A method and related device for real-time detection of conveyor belt items based on a grating device

Abstract

A kind of conveying belt article real-time detection method based on grating device and related equipment, in the method, the emission unit of each group of grating transmitter is controlled and emits light signal of different wavelength according to preset timing cycle;Intensity value of the light signal received by each group of grating receiver is recorded;Three-dimensional light intensity distribution matrix is constructed based on intensity value;Image segmentation processing is carried out on three-dimensional light intensity distribution matrix, and continuous dark area in three-dimensional light intensity distribution matrix is identified, and each continuous dark area represents the contour of an article;According to the change result of the contour of the article identified according to continuous dark area at different heights and different time points, the number, size and relative position relationship of the article are judged according to the change result, and the judgment result is obtained;Based on the judgment result, the real-time detection information of conveying belt is obtained, and the real-time detection information includes the number of articles, the size and position of each article.The application improves the accuracy of detecting closely arranged or partially overlapped articles.

Description

Technical Field

[0001] This application belongs to the field of article detection, and in particular relates to a method and related equipment for real-time detection of conveyor belt articles based on grating devices. Background Technology

[0002] Conveyor belt systems are widely used in various scenarios in modern industrial production and logistics transportation, such as production lines in manufacturing, sorting systems in warehousing, and baggage handling in airports. To ensure the efficient operation and accurate management of conveyor belt systems, real-time monitoring of the status of items on the conveyor belt has become a critical issue. Among these methods, detection methods based on grating devices have been widely applied in the field of conveyor belt item detection due to their non-contact and rapid response characteristics.

[0003] Traditional conveyor belt item detection methods based on grating devices typically employ the following approach: a grating transmitter is placed on one side of the conveyor belt, and a grating receiver is placed on the opposite side. When an item on the conveyor belt passes through the grating area, it blocks some or all of the light, causing a change in the intensity of the light signal received by the receiver. The system analyzes this signal change to determine the presence and location of the item.

[0004] However, when items on the conveyor belt are closely arranged or partially overlapped, the beam emitted by the transmitter in the grating device will be blocked by these items. From the receiver's perspective, it can only detect a continuous blocking signal, making it difficult to distinguish between a large item and two closely arranged small items. This reduces the accuracy of detecting closely arranged or partially overlapping items. Summary of the Invention

[0005] This application provides a method and related equipment for real-time detection of conveyor belt items based on grating devices, which can improve the accuracy of detecting closely arranged or partially overlapping items.

[0006] In the first aspect, this application provides a method for real-time detection of conveyor belt items based on a grating device, which controls the emission units of each group of grating emitters to cyclically emit light signals of different wavelengths according to a preset time sequence. Each group of grating emitters is included in the grating device, and the grating device also includes each group of grating receivers corresponding to each group of grating emitters. Once it is confirmed that each group of grating receivers has received an optical signal, the intensity value of the optical signal received by each group of grating receivers is recorded. A three-dimensional light intensity distribution matrix is ​​constructed based on the intensity values. The three dimensions of the three-dimensional light intensity distribution matrix correspond to the position, height and time on the conveyor belt, respectively. Image segmentation processing is performed on the three-dimensional light intensity distribution matrix to identify continuous dark areas in the three-dimensional light intensity distribution matrix, and each continuous dark area represents the outline of an object; Based on the results of identifying changes in the outline of an object at different heights and time points in continuous dark areas, and judging the quantity, size, and relative position of the object based on the changes, the judgment result is obtained. Based on the judgment results, the real-time detection information of the conveyor belt is obtained, which includes the number of items, the size and position of each item.

[0007] By employing the above technical solutions, different wavelengths of light exhibit varying reflection and absorption characteristics towards objects with different materials and surface properties, enabling better differentiation and identification of various types of objects and reducing the probability of false detections and missed detections. The three-dimensional light intensity distribution matrix not only contains information about the position and height of objects on the conveyor belt but also records how this information changes over time, capturing dynamic features such as the object's trajectory and shape changes, thereby improving detection accuracy. Image segmentation processing of the three-dimensional light intensity distribution matrix identifies continuous dark areas, transforming complex three-dimensional data into understandable and processable object contour information. This improves the accuracy of identifying the shape and size of objects and reduces the adverse effects of overlapping or partial occlusion, enhancing detection capabilities in complex scenes. Analyzing the changes in continuous dark areas at different heights and time points improves the accuracy of detecting closely arranged or partially overlapping objects.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, before controlling the transmitting units of each group of grating emitters to cyclically transmit optical signals of different wavelengths according to a preset timing sequence, the method further includes: Adjust the angles of the transmitting and receiving units so that the optical axes corresponding to the transmitting and receiving units are parallel to each other and perpendicular to the direction of movement of the conveyor belt; When the conveyor belt is unloaded, the control unit transmits the initial light signal and records the initial light intensity value received by each receiving unit. Based on the initial light intensity value, the transmitting unit and receiving unit pair whose initial light intensity value is not in the preset range are identified, and the angle of the transmitting unit and receiving unit pair is adjusted so that the initial light intensity value of the corresponding transmitting unit and receiving unit pair is within the preset range. A standard test object was placed on a conveyor belt, and the conveyor belt was controlled to run at different speeds. The light intensity changes of each receiving unit were recorded at different conveyor belt speeds. Based on the recorded changes in light intensity, the system's response time and detection sensitivity are calculated, and parameters are adjusted accordingly.

