Automatic operation and maintenance management method and system based on belt operation state

Abstract

The invention provides an automatic operation and maintenance management method and system based on a belt operation state, and the method comprises the steps: collecting a first belt operation image of a belt in a preset length segment based on a preset image collection device, and carrying out the binarization processing of the first belt operation image, and obtaining a second belt operation image; obtaining gravity data of a plurality of gravity sensors corresponding to the belt length section where the first belt operation image is located, and constructing a gravity distribution image based on the gravity data; determining a material thickness parameter of each position in the second belt operation image based on the gravity distribution image to obtain a third belt operation image; determining the gravity center position of each length position in a preset length section based on the gravity distribution image; and determining the leakage risk of each length position in each preset length section based on the third belt running image and the gravity center position of each length position in the preset length section.

Description

Technical Field

[0001] This invention relates to the field of conveyor belt operation and maintenance technology, and in particular to an automated operation and maintenance management method and system based on the belt's operating status. Background Technology

[0002] In the coal mining, washing, transportation, and thermal power generation industry chain, the coal conveyor belt serves as the "artery" connecting various production nodes, and its operating status directly affects the continuity of coal supply, production safety, and economic benefits. Due to the flammable, explosive, and highly corrosive properties of coal, and the complex working conditions involving high loads, long distances, and high dust levels during transportation, real-time monitoring of the conveyor belt is of irreplaceable importance.

[0003] Coal transport equipment operates under high loads and highly corrosive environments for extended periods. Traditional "periodic maintenance" methods can easily lead to over-maintenance or missed inspections. Therefore, traditional monitoring of conveyor belts often relies on "periodic maintenance." However, this method often suffers from significant delays, making it difficult to provide real-time feedback on the conveyor belt's operating status. If the conveyor belt malfunctions, cargo spillage can easily occur. Therefore, real-time feedback on the conveyor belt's operating status is equally important.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide an automated operation and maintenance management method and system based on the belt running status. This solution can perform real-time monitoring during belt operation and provide real-time feedback on the leakage risk at each length position.

[0006] This invention provides an automated operation and maintenance management method based on the belt conveyor's operating status, the method comprising the following steps: The first belt running image is acquired by a preset image acquisition device at a predetermined length, and the first belt running image is binarized to obtain the second belt running image. Gravity data from multiple gravity sensors corresponding to the belt length segment in the first belt running image are obtained, and a gravity distribution image is constructed based on the gravity data; Based on the gravity distribution image, the material thickness parameters at each position in the second belt running image are determined to obtain the third belt running image; The center of gravity position of each length location in the predetermined length segment is determined based on the gravity distribution image. The risk of spillage at each length position in each predetermined length segment is determined based on the third belt running image and the center of gravity position at each length position in the predetermined length segment.

[0007] Using the above scheme, this scheme collects real-time images of the first belt running along the same length segment and gravity sensor data. The gravity sensor data is used to determine the gravity distribution image, and the first belt running image is optimized using the gravity distribution image to obtain the third belt running image. The material thickness at each position is marked in the third belt running image. Combined with the center of gravity position determined by the gravity distribution image at each length position, the spillage risk at each length position is determined. This scheme can perform real-time monitoring during belt operation and provide real-time feedback on the spillage risk at each length position.

[0008] In some embodiments of the present invention, in the step of acquiring a first belt running image of a belt at a predetermined length based on a preset image acquisition device, and performing binarization processing on the first belt running image to obtain a second belt running image, the first belt running image is binarized based on a preset pixel threshold to obtain a second belt running image marked with material areas and blank areas.

[0009] By adopting the above scheme, the initial first belt running image is binarized, which can clearly distinguish between areas with material and areas without material, reduce image complexity, and ensure the efficiency of subsequent processing.

[0010] In some embodiments of the present invention, in the step of acquiring gravity data from multiple gravity sensors corresponding to the belt length segment where the first belt running image is located, and constructing a gravity distribution image based on the gravity data, for each image position in the gravity distribution image, a weighted calculation is performed based on the positions of a preset number of gravity sensors closest to that image position and the corresponding gravity data to obtain the rendering value of the image position in the gravity distribution image.

