A real-time control method and system for coal flow in working face based on video monitoring

Abstract

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

[0001] The present application relates to the technical field of coal flow control, and in particular to a method and system for real-time control of coal flow in a working face based on video monitoring. Background Art

[0002] At present, in the comprehensive mechanized coal mining face of coal mines (abbreviated as: fully mechanized mining face), coal mining and production are realized by controlling the functions of coal cutting by coal mining machines, hydraulic support support, and scraper conveyor coal transportation.

[0003] In the related technologies, the coal flow monitor detects the frequency signal generated by friction through bandpass filtering, which is widely used in coal feeders and for measuring the flow of materials in closed pipes or hoppers; or uses a dynamic coal flow monitoring and weighing device to extract the parameters of the coal mine transmission belt in real time, and accurately measures the amount of coal by the weight of the coal on the coal mine transmission belt and the speed of the coal mine transmission belt; or uses a scraper feeder coal quantity monitoring device to measure the instantaneous amount of coal used in the boiler and the cumulative amount of coal. However, it is impossible to coordinate the speed of the coal flow. At the same time, there are many factors affecting the construction of intelligent working faces under complex geological conditions, especially deep mines are affected by multiple factors such as high ground pressure, high temperature and high mine water corrosion environment and working face inclination angle, which makes it difficult to advance the working face. The working face requires multiple operators, and the existing systems and methods are not highly adaptable and have low safety.

[0004] The current method of controlling the coal flow speed requires workers to observe the actual operating conditions of the working face equipment through video monitoring at the chute monitoring center or on the ground, and then use the console to send corresponding control signals to handle abnormal conditions on the working face. This method has problems such as incomplete video, large communication delay, reliance on manual observation, and low reliability, and also has great limitations. Summary of the invention

[0005] The present application provides a method and system for real-time control of coal flow in a working face based on video monitoring, so as to at least solve the technical problems in the related art that the coal flow velocity cannot be coordinated and the coal flow detection accuracy is not high.

[0006] The first embodiment of the present application proposes a real-time control method for coal flow of a working face based on video monitoring, comprising: firstly, using a camera arranged on a hydraulic support to collect image information within a preset range of a scraper conveyor in the working face in real time; then, inputting the image information into a pre-trained coal flow recognition model to identify the coal flow information within the preset range of the scraper conveyor in the working face; secondly, using a host computer in the working face to collect coal flow information within each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor on the working face; then, inputting the instantaneous coal flow of the scraper conveyor on the working face into a pre-trained coal flow recognition model. In the coal flow load model, 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 are obtained; finally, based on 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, the hydraulic support action in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled to achieve real-time control of the coal flow of the working face; wherein, the coal flow information within a preset range of the scraper conveyor in the working face includes: the coal flow within the preset range, the presence or absence of large coal, the time and the frame number of the corresponding hydraulic support within the preset range.

[0007] The second aspect of the present application proposes a real-time control system for coal flow in a working face based on video monitoring, comprising: at least one hydraulic support, at least one intelligent wireless gateway arranged under the top beam of the hydraulic support, and at least one host computer, wherein the intelligent wireless gateway is integrated with an artificial intelligence AI chip device; the intelligent wireless gateway is built with at least one rotatable camera, and the rotatable camera is used to collect images within a preset range of a scraper conveyor in the working face; the artificial intelligence AI chip device is used to receive images collected by the rotatable camera, and based on the collected images, identify coal flow information within a preset range of the scraper conveyor in the working face; the host computer is used to receive the identified coal flow information within the preset range of the scraper conveyor in the working face, and generate control instructions based on the coal flow information to control the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor, thereby performing real-time control of the coal flow in the working face.