[0009] By adopting the above technical solution, adjusting the angles of the transmitting and receiving units to ensure their optical axes are parallel and perpendicular to the conveyor belt's direction of movement reduces signal attenuation and distortion caused by angular deviations, thus improving the signal-to-noise ratio. Identifying transmitting and receiving unit pairs whose initial light intensity values ​​are outside the preset range and making corresponding adjustments reduces system performance differences caused by manufacturing errors, installation deviations, or environmental factors. Testing with standard test objects at different conveyor belt speeds allows for evaluation of performance in dynamic environments. The system's response time and detection sensitivity are calculated based on recorded light intensity changes, and parameters are adjusted to adapt the system to different operating conditions.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, controlling the emitting units of each group of grating emitters to cyclically emit optical signals of different wavelengths according to a preset timing sequence specifically includes: Each group of grating emitters is assigned a unique time slot, the length of which is determined by the conveyor belt speed. Within each unique time slot, the various transmitting units of the control grating emitter sequentially transmit optical signals of different wavelengths in a preset order.

[0011] By adopting the above technical solution, it is possible that the simultaneous operation of multiple light sources may lead to signal overlap and confusion, affecting the accuracy of detection. The strategy of assigning a unique time slot to each group of grating transmitters reduces signal interference between different transmitters. Through time-division multiplexing, each group of transmitters operates within its dedicated time window, ensuring that the received signal can be accurately mapped to a specific source, thereby improving the system's anti-interference capability and the accuracy of signal identification.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, after controlling the various transmitting units of the grating emitter to sequentially emit optical signals of different wavelengths in a preset order, the method further includes: After one transmission cycle is completed, a preset calibration time slot is inserted. During the preset calibration time slot, each transmission unit is controlled to transmit a preset calibration optical signal. The transmission cycle is when each transmission unit transmits optical signals of different wavelengths in a preset order. Real-time monitoring of the operating parameters of each transmitting unit, including light intensity stability and wavelength accuracy; If a fault is found in a transmitting unit based on the operating parameters, the transmitting unit is marked.

[0013] By employing the above technical solutions, various factors such as temperature changes, mechanical vibration, and light source aging can cause system performance to deviate over time. By periodically transmitting calibration signals, the system can monitor and compensate for these drifts in real time, maintaining consistent detection accuracy. Real-time monitoring of the operating parameters of each transmitting unit, including light intensity stability and wavelength accuracy, enables the system to promptly detect and address potential problems. Continuous monitoring of these key parameters allows the system to identify performance degradation trends in advance, providing crucial information for preventative maintenance. When a transmitting unit malfunctions, the system automatically flags it, allowing for the exclusion of unreliable data from these units in subsequent data processing, thereby improving the overall accuracy of the detection results.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, image segmentation processing is performed on the three-dimensional light intensity distribution matrix to identify continuous dark areas in the three-dimensional light intensity distribution matrix, specifically including: The three-dimensional light intensity distribution matrix is ​​denoised to obtain a denoised three-dimensional light intensity distribution matrix. Using a pre-defined segmentation algorithm, the denoised three-dimensional light intensity distribution matrix is ​​binarized to obtain preliminary segmentation results; A three-dimensional connected component analysis algorithm was used to identify preliminary continuous dark areas based on the initial segmentation results; Morphological processing is performed on each initial continuous dark area to obtain continuous dark areas.

[0015] By employing the above technical solutions, the system effectively removes interference signals, highlights true object information, improves the accuracy of subsequent segmentation, and enhances the system's ability to detect weak signals, enabling it to identify small or low-reflectivity objects. Using a preset segmentation algorithm to binarize the denoising matrix simplifies the subsequent analysis process. By selecting an appropriate threshold algorithm, the system can maintain stable segmentation results under different lighting conditions, improving robustness and adaptability. Morphological processing of the initial continuous dark areas further optimizes the object contour. It can correct contour defects caused by uneven lighting, irregular object surfaces, etc., and can also merge incorrectly segmented object parts, improving the completeness and accuracy of object recognition.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after obtaining the real-time detection information of the conveyor belt based on the judgment result, the method further includes: Real-time monitoring of conveyor belt speed and vibration parameters; The transmission frequency of the grating transmitter and the sampling rate of the grating receiver are dynamically adjusted according to the running speed of the conveyor belt. Vibration parameters are analyzed using Fast Fourier Transform to identify vibration frequency and amplitude; A vibration compensation model is established based on the vibration frequency and vibration amplitude. The intensity value of each optical signal is input into the vibration compensation model to obtain the compensation intensity value; A three-dimensional light intensity distribution matrix is ​​constructed based on the compensation intensity value, and image segmentation processing is performed on the three-dimensional light intensity distribution matrix to identify continuous dark areas in the three-dimensional light intensity distribution matrix.