[0011] In some embodiments of the present invention, in the step of determining the rendering value of the image position in the gravity distribution image by performing a weighted calculation based on the preset number of gravity sensor positions closest to the image position and the corresponding gravity data, the gravity influence value of the image position is obtained by performing a weighted calculation based on the preset number of gravity sensor positions closest to the image position and the corresponding gravity data, and the corresponding rendering value is obtained by comparing the gravity influence value.

[0012] In some embodiments of the present invention, in the step of calculating the gravity influence value of the image location by weighting the gravity sensor locations and corresponding gravity data of the nearest preset number of gravity sensor locations, the gravity influence value of each image location in the gravity distribution image is calculated using the following formula:

[0013] in, This indicates the influence of gravity. This indicates the preset quantity. Indicates the first The distance between each gravity sensor and the target's image position. Indicates the first Gravity data from a gravity sensor.

[0014] Using the above scheme, the weight of the goods on the belt is measured by gravity sensors evenly arranged under the belt. Multiple gravity sensors are used to jointly sense the gravity at each position on the belt surface to determine the gravity. Then, the pixel value corresponding to the gravity at each position is rendered to construct a gravity distribution image. By constructing a gravity distribution image, the force at each position can be determined more accurately, ensuring the processing precision of the scheme.

[0015] In some embodiments of the present invention, in the step of determining the material thickness parameter at each position in the second belt running image based on the gravity distribution image to obtain the third belt running image, the corresponding material thickness parameter is determined based on the pixel value of each pixel in the gravity distribution image to obtain the third belt running image.

[0016] Using the above scheme, the area where the material is located is first delineated in the second belt running image. Then, the thickness of each position in the area where the material exists in the second belt running image is determined by the gravity information of each position in the gravity distribution image. On the one hand, the thickness of the material at each position can be accurately calculated. The higher the thickness, the higher the possibility of spillage. On the other hand, areas where there is no material in the second belt running image are not included in the calculation, which can reduce the amount of calculation.

[0017] In some embodiments of the present invention, the center of gravity position of each length position in a predetermined length segment is determined based on the gravity distribution image. The gravity distribution image is input into a preset first neural network model. The first neural network outputs a center of gravity position vector. Each dimension of the center of gravity position vector corresponds to a length position in the predetermined length segment, and the value of the dimension corresponds to the center of gravity position of that length position.

[0018] Using the above method, the center of gravity position at each length is calculated. The greater the deviation of the center of gravity from the center line of the belt, the higher the possibility of leakage, thus ensuring the accuracy of subsequent leakage risk calculations.

[0019] In some embodiments of the present invention, the step of determining the spillage risk at each length position in each predetermined length segment based on the third belt running image and the center of gravity position at each length position in the predetermined length segment includes: Calculate the relative distance between the width position of the maximum thickness at each length location and the centerline of the belt; A spill risk value is calculated based on the relative distance value and the maximum thickness at each length position, and the spill risk is determined based on the spill risk value.

[0020] In some embodiments of the present invention, the step of determining the leakage risk of each length position in each predetermined length segment based on the third belt running image and the center position of each length position in the predetermined length segment further includes calculating the deviation distance between the center position of each length position and the belt centerline. If the deviation distance is greater than a distance threshold, it is directly determined that there is a leakage risk at that length position.

[0021] Using the above scheme, this scheme adopts a two-stage processing method. In the first stage of processing, the position of the center of gravity is directly used for judgment. If the center of gravity deviates too much, it is directly determined that there is a risk of spillage. If the center of gravity deviates only slightly, the second stage of processing is carried out. In the second stage of processing, the spillage risk value is calculated by using the relative distance value and the maximum thickness value at each length position, thereby determining whether there is a risk of spillage.

[0022] In some embodiments of the present invention, in the step of calculating the spill risk based on the relative distance value and the maximum thickness at each length position, the spill risk value is calculated using the following formula:

[0023] in, Indicates length position The risk value of leakage, and All of these are pre-set weight parameters. Indicates length position The maximum thickness, Indicates length position The relative distance value, This indicates the width of the belt.

[0024] In some embodiments of the present invention, the method further includes the following steps: When it is determined that there is a risk of spillage in the predetermined length segment, obtain the time point of the previous determination that there was a risk of spillage; The time interval is calculated based on the previous time point when a spill risk was determined and the current time point; Calculate the distance interval based on the time interval and belt speed; The joint leakage risk value is calculated based on the distance interval, and a joint early warning is determined based on the joint leakage risk value.

