Method, device and system for detecting deviation and material blockage imbalance of conveying belt and electronic equipment

Abstract

The invention provides a method, device and system for detecting deviation and material blockage imbalance of a conveying belt and electronic equipment, and the method comprises the steps that contour data of the conveying belt are acquired, and the contour data represent height distribution of a cross section formed by a material on the conveying belt; according to the contour data, abnormal conveying state parameters are determined, the abnormal conveying state parameters represent the stability of the materials on the conveying belt in the conveying process, the abnormal conveying state parameters comprise the deviation amplitude, the blocking state of the materials at the transfer point and the material flow unbalance degree, and the deviation amplitude represents the transverse deviation degree of the conveying belt relative to the preset reference position; and the material flow imbalance degree is the transverse distribution uniformity degree of the materials on the conveying belt. By acquiring the contour data of the height distribution of the cross section of the material formed on the conveying belt, the contour data can directly reflect the actual stacking form of the material in the conveying process, accurate detection of the abnormal state of the conveying belt is achieved, and the conveying stability of the material on the conveying belt is effectively improved.

Description

Technical Field

[0001] This application relates to the technical field of industrial automation and intelligent sensing, and more specifically, to a method, device, system, and electronic equipment for detecting conveyor belt misalignment, material blockage, and unevenness. Background Technology

[0002] In industrial production and logistics, belt conveyors are widely used for transporting bulk goods such as ores in mines, bulk cargo in ports, and coal in power plants due to their advantages of continuous conveying, high load-bearing capacity, and high efficiency. However, in actual operation, belt conveyor systems often experience various operational anomalies due to factors such as abnormal material distribution, equipment wear, and environmental interference. Existing technologies typically employ contact detection methods (such as limit switches and mechanical sensors) or single-parameter detection schemes to detect conveyor belt anomalies. Contact detection methods, for example, rely on physical contact for condition monitoring, but they are susceptible to material impact, dust contamination, and changes in environmental temperature and humidity, leading to decreased accuracy over long-term operation and high maintenance costs. Furthermore, contact sensors are difficult to operate stably in harsh conditions such as transfer points (e.g., muddy or dusty environments), resulting in low reliability. Single-parameter detection schemes, for example, design independent detection modules for specific anomalies (e.g., deviation or blockage), lack the ability to collaboratively analyze multiple anomalies, leading to high system complexity and large response delays. Consequently, the stability of material transport on the conveyor belt is poor. Summary of the Invention

[0003] The purpose of this application is to provide a method, device, system, and electronic equipment for detecting uneven material flow and blockage on a conveyor belt, in order to improve the problem of poor stability in the conveying of materials on the conveyor belt.

[0004] This application provides a method for detecting conveyor belt misalignment, material blockage, and uneven material distribution, including: acquiring the contour data of the conveyor belt, the contour data representing the height distribution of the cross-section formed by the material on the conveyor belt; determining conveying abnormality parameters based on the contour data, the conveying abnormality parameters representing the stability of the material conveying process on the conveyor belt, the conveying abnormality parameters including: misalignment amplitude, material blockage status at transfer points, and material flow unevenness, the misalignment amplitude representing the degree of lateral deviation of the conveyor belt relative to a preset reference position, and the material flow unevenness representing the uniformity of the lateral distribution of the material on the conveyor belt. In the implementation of the above scheme, the contour data of the height distribution of the cross-section formed by the material on the conveyor belt is obtained, and the abnormal state parameters of the conveying are determined based on the contour data. Since these contour data can directly reflect the actual accumulation form of the material during the conveying process, the abnormal state of the conveyor belt can be accurately detected. This improves the problem of misjudgment or omission that may be caused by relying solely on contact detection methods or single-parameter detection schemes in traditional methods. In addition, the abnormal state parameters of the conveying based on the contour data can quantitatively characterize the stability of the material conveying process, making the judgment of abnormal state more objective and accurate, thereby effectively improving the stability of the material conveying on the conveyor belt.

[0005] Optionally, in this embodiment, acquiring the contour data of the conveyor belt includes: projecting a laser line onto the surface of the conveyor belt using a laser emitter, the direction of the laser line being perpendicular to the running direction of the conveyor belt; acquiring an image of the laser line on the surface of the conveyor belt using an industrial camera; and calculating the height distribution of each point in the surface image of the conveyor belt based on a fixed baseline distance between the laser emitter and the industrial camera to obtain the contour data. In the implementation of the above scheme, projecting a laser line perpendicular to the running direction onto the surface of the conveyor belt using a laser emitter ensures that the laser line forms a stable linear projection on the surface of the conveyor belt, avoiding deformation or blurring of the laser line due to the movement of the conveyor belt, thereby improving the accuracy and stability of the contour data acquisition. Furthermore, by using an industrial camera to acquire an image of the laser line on the surface of the conveyor belt, combined with the fixed baseline distance between the laser emitter and the industrial camera, the height distribution of each point can be accurately calculated using the principle of triangulation. This method not only simplifies the calculation process but also significantly improves the spatial resolution and accuracy of the contour data. Furthermore, by calculating the height distribution of each point in the conveyor belt surface image to obtain contour data, the micro-morphological changes of the conveyor belt surface can be reflected in real time, providing high-precision basic data for subsequent conveyor belt condition monitoring and fault diagnosis, thereby improving the reliability and maintenance efficiency of the entire conveying system.

[0006] Optionally, in this embodiment, determining the abnormal conveying state parameters based on the contour data includes: identifying the edge position of the conveyor belt based on the contour data; comparing the edge position of the conveyor belt with a preset reference position to obtain the offset direction and lateral offset; and determining the deviation amplitude based on the offset direction and lateral offset. In the implementation of the above scheme, by introducing the deviation amplitude as a parameter for abnormal conveying state, a quantitative assessment of the degree of lateral offset of the conveyor belt is achieved. This makes the monitoring of the conveyor belt deviation state more accurate and intuitive, avoiding the subjectivity and uncertainty of traditional methods that rely solely on experience, thereby improving the accuracy and reliability of conveyor belt operation status monitoring. Furthermore, determining the deviation amplitude through the comprehensive calculation of the offset direction and lateral offset not only reflects the degree of conveyor belt offset but also clarifies the specific direction of the offset. This makes the diagnosis of the deviation state more comprehensive, providing a clear technical basis for targeted adjustment measures, thereby improving the safety and stability of conveyor belt operation.

[0007] Optionally, in this embodiment, determining the abnormal state parameters of the conveyor based on the contour data includes: determining the instantaneous flow rate of the material based on the contour data; determining the cumulative flow difference between the upstream and downstream detection points of the conveyor belt based on the instantaneous flow rate of the material; if the cumulative flow difference exceeds a preset flow threshold and persists for a preset duration, the blockage state is determined to be blocked; otherwise, the blockage state is determined to be non-blocked. In the implementation of the above scheme, by real-time monitoring of the instantaneous flow rates of the upstream and downstream detection points and calculating the cumulative flow difference, abnormal changes in material flow can be dynamically captured, thereby achieving accurate judgment of the blockage state. This judgment method based on flow difference avoids the lag of traditional single-threshold detection and improves the real-time performance and accuracy of blockage detection. Furthermore, by combining the preset flow threshold and duration as dual conditions for blockage determination, false judgments caused by instantaneous flow fluctuations or brief anomalies can be effectively filtered, enhancing the stability and reliability of blockage state judgment. This dual determination mechanism reduces the system's false alarm rate and improves the robustness of anomaly detection.

