Conveyor belt tilt monitoring system and monitoring method

Abstract

The present invention relates to the technical field of conveyor belt inclination monitoring, and specifically to a conveyor belt inclination monitoring system and monitoring method, comprising a monitoring point layout module, a data acquisition module, a data monitoring and analysis module, a tilt determination module and a display terminal; the present invention obtains three-dimensional structural data of the conveyor belt, constructs a three-dimensional model, and respectively arranges data collectors on both sides, key areas and key positions of the three-dimensional model to form a monitoring point set, obtains the operating status information of the conveyor belt through the monitoring point set, and analyzes and processes the information to obtain a first evaluation index, a second evaluation index and a third evaluation index, normalizes the above evaluation indexes, calculates a comprehensive evaluation value of the conveyor belt, and determines the tilt abnormality level accordingly, thereby achieving accurate monitoring and real-time early warning, and improving the safety and stability of the conveyor belt.

Description

Technical Field

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

[0002] In modern industrial production and logistics, conveyor belt systems, as core equipment for material transportation, are widely used in multiple fields such as mining, ports, manufacturing, and warehousing. However, during long-term operation, conveyor belts may tilt due to factors such as mechanical wear, material accumulation, bracket deformation, and external interference, resulting in reduced conveying efficiency and even equipment damage and safety accidents. Therefore, real-time monitoring of the conveyor belt's tilt status and taking early warning measures are of great significance to ensuring production safety and improving equipment operation stability.

[0003] Currently, conveyor belt tilt monitoring mainly relies on manual inspections and single fixed-point detection. However, manual inspections are inefficient and lack real-time performance, making them difficult to meet the continuous monitoring needs of large-scale conveying. Traditional fixed-point monitoring only covers some key locations, limiting the monitoring range and easily forming monitoring blind spots. This leads to inaccurate conveyor belt tilt monitoring and is prone to misjudgment. The lack of real-time perception of the overall operating status of the conveyor belt makes it difficult to fully understand the conveyor belt's tilt, thus affecting the safety and stability of the conveyor belt.

[0004] In order to solve the above-mentioned defects, a technical solution is now provided. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem that traditional conveyor belt inclination monitoring mainly relies on manual inspection and single fixed point detection, which cannot meet the continuous monitoring needs of large-scale transportation, nor can it fully grasp the inclination of the conveyor belt and provide timely and accurate warnings. A conveyor belt inclination monitoring system and monitoring method are proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A conveyor belt inclination monitoring system, comprising:

[0008] 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.

[0009] A data acquisition module is used to collect the running status information of the conveyor belt through a set of monitoring points;

[0010] The data monitoring and analysis module is used to 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, wherein:

[0011] Calculating a first evaluation index by a first unit based on the offset volume of the left and right edge position coordinates and the reference baseline;

[0012] The second unit performs grid division and coverage area analysis on the key area image, and calculates the second evaluation index based on the total coverage area value of the left and right area materials of the abnormal image sequence;

[0013] The real-time vibration waveform is compared with the reference vibration waveform by the third unit, and the overlap length value, amplitude deviation value and peak number ratio value are extracted to calculate the third evaluation index;

[0014] 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.

[0015] Furthermore, the process of setting up the monitoring point set is as follows:

[0016] In the 3D model, data collectors are placed on both sides of the conveyor belt at an interval of K1 meters to form the first set of monitoring points on the conveyor belt.

[0017] In the three-dimensional model, data collectors are deployed in key areas to form a second set of monitoring points for the conveyor belt;

[0018] In the three-dimensional model, data collectors are placed at key locations to form a third set of monitoring points for the conveyor belt;

[0019] 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.

[0020] Furthermore, the process of collecting the running status information of the conveyor belt is as follows:

[0021] The edge state parameter of the conveyor belt is collected through the first monitoring point in the monitoring point set to obtain the edge state parameter of the conveyor belt;

[0022] The material state parameters 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;

[0023] 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;

[0024] The operation status information is composed of the edge status parameters, material status parameters and vibration status parameters of the conveyor belt.

[0025] Furthermore, the process of solving the first evaluation index is as follows:

[0026] 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;

[0027] The starting point of the conveyor belt is selected as the reference point to establish a global coordinate system. The coordinate transformation of the left and right coordinate point sets of the conveyor belt is performed and uniformly mapped to the global coordinate system.

