Conveying belt inclination monitoring system and monitoring method

Abstract

The invention relates to the technical field of conveying belt inclination monitoring, in particular to a conveying belt inclination monitoring system and method, and the system comprises a monitoring point laying module, a data collection module, a data monitoring analysis module, an inclination judgment module and a display terminal. According to the method, the three-dimensional structure data of the conveying belt is obtained, the three-dimensional model is constructed, the data collectors are arranged on the two sides, the key area and the key position of the three-dimensional model respectively, the monitoring point set is formed, the running state information of the conveying belt is obtained through the monitoring point set, and the running state information is analyzed and processed; according to the method, the first evaluation index, the second evaluation index and the third evaluation index are obtained, the evaluation indexes are normalized, the comprehensive evaluation value of the conveying belt is calculated, and accordingly the inclination abnormity level is determined, so that accurate monitoring and real-time early warning are achieved, and the safety and stability of the conveying belt are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of conveyor belt inclination monitoring, and specifically to a conveyor belt inclination monitoring system and a monitoring method. Background Art

[0002] In modern industrial production and logistics transportation processes, the conveyor belt system, as the core equipment for material transportation, is widely used in multiple fields such as mines, ports, manufacturing, and warehousing. However, during long-term operation, the conveyor belt may tilt due to factors such as mechanical wear, material accumulation, support deformation, and external interference, resulting in a decrease in transportation efficiency and even causing equipment damage and safety accidents. Therefore, real-time monitoring of the inclination state of the conveyor belt and taking warning measures are of great significance for ensuring production safety and improving the operational stability of equipment; Currently, the inclination monitoring of conveyor belts mainly relies on manual inspections and single fixed-point detections. However, the manual inspection method has problems such as low efficiency and poor real-time performance, and it is difficult to meet the continuous monitoring requirements of large-scale transportation; the traditional fixed-point monitoring method only covers some key positions, with a limited monitoring range, easily forming monitoring blind spots, resulting in inaccurate inclination monitoring of the conveyor belt, prone to misjudgment, lacking the ability to perceive the overall operating state of the conveyor belt in real time, and it is difficult to comprehensively grasp the inclination of the conveyor belt, thus affecting the safety and stability of the conveyor belt; To solve the above defects, a technical solution is provided now. Summary of the Invention

[0003] The purpose of the present invention is to solve the problems that the traditional conveyor belt inclination monitoring mainly relies on manual inspections and single fixed-point detections, which cannot meet the continuous monitoring requirements of large-scale transportation, nor can it comprehensively grasp the inclination of the conveyor belt and give timely and accurate warnings, and to propose a conveyor belt inclination monitoring system and a monitoring method.

[0004] The purpose of the present invention can be achieved through the following technical solutions: A conveyor belt inclination monitoring system, comprising: A monitoring point layout module, used to obtain the three-dimensional structure data of the conveyor belt and construct a three-dimensional model, and respectively deploy data collectors on both sides, key areas, and key parts of the three-dimensional model to form a monitoring point set; A data acquisition module, used to collect the operating state information of the conveyor belt through the monitoring point set; A data monitoring and analysis module, used to monitor and analyze the operating state information of the conveyor belt to obtain the operating evaluation parameters of the conveyor belt. The operating evaluation parameters include a first evaluation index, a second evaluation index, and a third evaluation index, where: The first evaluation index is calculated by a first unit according to the offset volume between the left and right edge position coordinates and the reference baseline; The key area image is divided into grids and the coverage area is analyzed by the second unit, and the second evaluation index is calculated based on the total coverage area values of the materials in the left and right areas of the abnormal image sequence; The real-time vibration waveform is compared with the reference vibration waveform by the third unit, and the coincidence length value, amplitude deviation value and peak number ratio are extracted to calculate the third evaluation index; The inclination determination module is used to normalize the first evaluation index, the second evaluation index and the third evaluation index to obtain a comprehensive evaluation value, and accordingly determine the inclination abnormal level.

[0005] Furthermore, the process of arranging the monitoring point set is as follows: In the 3D model, data collectors are arranged on both sides of the conveyor belt at intervals of K1 meters to form the first monitoring point set of the conveyor belt; In the 3D model, data collectors are arranged for the key area to form the second monitoring point set of the conveyor belt; In the 3D model, data collectors are arranged for the key parts to form the third monitoring point set of the conveyor belt; The monitoring point set is jointly composed of the first monitoring point set, the second monitoring point set and the third monitoring point set of the conveyor belt.

[0006] Furthermore, the process of collecting the operating state information of the conveyor belt is as follows: The edge state parameters of the conveyor belt are collected through the first monitoring point in the monitoring point set to obtain the edge state parameters of the conveyor belt; The material state parameters of the key area of the conveyor belt are collected through the second monitoring point in the monitoring point set to obtain the material state parameters of the conveyor belt; The vibration state parameters of the key parts of the conveyor belt are collected through the third monitoring point in the monitoring point set to obtain the vibration state parameters of the conveyor belt; The operating state information is composed of the edge state parameters, material state parameters and vibration state parameters of the conveyor belt.