[0008] Optionally, in this embodiment, determining the instantaneous flow rate of the material based on the contour data includes: acquiring height data of multiple sampling points on the cross-section of the conveyor belt from the contour data; calculating the cross-sectional area based on the height data of the multiple sampling points; and determining the instantaneous flow rate of the material based on the cross-sectional area and the conveyor belt speed. In the implementation of the above scheme, by acquiring height data of multiple sampling points on the cross-section of the conveyor belt from the contour data, a high-precision digital representation of the material's accumulation shape can be achieved. Compared with traditional single-point or double-point measurement methods, this multi-point sampling method can more accurately reflect the actual distribution of the material on the conveyor belt, thereby avoiding measurement errors caused by uneven material distribution. Furthermore, by calculating the cross-sectional area based on the height data of multiple sampling points, this method can automatically adapt to changes in different material accumulation shapes. Whether it is a regular shape or an irregular bulk material accumulation, the true cross-sectional area can be accurately calculated, improving the adaptability and accuracy of flow measurement. In addition, the entire technical solution, through the organic combination of data acquisition, area calculation, and flow derivation, forms a complete closed-loop measurement system, which not only improves measurement accuracy but also simplifies hardware configuration and reduces the reliance on complex mechanical devices or expensive sensors in traditional flow measurement.

[0009] Optionally, in this embodiment, determining the conveying anomaly parameters based on the contour data includes: calculating the left-side material flow rate based on the left side of the contour data and calculating the right-side material flow rate based on the right side of the contour data; and determining the material flow imbalance based on the left-side and right-side material flow rates. In implementing the above scheme, by specifying the conveying anomaly parameters as material flow imbalance and calculating the material flow rate based on the left and right sides of the contour data respectively, the unevenness of the lateral material distribution on the conveyor belt can be accurately quantified. Compared with traditional qualitative judgment, this quantification method provides a more accurate basis for anomaly detection. Furthermore, by dividing the contour data into left and right parts for independent calculation, the sensitivity and accuracy of detection are improved. This segmentation calculation method can capture subtle changes in material distribution, thereby achieving early warning of conveying anomalies.

[0010] Optionally, in this embodiment, the abnormal conveying status parameters include: deviation amplitude, material flow imbalance, and material blockage status at the transfer point; determining the abnormal conveying status parameters based on contour data includes simultaneously determining deviation amplitude, blockage status, and material flow imbalance based on the contour data. In the implementation of the above scheme, by integrating the three key parameters—deviation amplitude, material flow imbalance, and blockage status—into unified abnormal conveying status parameters, comprehensive monitoring of the conveying system's operating status is achieved. This integrated monitoring method can more accurately reflect the overall operating status of the conveying system, avoiding misjudgments or omissions that may occur with single-parameter monitoring. Furthermore, by simultaneously determining multiple abnormal status parameters based on contour data, the efficiency of the monitoring system is significantly improved. Since it is not necessary to collect and process data for different parameters separately, the computational load of data processing is reduced, and the complexity of the system is also reduced, making the monitoring process more efficient and reliable. In addition, by uniformly determining the three seemingly independent parameters—deviation amplitude, material flow imbalance, and blockage status—through contour data, an intrinsic connection between these parameters is creatively established. This correlation analysis method can reveal the root causes of abnormalities in the conveying system more deeply, providing a new technical approach for fault diagnosis.

[0011] This application embodiment also provides a conveyor belt misalignment, blockage, and uneven material distribution detection system, including: a laser emitter for projecting laser lines onto the surface of the conveyor belt; an industrial camera for acquiring images of the laser lines on the surface of the conveyor belt; a processor module for calculating the surface image based on a fixed baseline distance between the laser emitter and the industrial camera to obtain the contour data of the conveyor belt, wherein the contour data characterizes the height distribution of the cross-section formed by the material on the conveyor belt; the processor module is further used to determine conveying abnormality parameters based on the contour data, wherein the conveying abnormality parameters characterize the stability of the material conveying process on the conveyor belt, and the conveying abnormality parameters include: misalignment amplitude, blockage state of the material at the transfer point, and material flow unevenness, wherein the misalignment amplitude represents the degree of lateral deviation of the conveyor belt relative to a preset reference position, and the material flow unevenness represents the degree of uniformity of the lateral distribution of the material on the conveyor belt. In the implementation of the above scheme, the laser emitter and industrial camera work together to acquire laser line images of the conveyor belt surface in real time. Combined with a fixed baseline distance, precise calculations are performed to generate high-precision contour data. This non-contact measurement method avoids the accuracy degradation problem caused by contact wear of traditional mechanical sensors, significantly improving the long-term stability and reliability of the detection. Furthermore, by using contour data to characterize the height distribution of the material cross-section, the accumulation state and distribution of the material on the conveyor belt can be intuitively reflected, providing a direct quantitative basis for the stability assessment of the conveying process. This height distribution-based analysis method can more comprehensively reflect the actual operating state of the conveyor belt than traditional single-parameter detection.

[0012] This application embodiment also provides a conveyor belt misalignment, blockage, and uneven material distribution detection device, including: a contour data acquisition module for acquiring contour data of the conveyor belt, the contour data representing the height distribution of the cross-section formed by the material on the conveyor belt; and a state parameter determination module for determining abnormal conveying state parameters based on the contour data, the abnormal conveying state parameters representing the stability of the material conveying process on the conveyor belt, the abnormal conveying state parameters including: misalignment amplitude, blockage state of the material at the transfer point, and material flow unevenness, the misalignment amplitude representing the degree of lateral deviation of the conveyor belt relative to a preset reference position, and the material flow unevenness representing the uniformity of the lateral distribution of the material on the conveyor belt.

[0013] Optionally, in this embodiment, the contour data acquisition module includes: a surface laser projection submodule, used to project a laser line onto the surface of the conveyor belt through a laser emitter, the direction of the laser line being perpendicular to the running direction of the conveyor belt; a surface image acquisition submodule, used to acquire an image of the laser line on the surface of the conveyor belt through an industrial camera; and a contour data acquisition submodule, used to calculate the height distribution of each point in the surface image of the conveyor belt based on a fixed baseline distance between the laser emitter and the industrial camera, and obtain contour data.

[0014] Optionally, in this embodiment of the application, the state parameter determination module includes: an edge position recognition submodule, used to identify the edge position of the conveyor belt based on the contour data; a direction offset acquisition submodule, used to compare the edge position of the conveyor belt with a preset reference position to obtain the offset direction and lateral offset amount; and a deviation amplitude determination submodule, used to determine the deviation amplitude based on the offset direction and lateral offset amount.

[0015] Optionally, in this embodiment of the application, the state parameter determination module includes: an instantaneous flow rate determination submodule, used to determine the instantaneous flow rate of the material based on the contour data; a cumulative flow rate determination submodule, used to determine the cumulative flow rate difference between the upstream detection point and the downstream detection point of the conveyor belt based on the instantaneous flow rate of the material; and a blockage status determination submodule, used to determine the blockage status as blocked if the cumulative flow rate difference exceeds a preset flow rate threshold and continues for a preset duration, otherwise, determine the blockage status as not blocked.