[0028] 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;

[0029] Thus, a dynamic coordinate system of the conveyor belt's edge changes is constructed;

[0030] Extract the edge position coordinates of the left and right sides of the conveyor belt and the position coordinates of the reference baseline at each monitoring time point from the dynamic coordinate system of the conveyor belt's edge change. Calculate the offset cross-sectional area of ​​the left and right edges of the conveyor belt relative to the reference baseline at each monitoring time point.

[0031] Based on the calculated offset cross-sectional area, further calculate the offset volume formed by the left and right edges of the conveyor belt relative to the reference baseline;

[0032] The offset volumes formed by the left and right edges of the conveyor belt relative to the reference baseline are added together to obtain the first evaluation index of the conveyor belt.

[0033] Furthermore, the process of gridding and coverage area analysis of the key area image is as follows:

[0034] 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;

[0035] 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;

[0036] 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;

[0037] 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.

[0038] Furthermore, the screening process for abnormal image sequences is as follows:

[0039] 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. If the total coverage area value of the material in the image exceeds the set reference comparison interval, the image is judged to be an abnormal image;

[0040] According to the timestamps of the abnormal images, the abnormal images are sorted in time sequence to obtain an abnormal image sequence.

[0041] Furthermore, the process of solving the second evaluation index is as follows:

[0042] 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. The total coverage area values ​​of the materials in the left area and the right area in the abnormal image are obtained and marked as F respectively. 左r y and F 右r y ;

[0043] According to the formula: , calculate the second evaluation index δ2 of the conveyor belt;

[0044] Where y represents the number of abnormal images, 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 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 of 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.

[0045] Furthermore, the solution process for the third evaluation index is as follows:

[0046] The vibration signals of the key parts of the conveyor belt are extracted in real time, and a vibration waveform diagram of the key parts of the conveyor belt is generated through specific software. At the same time, a reference vibration waveform diagram of the key parts of the conveyor belt is extracted from the system library, and the vibration waveform diagram of the key parts of the conveyor belt is overlapped with the reference vibration waveform diagram to obtain a vibration waveform overlap diagram of the key parts of the conveyor belt;

[0047] Extract the overlap length value, amplitude deviation value and peak-to-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;

[0048] 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;

[0049] 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.

[0050] 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.

[0051] Furthermore, the analysis process for determining the tilt anomaly level is as follows:

[0052] Comparing and analyzing the comprehensive evaluation value of the conveyor belt with a 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 tilt state;

[0053] 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 tilt abnormality level to obtain the tilt abnormality level of the conveyor belt.

[0054] Furthermore, a method for monitoring conveyor belt inclination includes the following steps:

[0055] Step 1: Obtain the 3D structural data of the conveyor belt and build a 3D model. Deploy data collectors on both sides, key areas, and key locations of the 3D model to form a set of monitoring points.

[0056] Step 2: Collect the running status information of the conveyor belt through the monitoring point set;

[0057] 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:

[0058] Calculating a first evaluation index by a first unit based on the offset volume of the left and right edge position coordinates and the reference baseline;

[0059] The second unit performs grid division and coverage area analysis on the key area image, and calculates the second evaluation index based on the total coverage area value of the left and right area materials of the abnormal image sequence;

[0060] The real-time vibration waveform is compared with the reference vibration waveform by the third unit, and the overlap length value, amplitude deviation value and peak number ratio value are extracted to calculate the third evaluation index;

[0061] 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 this.

[0062] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0063] 1. This invention uses laser radar scanning technology to construct a three-dimensional model of the conveyor belt. Multiple types of data collectors are deployed on both sides of the conveyor belt, in key areas, and at key locations, forming a multimodal data acquisition method. These sensors collect information about the conveyor belt's edge offset, material status, and vibration signals, ensuring the accuracy and integrity of the monitoring data. This effectively eliminates the blind spots of traditional monitoring methods, enables global conveyor belt status monitoring, and provides reliable data support for subsequent operational status analysis.

[0064] 2. This invention calculates and analyzes the conveyor belt's edge offset volume, material coverage area in key areas, and vibration waveform changes in key parts. It then combines multi-dimensional evaluation parameters to comprehensively calculate the conveyor belt's inclination, achieving precise identification. Furthermore, based on an intelligent analysis algorithm, it intelligently determines the conveyor belt's inclination state, improving detection accuracy and real-time performance.