[0007] Furthermore, the solution process of the first evaluation index is as follows: The edge position coordinate data on the left and right sides of the conveyor belt are extracted in real time to form the left coordinate point set and the right coordinate point set of the conveyor belt; The starting point of the conveyor belt is selected as the reference point, a global coordinate system is established, and the left coordinate point set and the right coordinate point set of the conveyor belt are subjected to coordinate transformation and uniformly mapped into the global coordinate system; The midpoint line of the conveyor belt in the normal state is selected as the reference baseline, and the position coordinate data of the reference baseline are extracted and also mapped into the global coordinate system; Thus, a dynamic coordinate system for the edge change of the conveyor belt is constructed; Extract the edge position coordinates on the left and right sides and the position coordinates of the reference baseline corresponding to each monitoring time point from the dynamic coordinate system of the conveyor belt edge. At each monitoring time point, calculate the offset cross-sectional area of the left and right sides of the conveyor belt edge relative to the reference baseline. According to the calculated offset cross-sectional area, further calculate the offset volume formed by the left and right sides of the conveyor belt edge relative to the reference baseline. Add up the offset volumes formed by the left and right sides of the conveyor belt edge relative to the reference baseline to obtain the first evaluation index of the conveyor belt.

[0008] Furthermore, the process of grid division and coverage area analysis for the key area image is as follows: Extract the video stream of the key area of the conveyor belt in real time, perform frame-by-frame segmentation extraction on the video stream of the key area of the conveyor belt to form a series of static image frames, and preprocess the extracted image frames. Adopt the uniform grid division method to divide the preprocessed image area into rectangular grid cells, identify the edge of the material area, and calculate the coverage ratio of the material in each grid cell. Set the grid determination rule as: if the material coverage area ≥ 50% of the grid cell, then set the coverage area value of this grid cell to 1. If the material coverage area < 50% of the grid cell, then set the coverage area value of this grid cell to 0.

[0009] Furthermore, the screening process for the abnormal image sequence is as follows: Statistically calculate the coverage area values of all grid cells in the image to obtain the total coverage area value of the material in the image. Compare and analyze the total coverage area value of the material in the image with the set reference comparison interval. If the total coverage area value of the material in the image exceeds the set reference comparison interval, then determine that this image is an abnormal image. According to the time stamp of the abnormal image, sort the abnormal images in time series to obtain the abnormal image sequence.

[0010] Furthermore, the solution process for the second evaluation index is as follows: Symmetrically divide the abnormal image with the center line of the abnormal image to divide the abnormal image into a left area and a right area, and respectively extract the total coverage area values of the materials in the left area and the right area to obtain the total coverage area values of the materials in the left area and the right area of the abnormal image, and mark them as F 左r y and F 右r y ; According to the formula: , calculate the second evaluation index δ2 of the conveyor belt; Among them, y represents the number of abnormal images, g represents the total number of abnormal image numbers, r represents the number of key areas of the conveyor belt, r* represents the total number of key area numbers of the conveyor belt, and F 左r y-1 represents the total coverage area value of the materials in the left area of the (y - 1)-th frame abnormal image, and F 右r y-1 represents the total coverage area value of the materials in the right area of the (y - 1)-th frame abnormal image, and ΔF r represents the set reference coverage ratio value, η1 and η2 respectively represent the weight coefficients of the coverage ratio difference of the materials in the left area and the right area and the total area change rate, and η1 > η2, and f1 and f2 respectively represent the correction factor coefficients of the area change rate of the materials in the left area and the right area.

[0011] Furthermore, the solution process of the third evaluation index is as follows: Extract the vibration signal of the key part of the conveyor belt in real time, and generate the vibration waveform diagram of the key part of the conveyor belt through specific software. At the same time, extract the reference vibration waveform diagram of the key part of the conveyor belt from the system repository, and perform an overlapping operation on the vibration waveform diagram of the key part of the conveyor belt and the reference vibration waveform diagram to obtain the vibration waveform overlapping diagram of the key part of the conveyor belt; Extract the overlapping length value, amplitude deviation value and peak number ratio from the vibration waveform overlapping diagram of the key part of the conveyor belt, and thereby calculate the third evaluation index of the conveyor belt; Among them, the overlapping length value refers to the time alignment length of the measured vibration waveform and the reference vibration waveform within the allowable error threshold; The amplitude deviation value refers to the difference between the maximum amplitude of the measured vibration waveform and the maximum amplitude of the reference vibration waveform. The peak number ratio refers to the ratio of the number of peaks of the measured vibration waveform to the number of peaks of the reference vibration waveform.

