value of the action of a hydraulic support in the working face, a speed control command value of a coal mining machine and a speed control command value of the scraper conveyor;
In an embodiment of the disclosure, before inputting the instantaneous coal flow of the face scraper conveyor into a pre-trained coal flow load model, comprising:
Step 4-1, judging whether the state of the coal flow to which the instantaneous coal flow of the working face scraper conveyor belongs at the current moment is the same as the state of the coal flow to which the instantaneous coal flow of the working face scraper conveyor belongs at the last moment;
step 4-2, if the state of the instantaneous coal flow at the current moment is different from the state of the coal flow to which the instantaneous coal flow at the previous moment belongs, entering a step 3, otherwise returning to the step 1;
And 4-3, inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and obtaining a control command value of the action of the hydraulic support in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor.
Wherein the coal flow rate state comprises an overload state, a full load state, an excessive state, a moderate state, a small state and an extremely small state.
Specifically, when the coal flow rate of the scraper conveyor is greater than the rated conveying capacity of the scraper conveyor, the coal flow rate is in an overload state.
When the coal flow rate of the scraper conveyor is less than or equal to the rated transport capacity of the scraper conveyor and greater than eighty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in a full load state.
When the coal flow rate of the scraper conveyor is equal to or less than eighty percent of the rated transport capacity of the scraper conveyor and is greater than sixty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in an excessive state.
When the coal flow rate of the scraper conveyor is equal to or less than sixty percent of the rated transport capacity of the scraper conveyor and greater than forty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in a moderate state.
When the coal flow rate of the scraper conveyor is forty percent or less of the rated transport capacity of the scraper conveyor and twenty percent or more of the rated transport capacity of the scraper conveyor, the coal flow rate is in a small amount.
When the coal flow rate of the scraper conveyor is twenty percent or less of the rated transport capacity of the scraper conveyor, the coal flow rate is in a very small state.
In the embodiment of the disclosure, the training process of the coal flow load model comprises the steps of selecting instantaneous coal flow at the historical moment of a working face scraper conveyor and a control instruction corresponding to the instantaneous coal flow as training samples, and training a multiple linear regression empirical model to obtain a trained coal flow load model.
And 105, controlling the hydraulic support in the working surface, the speed of the coal mining machine and the speed of the scraper conveyor based on the command value of the hydraulic support in the working surface, the command value of the coal mining machine and the speed command value of the scraper conveyor so as to control the coal flow of the working surface in real time.
In an embodiment of the disclosure, the hydraulic support action in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled according to the command value of the hydraulic support action in the working face, the command value of the coal mining machine and the speed command 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 accuracy of coal flow detection is improved, and safe and efficient operation of the working face is ensured.
The method comprises the steps of firstly collecting images within a preset range of a scraper conveyor in a working face in real time by using a rotatable camera, inputting the collected images into a pre-trained coal flow identification model to identify coal flow information, secondly uploading the coal flow information to an upper computer, 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 identical to the coal flow state of the instantaneous coal flow at the last moment or not, generating a control instruction based on the instantaneous coal flow if the determined instantaneous coal flow is different from the instantaneous coal flow, controlling the action of a hydraulic support in the working face, the speed of the 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 the determined instantaneous coal flow is identical to the instantaneous coal flow, continuing coal flow identification. The scheme provided by the embodiment can realize real-time detection and identification of the coal flow by processing the acquired images on site, so that the coal flow of the working face can be cooperatively controlled, the accuracy of coal flow detection is improved, and the safe and efficient operation of the working face is ensured.