[0065] 3. The present invention triggers corresponding warning lights according to the abnormal tilt level based on the operation evaluation results of the conveyor belt, realizing real-time abnormality notification. This warning mechanism can promptly remind operation and maintenance personnel to take countermeasures quickly, thereby effectively ensuring the safety and stability of the conveying system, improving operation efficiency and reducing accident risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0067] Figure 1 It is the overall module block diagram of the present invention.

[0068] Figure 2 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION

[0069] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0070] like Figure 1 As shown, a conveyor belt tilt monitoring system includes: a monitoring point layout module, a data acquisition module, a data monitoring and analysis module, a tilt determination module and a display terminal, wherein the data monitoring and analysis module includes a first unit, a second unit and a third unit;

[0071] The monitoring point layout module is used to analyze and process the monitoring point layout of the conveyor belt. The specific analysis process is as follows:

[0072] Use laser radar scanning technology to obtain the three-dimensional structural data of the conveyor belt, and build a three-dimensional model of the conveyor belt based on the acquired data;

[0073] In the constructed 3D model of the conveyor belt, data collectors are placed on both sides of the conveyor belt at intervals of K1 meters to form a first set of monitoring points for the conveyor belt. The specific interval value of K1 can be set by those skilled in the art based on the actual length of the conveyor belt. The first set of monitoring points is used to monitor the edge position deviation of the conveyor belt, thereby providing high-precision conveyor belt edge monitoring data.

[0074] In the constructed 3D conveyor belt model, data collectors are deployed in key areas (such as transfer points, ramps, and bends) to form a second set of monitoring points on the conveyor belt. This second set of monitoring points is used to monitor whether there are problems such as abnormal material accumulation in key areas of the conveyor belt, thereby providing high-precision monitoring data for key areas of the conveyor belt.

[0075] In the constructed 3D conveyor belt model, data collectors are deployed at key locations (such as rollers, drive wheels, and tension pulleys) to form a third set of monitoring points for the conveyor belt. This third set of monitoring points is used to monitor the vibration status of key locations, thereby providing high-precision monitoring data for key locations of the conveyor belt.

[0076] 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;

[0077] It should be noted that data collectors include but are not limited to infrared light curtain sensors, high-definition infrared cameras and vibration sensors;

[0078] The data acquisition module is used to collect the running status information of the conveyor belt through the monitoring point set to obtain the running status information of the conveyor belt. The specific collection process is as follows:

[0079] The edge state parameter of the conveyor belt is collected through the first monitoring point in the monitoring point set to obtain the edge state parameter of the conveyor belt;

[0080] The material state parameters 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;

[0081] 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;

[0082] The operation status information is composed of the edge status parameters, material status parameters and vibration status parameters of the conveyor belt;

[0083] The data monitoring and analysis module is used to monitor and analyze the operating status information of the conveyor belt and obtain the operating evaluation parameters of the conveyor belt. The specific monitoring and analysis process is as follows:

[0084] 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 is as follows:

[0085] 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;

[0086] in:

[0087] The edge position coordinates on the left side of the conveyor belt are expressed as: P 左 j (X 左 j , Y 左 j , Z 左 j );

[0088] The edge position coordinates on the right side of the conveyor belt are expressed as P 右 j ( 右 j , Y 右 j , Z 右 j );

[0089] The X-axis represents the forward direction of the conveyor belt, the Y-axis represents the left and 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;

[0090] 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 and right coordinate point sets of the conveyor belt and uniformly map them to the global coordinate system;

[0091] The midpoint line of the conveyor belt in normal state is selected as the reference baseline, and the position coordinate data of the reference baseline is extracted and calibrated as Q mid j (X mid j , Y mid j , Z mid j ), the position coordinate data of the reference baseline is also mapped to the global coordinate system;

[0092] Thus, a dynamic coordinate system of the conveyor belt's edge changes is constructed;

[0093] Extract the edge position coordinates of the left and right sides of the conveyor belt and the position coordinates of the reference baseline at each monitoring time point from the dynamic coordinate system of the conveyor belt's edge change. Calculate the offset cross-sectional area of ​​the left and right edges of the conveyor belt relative to the reference baseline at each monitoring time point.