[0025] In some embodiments of the present invention, in the step of calculating the joint spill risk value based on the distance interval, the joint spill risk value is calculated using the following formula:

[0026] in, Indicates the joint leakage risk value. This indicates the leakage risk value at the current point in time. This represents the spill risk value from the previous assessment that indicated a risk of spillage. Indicates a distance interval. Using the above scheme, when a predetermined length segment is determined to have a risk of spillage, if the two spillage locations are too close together, it can easily lead to further shift in the center of gravity and further aggravate the spillage. This scheme makes a joint judgment based on the location where there was a risk of spillage in the previous instance. The closer the distance, the greater the weight, and the greater the final calculated joint spillage risk value, thus ensuring the accuracy of the calculation.

[0027] In some embodiments of the present invention, in the step of obtaining the time point at which the previous determination of the risk of leakage was made, the width position of the maximum thickness of the predetermined length segment at which the risk of leakage was determined twice is obtained, and it is determined whether the two width positions are on the same side of the belt centerline.

[0028] Using the above scheme, in the process of determining the joint spillage risk, the scheme first determines whether the width position of the maximum thickness of the predetermined length segment where the spillage risk exists in two determinations is on the same side of the belt centerline. If they are not on the same side, they can maintain a certain balance, and there is no need to calculate the joint spillage risk value in the future, thus saving computational resources. If they are on the same side, it is easy to cause further shift of the center of gravity, which will further aggravate the spillage situation, and further calculation is required.

[0029] Another aspect of the present invention relates to an automated operation and maintenance management system based on the belt running status. The system includes a computer device, which includes a processor and a memory. The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method.

[0030] In summary, the present invention has the following beneficial effects: 1. This solution acquires real-time images of the first belt running along the same length segment and data from gravity sensors. The gravity sensor data is used to determine a gravity distribution image, which is then used to optimize the first belt running image to obtain a third belt running image. The third belt running image marks the material thickness at each location. Combined with the center of gravity position determined from the gravity distribution image, the spillage risk at each length location is determined. This solution enables real-time monitoring and feedback of the spillage risk at each length location during belt operation. 2. This solution measures the weight of goods on the belt by evenly distributing gravity sensors under the belt and uses multiple gravity sensors to jointly sense the gravity at each position on the belt surface. Then, it renders the pixel value corresponding to the gravity at each position to construct a gravity distribution image. By constructing a gravity distribution image, the force at each position can be determined more accurately, ensuring the processing precision of the solution. 3. This solution first delineates the area where the material is located in the second belt conveyor image, and then determines the thickness of each position in the area where the material exists in the second belt conveyor image by using the gravity information of each position in the gravity distribution image. On the one hand, it can accurately calculate the thickness of the material at each position. The higher the thickness, the higher the possibility of spillage. On the other hand, areas where there is no material in the second belt conveyor image are not included in the calculation, which can reduce the amount of calculation. 4. This solution adopts a two-stage processing method. In the first stage, the position of the center of gravity is directly used for judgment. If the center of gravity deviates too much, it is directly determined that there is a risk of spillage. If the center of gravity deviates only slightly, the second stage of processing is carried out. In the second stage, the spillage risk value is calculated by using the relative distance value and the maximum thickness value at each length position, thereby determining whether there is a risk of spillage. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the first embodiment of the automated operation and maintenance management method based on belt operating status of the present invention; Figure 2 This is a schematic diagram of the second embodiment of the automated operation and maintenance management method based on belt operating status of the present invention; Figure 3 This is a schematic diagram of the third embodiment of the automated operation and maintenance management method based on belt operating status of the present invention; Figure 4 This is a schematic diagram of the fourth embodiment of the automated operation and maintenance management method based on belt running status of the present invention. Detailed Implementation

[0033] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of systems and methods consistent with some aspects of the invention as detailed in the appended claims.

[0034] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular forms “a,” “the,” and “the” used in this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0035] like Figure 1 As shown, this invention provides an automated operation and maintenance management method based on the belt's operating status. The steps of the method include: Step S100: Acquire a first belt running image of the belt at a predetermined length using a preset image acquisition device, and perform binarization processing on the first belt running image to obtain a second belt running image; In the specific implementation process, the first belt running image is binarized, and the area where there is material is marked as black and the area where there is no material is marked as white, to obtain the second belt running image.