[0008] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects:

[0009] In summary, the present application proposes a real-time control method and system for coal flow of a working face based on video monitoring, 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; inputting the image information into a pre-trained coal flow recognition model to identify the coal flow information within a preset range of the scraper conveyor in the working face; using a host computer in the working face to collect coal flow information within each preset range 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 scraper conveyor of the working face into a pre-trained coal flow load model to obtain the control command value of the action of the hydraulic support 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 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, the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled, thereby performing real-time control of the coal flow of the working face. The technical solution provided by the present invention can dynamically monitor 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.

[0010] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0012] Figure 1 A flowchart of a method for real-time control of coal flow at a working face based on video monitoring according to an embodiment of the present application;

[0013] Figure 2 A structural diagram of a real-time control system for coal flow at a working face based on video monitoring provided according to an embodiment of the present application;

[0014] Figure 3 The figure is a structural diagram of an intelligent wireless gateway provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0015] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0016] In the real-time control method and system of coal flow in a working face based on video monitoring proposed in the present application, image information within a preset range of a scraper conveyor in the working face is collected in real time by a camera arranged on a hydraulic support; the image information is input into a pre-trained coal flow recognition model to identify the coal flow information within a preset range of the scraper conveyor in the working face; the upper computer in the working face is used to collect the coal flow information within 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 to obtain the control command value of the action of the hydraulic support 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 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, the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled to thereby control the coal flow of the working face in real time. Therefore, the real-time control method and system of coal flow at the working face based on video monitoring provided by the embodiments of the present disclosure can dynamically monitor the coal flow information and then coordinately control the coal flow at the working face, thereby improving the accuracy of coal flow detection and ensuring safe and efficient operation of the working face.

[0017] The following describes, with reference to the accompanying drawings, a method and system for real-time control of coal flow at a working face based on video monitoring according to an embodiment of the present application.

[0018] Figure 1 Flow chart of a method for real-time control of coal flow in a working face based on video monitoring according to an embodiment of the present application, such as Figure 1 As shown, the method includes:

[0019] Step 101: using a camera disposed on a hydraulic support to collect image information within a preset range of a scraper conveyor on a working surface in real time;

[0020] Step 102: inputting the image information into a pre-trained coal flow recognition model to recognize coal flow information within a preset range of a scraper conveyor in the working face;

[0021] In the disclosed embodiment, the training process of the coal flow recognition model includes: selecting images corresponding to historical moments of the scraper conveyor in the working face and the coal flow information corresponding to the images as training samples, training the deep learning model to obtain a trained coal flow recognition model.

[0022] The coal flow information within the preset range of the scraper conveyor in the working face includes: the coal flow within the preset range, the presence or absence of large coal, the time and the frame number of the corresponding hydraulic support within the preset range.

[0023] It should be noted that when large pieces of coal are identified within the preset range of the scraper conveyor in the working face, the coal mining machine and the scraper conveyor are stopped, and manual processing is called.

[0024] After the identified information is reported to the host computer, the display screen of the host computer 3 will display the rack where the large coal block is located, prompting the workers to handle it.

[0025] Step 103: using the upper computer in the working face to collect coal flow information within each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor of the working face;

[0026] In the embodiment of the present disclosure, the instantaneous coal flow rate X of the scraper conveyor at the working face at time t is determined by the following formula: t :

[0027]

[0028] In the formula, x i,t is the instantaneous coal flow at time t captured by the camera on the i-th hydraulic support, and N is the total number of hydraulic supports in the working face.

[0029] Step 104: input the instantaneous coal flow of the scraper conveyor of the working face into the pre-trained coal flow load model to obtain 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;

[0030] In the embodiment of the present disclosure, before the instantaneous coal flow of the working face scraper conveyor is input into the pre-trained coal flow load model, the method includes:

[0031] Step 4-1: Determine whether the coal flow state to which the instantaneous coal flow of the scraper conveyor of the working face at the current moment belongs is the same as the coal flow state to which the instantaneous coal flow of the scraper conveyor of the working face at the previous moment belongs;

[0032] Step 4-2: If the instantaneous coal flow rate at the current moment is different from the coal flow rate state at the previous moment, proceed to step 3, otherwise return to step 1;

[0033] Step 4-3: Input the instantaneous coal flow of the scraper conveyor of the working face into the pre-trained coal flow load model to obtain 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.