[0094] 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 of adjacent sampling points, and A 左 i and A 右 i They are respectively expressed as 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;

[0095] Based on the calculated offset cross-sectional area, further calculate the offset volume formed by the left and right edges of the conveyor belt relative to the reference baseline according to the formula: , where (X i -X i-1 ) represents the conveyor belt advance distance between adjacent monitoring time points, n represents the total number of monitoring time points, V 左 and V 右 Respectively represent the offset volume formed by the left and right edges of the conveyor belt relative to the reference baseline;

[0096] The offset volumes formed by the left and right edges of the conveyor belt relative to the reference baseline are added together to obtain the first evaluation index δ1 of the conveyor belt. The first evaluation index δ1 reflects the overall inclination of the left and right edges of the conveyor belt relative to the reference baseline. The larger the value, the more serious the inclination of the conveyor belt.

[0097] The second unit monitors and analyzes the material status parameters of the conveyor belt and calculates the second evaluation index of the conveyor belt. The specific monitoring and analysis is as follows:

[0098] 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 preprocess the extracted image frames. The preprocessing includes image denoising, grayscale conversion, contrast enhancement and perspective transformation;

[0099] The uniform grid division method is used to divide the preprocessed image area into M×N rectangular grid units. The deep learning-based target detection technology is used to identify the edge of the material area and calculate the coverage ratio of the material in each grid unit.

[0100] 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;

[0101] 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;

[0102] 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. If the total coverage area value of the material in the image exceeds the set reference comparison interval, the image is judged to be an abnormal image;

[0103] According to the timestamps of the abnormal images, the abnormal images are sorted in time sequence to obtain an abnormal image sequence;

[0104] 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. The total coverage area values ​​of the materials in the left area and the right area in the abnormal image are obtained and marked as F respectively. 左r y and F 右r y ;

[0105] 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 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 rIt represents the set reference coverage ratio, η1 and η2 represent the coverage ratio difference of 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.

[0106] The third unit monitors and analyzes the vibration state parameters of the conveyor belt and calculates the third evaluation index of the conveyor belt. The specific monitoring and analysis is as follows:

[0107] The vibration signals of the key parts of the conveyor belt are extracted in real time, and a vibration waveform diagram of the key parts of the conveyor belt is generated through specific software. At the same time, a reference vibration waveform diagram of the key parts of the conveyor belt is extracted from the system library, and the vibration waveform diagram of the key parts of the conveyor belt is overlapped with the reference vibration waveform diagram to obtain a vibration waveform overlap diagram of the key parts of the conveyor belt;

[0108] Extract the overlap length value, amplitude deviation value and peak-to-peak ratio from the vibration waveform overlap diagram of the key parts of the conveyor belt and mark them as Dchcz respectively. k 、Dzfpz k and Dfghz k , according to the formula: , calculate the third evaluation index δ3 of the conveyor belt, where k represents the number of the key part of the conveyor belt, k* represents the total number of key part numbers of the conveyor belt, γ1, γ2 and γ3 represent the weight coefficients of the overlap length value, amplitude deviation value and peak number ratio value respectively, and γ1>γ2>γ3;

[0109] 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 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 include this time point t in the overlap time interval, thereby calculating the total length of the overlap time interval. The total length of the overlap time interval is proportional to 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 match between the current vibration state and the reference vibration state, and the more stable the conveyor belt operation. Conversely, it indicates that the conveyor belt operation is unstable and there may be a risk of tilting.

[0110] 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.

[0111] 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;

[0112] The first evaluation index, the second evaluation index, and the third evaluation index of the conveyor belt constitute an operation evaluation parameter of the conveyor belt, and the operation evaluation parameter of the conveyor belt is sent to the tilt determination module;

[0113] The tilt determination module is used to receive the conveyor belt's operating evaluation parameters and perform tilt determination analysis on the conveyor belt. The specific analysis process is as follows:

[0114] By extracting the values ​​of the first evaluation index δ1, the second evaluation index δ2 and the third evaluation index δ3 from the conveyor belt operation evaluation parameters and performing normalization processing, according to the formula: , calculate the comprehensive evaluation value PGZ of the conveyor belt, where λ1, λ2 and λ3 represent the exponential factor coefficients of the set first evaluation index, second evaluation index and third evaluation index respectively;

[0115] Compare and analyze the comprehensive evaluation value of the conveyor belt with the preset comprehensive evaluation threshold value. 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. Conversely, when the comprehensive evaluation value of the conveyor belt is less than the preset comprehensive evaluation threshold value, the conveyor belt is determined to be in a normal tilt state.