[0036] In some embodiments of the present invention, the first belt running image of the belt at a predetermined length segment is obtained by acquiring images through multiple image acquisition devices based on preset image acquisition devices, and the acquired images are subjected to preset cropping and splicing processing to obtain the first belt running image of the target predetermined length segment.

[0037] Step S200: Obtain gravity data from multiple gravity sensors for the belt length segment corresponding to the first belt running image, and construct a gravity distribution image based on the gravity data; In the specific implementation process, this solution uses multiple gravity sensors evenly distributed under the belt to provide real-time gravity feedback.

[0038] Step S300: Based on the gravity distribution image, determine the material thickness parameter at each position in the second belt running image to obtain the third belt running image; In the specific implementation process, the higher the gravity value in the gravity distribution image, the higher the material thickness is determined. This solution determines the correspondence between gravity value and material height based on a preset reference table. Specifically, this solution determines the reference table between gravity value and material height based on the density of coal, and quickly matches gravity value and material thickness through the reference table.

[0039] Step S400: Determine the position of the center of gravity at each length position in the predetermined length segment based on the gravity distribution image; In the specific implementation process, the centroid position of each length position is calculated through a pre-trained neural network model.

[0040] Step S500: Based on the third belt running image and the center of gravity position of each length position in the predetermined length segment, determine the leakage risk of each length position in each predetermined length segment.

[0041] Using the above scheme, this scheme collects real-time images of the first belt running along the same length segment and gravity sensor data. The gravity sensor data is used to determine the gravity distribution image, and the first belt running image is optimized using the gravity distribution image to obtain the third belt running image. The material thickness at each position is marked in the third belt running image. Combined with the center of gravity position determined by the gravity distribution image at each length position, the spillage risk at each length position is determined. This scheme can perform real-time monitoring during belt operation and provide real-time feedback on the spillage risk at each length position.

[0042] In some embodiments of the present invention, in the step of acquiring a first belt running image of a belt at a predetermined length based on a preset image acquisition device, and performing binarization processing on the first belt running image to obtain a second belt running image, the first belt running image is binarized based on a preset pixel threshold to obtain a second belt running image marked with material areas and blank areas.

[0043] In practice, areas containing material are rendered as the first pixel value, and areas without material are rendered as the second pixel value. Understandably, the first and second pixel values ​​are different.

[0044] By adopting the above scheme, the initial first belt running image is binarized, which can clearly distinguish between areas with material and areas without material, reduce image complexity, and ensure the efficiency of subsequent processing.

[0045] In some embodiments of the present invention, in the step of acquiring gravity data from multiple gravity sensors corresponding to the belt length segment where the first belt running image is located, and constructing a gravity distribution image based on the gravity data, for each image position in the gravity distribution image, a weighted calculation is performed based on the positions of a preset number of gravity sensors closest to that image position and the corresponding gravity data to obtain the rendering value of the image position in the gravity distribution image.

[0046] In some embodiments of the present invention, in the step of determining the rendering value of the image position in the gravity distribution image by performing a weighted calculation based on the preset number of gravity sensor positions closest to the image position and the corresponding gravity data, the gravity influence value of the image position is obtained by performing a weighted calculation based on the preset number of gravity sensor positions closest to the image position and the corresponding gravity data, and the corresponding rendering value is obtained by comparing the gravity influence value.

[0047] In some embodiments of the present invention, in the step of calculating the gravity influence value of the image location by weighting the gravity sensor locations and corresponding gravity data of the nearest preset number of gravity sensor locations, the gravity influence value of each image location in the gravity distribution image is calculated using the following formula:

[0048] in, This indicates the influence of gravity. This indicates the preset quantity. Indicates the first The distance between each gravity sensor and the target's image position. Indicates the first Gravity data from a gravity sensor.

[0049] In the specific implementation process, this scheme calculates the gravity influence value of each location by jointly using gravity sensor data from multiple locations. For locations that are closer, the influence is greater, and the corresponding weight value is larger. Finally, the gravity influence value of the image location is obtained by superimposing the influence of multiple gravity sensors.

[0050] Using the above scheme, the weight of the goods on the belt is measured by gravity sensors evenly arranged under the belt. Multiple gravity sensors are used to jointly sense the gravity at each position on the belt surface to determine the gravity. Then, the pixel value corresponding to the gravity at each position is rendered to construct a gravity distribution image. By constructing a gravity distribution image, the force at each position can be determined more accurately, ensuring the processing precision of the scheme.