[0034] The coal flow state includes: overload state, full load state, excessive state, moderate state, small amount state and very small amount state.

[0035] Specifically, when the coal flow rate of the scraper conveyor is greater than the rated transportation capacity of the scraper conveyor, the coal flow rate is in an overload state.

[0036] When the coal flow rate of the scraper conveyor is less than or equal to the rated transport capacity of the scraper conveyor and is greater than eighty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in a full load state.

[0037] When the coal flow rate of the scraper conveyor is less than or equal to 80% of the rated transport capacity of the scraper conveyor and greater than 60% of the rated transport capacity of the scraper conveyor, the coal flow rate is in an excessive state.

[0038] When the coal flow rate of the scraper conveyor is less than or equal to 60% of the rated transport capacity of the scraper conveyor and greater than 40% of the rated transport capacity of the scraper conveyor, the coal flow rate is in a moderate state.

[0039] When the coal flow rate of the scraper conveyor is less than or equal to 40% of the rated transport capacity of the scraper conveyor and greater than 20% of the rated transport capacity of the scraper conveyor, the coal flow rate is in a small amount state.

[0040] When the coal flow rate of the scraper conveyor is less than or equal to 20 percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in an extremely low state.

[0041] In the disclosed embodiment, the training process of the coal flow load model includes: selecting the instantaneous coal flow of the working face scraper conveyor at historical moments and the control instructions corresponding to the instantaneous coal flow as training samples, and training the empirical model of multiple linear regression to obtain a trained coal flow load model.

[0042] Step 105: Based on 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, the hydraulic support action, the speed of the coal mining machine and the speed of the scraper conveyor in the working face are controlled to thereby perform real-time control of the coal flow rate in the working face.

[0043] In one embodiment of the present disclosure, the action 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 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, thereby performing real-time control of the coal flow of the working face, thereby enabling coordinated control of the coal flow of the working face, improving the accuracy of coal flow detection, and ensuring safe and efficient operation of the working face.

[0044] For example, firstly, a rotatable camera is used to collect images within a preset range of a scraper conveyor in a working face in real time, and the collected images are input into a pre-trained coal flow recognition model to identify coal flow information; secondly, the coal flow information is uploaded to a host computer, and the host computer determines the instantaneous coal flow of the scraper conveyor in the working face based on the coal flow information; then, it is determined whether the determined instantaneous coal flow is the same as the coal flow state of the instantaneous coal flow at the previous moment. If different, a control instruction is generated based on the instantaneous coal flow to control the action of the hydraulic support, the speed of the coal mining machine and the speed of the scraper conveyor in the working face, thereby controlling the coal flow of the working face in real time. If the same, no control is performed and the coal flow recognition is continued. The solution provided in this embodiment can process the collected images on-site to realize real-time detection and identification of the coal flow, so that the coal flow of the working face can be coordinated and controlled, the accuracy of coal flow detection is improved, and the safe and efficient operation of the working face is ensured.

[0045] In summary, the present application proposes a real-time control method and system for coal flow of a working face based on video monitoring, 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; inputting the image information into a pre-trained coal flow recognition model to identify the coal flow information within a preset range of the scraper conveyor in the working face; using a host computer in the working face to collect coal flow information within each preset range 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 scraper conveyor of the working face into a pre-trained coal flow load model to obtain the control command value of the action of the hydraulic support 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 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, the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled, thereby performing real-time control of the coal flow of the working face. The technical solution provided by the present invention can dynamically monitor 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.

[0046] Figure 2 The structure diagram of the real-time control system of coal flow in a working face based on video monitoring provided in accordance with an embodiment of the present application is as follows: Figure 2 As shown, the system may include: at least one hydraulic support 1, at least one intelligent wireless gateway 2 arranged under the top beam of the hydraulic support, and at least one host computer 3, wherein the intelligent wireless gateway 2 is integrated with an artificial intelligence AI chip device 4.