In summary, the application provides a real-time control method and a real-time control system for working face coal flow based on video monitoring, wherein image information in a preset range of a scraper conveyor in a working face is acquired in real time through a camera arranged on a hydraulic support, the image information is input into a pre-trained coal flow identification model, coal flow information in the preset range of the scraper conveyor in the working face is identified, an upper computer in the working face is used for collecting the coal flow information in each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor in the working face, the instantaneous coal flow of the scraper conveyor in the working face is input into a pre-trained coal flow load model, a control command value of the hydraulic support action in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor are acquired, the hydraulic support action in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled based on the command value of the hydraulic support action in the working face, the command value of the scraper conveyor and the speed command value of the scraper conveyor, and then the real-time control is carried out on the working face coal flow. According to the technical scheme provided by the application, the coal flow information can be dynamically monitored so as to cooperatively control the coal flow of the working face, the accuracy of coal flow detection is improved, and the safe and efficient operation of the working face is ensured.
Fig. 2 is a block diagram of a real-time control system for coal flow on 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 at least one hydraulic support 1, at least one intelligent wireless gateway 2 disposed below a top beam of the hydraulic support, and at least one host computer 3, where 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 the top beam of the hydraulic support, and at least one host computer 3, and fig. 2 is only for illustration, and is not meant to limit the embodiments of the present application.
As shown in fig. 3, in the embodiment of the disclosure, the system further includes a rotatable camera 21 disposed in the intelligent wireless gateway 2, where the rotatable camera 21 is configured to collect an image within a preset range of the scraper conveyor in the working surface in real time, and send the collected image to the artificial intelligence AI chip device 4. The artificial intelligence AI chip device 4 is configured to receive an image acquired by the rotatable camera 21, process the image in real time, identify the image according to a pre-trained coal flow identification model, identify coal flow information within a preset range of the scraper conveyor in the working surface, and send the identified coal flow information to the upper computer 3. The upper computer 3 is configured to receive the identified coal flow information in the preset range of the scraper conveyor in the working surface, determine an instantaneous coal flow of the scraper conveyor in the working surface based on the coal flow information, then determine whether the determined instantaneous coal flow is the same as a coal flow state to which the instantaneous coal flow at the previous moment belongs, if so, generate a control instruction based on the instantaneous coal flow, and control the hydraulic support action in the working surface, the speed of the coal mining machine and the speed of the scraper conveyor, thereby further controlling the coal flow of the working surface 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 local processing to the image information that rotatable appearance 21 gathered, 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 flow detected, guarantee the safe high-efficient operation of working face.
The coal flow information in the preset range of the scraper conveyor in the working face comprises coal flow in the preset range, whether massive coal exists or not, time and frame numbers of corresponding hydraulic supports 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 that can capture images, which is not particularly limited in this 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 recognition comparison.
In the embodiment of the present disclosure, the rotatable camera 21 is provided at a specific position of the hydraulic mount 1 so as to be able to acquire an image within a preset range.
When the coal flow identification model identifies that large coal appears 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 large coal appears in the preset range of the scraper conveyor in the working face, the identified information is reported to the upper computer, and then the display screen of the upper computer 3 displays the number of frames of the large coal, so that workers are prompted to process the large coal.
In the disclosed embodiments, the coal flow conditions include an overload condition, a full load condition, an excess condition, a moderate condition, a small quantity condition, and a very small quantity condition.
Specifically, when the coal flow rate of the scraper conveyor is greater than the rated conveying capacity of the scraper conveyor, the coal flow rate is in an overload state.
When the coal flow rate of the scraper conveyor is less than or equal to the rated transport capacity of the scraper conveyor and greater than eighty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in a full load state.
When the coal flow rate of the scraper conveyor is equal to or less than eighty percent of the rated transport capacity of the scraper conveyor and is greater than sixty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in an excessive state.
When the coal flow rate of the scraper conveyor is equal to or less than sixty percent of the rated transport capacity of the scraper conveyor and greater than forty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in a moderate state.
When the coal flow rate of the scraper conveyor is forty percent or less of the rated transport capacity of the scraper conveyor and twenty percent or more of the rated transport capacity of the scraper conveyor, the coal flow rate is in a small amount.
When the coal flow rate of the scraper conveyor is twenty percent or less of the rated transport capacity of the scraper conveyor, the coal flow rate is in a very small state.