[0012] Furthermore, the analysis process for determining the tilt anomaly level is as follows: Compare and analyze the comprehensive evaluation value of the conveyor belt with the preset comprehensive evaluation threshold. When the comprehensive evaluation value of the conveyor belt is greater than or equal to the preset comprehensive evaluation threshold, the conveyor belt is determined to be in a tilt anomaly state; If the conveyor belt is determined to be in a tilt anomaly state, retrieve the comprehensive evaluation value of the conveyor belt, and subtract it from the preset comprehensive evaluation threshold to obtain the comprehensive evaluation difference of the conveyor belt. Then match the comprehensive evaluation difference of the conveyor belt with the comprehensive evaluation difference corresponding to the set tilt anomaly level to obtain the tilt anomaly level of the conveyor belt.

[0013] Furthermore, a conveyor belt tilt monitoring method includes the following steps: Step 1: Obtain the three-dimensional structure data of the conveyor belt and construct a three-dimensional model. Data collectors are arranged on both sides, key areas, and key parts of the three-dimensional model respectively to form a set of monitoring points. Step 2: Collect the operating status information of the conveyor belt through the set of monitoring points. Step 3: Monitor and analyze the operating status information of the conveyor belt to obtain the operating evaluation parameters of the conveyor belt. The operating evaluation parameters include a first evaluation index, a second evaluation index, and a third evaluation index, where: The first evaluation index is calculated by the first unit according to the offset volume between the left and right edge position coordinates and the reference baseline. The second unit divides the key area image into grids and analyzes the coverage area, and calculates the second evaluation index based on the total coverage area value of the materials in the left and right areas of the abnormal image sequence. The third unit compares the real-time vibration waveform with the reference vibration waveform, and extracts the coincidence length value, amplitude deviation value, and peak number ratio to calculate the third evaluation index. Step 4: Normalize the first evaluation index, the second evaluation index, and the third evaluation index to obtain a comprehensive evaluation value, and determine the tilt abnormality level accordingly.

[0014] The technical solution provided by the present invention has the following beneficial effects compared with the known prior art: 1. In the present invention, a three-dimensional model of the conveyor belt is constructed by using lidar scanning technology, and multi-type data collectors are arranged on both sides, key areas, and key parts of the conveyor belt to form a multi-modal data collection method, which respectively collects the edge offset, material state, and vibration signal of the conveyor belt, ensuring the accuracy and integrity of the monitoring data, thus effectively eliminating the blind area of the traditional monitoring method and realizing the global state monitoring of the conveyor belt, providing reliable data support for subsequent operating status analysis. 2. In the present invention, by calculating and analyzing the edge offset volume of the conveyor belt, the material coverage area of the key area, and the vibration waveform change of the key part, and comprehensively calculating the tilt degree of the conveyor belt in combination with multi-dimensional evaluation parameters, accurate identification is realized, and the intelligent determination of the tilt state of the conveyor belt is completed based on the intelligent analysis algorithm, improving the accuracy and real-time performance of detection. 3. In the present invention, based on the operating evaluation result of the conveyor belt, corresponding warning lights are triggered according to the tilt abnormality level to realize real-time abnormality notification. This warning mechanism can timely remind the operation and maintenance personnel to quickly take countermeasures, thus effectively ensuring the safety and stability of the conveying system, improving the operation efficiency and reducing the accident risk. Description of the Drawings

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is the overall module block diagram of the present invention.

[0017] Figure 2 This is the method flow block diagram of the present invention. Detailed implementation manners