[0116] 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 tilt abnormality level to obtain the tilt abnormality level of the conveyor belt.

[0117] The display terminal is used to light up the corresponding warning lights according to the abnormal level of inclination of the conveyor belt to provide notification and prompts of abnormal conditions.

[0118] like Figure 2 As shown, a conveyor belt inclination monitoring method includes the following steps:

[0119] Step 1: Analyze and arrange monitoring points on the conveyor belt. The specific analysis process is as follows:

[0120] Use laser radar scanning technology to obtain the three-dimensional structural data of the conveyor belt, and build a three-dimensional model of the conveyor belt based on the acquired data;

[0121] In the constructed 3D model of the conveyor belt, data collectors are placed on both sides of the conveyor belt at intervals of K1 meters to form the first set of monitoring points of the conveyor belt.

[0122] In the constructed three-dimensional model of the conveyor belt, data collectors are deployed in key areas to form a second set of monitoring points for the conveyor belt;

[0123] In the constructed three-dimensional model of the conveyor belt, data collectors are deployed at key locations to form a third monitoring point set of the conveyor belt;

[0124] 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;

[0125] Step 2: Collect the running status information of the conveyor belt through the monitoring point set to obtain the running status information of the conveyor belt. The specific collection process is as follows:

[0126] The edge state parameter of the conveyor belt is collected through the first monitoring point in the monitoring point set to obtain the edge state parameter of the conveyor belt;

[0127] The material state parameters 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;

[0128] 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;

[0129] The operation status information is composed of the edge status parameters, material status parameters and vibration status parameters of the conveyor belt.

[0130] Step 3: Monitor and analyze the conveyor belt's operating status information to obtain the conveyor belt's operating evaluation parameters. The specific monitoring and analysis process is as follows:

[0131] The first unit monitors and analyzes the edge state parameters of the conveyor belt and calculates a first evaluation index of the conveyor belt. The specific monitoring and analysis includes: extracting the edge position coordinate data of the left and right sides of the conveyor belt in real time to form a left coordinate point set and a right coordinate point set of the conveyor belt;

[0132] The starting point of the conveyor belt is selected as the reference point to establish a global coordinate system. The coordinate transformation of the left and right coordinate point sets of the conveyor belt is performed and uniformly mapped to the global coordinate system.

[0133] 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;

[0134] Thus, a dynamic coordinate system of the conveyor belt's edge changes is constructed;

[0135] Extract the edge position coordinates of the left and right sides of the conveyor belt and the position coordinates of the reference baseline at each monitoring time point from the dynamic coordinate system of the conveyor belt's edge change. Calculate the offset cross-sectional area of ​​the left and right edges of the conveyor belt relative to the reference baseline at each monitoring time point.

[0136] Based on the calculated offset cross-sectional area, further calculate the offset volume formed by the left and right edges of the conveyor belt relative to the reference baseline;

[0137] The offset volumes formed by the left and right edges of the conveyor belt relative to the reference baseline are added together to obtain the first evaluation index of the conveyor belt.

[0138] The second unit monitors and analyzes the material status parameters of the conveyor belt and calculates the second evaluation index of the conveyor belt. The specific monitoring and analysis includes: extracting the video stream of the key area of ​​the conveyor belt in real time, segmenting and extracting the video stream of the key area of ​​the conveyor belt frame by frame to form a series of static image frames, and preprocessing the extracted image frames;

[0139] 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;

[0140] 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;

[0141] 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;

[0142] 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. If the total coverage area value of the material in the image exceeds the set reference comparison interval, the image is judged to be an abnormal image;

[0143] According to the timestamps of the abnormal images, the abnormal images are sorted in time sequence to obtain an abnormal image sequence;

[0144] The abnormal image is divided symmetrically along its center line into a left area and a 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, thereby calculating the second evaluation index of the conveyor belt.