[0051] In some embodiments of the present invention, in the step of determining the material thickness parameter at each position in the second belt running image based on the gravity distribution image to obtain the third belt running image, the corresponding material thickness parameter is determined based on the pixel value of each pixel in the gravity distribution image to obtain the third belt running image.

[0052] Using the above scheme, the area where the material is located is first delineated in the second belt running image. Then, the thickness of each position in the area where the material exists in the second belt running image is determined by the gravity information of each position in the gravity distribution image. On the one hand, the thickness of the material at each position can be accurately calculated. The higher the thickness, the higher the possibility of spillage. On the other hand, areas where there is no material in the second belt running image are not included in the calculation, which can reduce the amount of calculation.

[0053] In some embodiments of the present invention, the center of gravity position of each length position in a predetermined length segment is determined based on the gravity distribution image. The gravity distribution image is input into a preset first neural network model. The first neural network outputs a center of gravity position vector. Each dimension of the center of gravity position vector corresponds to a length position in the predetermined length segment, and the value of the dimension corresponds to the center of gravity position of that length position.

[0054] In the specific implementation process, the first neural network model includes a feature extraction module, a temporal modeling branch module, and a centroid prediction branch module; The feature extraction module includes a first convolutional layer, a max pooling layer, a second convolutional layer, and a global average pooling layer; The first convolutional layer consists of 32 5×5 convolutional kernels, using the ReLU activation function; The max pooling layer uses 2×2 pooling; The second convolutional layer has 64 3×3 convolutional kernels and uses the ReLU activation function.

[0055] The temporal modeling branch module uses an LSTM network; The central prediction branch module uses multiple interconnected fully connected layers, and outputs the centroid position coordinates for each length position through the last fully connected layer.

[0056] Using the above method, the center of gravity position at each length is calculated. The greater the deviation of the center of gravity from the center line of the belt, the higher the possibility of leakage, thus ensuring the accuracy of subsequent leakage risk calculations.

[0057] like Figure 2 As shown, in some embodiments of the present invention, the step of determining the spillage risk at each length position in each predetermined length segment based on the third belt running image and the center of gravity position at each length position in the predetermined length segment includes: Step S520: Calculate the relative distance between the width position of the maximum thickness at each length position and the centerline of the belt. In the specific implementation process, the vertical distance between the maximum thickness position at each length location and the centerline of the belt is calculated as the relative distance value.

[0058] Step S530: Calculate the spill risk value based on the relative distance value and the maximum thickness at each length position, and determine the spill risk based on the spill risk value.

[0059] In the specific implementation process, in the step of determining the leakage risk based on the leakage risk value, the leakage risk value is compared with a preset risk threshold. If it is greater than the preset risk threshold, it is determined that there is a leakage risk at that length position.

[0060] In some embodiments of the present invention, the method further includes, for length locations where there is a risk of spillage, providing feedback on the location information of the location to the staff, and updating the location information in real time based on the speed of the belt, so that the staff can eliminate the risk in a timely manner.

[0061] In the specific implementation process, the entire belt operation image is pre-built on the monitoring terminal of the staff. For the length position with the risk of spillage, a preset color is used to flash. The flashing length position is determined based on the initial feedback position information, and the flashing position is updated in real time based on the belt's running speed.

[0062] In the actual implementation process, each location with a risk of spillage is marked in the operation image of the entire conveyor belt.

[0063] like Figure 3 As shown, in some embodiments of the present invention, the step of determining the leakage risk of each length position in each predetermined length segment based on the third belt running image and the center position of each length position in the predetermined length segment further includes step S510, calculating the deviation distance between the center position of each length position and the belt centerline, and if the deviation distance is greater than the distance threshold, then it is directly determined that there is a leakage risk at that length position.

[0064] Using the above scheme, this scheme adopts a two-stage processing method. In the first stage of processing, the position of the center of gravity is directly used for judgment. If the center of gravity deviates too much, it is directly determined that there is a risk of spillage. If the center of gravity deviates only slightly, the second stage of processing is carried out. In the second stage of processing, the spillage risk value is calculated by using the relative distance value and the maximum thickness value at each length position, thereby determining whether there is a risk of spillage.