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0019] As Figure 1 shown, a conveyor belt inclination monitoring system includes: a monitoring point layout module, a data acquisition module, a data monitoring and analysis module, an inclination determination module, and a display terminal. Among them, the data monitoring and analysis module includes a first unit, a second unit, and a third unit; The monitoring point layout module is used to perform analysis and processing on the layout of monitoring points for the conveyor belt. The specific analysis process is as follows: Adopt lidar scanning technology to obtain the three-dimensional structure data of the conveyor belt, and construct a three-dimensional model of the conveyor belt based on the obtained data; In the constructed three-dimensional model of the conveyor belt, data collectors are arranged on both sides of the conveyor belt at intervals of K1 meters to form a first monitoring point set of the conveyor belt. Among them, the specific interval value of K1 can be set by those skilled in the art according to the actual length of the conveyor belt. The first monitoring point set is used to monitor the edge position deviation of the conveyor belt, so as to provide high-precision conveyor belt edge monitoring data; In the constructed three-dimensional model of the conveyor belt, data collectors are arranged in key areas (such as transfer points, ramps, turning points, etc.) to form a second monitoring point set of the conveyor belt. The second monitoring point set is used to monitor whether problems such as abnormal material accumulation occur in the key areas of the conveyor belt, so as to provide high-precision conveyor belt key area monitoring data; In the constructed three-dimensional model of the conveyor belt, data collectors are arranged at key parts (such as idlers, driving wheels, tensioning wheels, etc.) to form a third monitoring point set of the conveyor belt. The third monitoring point set is used to monitor the vibration state of key parts, so as to provide high-precision monitoring data of key parts of the conveyor belt; The monitoring point set is jointly composed of the first monitoring point set, the second monitoring point set and the third monitoring point set of the conveyor belt; It should be noted that the data collector includes but is not limited to infrared light curtain sensors, high-definition infrared cameras and vibration sensors; The data acquisition module is used to acquire the operating state information of the conveyor belt through the monitoring point set to obtain the operating state information of the conveyor belt. The specific acquisition process is as follows: Collect the edge state parameters of the conveyor belt through the first monitoring point in the monitoring point set to obtain the edge state parameters of the conveyor belt; Collect the material state parameters of the key area of the conveyor belt through the second monitoring point in the monitoring point set to obtain the material state parameters of the conveyor belt; Collect the vibration state parameters of the key parts of the conveyor belt through the third monitoring point in the monitoring point set to obtain the vibration state parameters of the conveyor belt; The operating state information is composed of the edge state parameters, material state parameters and vibration state parameters of the conveyor belt; The data monitoring and analysis module is used to monitor and analyze the operating state information of the conveyor belt to obtain the operating evaluation parameters of the conveyor belt. The specific monitoring and analysis process is as follows: Monitor and analyze the edge state parameters of the conveyor belt through the first unit to calculate the first evaluation index of the conveyor belt. The specific monitoring and analysis is as follows: Extract the edge position coordinate data on the left and right sides of the conveyor belt in real time to form the left coordinate point set and the right coordinate point set of the conveyor belt; Among them: The edge position coordinate on the left side of the conveyor belt is expressed as: P 左 j (X 左 j ,Y 左 j ,Z 左 j ); The edge position coordinate on the right side of the conveyor belt is expressed as P 右 j ( 右 j ,Y 右 j ,Z 右 j ); The X-axis represents the forward direction of the conveyor belt, the Y-axis represents the left-right direction of the conveyor belt, the Z-axis represents the height direction of the conveyor belt, and j represents the discrete sampling point number; Select the starting point P0 (X0, Y0, Z0) of the conveyor belt as the reference point, establish a global coordinate system, and perform coordinate transformation on the left-side coordinate point set and the right-side coordinate point set of the conveyor belt, and uniformly map them into the global coordinate system; Select the midpoint line of the conveyor belt under normal conditions as the reference baseline, and extract the position coordinate data of the reference baseline, and calibrate it as Q mid j (X mid j , Y mid j , Z mid j ), and map the position coordinate data of the reference baseline into the global coordinate system as well; Thus, construct the dynamic coordinate system for the edge change of the conveyor belt; Extract the edge position coordinates on the left and right sides and the position coordinates of the reference baseline corresponding to each monitoring time point from the dynamic coordinate system for the edge change of the conveyor belt. At each monitoring time point, calculate the offset cross-sectional area of the edge positions on the left and right sides of the conveyor belt relative to the reference baseline; According to the formula: , where i represents the number of each monitoring time point, m represents the total number of discrete sampling points, ΔZ represents the height increment between adjacent sampling points, A 左 i and A 右 i respectively represent the offset cross-sectional areas of the edge positions on the left and right sides corresponding to each monitoring time point relative to the reference baseline; According to the calculated offset cross-sectional area, further calculate the offset volume formed by the edges on the left and right sides of the conveyor belt relative to the reference baseline. According to the formula: , where (X i -X i-1 ) represents the forward distance of the conveyor belt between adjacent monitoring time points, n represents the total number of monitoring time point numbers, V 左 and V 右 respectively represent the offset volumes formed by the edges on the left and right sides of the conveyor belt relative to the reference baseline; Add the offset volumes formed by the edges on the left and right sides of the conveyor belt relative to the reference baseline to calculate the first evaluation index δ1 of the conveyor belt. The first evaluation index δ1 reflects the overall inclination degree of the edges on the left and right sides of the conveyor belt relative to the reference baseline, and the larger the value, the more serious the inclination of the conveyor belt.

[0020] The second unit monitors and analyzes the material state parameters of the conveyor belt and calculates the second evaluation index of the conveyor belt. The specific monitoring and analysis are as follows: Extract the video stream of the key area of the conveyor belt in real time, perform frame-by-frame segmentation and extraction on the video stream of the key area of the conveyor belt to form a series of static image frames, and preprocess the extracted image frames. The preprocessing includes denoising, grayscale conversion, contrast enhancement, and perspective transformation of the images; Adopt the uniform grid division method to divide the preprocessed image area into rectangular grid cells of M×N, use the deep learning object detection technology to identify the edge of the material area, and calculate the coverage ratio of the material in each grid cell; Set the grid judgment rule as: if the material coverage area ≥ 50% of the grid cell, then set the coverage area value of this grid cell to 1; If the material coverage area < 50% of the grid cell, then set the coverage area value of this grid cell to 0; Statistically calculate the coverage area values of all grid cells in the image to obtain the total coverage area value of the material in the image. Compare and analyze the total coverage area value of the material in the image with the set reference comparison interval. If the total coverage area value of the material in the image exceeds the set reference comparison interval, then determine that this image is an abnormal image; According to the time stamps of the abnormal images, sort the abnormal images in time series to obtain an abnormal image sequence; Symmetrically divide the abnormal image with the center line of the abnormal image into a left area and a right area, and respectively extract the total coverage area values of the materials in the left area and the right area to obtain the total coverage area values of the materials in the left area and the right area of the abnormal image, and mark them as F 左r y and F 右r y ; According to the formula: , calculate the second evaluation index δ2 of the conveyor belt, where y represents the number of the abnormal image, g represents the total number of abnormal image numbers, r represents the number of the key area of the conveyor belt, r* represents the total number of the key area numbers of the conveyor belt, F 左r y-1 represents the total coverage area value of the material in the left area of the (y - 1)-th frame abnormal image, F 右r y-1 represents the total coverage area value of the material in the right area of the (y - 1)-th frame abnormal image, ΔF r represents the set reference coverage ratio, η1 and η2 respectively represent the weight coefficients of the coverage ratio difference and the total area change rate of the materials in the left area and the right area, and η1 > η2, f1 and f2 respectively represent the correction factor coefficients of the area change rate of the materials in the left area and the right area.