[0016] Optionally, in this embodiment of the application, the instantaneous flow rate determination submodule includes: a height data acquisition unit, used to acquire height data of multiple sampling points of the cross-section of the conveyor belt from the contour data; a cross-sectional area calculation unit, used to calculate the cross-sectional area based on the height data of the multiple sampling points; and an instantaneous flow rate determination unit, used to determine the instantaneous flow rate of the material based on the cross-sectional area and the transmission speed of the conveyor belt.

[0017] Optionally, in this embodiment of the application, the state parameter determination module includes: a material flow calculation unit, used to calculate the left material flow based on the left part of the contour data and the right material flow based on the right part of the contour data; and an imbalance determination unit, used to determine the material flow imbalance based on the left material flow and the right material flow.

[0018] Optionally, in this embodiment of the application, the abnormal conveying status parameters include: deviation amplitude, material flow imbalance, and material blockage status at the transfer point; the status parameter determination module includes: a status parameter determination submodule, used to simultaneously determine the deviation amplitude, material blockage status, and material flow imbalance based on the contour data.

[0019] This application also provides an electronic device, including a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the machine-readable instructions are executed by the processor to perform the methods described above.

[0020] This application also provides a computer-readable storage medium storing a computer program, which is executed by a processor to perform the methods described above.

[0021] This application also provides a computer program product, including: a computer program or computer instructions, which are executed by a processor to perform the method described above. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 The diagram shown is a flowchart illustrating the conveyor belt misalignment and material blockage detection method provided in an embodiment of this application. Figure 2 The diagram shown is a structural schematic of the sensor module provided in an embodiment of this application; Figure 3 The diagram shown illustrates the principle of the triangulation method provided in the embodiments of this application. Figure 4 The diagram shown is a schematic diagram illustrating the calculation of the deviation amplitude provided in an embodiment of this application; Figure 5 The diagram shown illustrates the determination of the instantaneous flow rate of a material according to an embodiment of this application. Figure 6The diagram shown illustrates the calculation of material flow imbalance provided in an embodiment of this application. Figure 7 The diagram shown is a structural schematic of the conveyor belt misalignment and material blockage detection system provided in an embodiment of this application. Figure 8 The diagram shown is a structural schematic of the conveyor belt misalignment and material blockage detection device provided in an embodiment of this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in the embodiments of this application are for illustrative and descriptive purposes only and are not intended to limit the protection scope of the embodiments of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the embodiments of this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of the embodiments of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0025] Furthermore, the described embodiments are merely a part of the embodiments of this application, and not all of them. The components of the embodiments of this application described and illustrated herein can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed embodiments of this application, but merely to illustrate selected embodiments of this application.

[0026] It is understood that the terms "first" and "second" in the embodiments of this application are used to distinguish similar objects. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different. In the description of the embodiments of this application, the term "and / or" is merely a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship. The term "multiple" refers to two or more (including two), and similarly, "multiple groups" refers to two or more groups (including two groups).

[0027] It should be noted that the conveyor belt misalignment and material blockage detection method provided in this application embodiment can be executed by electronic equipment. Here, electronic equipment refers to a device terminal or server with the function of executing computer programs. Device terminals include, for example, smartphones, personal computers, tablets, personal digital assistants, or mobile internet devices. Servers refer to devices that provide computing services through a network. Servers include, for example, x86 servers and non-x86 servers. Non-x86 servers include, for example, mainframes, minicomputers, and UNIX servers.

[0028] In industrial production and logistics, belt conveyors are widely used for the transfer of bulk goods such as ores in mines, bulk cargo in ports, and coal in power plants due to their continuous conveying capacity, high load capacity, and energy efficiency. Especially in remote control systems for port container cranes, this detection method can work in conjunction with automated guided vehicles (AGVs) to monitor the stability of belt conveyors during container loading and unloading in real time, improving the level of terminal automation. However, in actual operation, belt conveyor systems often experience abnormal problems such as belt misalignment, material blockage at transfer points, and uneven lateral distribution of material flow due to factors such as uneven material distribution (e.g., uneven loading, material piling), equipment wear (e.g., roller failure, belt aging), and environmental interference (e.g., dust, temperature fluctuations, humidity). These problems not only lead to decreased conveying efficiency and increased equipment wear but may also cause safety accidents and production interruptions, resulting in significant economic losses.

[0029] Currently, contact-based detection methods (such as limit switches and mechanical sensors) are commonly used to monitor belt operation. These methods acquire data through physical contact, for example, by using mechanical contacts to detect the belt edge position or by using pressure sensors to determine material accumulation. However, these methods have significant drawbacks: physical contact is susceptible to material impact (such as ore impact causing sensor damage), dust contamination leading to signal distortion, and changes in ambient temperature and humidity causing measurement drift. After long-term operation, sensor accuracy degrades, maintenance costs are high, and frequent calibration and replacement severely impact system stability.

[0030] In harsh working conditions such as transfer points (e.g., muddy, dusty environments), contact sensors struggle to operate stably. For example, mud can clog mechanical contacts, and dust can adhere to the sensor surface, leading to signal loss or misjudgment, significantly reducing reliability. Furthermore, single-parameter detection solutions (such as designing independent modules only for deviation or blockage) have fatal flaws: firstly, they lack multi-parameter collaborative analysis capabilities, failing to correlate deviation, blockage, and material flow imbalance; secondly, they have high system complexity (requiring the deployment of multiple independent devices) and significant response delays (asynchronous data processing across different modules), resulting in delayed anomaly identification and difficulty in timely intervention, further exacerbating the instability of the conveying process.

[0031] The above analysis reveals that current technological limitations directly contribute to the stability issues of belt conveyor systems: contact-based detection methods fail due to physical contact and environmental interference, while single-parameter detection schemes lack the ability to comprehensively monitor abnormal states due to a lack of collaborative analysis capabilities. During material transport, anomalies such as deviation, blockage, and uneven material flow are often interconnected (e.g., blockage may cause deviation, and uneven material flow may lead to spillage), but current technology cannot detect and respond synchronously in real time, resulting in the accumulation and spread of anomalies. Therefore, the stability of materials on the conveyor belt is poor, manifesting as low efficiency, increased equipment wear and tear, and increased safety risks.

[0032] Please see Figure 1 The diagram shows a flowchart of the conveyor belt misalignment and material blockage detection method provided in this application embodiment. The main idea of ​​this method is to directly reflect the actual accumulation pattern of the material during conveying by using the contour data of the height distribution of the cross-section formed by the material on the conveyor belt. This allows for accurate detection of abnormal conditions on the conveyor belt, making it particularly suitable for intelligent overhead conveyor systems and automated warehouses. In collaborative operations with stacker cranes in aisle areas, it can provide real-time warnings of abnormal material flow, ensuring the stability of the unmanned storage yard intelligent control system. The implementation methods of the above-mentioned conveyor belt misalignment and material blockage detection method may include: Step S110: Obtain the contour data of the conveyor belt. The contour data represents the height distribution of the cross-section formed by the material on the conveyor belt.

[0033] A conveyor belt is a mechanical device used for the continuous transport of materials. It usually consists of a ring-shaped belt and a drive unit. It is used for material transport in industrial production, such as rubber conveyor belts, steel conveyor belts, or plastic modular conveyor belts installed on belt conveyors in industrial production and logistics transportation industries.