[0065] In some embodiments of the present invention, in the step of calculating the spill risk based on the relative distance value and the maximum thickness at each length position, the spill risk value is calculated using the following formula:

[0066] in, Indicates length position The risk value of leakage, and All of these are pre-set weight parameters. Indicates length position The maximum thickness, Indicates length position The relative distance value, This indicates the width of the belt.

[0067] In some embodiments of the present invention, in the step of calculating the spill risk based on the relative distance value and the maximum thickness at each length position, the spill risk value is calculated using the following formula:

[0068] in, For the preset weight parameters, This indicates the speed at which the belt runs.

[0069] Using the above scheme, this scheme further calculates the risk of spillage by combining the belt running speed. The belt running speed also affects the probability of spillage. The faster the belt runs, the greater the vibration and the greater the inertia, which makes it easier for materials to spill.

[0070] like Figure 4 As shown, in some embodiments of the present invention, the method further includes the following steps: Step S610: When it is determined that there is a risk of leakage in the predetermined length segment, obtain the time point of the previous determination that there is a risk of leakage. Step S620: Calculate the time interval based on the previous determination time point where a spill risk was identified and the current time point; Step S630: Calculate the distance interval based on the time interval and belt running speed; Step S640: Calculate the joint leakage risk value based on the distance interval, and determine whether to trigger a joint early warning based on the joint leakage risk value.

[0071] In the specific implementation process, the joint leakage risk value is compared with the preset joint judgment threshold. If it is greater than the preset joint judgment threshold, a joint early warning is triggered.

[0072] In some embodiments of the present invention, in the step of calculating the joint spill risk value based on the distance interval, the joint spill risk value is calculated using the following formula:

[0073] in, Indicates the joint leakage risk value. This indicates the leakage risk value at the current point in time. This represents the spill risk value from the previous assessment that indicated a risk of spillage. Indicates distance interval.

[0074] Using the above scheme, when a predetermined length segment is determined to have a risk of spillage, if the two spillage locations are too close together, it can easily lead to further shift in the center of gravity and further aggravate the spillage. This scheme makes a joint judgment based on the location where there was a risk of spillage in the previous instance. The closer the distance, the greater the weight, and the greater the final calculated joint spillage risk value, thus ensuring the accuracy of the calculation.

[0075] In some embodiments of the present invention, in the step of obtaining the time point at which the previous determination of the risk of leakage was made, the width position of the maximum thickness of the predetermined length segment at which the risk of leakage was determined twice is obtained, and it is determined whether the two width positions are on the same side of the belt centerline.

[0076] Using the above scheme, in the process of determining the joint spillage risk, the scheme first determines whether the width position of the maximum thickness of the predetermined length segment where the spillage risk exists in two determinations is on the same side of the belt centerline. If they are not on the same side, they can maintain a certain balance, and there is no need to calculate the joint spillage risk value in the future, thus saving computational resources. If they are on the same side, it is easy to cause further shift of the center of gravity, which will further aggravate the spillage situation, and further calculation is required.

[0077] Another aspect of the present invention relates to an automated operation and maintenance management system based on the belt running status. The system includes a computer device, which includes a processor and a memory. The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method.

[0078] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the aforementioned automated operation and maintenance management method based on belt running status. The computer-readable storage medium can be a tangible storage medium, such as random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, floppy disk, hard disk, removable storage disk, CD-ROM, or any other form of storage medium known in the art.

[0079] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0080] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0081] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0082] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations of the embodiments of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automated operation and maintenance management method based on belt conveyor operating status, characterized in that, The steps of the method include: The first belt running image is acquired by a preset image acquisition device at a predetermined length, and the first belt running image is binarized to obtain the second belt running image. Gravity data from multiple gravity sensors corresponding to the belt length segment in the first belt running image are obtained, and a gravity distribution image is constructed based on the gravity data; Based on the gravity distribution image, the material thickness parameters at each position in the second belt running image are determined to obtain the third belt running image; The center of gravity position of each length location in the predetermined length segment is determined based on the gravity distribution image. The risk of spillage at each length position in each predetermined length segment is determined based on the third belt running image and the center of gravity position at each length position in the predetermined length segment.

2. The automated operation and maintenance management method based on belt operating status according to claim 1, characterized in that, In the step of acquiring a first belt running image of a belt at a predetermined length using a preset image acquisition device and binarizing the first belt running image to obtain a second belt running image, the first belt running image is binarized based on a preset pixel threshold to obtain a second belt running image marked with material areas and blank areas.