[0021] The vibration state parameters of the conveyor belt are monitored and analyzed by the third unit to calculate the third evaluation index of the conveyor belt. The specific monitoring and analysis are as follows: The vibration signals of the key parts of the conveyor belt are extracted in real time, and the vibration waveform diagram of the key parts of the conveyor belt is generated by specific software. At the same time, the reference vibration waveform diagram of the key parts of the conveyor belt is extracted from the system repository, and the vibration waveform diagram of the key parts of the conveyor belt is overlapped with the reference vibration waveform diagram to obtain the vibration waveform overlap diagram of the key parts of the conveyor belt; The overlap length value, amplitude deviation value and peak number ratio are extracted from the vibration waveform overlap diagram of the key parts of the conveyor belt, and are respectively marked as Dchcz k 、Dzfpz k and Dfghz k , and according to the formula: , the third evaluation index δ3 of the conveyor belt is calculated, where k represents the number of the key parts of the conveyor belt, k* represents the total number of the key parts of the conveyor belt, and γ1, γ2 and γ3 respectively represent the weight coefficients of the overlap length value, amplitude deviation value and peak number ratio, and γ1 > γ2 > γ3; Among them, the overlap length value refers to the time alignment length of the measured vibration waveform and the reference vibration waveform within the allowable error threshold. The specific solution process is as follows: Set the vibration error allowable threshold ΔGth. When the vibration error at a certain time point t is less than or equal to the vibration error allowable threshold, then the time point t is included in the overlap time interval. Thus, the total length of the overlap time interval is calculated, and the total length of the overlap time interval is proportionally calculated with the time window length of the complete vibration waveform to obtain the overlap length value Dchcz; The larger the overlap length value, the higher the matching degree of the current vibration state and the reference vibration state, and the more stable the conveyor belt runs. On the contrary, it means that the conveyor belt runs unstably and may have the risk of tilting; The amplitude deviation value refers to the difference between the maximum amplitude of the measured vibration waveform and the maximum amplitude of the reference vibration waveform, The peak number ratio refers to the ratio of the number of peaks of the measured vibration waveform to the number of peaks of the reference vibration waveform; The operation evaluation parameters of the conveyor belt are composed of the first evaluation index, the second evaluation index and the third evaluation index of the conveyor belt, and the operation evaluation parameters of the conveyor belt are sent to the tilt determination module; The tilt determination module is used to receive the operation evaluation parameters of the conveyor belt, and thus conduct tilt determination and analysis on the conveyor belt. The specific analysis process is as follows: By extracting the values of the first evaluation index δ1, the second evaluation index δ2 and the third evaluation index δ3 in the operation evaluation parameters of the conveyor belt for normalization processing, according to the formula: , calculate the comprehensive evaluation value PGZ of the conveyor belt, where λ1, λ2, and λ3 respectively represent the exponential factor coefficients of the set first evaluation index, second evaluation index, and third evaluation index; Compare and analyze the comprehensive evaluation value of the conveyor belt with the preset comprehensive evaluation threshold. When the comprehensive evaluation value of the conveyor belt is greater than or equal to the preset comprehensive evaluation threshold, the conveyor belt is determined to be in an abnormal inclination state. On the contrary, when the comprehensive evaluation value of the conveyor belt is less than the preset comprehensive evaluation threshold, the conveyor belt is determined to be in a normal inclination state; If the conveyor belt is determined to be in an abnormal inclination state, retrieve the comprehensive evaluation value of the conveyor belt, subtract it from the preset comprehensive evaluation threshold to obtain the comprehensive evaluation difference of the conveyor belt, and match the comprehensive evaluation difference of the conveyor belt with the comprehensive evaluation difference corresponding to the set abnormal inclination level to obtain the abnormal inclination level of the conveyor belt; The display terminal is used to light the corresponding warning light according to the abnormal inclination level of the conveyor belt to realize the notification and prompt of the abnormal state.