[0047] It should be noted that Figure 2 The figure shows a hydraulic support 1, at least one intelligent wireless gateway 2 and at least one host computer 3 arranged under the top beam of the hydraulic support. Figure 2 This is only for illustration and is not intended to limit the embodiments of the present application.

[0048] like Figure 3 As shown, in the embodiment of the present disclosure, the system further includes a rotatable camera 21 arranged in the intelligent wireless gateway 2, and the rotatable camera 21 is used to collect images within a preset range of the scraper conveyor in the working face in real time, and send the collected images to the artificial intelligence AI chip device 4. The artificial intelligence AI chip device 4 is used to receive the images collected by the rotatable camera 21, and process the images in real time, recognize the images according to the pre-trained coal flow recognition model, recognize the coal flow information within the preset range of the scraper conveyor in the working face, and send the recognized coal flow information to the host computer 3. The upper computer 3 is used to receive the coal flow information within the preset range of the scraper conveyor in the identified working face, and determine the instantaneous coal flow of the scraper conveyor of the working face based on the coal flow information, and then judge whether the determined instantaneous coal flow is the same as the coal flow state of the instantaneous coal flow at the previous moment. If different, a control instruction is generated based on the instantaneous coal flow to control the action of the hydraulic support, the speed of the coal mining machine and the speed of the scraper conveyor in the working face, thereby controlling the coal flow of the working face in real time. If the same, no control is performed and the coal flow identification continues. The solution provided in this embodiment uses an artificial intelligence AI chip device 4 to process the image information collected by the rotatable camera 21 on-site, realizes real-time detection and identification of the coal flow, and thus can coordinate the control of the coal flow of the working face, improve the accuracy of coal flow detection, and ensure safe and efficient operation of the working face.

[0049] The coal flow information within the preset range of the scraper conveyor in the working face includes: the coal flow within the preset range, the presence or absence of large coal, the time and the frame number of the corresponding hydraulic support within the preset range.

[0050] In the embodiment of the present disclosure, the rotatable camera 21 can be a camera, a monocular camera or other device that can collect images, and the present disclosure does not make specific restrictions on this. The monocular camera is mainly an RGB camera, which can quickly complete the collection with the monocular algorithm and transmit high-quality images to the back end for recognition and comparison.

[0051] In the embodiment of the present disclosure, the rotatable camera 21 is disposed at a specific position of the hydraulic support 1 so as to be able to acquire images within a preset range.

[0052] It should be noted that when the coal flow recognition model recognizes that large pieces of coal appear within the preset range of the scraper conveyor in the working face, the recognized information is reported to the host computer and a call is made for manual processing.

[0053] Specifically, when the coal flow recognition model recognizes that large lumps of coal appear within the preset range of the scraper conveyor in the working face, the recognized information is reported to the host computer, and the display screen of the host computer 3 displays the rack where the large lumps of coal are located, prompting workers to handle them.

[0054] In the embodiment of the present disclosure, the coal flow state includes: an overload state, a full load state, an excessive state, a moderate state, a small amount state and a very small amount state.

[0055] Specifically, when the coal flow rate of the scraper conveyor is greater than the rated transportation capacity of the scraper conveyor, the coal flow rate is in an overload state.

[0056] When the coal flow rate of the scraper conveyor is less than or equal to the rated transport capacity of the scraper conveyor and is greater than eighty percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in a full load state.

[0057] When the coal flow rate of the scraper conveyor is less than or equal to 80% of the rated transport capacity of the scraper conveyor and greater than 60% of the rated transport capacity of the scraper conveyor, the coal flow rate is in an excessive state.

[0058] When the coal flow rate of the scraper conveyor is less than or equal to 60% of the rated transport capacity of the scraper conveyor and greater than 40% of the rated transport capacity of the scraper conveyor, the coal flow rate is in a moderate state.