3. The automated operation and maintenance management method based on belt operating status according to claim 1, characterized in that, In the step of acquiring gravity data from multiple gravity sensors corresponding to the belt length segment where the first belt running image is located, and constructing a gravity distribution image based on the gravity data, for each image position in the gravity distribution image, a weighted calculation is performed based on the positions of a preset number of gravity sensors closest to that image position and the corresponding gravity data to obtain the rendering value of the image position in the gravity distribution image.

4. The automated operation and maintenance management method based on belt operating status according to claim 3, characterized in that, In the step of determining the rendering value of the image position in the gravity distribution image by performing a weighted calculation based on the preset number of gravity sensor positions closest to the image position and the corresponding gravity data, the gravity influence value of the image position is obtained by performing a weighted calculation based on the preset number of gravity sensor positions closest to the image position and the corresponding gravity data, and the corresponding rendering value is obtained by comparing the gravity influence value.

5. The automated operation and maintenance management method based on belt operating status according to claim 4, characterized in that, In the step of calculating the gravity influence value of the image location by weighting the gravity sensor locations and corresponding gravity data of the nearest preset number of gravity sensor locations, the gravity influence value of each image location in the gravity distribution image is calculated using the following formula: ； in, This indicates the influence of gravity. This indicates the preset quantity. Indicates the first The distance between each gravity sensor and the target's image position. Indicates the first Gravity data from a gravity sensor.

6. The automated operation and maintenance management method based on belt operating status according to claim 1, characterized in that, In the step of determining the material thickness parameter at each position in the second belt running image based on the gravity distribution image to obtain the third belt running image, the corresponding material thickness parameter is determined based on the pixel value of each pixel in the gravity distribution image to obtain the third belt running image.

7. The automated operation and maintenance management method based on belt operating status according to claim 1, characterized in that, In the step of determining the center of gravity position of each length position in a predetermined length segment based on the gravity distribution image, the gravity distribution image is input into a preset first neural network model, and the first neural network outputs a center of gravity position vector. Each dimension of the center of gravity position vector corresponds to a length position in the predetermined length segment, and the value of the dimension corresponds to the center of gravity position of that length position.

8. The automated operation and maintenance management method based on belt operating status according to any one of claims 1-7, characterized in that, The step of determining the leakage risk at each length position in each predetermined length segment based on the third belt running image and the center of gravity position at each length position in the predetermined length segment includes: Calculate the relative distance between the width position of the maximum thickness at each length location and the centerline of the belt; A spill risk value is calculated based on the relative distance value and the maximum thickness at each length position, and the spill risk is determined based on the spill risk value.

9. The automated operation and maintenance management method based on belt operating status according to claim 8, characterized in that, In the step of calculating the spill risk based on the relative distance value and the maximum thickness at each length location, the spill risk value is calculated using the following formula: ； in, Indicates length position The risk value of leakage, and All of these are pre-set weight parameters. Indicates length position The maximum thickness, Indicates length position The relative distance value, This indicates the width of the belt.

10. The automated operation and maintenance management method based on belt operating status according to claim 1, characterized in that, The method further includes the following steps: When it is determined that there is a risk of spillage in the predetermined length segment, obtain the time point of the previous determination that there was a risk of spillage; The time interval is calculated based on the previous time point when a spill risk was determined and the current time point; Calculate the distance interval based on the time interval and belt speed; The joint leakage risk value is calculated based on the distance interval, and a joint early warning is determined based on the joint leakage risk value.

11. The automated operation and maintenance management method based on belt operating status according to claim 10, characterized in that, In the step of calculating the joint spill risk value based on the distance interval, the joint spill risk value is calculated using the following formula: ； in, Indicates the joint leakage risk value. This indicates the leakage risk value at the current point in time. This represents the spill risk value from the previous assessment that there was a risk of spillage. Indicates distance interval.

12. The automated operation and maintenance management method based on belt operating status according to claim 10, characterized in that, In the step of obtaining the time point at which the previous judgment of the risk of leakage was determined, the width position of the maximum thickness of the predetermined length segment at which the risk of leakage was determined in the two previous determinations is obtained, and it is determined whether the two width positions are on the same side of the belt centerline.

13. An automated operation and maintenance management system based on belt conveyor operating status, characterized in that: The system includes a computer device, which includes a processor and a memory. The memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method according to any one of claims 1-12.

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