[0022] As Figure 2 shown, a method for monitoring the inclination of a conveyor belt includes the following steps: Step 1: Analyze and process the layout of monitoring points for the conveyor belt. The specific analysis process is as follows: Use lidar scanning technology to obtain the three-dimensional structure data of the conveyor belt, and construct a three-dimensional model of the conveyor belt based on the obtained data; In the constructed three-dimensional model of the conveyor belt, data collectors are arranged on both sides of the conveyor belt at intervals of K1 meters to form the first monitoring point set of the conveyor belt; In the constructed three-dimensional model of the conveyor belt, data collectors are arranged in key areas to form the second monitoring point set of the conveyor belt; In the constructed three-dimensional model of the conveyor belt, data collectors are arranged in key parts to form the third monitoring point set of the conveyor belt; The monitoring point set is jointly composed of the first monitoring point set, the second monitoring point set, and the third monitoring point set of the conveyor belt; Step 2: Collect the operating state information of the conveyor belt through the monitoring point set to obtain the operating state information of the conveyor belt. The specific collection process is as follows: Collect the edge state parameters of the conveyor belt through the first monitoring point in the monitoring point set to obtain the edge state parameters of the conveyor belt; Collect the material state parameters of the key area of the conveyor belt through the second monitoring point in the monitoring point set to obtain the material state parameters of the conveyor belt; Collect the vibration state parameters of the key parts of the conveyor belt through the third monitoring point in the monitoring point set to obtain the vibration state parameters of the conveyor belt; The operating state information is composed of the edge state parameters, material state parameters, and vibration state parameters of the conveyor belt.

[0023] Step 3: Monitor and analyze the operating state information of the conveyor belt to obtain the operating evaluation parameters of the conveyor belt. The specific monitoring and analysis process is as follows: The first unit monitors and analyzes the edge state parameters of the conveyor belt and calculates the first evaluation index of the conveyor belt. The specific monitoring and analysis are as follows: Real-time extract the edge position coordinate data on the left and right sides of the conveyor belt to form the left coordinate point set and the right coordinate point set of the conveyor belt; Select the starting point of the conveyor belt as the reference point, establish a global coordinate system, and perform coordinate transformation on the left coordinate point set and the right coordinate point set of the conveyor belt, and uniformly map them into the global coordinate system; Select the midpoint line of the conveyor belt in the normal state as the reference baseline, and extract the position coordinate data of the reference baseline, and also map the position coordinate data of the reference baseline into the global coordinate system; Thus, construct the dynamic coordinate system for the edge change of the conveyor belt; Extract the edge position coordinates on the left and right sides and the position coordinate of the reference baseline corresponding to each monitoring time point from the dynamic coordinate system for the edge change of the conveyor belt. At each monitoring time point, calculate the offset cross-sectional area of the edge positions on the left and right sides of the conveyor belt relative to the reference baseline; According to the calculated offset cross-sectional area, further calculate the offset volume formed by the edges on the left and right sides of the conveyor belt relative to the reference baseline; Add up the offset volumes formed by the edges on the left and right sides of the conveyor belt relative to the reference baseline to calculate the first evaluation index of the conveyor belt.

[0024] The second unit monitors and analyzes the material state parameters of the conveyor belt and calculates the second evaluation index of the conveyor belt. The specific monitoring and analysis are as follows: Real-time extract the video stream of the key area of the conveyor belt, and perform frame-by-frame segmentation extraction on the video stream of the key area of the conveyor belt to form a series of static image frames, and preprocess the extracted image frames; Adopt the uniform grid division method to divide the preprocessed image area into rectangular grid units, identify the edge of the material area, and calculate the coverage ratio of the material in each grid unit; Set the grid determination rule as: If the material coverage area ≥ 50% of the grid unit, then set the coverage area value of this grid unit to 1; If the material coverage area < 50% of the grid unit, then set the coverage area value of this grid unit to 0; Statistically calculate the covered area values of all grid cells in the image to obtain the total covered area value of the material in the image. Compare and analyze the total covered area value of the material in the image with the set reference comparison range. If the total covered area value of the material in the image exceeds the set reference comparison range, then determine that the image is an abnormal image; According to the timestamps of the abnormal images, sort the abnormal images in time series to obtain an abnormal image sequence; Symmetrically divide the abnormal image with its center line, divide the abnormal image into a left region and a right region, and separately extract the total covered area values of the materials in the left region and the right region to obtain the total covered area values of the materials in the left region and the right region of the abnormal image, and thereby calculate the second evaluation index of the conveyor belt.

[0025] Monitor and analyze the vibration state parameters of the conveyor belt through the third unit, and calculate the third evaluation index of the conveyor belt. The specific monitoring and analysis are as follows: Real-time extract the vibration signals of the key parts of the conveyor belt, and generate a vibration waveform diagram of the key parts of the conveyor belt through specific software. At the same time, extract the reference vibration waveform diagram of the key parts of the conveyor belt from the system repository, and perform a coincidence operation on the vibration waveform diagram of the key parts of the conveyor belt and the reference vibration waveform diagram to obtain a vibration waveform coincidence diagram of the key parts of the conveyor belt; Extract the coincidence length value, amplitude deviation value, and peak number ratio from the vibration waveform coincidence diagram of the key parts of the conveyor belt, and thereby calculate the third evaluation index of the conveyor belt.