[0034] Contour data refers to the height distribution information of materials on the cross-section of a conveyor belt, obtained through measurement or scanning methods. For example, height distribution data of materials on the surface of the conveyor belt obtained through laser triangulation technology characterizes the shape and height changes of the material on the cross-section of the conveyor belt. Specifically, the height information of the conveyor belt cross-section can be collected in real time using laser emitters, industrial cameras, 3D vision sensors, and / or ultrasonic sensors, and contour data can be generated through data processing algorithms.

[0035] A cross section refers to a section perpendicular to the direction of the conveyor belt's operation. It is used to analyze the distribution of the material's accumulation height on the conveyor belt, such as a vertical section in the width direction of the conveyor belt, a vertical section of the material accumulation area, or a detection plane covered by a scanning sensor.

[0036] Height distribution refers to the set of height values ​​of materials at different locations on the cross-section of the conveyor belt, reflecting the uniformity or abnormal state of material accumulation. Specifically, the height values ​​of each location point can be extracted from the contour data to form a continuous or discrete height distribution curve or matrix.

[0037] It is understandable that by acquiring the contour data of the conveyor belt and analyzing the height distribution of the material cross-section, the actual distribution state of the material during the conveying process can be directly reflected, thereby achieving accurate detection of abnormal conditions of the conveyor belt. This direct measurement method based on height distribution avoids the errors caused by indirect inference in traditional methods, and improves the accuracy and reliability of detection.

[0038] Step S120: Determine the abnormal state parameters of the conveying based on the contour data. The abnormal state parameters of the conveying represent the stability of the material conveying process on the conveyor belt. The abnormal state parameters of the conveying include: deviation amplitude, material blockage at the transfer point and material flow imbalance. Deviation amplitude indicates the degree of lateral offset of the conveyor belt relative to the preset reference position. Material flow imbalance is the degree of uniformity of the material distribution in the lateral direction on the conveyor belt.

[0039] Conveying abnormality parameters are quantitative indicators derived from the analysis of profile data. They are used to determine whether there are abnormalities such as uneven accumulation, deviation, or blockage during the material conveying process. Specifically, they include: deviation range, material flow imbalance, and / or the blockage status of materials at transfer points.

[0040] Stability refers to the uniformity and continuity of material distribution on the conveyor belt. The lower the abnormal state parameter, the higher the stability. For example, material evenly covering the conveyor belt without collapsing is considered high stability, while material locally accumulating or leaking is considered low stability.

[0041] Understandably, the abnormal state parameters determined based on contour data can quantify the stability of the material conveying process, making the judgment of abnormal states more objective and standardized. This parameterized detection method not only facilitates real-time monitoring but also provides data support for subsequent automated control and optimization, thereby improving the operating efficiency and safety of the entire conveying system. Furthermore, detecting abnormal states by analyzing the height distribution of materials can promptly identify problems such as material accumulation, deviation, or uneven distribution, thus preventing potential conveyor belt failures or material losses. This proactive detection mechanism helps reduce downtime and maintenance costs, improving the continuity and economy of the production line.

[0042] In the implementation of the above scheme, the contour data of the height distribution of the cross-section formed by the material on the conveyor belt is obtained, and the abnormal state parameters of the conveying are determined based on the contour data. Since these contour data can directly reflect the actual accumulation form of the material during the conveying process, the abnormal state of the conveyor belt can be accurately detected. This improves the problem of misjudgment or omission that may be caused by relying solely on contact detection methods or single-parameter detection schemes in traditional methods. In addition, the abnormal state parameters of the conveying based on the contour data can quantitatively characterize the stability of the material conveying process, making the judgment of abnormal state more objective and accurate, thereby effectively improving the stability of the material conveying on the conveyor belt.

[0043] As an optional implementation of step S110 above, the implementation of obtaining the contour data of the conveyor belt may include: Step S111: Project a laser line onto the surface of the conveyor belt using a laser emitter. The direction of the laser line is perpendicular to the running direction of the conveyor belt.

[0044] Please see Figure 2 The diagram shows a schematic of the sensor module provided in this application embodiment. The sensor module includes a laser emitter and an industrial camera. The laser emitter is an optical device for generating and projecting a laser line, with its projection direction perpendicular to the conveyor belt's running direction. Examples include semiconductor lasers, solid-state lasers, and / or line laser emitters. This type of laser emitter can generate laser light through laser diode excitation, forming a straight laser beam with an optical lens. It is understood that the laser emitter can project a laser line onto the surface of the conveyor belt. This laser line can be projected onto the upper surface of the conveyor belt (when there is no material on the upper surface) or the surface of the material (when there is material on it). Then, the laser line can be reflected to the lens of the industrial camera, and the reflected light is received by the industrial camera. Since the laser emitter and the industrial camera are separated by a distance, objects at different distances will be imaged at different positions in the industrial camera according to the optical path. Therefore, the distance of the measured object (i.e., the material) can be derived from the fixed baseline distance between the laser emitter and the industrial camera using trigonometric formulas. It is understandable that by projecting a laser line perpendicular to the running direction onto the surface of the conveyor belt through a laser emitter, it is possible to ensure that the laser line forms a stable linear projection on the surface of the conveyor belt, avoiding the deformation or blurring of the laser line caused by the movement of the conveyor belt, thereby improving the accuracy and stability of contour data acquisition.

[0045] Step S112: Acquire an image of the laser line on the surface of the conveyor belt using an industrial camera.

[0046] Industrial cameras are high-resolution image acquisition devices used to capture images of laser lines on the surface of conveyor belts. Examples include linear charge-coupled device (CCD) industrial cameras, CMOS industrial cameras, or high-speed industrial cameras. These industrial cameras typically consist of an image sensor, optical lens, image processing circuitry, etc., and are fixed in a specific position to acquire images.

[0047] An example implementation of step S112 above is as follows: The method for acquiring images of laser lines on the conveyor belt surface using an industrial camera is as follows: The laser generator and the industrial camera are mounted above the conveyor belt at a specific angle (e.g., the laser shines vertically upwards, and the camera is tilted at a certain angle), so that the light spot formed by the reflection of the laser line after it is projected onto the conveyor belt surface can be clearly captured by the camera. The industrial camera (usually using a CCD or CMOS sensor) acts as an image sensor, converting the image of the light spot formed by the laser line on the conveyor belt surface into a digital signal. Its high resolution and high frame rate characteristics (e.g., 49kHz frame rate) allow for real-time capture of the deformation or positional changes of the laser line. Using the principle of laser triangulation, the contour or anomaly information of the conveyor belt surface is calculated based on the position of the laser line in the image and a preset geometric relationship, enabling real-time monitoring and analysis of the conveyor belt's condition. In the implementation of the above scheme, by using an industrial camera to acquire images of laser lines on the conveyor belt surface, combined with the fixed baseline distance between the laser emitter and the industrial camera, the height distribution of each point can be accurately calculated using the principle of triangulation. This method not only simplifies the calculation process but also significantly improves the spatial resolution and accuracy of the contour data.

[0048] Step S113: Based on the fixed baseline distance between the laser emitter and the industrial camera, calculate the height distribution of each point in the surface image of the conveyor belt to obtain contour data.