[0145] The third unit monitors and analyzes the vibration state parameters of the conveyor belt and calculates the third evaluation index of the conveyor belt. The specific monitoring and analysis includes: extracting the vibration signals of the key parts of the conveyor belt in real time, generating the vibration waveform diagram of the key parts of the conveyor belt through specific software, and extracting the reference vibration waveform diagram of the key parts of the conveyor belt from the system repository. 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;

[0146] The overlap length value, amplitude deviation value and peak-to-peak ratio value are extracted from the vibration waveform overlap diagram of the key parts of the conveyor belt, and the third evaluation index of the conveyor belt is calculated based on this.

[0147] Step 4: Normalizing the first evaluation index, the second evaluation index, and the third evaluation index to obtain a comprehensive evaluation value, and comparing the comprehensive evaluation value with a 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 tilt state.

[0148] 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 tilt abnormality level to obtain the tilt abnormality level of the conveyor belt.

[0149] According to the abnormal degree of conveyor belt inclination, the corresponding warning light is lit to provide notification and prompt of abnormal status.

[0150] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only 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 is 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 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, wherein: Calculating a first evaluation index by a first unit based on the offset volume of the left and right edge position coordinates and the reference baseline; The second unit performs grid division and coverage analysis on the key area images, and calculates the second evaluation index based on the total coverage area values ​​of the left and right area materials of the abnormal image sequence. The specific solution process 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. The total coverage area values ​​of the materials in the left area and the right area in the abnormal image are obtained and 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 the key area of ​​the conveyor belt, r* represents the total number of the key area 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 Represents the set reference coverage ratio, η1 and η2 represent the coverage ratio difference of 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; The real-time vibration waveform is compared with the reference vibration waveform by the third unit, and the overlap length value, amplitude deviation value and 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 process of setting up the monitoring point set is as follows: In the 3D model, data collectors are placed on both sides of the conveyor belt at intervals of K1 meters to form the first set of monitoring points on the conveyor belt. The specific interval value of K1 is set according to the actual length of the conveyor belt. In the 3D model, data collectors are deployed in key areas to form a second set of monitoring points on the conveyor belt. Key areas can be transfer points, ramps, or turns. In the 3D model, data collectors are placed at key locations to form a third set of monitoring points for the conveyor belt. Key locations can be rollers, drive wheels, or tension pulleys. 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 operating status information of the conveyor belt is as follows: The edge state parameter of the conveyor belt is collected through the first monitoring point in the monitoring point set to obtain the edge state parameter of the conveyor belt; The material state parameters 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. The coordinate transformation of the left and right coordinate point sets of the conveyor belt is performed 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 conveyor belt's edge changes is constructed; Extract the edge position coordinates of the left and right sides of the conveyor belt and the position coordinates of the reference baseline at each monitoring time point from the dynamic coordinate system of the conveyor belt's edge change. Calculate the offset cross-sectional area of ​​the left and right edges of the conveyor belt relative to the reference baseline at each monitoring time point. Based on the calculated offset cross-sectional area, further calculate the offset volume formed by the left and right edges of the conveyor belt relative to the reference baseline; The offset volumes formed by the left and right edges of the conveyor belt relative to the reference baseline 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 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. If the total coverage area value of the material in the image exceeds the set reference comparison interval, the image is judged to be an abnormal image; According to the timestamps of the abnormal images, the abnormal images are sorted in time sequence to obtain an abnormal image sequence.

7. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The solution process for the third evaluation index is as follows: The vibration signals of the key parts of the conveyor belt are extracted in real time, and a vibration waveform diagram of the key parts of the conveyor belt is generated through specific software. At the same time, a reference vibration waveform diagram of the key parts of the conveyor belt is extracted from the system library, and the vibration waveform diagram of the key parts of the conveyor belt is overlapped with the reference vibration waveform diagram to obtain a vibration waveform overlap diagram of the key parts of the conveyor belt; Extract the overlap length value, amplitude deviation value and peak-to-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.

8. A conveyor belt inclination monitoring system according to claim 1, characterized in that: The analytical process for determining the tilt anomaly grade is as follows: Comparing and analyzing the comprehensive evaluation value of the conveyor belt with a 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 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 tilt abnormality level to obtain the tilt abnormality level of the conveyor belt.

9. 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 build a 3D model. Deploy data collectors on both sides, key areas, and key locations 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: Calculating a first evaluation index by a first unit based on 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 based on 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, amplitude deviation value and 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 this.

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