[0026] Step Four: Normalize the first evaluation index, the second evaluation index, and the third evaluation index to obtain a comprehensive evaluation value, and compare and analyze it with the preset comprehensive evaluation threshold. When the comprehensive evaluation value of the conveyor belt is greater than or equal to the preset comprehensive evaluation threshold, then determine that the conveyor belt is in an abnormal inclined state; If the conveyor belt is determined to be in an abnormal inclined state, then retrieve the comprehensive evaluation value of the conveyor belt, and take the difference between it and the preset comprehensive evaluation threshold to obtain the comprehensive evaluation difference of the conveyor belt, and match the comprehensive evaluation difference of the conveyor belt with the comprehensive evaluation difference corresponding to the set abnormal inclined level to obtain the abnormal inclined level of the conveyor belt; According to the abnormal inclined level of the conveyor belt, light up the corresponding warning lights to achieve the notification and prompt of the abnormal state.

[0027] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific embodiments. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A conveyor belt inclination monitoring system, characterized in that: include: The monitoring point layout module is used to obtain the three-dimensional structural data of the conveyor belt and build a three-dimensional model. Data collectors are arranged on both sides, key areas and key parts of the three-dimensional model to form a set of monitoring points. A data acquisition module, used to collect the running status information of the conveyor belt through a set of monitoring points; The data monitoring and analysis module is used to monitor and analyze the running status information of the conveyor belt to obtain the running evaluation parameters of the conveyor belt. The running evaluation parameters include the first evaluation index, the second evaluation index and the third evaluation index, wherein: The first unit calculates a first evaluation index according to the offset volume of the left and right edge position coordinates and the reference baseline; The second unit performs grid division and coverage area analysis on the key area image, and calculates the second evaluation index according to the total coverage area value of the left and right area materials of the abnormal image sequence; The real-time vibration waveform is compared with the reference vibration waveform by the third unit, and the overlap length value, the amplitude deviation value and the peak number ratio value are extracted to calculate the third evaluation index; The tilt determination module is used to normalize the first evaluation index, the second evaluation index and the third evaluation index to obtain a comprehensive evaluation value, and determine the tilt abnormality level based on the comprehensive evaluation value.

2. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The deployment process of the monitoring point set is as follows: In the three-dimensional model, data collectors are arranged on both sides of the conveyor belt at an interval of K1 meters to form the first set of monitoring points of the conveyor belt; In the three-dimensional model, data collectors are deployed in key areas to form a second set of monitoring points for the conveyor belt; In the three-dimensional model, data collectors are placed at key locations to form a third set of monitoring points for the conveyor belt; The first monitoring point set, the second monitoring point set and the third monitoring point set of the conveyor belt together constitute a monitoring point set.

3. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The process of collecting the running status information of the conveyor belt is as follows: The edge state parameters of the conveyor belt are collected through the first monitoring point in the monitoring point set to obtain the edge state parameters of the conveyor belt; The material state parameters of the key area of ​​the conveyor belt are collected through the second monitoring point in the monitoring point set to obtain the material state parameters of the conveyor belt; The vibration state parameters of the key parts of the conveyor belt are collected through the third monitoring point in the monitoring point set to obtain the vibration state parameters of the conveyor belt; The operation status information is composed of the edge status parameters, material status parameters and vibration status parameters of the conveyor belt.

4. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The solution process for the first evaluation index is as follows: Extract the edge position coordinate data of the left and right sides of the conveyor belt in real time to form the left and right coordinate point sets of the conveyor belt; The starting point of the conveyor belt is selected as the reference point to establish a global coordinate system, and the left and right coordinate point sets of the conveyor belt are transformed and uniformly mapped to the global coordinate system; The midpoint line of the conveyor belt in a normal state is selected as the reference baseline, and the position coordinate data of the reference baseline is extracted, and the position coordinate data of the reference baseline is also mapped to the global coordinate system; Thus, a dynamic coordinate system of the edge change of the conveyor belt is constructed; Extract the edge position coordinates of the left and right sides corresponding to each monitoring time point and the position coordinates of the reference baseline from the edge change dynamic coordinate system of the conveyor belt, and calculate the offset cross-sectional area of ​​the edge positions of the left and right sides of the conveyor belt relative to the reference baseline at each monitoring time point; Based on the calculated offset cross-sectional area, the offset volume formed by the left and right edges of the conveyor belt relative to the reference datum line is further calculated; The offset volumes formed by the left and right edges of the conveyor belt relative to the reference datum line are added together to obtain the first evaluation index of the conveyor belt.

5. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The process of gridding and coverage area analysis of key area images is as follows: Extract the video stream of the key area of ​​the conveyor belt in real time, segment and extract the video stream of the key area of ​​the conveyor belt frame by frame to form a series of static image frames, and pre-process the extracted image frames; The uniform grid division method is used to divide the preprocessed image area into rectangular grid units, identify the edge of the material area, and calculate the coverage ratio of the material in each grid unit; The grid judgment rule is set as follows: if the material coverage area is ≥ 50% of the grid unit, the coverage area value of the grid unit is set to 1; If the material coverage area is less than 50% of the grid unit, the coverage area value of the grid unit is set to 0.

6. A conveyor belt inclination monitoring system according to claim 5, characterized in that: The screening process for abnormal image sequences is as follows: Count the coverage area values ​​of all grid cells in the image to obtain the total coverage area value of the material in the image, compare and analyze the total coverage area value of the material in the image with the set reference comparison interval, and if the total coverage area value of the material in the image exceeds the set reference comparison interval, the image is determined to be an abnormal image; According to the timestamps of the abnormal images, the abnormal images are sorted in time series to obtain an abnormal image sequence.

7. A conveyor belt inclination monitoring system according to claim 6, characterized in that: The solution process for the second evaluation index is as follows: The abnormal image is divided symmetrically along the center line into the left area and the right area, and the total coverage area values ​​of the materials in the left area and the right area are extracted respectively to obtain the total coverage area values ​​of the materials in the left area and the right area in the abnormal image, and they are marked as F respectively. 左r y and F 右r y ; According to the formula: , calculate the second evaluation index δ2 of the conveyor belt; Where y represents the number of abnormal images, g represents the total number of abnormal image numbers, r represents the number of key areas of the conveyor belt, r* represents the total number of key areas of the conveyor belt, and F 左r y-1 Indicates the total coverage area of ​​the material in the left area of ​​the abnormal image in the y-1th frame, F 右r y-1 Indicates the total coverage area of ​​the material in the right area of ​​the abnormal image in the y-1th frame, ΔF r It represents the set reference coverage ratio, η1 and η2 represent the coverage ratio difference between the materials in the left area and the right area and the weight coefficient of the total area change rate, respectively, and η1>η2, f1 and f2 represent the correction factor coefficients of the area change rate of the materials in the left area and the right area, respectively.

8. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The solution process for the third evaluation index is as follows: Extract the vibration signal of the key part of the conveyor belt in real time, and generate the vibration waveform of the key part of the conveyor belt through specific software. At the same time, extract the reference vibration waveform of the key part of the conveyor belt from the system repository, and overlap the vibration waveform of the key part of the conveyor belt with the reference vibration waveform to obtain the vibration waveform overlap diagram of the key part of the conveyor belt; Extract the overlap length value, amplitude deviation value and peak ratio value from the vibration waveform overlap diagram of the key parts of the conveyor belt, and calculate the third evaluation index of the conveyor belt; The overlap length value refers to the time alignment length between the measured vibration waveform and the reference vibration waveform within the allowable error threshold; The amplitude deviation value refers to the difference between the maximum amplitude of the measured vibration waveform and the maximum amplitude of the reference vibration waveform. The peak ratio refers to the ratio of the number of peaks of the measured vibration waveform to the number of peaks of the reference vibration waveform.

9. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The analytical process for determining the level of tilt anomaly is as follows: Compare and analyze the comprehensive evaluation value of the conveyor belt with the preset comprehensive evaluation threshold value, and when the comprehensive evaluation value of the conveyor belt is greater than or equal to the preset comprehensive evaluation threshold value, the conveyor belt is determined to be in an abnormal tilt state; If the conveyor belt is determined to be in an abnormal tilt state, the comprehensive evaluation value of the conveyor belt is retrieved and subtracted from the preset comprehensive evaluation threshold to obtain the comprehensive evaluation difference of the conveyor belt. The comprehensive evaluation difference of the conveyor belt is then matched with the comprehensive evaluation difference corresponding to the set abnormal tilt level to obtain the abnormal tilt level of the conveyor belt.

10. A conveyor belt inclination monitoring method, applied to a conveyor belt inclination monitoring system according to claim 1, characterized in that: The following steps are involved: Step 1: Obtain the 3D structural data of the conveyor belt and construct a 3D model. Arrange data collectors on both sides, key areas and key parts of the 3D model to form a set of monitoring points. Step 2: Collect the running status information of the conveyor belt through the monitoring point set; Step 3: Monitor and analyze the running status information of the conveyor belt to obtain the running evaluation parameters of the conveyor belt. The running evaluation parameters include a first evaluation index, a second evaluation index and a third evaluation index, where: The first unit calculates a first evaluation index according to the offset volume of the left and right edge position coordinates and the reference baseline; The second unit performs grid division and coverage area analysis on the key area image, and calculates the second evaluation index according to the total coverage area value of the left and right area materials of the abnormal image sequence; The real-time vibration waveform is compared with the reference vibration waveform by the third unit, and the overlap length value, the amplitude deviation value and the peak number ratio value are extracted to calculate the third evaluation index; Step 4: Normalize the first evaluation index, the second evaluation index and the third evaluation index to obtain a comprehensive evaluation value, and determine the tilt anomaly level based on it.

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