[0049] Please see Figure 3 The diagram illustrates the principle of the triangulation method provided in this application embodiment. The core of the triangulation method is to calculate distance using the triangular geometric relationship formed between the laser emitter, industrial camera, and imaging point, where the laser line direction is perpendicular to the conveyor belt's running direction. Assuming a pre-set fixed baseline distance between the laser emitter and the industrial camera is represented by L, the horizontal distance between the optical centers of the laser emitter and the industrial camera needs to be calibrated during installation. The laser angle can be used... αThe laser angle, denoted by β, refers to the angle between the laser emitter's emission direction and the vertical direction. This laser angle needs to be calibrated before leaving the factory and can be obtained through calibration parameters afterward. The camera angle, denoted by β, refers to the angle between the optical axis of the industrial camera and the vertical direction. This camera angle also needs to be calibrated before leaving the factory and can be obtained through calibration parameters afterward. When the conveyor belt is unloaded, the vertical distance from the conveyor belt surface to the preset reference point can be represented as H0. The length of H0 can be measured during the calibration phase. When the conveyor belt is loaded, the vertical distance from the conveyor belt surface to the preset reference point can be represented as H1. The length of H1 can be obtained through real-time measurement. Then, the height of the loaded goods / materials can be calculated based on H0 and H1 (e.g., h = H0 - H1).

[0050] The aforementioned fixed baseline distance refers to the pre-set fixed spatial distance between the laser emitter and the industrial camera. It is a key parameter calculated using triangulation to measure the data. For example, there may be a 300mm installation gap between the laser emitter and the industrial camera, with a 500mm reference distance. Specifically, the relative positions of the two can be fixed using a mechanical bracket to ensure that the distance remains constant during the measurement process. This design is adaptable to industrial dust and temperature variations (-20℃ to 60℃).

[0051] The implementation of step S113 above is as follows: Assume the laser spot projected onto the surface of the goods is point P, the distance from the laser emitter to point P is L1, and the distance from the camera to point P is L2. According to trigonometric functions, the horizontal component of the laser direction is L1×sinα, and the horizontal component of the camera direction is L2×sinβ. Since L1×sinα + L2×sinβ = L (baseline distance), and L1 = H1 / cosα, L2 = H1 / cosβ, substituting these values, we get: H1 = L / (tanα + tanβ), thus obtaining H1. This eliminates the need for complex three-dimensional coordinate transformations, reducing data processing latency. It is understandable that by calculating the height distribution of each point in the conveyor belt surface image to obtain contour data, the microscopic morphological changes of the conveyor belt surface can be reflected in real time, providing high-precision basic data for subsequent conveyor belt condition monitoring and fault diagnosis, thereby improving the reliability and maintenance efficiency of the entire conveyor system.

[0052] As an optional implementation of step S120 above, the conveying abnormality parameters may include: misalignment amplitude, which represents the degree of lateral deviation of the conveyor belt relative to a preset reference position. The implementation of determining the conveying abnormality parameters based on contour data may include: Step S121: Identify the edge position of the conveyor belt based on the contour data, and compare the edge position of the conveyor belt with the preset reference position to obtain the offset direction and lateral offset.

[0053] It is understandable that conveyor belt misalignment on a belt conveyor can cause belt damage and operational stoppages. Therefore, calculating and monitoring the misalignment amplitude is crucial. In the implementation of the above solution, by identifying the edge position of the conveyor belt based on contour data and comparing it with a preset reference position, the offset direction and lateral offset of the conveyor belt can be obtained in real time. This technical feature makes the calculation of the misalignment amplitude real-time and dynamic, enabling timely detection of abnormal conveyor belt conditions and providing timely data support for subsequent adjustments and maintenance.

[0054] Step S122: Determine the deviation range based on the offset direction and lateral offset.

[0055] Please see Figure 4 The diagram shown illustrates the calculation of belt misalignment amplitude according to an embodiment of this application. Belt misalignment amplitude is a parameter that quantifies the degree of lateral offset of the conveyor belt, representing the amount of offset of the conveyor belt edge relative to a preset reference position. Specifically, it can be calculated by identifying the edge position through contour data and comparing it with the reference position. The preset reference position is a pre-defined standard edge position reference for normal conveyor belt operation, which can be represented as base(x1, x2…xn). It can be determined during system installation and calibration and stored in the processor as a comparison reference.

[0056] The implementation manners of the above steps S121 to S122 are as follows: For example, during the calculation of the profile data, a set of data with height, trans(x1, x2……xn), can be obtained. Assume that x1 is the leftmost and xn is the rightmost. The lateral offset is trans(x1) - base(x1). If trans(x1) - base(x1)>0, it means trans(x1)>base(x1). If trans(xn) - base(xn)>0, it means trans(xn)>base(xn); similarly, if trans(x1) - base(x1)<0, it means trans(x1)<base(x1). If trans(xn) - base(xn)<0, it means trans(xn)<base(xn). If trans(x1)>base(x1) and trans(xn)>base(xn), it is determined that the belt is running off to the right. On the contrary, when trans(x1)<base(x1) and trans(xn)<base(xn), it is determined that the belt is running off to the left. During the implementation of the above solution, by introducing the deviation amplitude as the conveying abnormal state parameter, the quantitative evaluation of the lateral offset degree of the conveyor belt is realized, which makes the monitoring of the conveyor belt deviation state more accurate and intuitive, avoiding the subjectivity and uncertainty of judgment based solely on experience in the traditional method, thus improving the accuracy and reliability of the monitoring of the conveyor belt operation state.

[0057] As an optional implementation manner of the above step S120, the above conveying abnormal state parameter may include: the material blockage state at the transfer point; the implementation manner of determining the conveying abnormal state parameter according to the profile data may include: Step S123: Determine the instantaneous flow rate of the material according to the profile data, and determine the cumulative flow difference between the upstream detection point and the downstream detection point of the conveyor belt according to the instantaneous flow rate of the material.

[0058] The instantaneous flow rate is the volume of the material passing through a certain cross-section of the conveyor belt per unit time, such as a coal flow rate of 0.5 m³ / s or an ore flow rate of 1.2 m³ / s.

[0059] The cumulative flow difference is the difference in the total amount of material passing through the upstream and downstream detection points within a specific time period. For example, within 10 minutes, the upstream passes 5 m³ more than the downstream. Specifically, the difference can be obtained by integrating the instantaneous flow rate over time.

[0060] For example, the implementation of step S123 above is as follows: It is understood that the contour data includes height data from multiple sampling points. Assuming the height of one of these sampling points is h, and there are n pixels on the entire conveyor belt, this data can be reflected into an industrial camera, yielding a set of information containing the cross-sectional position and height: [[x1,h1],[x2,h2]...[xn,hn]]. If the current belt speed is v, the current cross-sectional area S = h1 + h2 + ... + hn can be calculated, and the instantaneous flow rate of the material can be calculated using the formula V = S * v, thus obtaining the flow rate V per second. Assuming the flow rate in the first second is V1, the flow rate in the nth second is Vn, and the flow rate at the current position in the nth second is V1 + ... + Vn, upstream and downstream detection points can be set at the upstream and downstream ends of the conveyor belt, respectively. These upstream and downstream detection points can be represented by P1 and P2, respectively. Assuming the distance between P1 and P2 is d, and the current belt speed is v, then the time interval between P1 and P2 is d / v seconds. At this point, the instantaneous flow rate at point P1 can be calculated as: V1 + ... + Vn = VP1, and the instantaneous flow rate at point P2 is: V(1 + s / v) + ... + V(n + s / v) = VP2. VP2 - VP1 is the cumulative flow difference between the current upstream and downstream detection points. In the implementation of the above scheme, by monitoring the instantaneous flow rates of the upstream and downstream detection points in real time and calculating the cumulative flow difference, abnormal changes in material flow can be dynamically captured, thereby achieving accurate judgment of the blockage status. This flow difference-based judgment method avoids the lag of traditional single-threshold detection and improves the real-time performance and accuracy of blockage detection.