[0059] When the coal flow rate of the scraper conveyor is less than or equal to 40% of the rated transport capacity of the scraper conveyor and greater than 20% of the rated transport capacity of the scraper conveyor, the coal flow rate is in a small amount state.

[0060] When the coal flow rate of the scraper conveyor is less than or equal to 20 percent of the rated transport capacity of the scraper conveyor, the coal flow rate is in an extremely low state.

[0061] It is understandable that the artificial intelligence AI chip device 4, for example, 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 pre-set with a pre-trained coal flow recognition model, which can recognize images, and can recognize different images for different training samples.

[0062] In the disclosed embodiment, a pre-trained coal flow load model is pre-set in the host computer, which can output control instruction values. The control instruction values ​​can be output for different training samples.

[0063] In the exemplary embodiment, the images corresponding to the historical moments of the scraper conveyor in the working face and the coal flow information corresponding to the images are pre-selected as training samples in the disclosed embodiment, and the 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 subsequently recognized, an image that is the same or similar to the sample image can be recognized to achieve the purpose of recognizing the coal flow information.

[0064] In the exemplary embodiment, the instantaneous coal flow rate of the scraper conveyor at the working face at the historical moment and the control instructions corresponding to the instantaneous coal flow rate are pre-selected as training samples in the disclosed embodiment, and the empirical model of multiple linear regression is trained to obtain a trained coal flow load model. When the upper computer 3 subsequently inputs the instantaneous coal flow rate into the model, the corresponding control instruction value is output to achieve the purpose of real-time control of the coal flow rate of the working face.

[0065] In the exemplary embodiment, the rotatable camera 21 is used to collect images within a preset range of the scraper conveyor in the working face in real time, and the collected images are sent 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, recognizes the images according to the pre-trained coal flow recognition model, recognizes the coal flow information within the preset range of the scraper conveyor in the working face, and sends the recognized coal flow information to the host computer 3. The host computer 3 receives the recognized coal flow information within the preset range of the scraper conveyor in the working face, and determines the instantaneous coal flow of the scraper conveyor of the working face based on the coal flow information, and then determines whether the determined instantaneous coal flow is the same as the coal flow state of the instantaneous coal flow at the previous moment. If different, a control instruction is generated based on the instantaneous coal flow to control the hydraulic support action, the speed of the coal mining machine and the speed of the scraper conveyor in the working face, and then the coal flow of the working face is controlled in real time. If the same, no control is performed, and the coal flow recognition continues. The solution provided in this embodiment uses an artificial intelligence AI chip device 4 to perform on-site processing of image information collected by the rotatable camera 21, thereby realizing real-time detection and identification of coal flow, thereby enabling coordinated control of the coal flow of the working face, improving the accuracy of coal flow detection, and ensuring safe and efficient operation of the working face.

[0066] In summary, the present application proposes a real-time control method and system for coal flow of a working face based on video monitoring, 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; inputting the image information into a pre-trained coal flow recognition model to identify the coal flow information within a preset range of the scraper conveyor in the working face; using a host computer in the working face to collect coal flow information within each preset range 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 scraper conveyor of the working face into a pre-trained coal flow load model to obtain the control command value of the action of the hydraulic support 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 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, the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled, thereby performing real-time control of the coal flow of the working face. The technical solution provided by the present invention can dynamically monitor 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.