It is understood that the artificial intelligence AI chip apparatus 4 may be, for example, an artificial intelligence chip or an artificial intelligence processing program-integrated device. In the embodiment of the disclosure, the artificial intelligence AI chip device 4 is preset with a pre-trained coal flow identification model, so that images can be identified, and different images can be identified for different training samples.
In the embodiment of the disclosure, a pre-trained coal flow load model is preset in the upper computer, so that a control command value can be output, and the control command value can be output for different training samples.
In an exemplary embodiment, images corresponding to historical moments of a scraper conveyor in a working face and coal flow information corresponding to the images are selected in advance to serve as training samples, and a deep learning model is trained to obtain a trained coal flow recognition model. When the real-time image acquired by the rotatable camera 21 is identified later, the same or similar image as the sample image can be identified, so as to achieve the purpose of identifying the coal flow information.
In an exemplary embodiment, in the embodiment of the disclosure, an instantaneous coal flow at a historical moment of a working face scraper conveyor and a control instruction corresponding to the instantaneous coal flow are selected in advance as training samples, and a multiple linear regression empirical model is trained to obtain a trained coal flow load model. When the subsequent upper computer 3 inputs the instantaneous coal flow into the model, a control command value is correspondingly output so as to achieve the purpose of controlling the coal flow of the working face in real time.
In an exemplary embodiment, a rotatable camera 21 is utilized for capturing images within a predetermined range of the blade conveyor in the work surface in real time and transmitting the captured images to the artificial intelligence AI chip device 4. The artificial intelligence AI chip device 4 receives the image collected by the rotatable camera 21, processes the image in real time, recognizes the image according to a pre-trained coal flow recognition model, recognizes the coal flow information in the preset range of the scraper conveyor in the working face, and sends the recognized coal flow information to the upper computer 3. 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 of the working face based on the coal flow information, then judges whether the determined instantaneous coal flow is identical to the coal flow state of the instantaneous coal flow at the last moment, if so, generates a control instruction based on the instantaneous coal flow, controls the action of a hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor, further controls the coal flow of the working face in real time, and if so, does not control, and continues to identify the coal flow. The scheme that this embodiment provided uses artificial intelligence AI chip device 4 to carry out the local processing to the image information that rotatable appearance 21 gathered, 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 flow detected, guarantee the safe high-efficient operation of working face.
In summary, the application provides a real-time control method and a real-time control system for working face coal flow based on video monitoring, wherein image information in a preset range of a scraper conveyor in a working face is acquired in real time through a camera arranged on a hydraulic support, the image information is input into a pre-trained coal flow identification model, coal flow information in the preset range of the scraper conveyor in the working face is identified, an upper computer in the working face is used for collecting the coal flow information in each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor in the working face, the instantaneous coal flow of the scraper conveyor in the working face is input into a pre-trained coal flow load model, a control command value of the hydraulic support action in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor are acquired, the hydraulic support action in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled based on the command value of the hydraulic support action in the working face, the command value of the scraper conveyor and the speed command value of the scraper conveyor, and then the real-time control is carried out on the working face coal flow. According to the technical scheme provided by the application, the coal flow information can be dynamically monitored so as to cooperatively control the coal flow of the working face, the accuracy of coal flow detection is improved, and the safe and efficient operation of the working face is ensured.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," 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 present application. In this specification, schematic representations of the above terms are not necessarily directed 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, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those 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 specific logical functions or steps of the process, and additional 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 from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (5)
1. The method for controlling the coal flow of the working face in real time based on video monitoring is characterized by comprising the following steps of:
image information in a preset range of the scraper conveyor in the working surface is acquired in real time through a camera arranged on the 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 command value of the action of a hydraulic support in the working face, a speed control command value of a coal mining machine and a speed control command 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 command value of the action of the hydraulic support in the working face, the command value of the coal mining machine and the speed command value of the scraper conveyor so as to control the coal flow of the working face in real time;
The coal flow information in the preset range of the scraper conveyor in the working face comprises coal flow in the preset range, whether massive coal exists or not, time and frame numbers of corresponding hydraulic supports in the preset range;
Inputting the image information into a pre-trained coal flow identification model, stopping the work of the coal mining machine and the scraper conveyor when the large coal appears in the preset range of the scraper conveyor in the working face, and calling for manual treatment;
The instantaneous coal flow of the working face scraper conveyor is input into a pre-trained coal flow load model, and a control command value of the action of a hydraulic support in the working face, a speed control command value of a coal mining machine and a speed control command value of the scraper conveyor are obtained, wherein the method further comprises the following steps:
Step 1, judging whether a coal flow state of the instantaneous coal flow of the working face scraper conveyor at the current moment is the same as a coal flow state of the instantaneous coal flow of the working face scraper conveyor at the last moment, wherein the coal flow state comprises an overload state, a full load state, an excessive state, a moderate state, a small amount of state and a very small amount of state;
Step 2, if the state of the instantaneous coal flow at the current moment is different from the state of the coal flow to which the instantaneous coal flow at the previous moment belongs, entering a step 3, otherwise returning to the step 1;
and 3, inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and obtaining a control command value of the action of the hydraulic support in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor.
2. The method of claim 1, wherein the determining the instantaneous coal flow of the face scraper conveyor using the information of the coal flow in each preset range in the collection face of the upper computer in the face comprises:
Determining the instantaneous coal flow of a face scraper conveyor at time t by :
In the formula,The instantaneous coal flow at the time t which is shot by the camera on the ith hydraulic bracket,Is the total number of hydraulic supports in the working surface.
3. The working face coal flow real-time control system based on video monitoring is characterized by comprising at least one hydraulic support, at least one intelligent wireless gateway and at least one upper computer, wherein the intelligent wireless gateway is arranged below a top beam of the hydraulic support, and an artificial intelligent AI chip device is integrated in the intelligent wireless gateway;
A rotatable camera is arranged in the intelligent wireless gateway and is used for collecting images within a preset range of the scraper conveyor in the working face;
The artificial intelligent AI chip device is used for receiving images acquired by the rotatable camera and identifying coal flow information in a preset range of the scraper conveyor in the working face based on the acquired images;
The upper computer is used for receiving the coal flow information in the preset range of the scraper conveyor in the identified working face, generating a control instruction based on the coal flow information, controlling the action of a hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor, and further controlling the coal flow of the working face in real time;
The artificial intelligent AI chip device is provided with a pre-trained coal flow identification model which is used for acquiring image information in a preset range of the scraper conveyor in the working face in real time according to the camera, and identifying coal flow information in the preset range of the scraper conveyor in the working face;
The upper computer is also used for judging whether the coal flow state of the instantaneous coal flow of the working face scraper conveyor at the current moment is the same as the coal flow state of the instantaneous coal flow of the working face scraper conveyor at the last moment, wherein the coal flow state comprises an overload state, a full load state, an excessive state, a moderate state, a small amount of states and a very small state;
Step 2, if the state of the instantaneous coal flow at the current moment is different from the state of the coal flow to which the instantaneous coal flow at the previous moment belongs, entering a step 3, otherwise returning to the step 1;
and 3, inputting the instantaneous coal flow of the working face scraper conveyor into a pre-trained coal flow load model, and obtaining a control command value of the action of the hydraulic support in the working face, a speed control command value of the coal mining machine and a speed control command value of the scraper conveyor.
4. The system of claim 3, wherein the upper computer is provided with a pre-trained coal flow load model for determining control command values of hydraulic support actions in the working surface, speed control command values of the coal mining machine and speed control command values of the scraper conveyor according to instantaneous coal flow of the scraper conveyor.
5. The system of claim 4, wherein the instantaneous coal flow of the face scraper conveyor is determined based on the coal flow information collected by the host computer within each of the predetermined ranges in the face.
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