[0061] Step S124: If the cumulative flow difference exceeds the preset flow threshold and continues for a preset duration, the blockage status is determined to be blocked. If the cumulative flow difference does not exceed the preset flow threshold or does not continue for a preset duration, the blockage status is determined to be unblocked.

[0062] Understandably, the material blockage status at the aforementioned transfer point indicates whether a blockage has occurred at the transfer point of the conveyor system. This can be specifically detected by measuring the upstream and downstream flow difference and considering the duration of the blockage. Common causes of blockage include blockage on one side of the hopper and defects in the guide chute. In these cases, the material on the belt will be biased to one side, exhibiting an uneven material flow.

[0063] For example, in implementing step S124 above: if the cumulative flow difference (VP2 - VP1) between the current upstream and downstream detection points exceeds a preset flow threshold and persists for a preset duration, the blockage status is determined to be blocked. Similarly, if the cumulative flow difference does not exceed the preset flow threshold or does not persist for a preset duration, the blockage status is determined to be non-blocked. In the implementation of the above scheme, by combining the preset flow threshold and duration as dual conditions for blockage determination, false judgments caused by instantaneous flow fluctuations or brief anomalies can be effectively filtered, enhancing the stability and reliability of blockage status determination. This dual determination mechanism reduces the system's false alarm rate and improves the robustness of anomaly detection. Furthermore, by directly calculating the instantaneous flow and cumulative flow difference using contour data, continuous monitoring and analysis of the conveyor belt's operating status are achieved. This method does not require additional physical sensors, reducing system complexity while maintaining high detection accuracy, and has good economic efficiency and practicality.

[0064] As an optional implementation of step S120 above, the implementation of determining the instantaneous flow rate of the material based on the contour data may include: Step S125: Obtain the height data of multiple sampling points of the cross-section of the conveyor belt from the contour data.

[0065] The implementation of step S125 above is as follows: First, system calibration can be performed. When the conveyor belt is unloaded, a light spot image is acquired, and the vertical distance H0 from the conveyor belt surface to the preset reference point is calculated based on the light spot image. Second, when the conveyor belt is loaded, a laser emitter projects the laser image, which can be acquired by an industrial camera through vibration sampling. Then, the laser image is preprocessed to obtain a preprocessed image, and the preprocessed image is binarized to obtain a binarized image. Edge detection is then performed on the binarized image to obtain the center position information of the light spot in the binarized image. Finally, the center position information of the light spot is substituted into the formula of the triangulation method above to obtain the vertical distance H1 from the conveyor belt surface to the preset reference point. Finally, the height data of one of the multiple sampling points is calculated using the formula h = H0 - H1. In the implementation of the above scheme, by obtaining the height data of multiple sampling points of the conveyor belt cross-section from the contour data, the distribution of materials on the conveyor belt can be accurately depicted from the data obtained from multiple sampling points, effectively reducing the measurement error caused by uneven material distribution.

[0066] Step S126: Calculate the cross-sectional area based on the height data of multiple sampling points, and determine the instantaneous flow rate of the material based on the cross-sectional area and the conveyor belt speed.

[0067] Please see Figure 5The diagram illustrates the method for determining the instantaneous flow rate of materials according to an embodiment of this application. For example, the implementation of step S126 described above involves assuming the height data of one of the multiple sampling points is h, and there are n pixels on the entire conveyor belt. This data can be reflected into an industrial camera, yielding a set of information containing the cross-sectional position and height: [[x1,h1],[x2,h2]...[xn,hn]]. If the current belt speed is v, the current cross-sectional area S = h1 + h2 + ... + hn can be calculated, and the instantaneous flow rate of the material can be calculated using the formula V = S * v. This yields the flow rate V per second, where S represents the cross-sectional area and V represents the conveyor belt speed. It is understood that since the loaded material is not necessarily uniform, a 1-second calculation window can be used; a smaller calculation window results in higher accuracy. In the implementation of the above scheme, by calculating the cross-sectional area based on the height data of multiple sampling points, this method can automatically adapt to changes in different material accumulation patterns. Whether it is a regular shape or an irregular bulk material accumulation, the true cross-sectional area can be accurately calculated, improving the adaptability and accuracy of flow measurement. Furthermore, by combining the calculated cross-sectional area and the conveyor belt speed to determine the instantaneous flow rate, dynamic real-time measurement of material flow rate is achieved. This calculation method based on the combination of geometric and motion parameters can respond to flow rate changes more quickly than the traditional static weighing method, meeting the needs of real-time control.

[0068] As an optional implementation of step S120 above, the aforementioned conveying abnormality parameters may include: material flow imbalance, which is the degree of uniformity of material distribution in the lateral direction of the conveyor belt, used to quantify the degree of uniformity of material distribution in the lateral direction of the conveyor belt. The aforementioned implementation of determining the conveying abnormality parameters based on contour data may include: Step S127: Calculate the left material flow rate based on the left part of the contour data, and calculate the right material flow rate based on the right part of the contour data.

[0069] In the above calculation process, the cross-sectional area and instantaneous flow rate V have been calculated based on the cross-sectional height information: [[x1,h1],[x2,h2]……[xn,hn]]. In practical application, the cross-sectional height information can be divided into two dimensions: left and right. Specifically, the material flow rate on the left side is calculated based on the left portion of the contour data, and the material flow rate on the right side is calculated based on the right portion of the contour data. This yields the instantaneous flow rates: Vleft (left material flow rate) and Vright (right material flow rate). In implementing the above scheme, by specifying the abnormal conveying state parameters as material flow imbalance and calculating the material flow rate based on the left and right sides of the contour data respectively, the unevenness of the lateral material distribution on the conveyor belt can be accurately quantified. Compared to traditional qualitative judgment, this quantification method provides a more accurate basis for anomaly detection.

[0070] Step S128: Determine the material flow imbalance based on the material flow rates on the left and right sides.

[0071] Please see Figure 6The illustration shows a schematic diagram of the calculation of material flow imbalance provided in the embodiment of this application. For example, in the above calculation process, the cross-sectional height information can be divided into two dimensions: left and right. That is, the left material flow rate is calculated based on the left part of the contour data, and the right material flow rate is calculated based on the right part of the contour data. This yields the instantaneous flow rates: left material flow rate Vleft and right material flow rate Vright. The left cross-sectional height information can be represented as: [[x1,h1],[x2,h2]……[x(n / 2),h(n / 2)]], and the right cross-sectional height information can be represented as: [[x(n / 2+1),h(n / 2+1)],[x(n / 2+2),h(n / 2+2)]……[xn,hn]]. If the ratio between the left and right material flow rates is greater than a first preset threshold and less than a second preset threshold, then the material flow imbalance is determined to be material flow balance, where the first preset threshold is less than the second preset threshold. If the ratio of the material flow rate on the left to the material flow rate on the right is less than a first preset threshold, or the ratio is greater than a second preset threshold, then the material flow imbalance is determined to be material flow imbalance, where the first preset threshold is less than the second preset threshold. In the implementation of the above scheme, by calculating the material flow rates on the left and right sides separately to determine the material flow imbalance, dynamic monitoring of the lateral material distribution on the conveyor belt is achieved. This allows for timely detection of material eccentricity, preventing problems such as increased conveyor belt wear or misalignment caused by long-term eccentricity. Furthermore, by dividing the contour data into left and right parts for independent calculation, the sensitivity and accuracy of the detection are improved. This segmented calculation method can capture subtle changes in material distribution, thereby achieving early warning of conveying anomalies.