[0067] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0068] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0069] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in the field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A real-time control method for coal flow at a working face based on video monitoring, It is characterized in that The method comprises: The image information within the preset range of the scraper conveyor in the working surface is collected in real time by a camera arranged on the hydraulic support; Inputting the image information into a pre-trained coal flow recognition model to identify the coal flow information within a preset range of the scraper conveyor in the working face; The upper computer in the working face collects the coal flow information within each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor in the working face; Input the instantaneous coal flow of the scraper conveyor of the working face into the pre-trained coal flow load model to obtain 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 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, the hydraulic support action in the working face, the speed of the coal mining machine and the speed of the scraper conveyor are controlled, thereby controlling the coal flow rate of the working face in real time; The coal flow information within the preset range of the scraper conveyor in the working face includes: the coal flow within the preset range, the presence or absence of large coal, the time and the frame number of the corresponding hydraulic support within the preset range; The image information is input into a pre-trained coal flow recognition model. When a large piece of coal is recognized to appear within the preset range of the scraper conveyor in the working face, the coal mining machine and the scraper conveyor are stopped, and a manual process is called; Input the instantaneous coal flow of the scraper conveyor of the working face into the pre-trained coal flow load model to obtain 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, which also includes: Step 1: Determine whether the coal flow state to which the instantaneous coal flow of the scraper conveyor of the working face at the current moment belongs is the same as the coal flow state to which the instantaneous coal flow of the scraper conveyor of the working face at the previous moment belongs, and the coal flow state includes: overload state, full load state, excessive state, moderate state, small amount state and very small amount state; Step 2: If the instantaneous coal flow at the current moment is different from the coal flow state of the instantaneous coal flow at the previous moment, proceed to step 3, otherwise return to step 1; Step 3: Input the instantaneous coal flow of the scraper conveyor of the working face into the pre-trained coal flow load model to obtain 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.

2. The method according to claim 1, It is characterized in that The method of using the upper computer in the working face to collect coal flow information within each preset range in the working face to determine the instantaneous coal flow of the scraper conveyor in the working face includes: Determine the instantaneous coal flow rate of the scraper conveyor at the working face at time t by the following formula: : In the formula, is the instantaneous coal flow at time t captured by the camera on the i-th hydraulic support, is the total number of hydraulic supports in the working face.

3. A real-time control system for coal flow at the working face based on video monitoring, It is characterized in that The system comprises: at least one hydraulic support, at least one intelligent wireless gateway arranged below the top beam of the hydraulic support, and at least one host computer, wherein an artificial intelligence AI chip device is integrated in the intelligent wireless gateway; The intelligent wireless gateway is equipped with a rotatable camera, which is used to collect images within a preset range of the scraper conveyor in the working surface; The artificial intelligence AI chip device is used to receive images captured by the rotatable camera, and based on the captured images, identify coal flow information within a preset range of the scraper conveyor in the working face; The host computer is used to receive the coal flow information within the preset range of the scraper conveyor in the identified working face, and generate control instructions based on the coal flow information to control the action of the hydraulic support in the working face, the speed of the coal mining machine and the speed of the scraper conveyor, thereby controlling the coal flow of the working face in real time; The artificial intelligence AI chip device is provided with a pre-trained coal flow recognition model, which is used to collect image information within a preset range of the scraper conveyor in the working face in real time according to the camera, and identify the coal flow information within the preset range of the scraper conveyor in the working face; when a large piece of coal is identified within the preset range of the scraper conveyor in the working face, the identified information is reported to the host computer, and a call is made for manual processing; The host computer is also used for: step 1: judging whether the coal flow state to which the instantaneous coal flow of the scraper conveyor of the working face belongs at the current moment is the same as the coal flow state to which the instantaneous coal flow of the scraper conveyor of the working face belongs at the previous moment, and the coal flow state includes: overload state, full load state, excessive state, moderate state, small amount state and very small state; Step 2: If the instantaneous coal flow at the current moment is different from the coal flow state of the instantaneous coal flow at the previous moment, proceed to step 3, otherwise return to step 1; Step 3: Input the instantaneous coal flow of the scraper conveyor of the working face into the pre-trained coal flow load model to obtain 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.

4. The system according to claim 3, It is characterized in that The host computer is provided with a pre-trained coal flow load model, which is used to determine 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 according to the instantaneous coal flow of the scraper conveyor of the working face.

5. The system according to claim 4, It is characterized in that The instantaneous coal flow rate of the scraper conveyor of the working face is determined based on the coal flow rate information within each preset range in the working face collected by the host computer.

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