[0072] As an optional implementation of step S120 above, the aforementioned conveying abnormality parameters can be a comprehensive set of multiple indicators characterizing the operational stability of the conveyor belt, such as: deviation amplitude, material flow imbalance, and material blockage at transfer points. The implementation method for determining the conveying abnormality parameters based on contour data can include: Step S129: Determine the deviation range, blockage status, and material flow imbalance simultaneously based on the contour data.

[0073] The implementation of step S129 above includes, for example, simultaneously analyzing and calculating multiple sub-parameters based on the contour data. These sub-parameters include deviation amplitude, material blockage status, and material flow imbalance. Specifically, the implementation of calculating the deviation amplitude can be found in the implementations of steps S121 to S122 above; the implementation of calculating the material blockage status can be found in the implementations of steps S123 to S124 above; and the implementation of calculating the material flow imbalance can be found in the implementations of steps S125 to S128 above. In the implementation of the above scheme, by integrating the three key parameters—deviation amplitude, material flow imbalance, and material blockage status—into a unified conveying abnormality status parameter, comprehensive monitoring of the conveying system's operating status is achieved. This integrated monitoring method can more accurately reflect the overall operating status of the conveying system, avoiding misjudgments or omissions that may occur with single-parameter monitoring. Furthermore, by simultaneously acquiring multiple key parameters through a single data source (contour data), the data inconsistency problem caused by the need for multiple sensors in traditional methods is eliminated. This synchronous acquisition method ensures the time consistency between parameters, providing a reliable data foundation for accurately analyzing the abnormal status of the conveying system. Furthermore, by unifying three seemingly independent parameters—deviation amplitude, material flow imbalance, and blockage state—using profile data, an intrinsic relationship between these parameters was creatively established. This correlation analysis method can reveal the root causes of conveying system anomalies more deeply, providing a new technical approach for fault diagnosis.

[0074] Please see Figure 7 The diagram shows a schematic of the conveyor belt misalignment and material blockage detection system provided in this application embodiment. This application embodiment provides a conveyor belt misalignment and material blockage detection system, which can be applied in the field of food industrial processing and intelligent manufacturing equipment. This system can be integrated into specialized intelligent agricultural product transportation equipment, achieving precise material transport and status monitoring through a laser-guided vehicle (LGV), thereby improving the operational efficiency of intelligent post-harvest drying and fine sorting equipment for agricultural products. The aforementioned conveyor belt misalignment and material blockage detection system may include: a sensor module, a speed sensor, a processor module, a switch, a server, a monitoring terminal, a constant pressure device, and a high-pressure air source. The processor module is communicatively connected to the speed sensor, the sensor module, and the switch. The switch can communicate with the server via a basic network, and the monitoring terminal can communicate with the server via a network. The sensor module can be connected to the high-pressure air source via the constant pressure device. The aforementioned sensor module can be suspended above the conveyor belt and may specifically include: A laser emitter is used to project a laser line onto the surface of a conveyor belt. The laser line can be projected onto the upper surface of the conveyor belt (when there is no material on the upper surface) or the surface of the material (when there is material on the upper surface). The laser line can then be reflected onto the lens of an industrial camera, which receives the reflected light.

[0075] Industrial cameras are used to capture images of laser lines on the surface of a conveyor belt; for example, cameras using linear charge-coupled devices (CCDs) are used. It is understood that, because the laser emitter and the industrial camera are separated by a distance, objects at different distances will be imaged at different positions in the industrial camera according to the optical path. Therefore, the distance of the object being measured (i.e., the material) can be derived using trigonometric formulas based on the fixed baseline distance between the laser emitter and the industrial camera.

[0076] In the implementation of the above scheme, the laser emitter and industrial camera work together to acquire laser line images of the conveyor belt surface in real time. Combined with a fixed baseline distance, precise calculations are performed to generate high-precision contour data. This non-contact measurement method avoids the accuracy degradation problem caused by contact wear of traditional mechanical sensors, significantly improving the long-term stability and reliability of the detection. Furthermore, by using contour data to characterize the height distribution of the material cross-section, the accumulation state and distribution of the material on the conveyor belt can be intuitively reflected, providing a direct quantitative basis for the stability assessment of the conveying process. This height distribution-based analysis method can more comprehensively reflect the actual operating state of the conveyor belt than traditional single-parameter detection.

[0077] The aforementioned processor module is used to calculate the contour data of the conveyor belt based on the fixed baseline distance between the laser emitter and the industrial camera. This contour data characterizes the height distribution of the cross-section formed by the material on the conveyor belt. This processor module can be a computing unit that performs image processing and data analysis, and can consist of a CPU, memory, storage, etc., running dedicated algorithm programs.

[0078] The processor module is also used to determine abnormal transport parameters based on the profile data. These parameters characterize the stability of the material transport process on the conveyor belt. Understandably, by analyzing the profile data to determine these abnormal transport parameters, the processor module achieves dynamic monitoring and quantitative evaluation of the transport process stability. This parameterized abnormal state detection method enables the system to promptly detect minute changes in the transport process, providing data support for preventative maintenance and fault early warning, and effectively reducing the risk of sudden failures.

[0079] Please see Figure 8The diagram shown is a structural schematic of the conveyor belt misalignment and material blockage detection device provided in this application embodiment; this application embodiment provides a conveyor belt misalignment and material blockage detection device 200, including: The contour data acquisition module 210 is used to acquire the contour data of the conveyor belt. The contour data represents the height distribution of the cross-section formed by the material on the conveyor belt.

[0080] The state parameter determination module 220 is used to determine the abnormal state parameters of the conveyor based on the contour data. The abnormal state parameters of the conveyor represent the stability of the material conveying process on the conveyor belt. The abnormal state parameters of the conveyor include: deviation amplitude, material blockage at the transfer point and material flow imbalance. Deviation amplitude indicates the degree of lateral offset of the conveyor belt relative to the preset reference position. Material flow imbalance is the degree of uniformity of the material distribution in the lateral direction on the conveyor belt.

[0081] As an optional implementation of the above-mentioned device, the contour data acquisition module includes: The surface laser projection submodule is used to project laser lines onto the surface of the conveyor belt via a laser emitter, with the direction of the laser lines perpendicular to the direction of the conveyor belt's movement.

[0082] The surface image acquisition submodule is used to acquire surface images of laser lines on the conveyor belt using an industrial camera.

[0083] The contour data acquisition submodule is used to calculate the height distribution of each point in the surface image of the conveyor belt based on the fixed baseline distance between the laser emitter and the industrial camera, and obtain contour data.

[0084] As an optional implementation of the above-mentioned device, the state parameter determination module includes: The edge position recognition submodule is used to identify the edge position of the conveyor belt based on the contour data.

[0085] The direction offset acquisition submodule is used to compare the edge position of the conveyor belt with the preset reference position to obtain the offset direction and lateral offset amount.

[0086] The deviation range determination submodule is used to determine the deviation range based on the offset direction and lateral offset.

[0087] As an optional implementation of the above-mentioned device, the state parameter determination module includes: The instantaneous flow rate determination submodule is used to determine the instantaneous flow rate of the material based on the profile data.

[0088] The cumulative flow determination submodule is used to determine the cumulative flow difference between the upstream and downstream detection points of the conveyor belt based on the instantaneous flow rate of the material.

[0089] The material blockage status determination submodule is used to determine the material blockage status as blocked if the cumulative flow difference exceeds the preset flow threshold and continues for a preset duration; otherwise, it determines the material blockage status as not blocked.

[0090] As an optional implementation of the above-mentioned device, the instantaneous flow rate determination submodule includes: The height data acquisition unit is used to acquire the height data of multiple sampling points on the cross-section of the conveyor belt from the contour data.

[0091] The cross-sectional area calculation unit is used to calculate the cross-sectional area based on the height data of multiple sampling points.

[0092] The instantaneous flow rate determination unit is used to determine the instantaneous flow rate of the material based on the cross-sectional area and the conveyor belt speed.

[0093] As an optional implementation of the above-mentioned device, the state parameter determination module includes: The material flow calculation unit is used to calculate the left material flow based on the left part of the contour data and the right material flow based on the right part of the contour data.

[0094] The imbalance determination unit is used to determine the material flow imbalance based on the material flow rates on the left and right sides.

[0095] As an optional implementation of the above-mentioned device, the abnormal state parameters of the conveying system include: deviation amplitude, material flow imbalance, and material blockage status at the transfer point; the state parameter determination module includes: The status parameter determination submodule is used to simultaneously determine the deviation amplitude, material blockage status, and material flow imbalance based on the contour data.

[0096] It should be understood that this device corresponds to the above-described embodiment of the conveyor belt misalignment and material blockage detection method, and is capable of performing the various steps involved in the above-described method embodiment. The specific functions of this device can be found in the description above, and detailed descriptions are appropriately omitted here. This device includes at least one software function module that can be stored in memory or embedded in the device's operating system (OS) in the form of software or firmware.

[0097] An electronic device provided in this application includes a processor and a memory. The memory stores machine-readable instructions that can be executed by the processor. When the machine-readable instructions are executed by the processor, the method described above is performed.

[0098] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the method described above. The computer-readable storage medium can be implemented using any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0099] This application also provides a computer program product, including: a computer program or computer instructions, which are executed by a processor to perform the method described above.

[0100] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0101] It should be understood that the disclosed apparatus and methods can also be implemented in other ways, as provided in the embodiments of this application. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending primarily on the functions involved.

[0102] Furthermore, the functional modules of each embodiment in this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part. In addition, in the description of this specification, the reference to terms such as "one embodiment," "some embodiments," "example," "specific example," "some examples," etc., means that the specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0103] The above description is only an optional implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application.

Claims

1. A method for detecting a deviation of a conveyor belt, characterized in that, The method comprises: acquiring profile data of a conveying belt, the profile data representing a height distribution of a cross section of a material on the conveying belt; determining a conveying abnormal state parameter according to the profile data, the conveying abnormal state parameter representing stability of a conveying process of the material on the conveying belt, the conveying abnormal state parameter comprising: a deviation amplitude, a blockage state of the material at a transfer point, and a flow imbalance degree, the deviation amplitude representing a lateral deviation degree of the conveying belt relative to a preset reference position, the flow imbalance degree representing a uniformity degree of the material in a lateral direction of the conveying belt.

2. The method of claim 1, wherein, The acquiring of the profile data of the conveying belt comprises: projecting a laser line onto a surface of the conveying belt by a laser emitter, the laser line being perpendicular to a running direction of the conveying belt; capturing a surface image of the laser line on the surface of the conveying belt by an industrial camera; calculating a height distribution of each point in the surface image of the conveying belt based on a fixed baseline distance between the laser emitter and the industrial camera, to obtain the profile data.

3. The method of claim 1, wherein, The determining of the conveying abnormal state parameter according to the profile data comprises: identifying an edge position of the conveying belt according to the profile data; comparing the edge position of the conveying belt with the preset reference position to obtain a deviation direction and a lateral deviation amount; determining the deviation amplitude according to the deviation direction and the lateral deviation amount.

4. The method of claim 1, wherein, The determining of the conveying abnormal state parameter according to the profile data comprises: determining an instantaneous flow of the material according to the profile data; determining a cumulative flow difference between an upstream detection point and a downstream detection point of the conveying belt according to the instantaneous flow of the material; if the cumulative flow difference exceeds a preset flow threshold and lasts for a preset time length, determining that the blockage state is blocked, otherwise, determining that the blockage state is not blocked.

5. The method of claim 4, wherein, The determining of the instantaneous flow of the material according to the profile data comprises: acquiring height data of a plurality of sampling points of a cross section of the conveying belt from the profile data; calculating a cross-sectional area according to the height data of the plurality of sampling points; determining the instantaneous flow of the material according to the cross-sectional area and a conveying speed of the conveying belt.

6. The method of claim 1, wherein, The determining of the conveying abnormal state parameter according to the profile data comprises: calculating a left material flow according to a left portion of the profile data, and calculating a right material flow according to a right portion of the profile data; determining the flow imbalance degree according to the left material flow and the right material flow.

7. A conveyor belt misalignment, blockage and unevenness detection system characterized by, The method comprises: a laser emitter configured to project a laser line onto a surface of the conveying belt; an industrial camera configured to capture a surface image of the laser line on the surface of the conveying belt; a processor module configured to calculate the surface image according to a fixed baseline distance between the laser emitter and the industrial camera, to obtain profile data of the conveying belt, the profile data representing a height distribution of a cross section of a material on the conveying belt. The processor module is further configured to determine a conveying abnormality state parameter according to the profile data, the conveying abnormality state parameter representing stability of the material conveying process on the conveying belt, and the conveying abnormality state parameter including a deviation amplitude, a material blocking state of a transfer point, and a material flow imbalance degree, the deviation amplitude representing a lateral deviation degree of the conveying belt relative to a preset reference position, and the material flow imbalance degree representing a uniformity degree of the material distribution in a lateral direction of the conveying belt.

8. A device for detecting a deviation of a conveyor belt, a blockage, and an unevenness of a material, characterized by The profile data acquisition module is configured to acquire profile data of the conveying belt, the profile data representing a height distribution of a cross section of the material on the conveying belt. The state parameter determination module is configured to determine a conveying abnormality state parameter according to the profile data, the conveying abnormality state parameter representing stability of the material conveying process on the conveying belt, and the conveying abnormality state parameter including a deviation amplitude, a material blocking state of a transfer point, and a material flow imbalance degree, the deviation amplitude representing a lateral deviation degree of the conveying belt relative to a preset reference position, and the material flow imbalance degree representing a uniformity degree of the material distribution in a lateral direction of the conveying belt. The processor and the memory, the memory storing machine readable instructions executable by the processor, the machine readable instructions being executed by the processor to perform the method of any one of claims 1 to 6.

9. An electronic device, comprising: The computer readable storage medium stores a computer program, the computer program being executed by the processor to perform the method of any one of claims 1 to 6. The computer program or the computer instructions being executed by the processor to perform the method of any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, ​ 11. A computer program product, characterised in that, ​ ​

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