[0017] By adopting the above technical solution, the system monitors the conveyor belt's operating speed and vibration parameters in real time, enabling it to promptly capture dynamic changes in the working environment. Continuous monitoring of these parameters allows the system to understand its current operating status, providing accurate data for subsequent adjustments, improving its response speed and adaptability, and maintaining stable detection performance in changing environments. The system dynamically adjusts the emission frequency of the grating transmitter and the sampling rate of the grating receiver based on the conveyor belt's operating speed. Increasing the emission frequency and sampling rate when the conveyor belt speed increases prevents the omission of item information; conversely, appropriately decreasing the frequency and sampling rate when the speed decreases optimizes system resource utilization, reduces energy consumption, improves detection accuracy, optimizes system energy efficiency, and extends equipment lifespan. A vibration compensation model is established based on vibration analysis results, and the intensity value of each optical signal is input into this model to obtain a compensation intensity value, reducing the impact of vibration on the detection results.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, the transmission frequency of the grating transmitter and the sampling rate of the grating receiver are dynamically adjusted according to the operating speed of the conveyor belt, specifically including: Establish a mapping relationship between operating speed and transmission frequency and sampling rate; When a change in the conveyor belt's running speed is detected, the optimal transmission frequency and optimal sampling rate are recalculated using an interpolation algorithm based on the mapping relationship. Adjustment commands are sent to the grating transmitter and the grating receiver to make the transmitter's transmission frequency the optimal transmission frequency and the receiver's sampling rate the optimal sampling rate.

[0019] By adopting the above technical solution, the system can quickly determine the most suitable operating parameters at different operating speeds, avoiding performance fluctuations that may result from blind adjustments. This improves the system's adaptability and enhances the scientific rigor and reliability of parameter adjustments. When a change in the conveyor belt's operating speed is detected, an interpolation algorithm is used to recalculate the optimal transmission frequency and optimal sampling rate, enabling the system to smoothly and continuously adapt to speed changes. This reduces the adverse effects of potential parameter abrupt changes and also improves the system's sensitivity and response speed to minute speed variations.

[0020] This application provides a device for real-time detection of conveyor belt items based on a grating device. The device includes a system, a computer-readable storage medium, and a computer program product.

[0021] Secondly, embodiments of this application provide a real-time conveyor belt item detection system based on a grating device. The real-time conveyor belt item detection system based on a grating device includes: one or more processors and a memory; the memory is coupled to one or more processors, and the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the system to perform the method as described in the first aspect and any possible implementation of the first aspect.

[0022] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a system, cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Fourthly, embodiments of this application provide a computer program product, characterized in that, when the computer program product is run on a system, it causes the system to execute the method described in any possible implementation of the first aspect.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. This application provides a real-time detection method for conveyor belt items based on a grating device. Different wavelengths of light exhibit different reflection and absorption characteristics for items with different materials and surface properties, enabling better differentiation and identification of various types of items and reducing the probability of false detections and missed detections. The three-dimensional light intensity distribution matrix not only contains the position and height information of the item on the conveyor belt but also records the changes of this information over time, capturing the dynamic features of the item, such as its movement trajectory and shape changes, thereby improving detection accuracy. Image segmentation processing of the three-dimensional light intensity distribution matrix identifies continuous dark areas, transforming complex three-dimensional data into understandable and processable item contour information. This improves the accuracy of identifying the shape and size of items and reduces the adverse effects of overlapping or partial occlusion, enhancing detection capabilities in complex scenes. By analyzing the changes of continuous dark areas at different heights and time points, the accuracy of detecting closely arranged or partially overlapping items is improved.

[0025] 2. This application provides a real-time conveyor belt item detection method based on a grating device. Adjusting the angles of the transmitting and receiving units ensures their optical axes are parallel and perpendicular to the conveyor belt's direction of movement, reducing signal attenuation and distortion caused by angular deviations and improving the signal-to-noise ratio. By identifying transmitting and receiving unit pairs whose initial light intensity values ​​are outside a preset range and making corresponding adjustments, system performance differences caused by manufacturing errors, installation deviations, or environmental factors are reduced. Using standard test objects at different conveyor belt speeds allows for evaluation of performance in dynamic environments. The system's response time and detection sensitivity are calculated based on recorded light intensity changes, and parameters are adjusted to adapt the system to different working conditions.

[0026] 3. This application provides a real-time detection method for conveyor belt items based on a grating device. It monitors the conveyor belt's operating speed and vibration parameters in real time, enabling the system to promptly capture dynamic changes in the working environment. By continuously monitoring these parameters, the system can understand its current working status in real time, providing accurate basis for subsequent adjustments, improving the system's response speed and adaptability, and maintaining stable detection performance in changing environments. The transmission frequency of the grating transmitter and the sampling rate of the grating receiver are dynamically adjusted according to the conveyor belt's operating speed. When the conveyor belt speed increases, increasing the transmission frequency and sampling rate can prevent the omission of item information; when the speed decreases, appropriately reducing the frequency and sampling rate can optimize system resource utilization, reduce energy consumption, improve detection accuracy, optimize system energy efficiency, and extend equipment lifespan. A vibration compensation model is established based on vibration analysis results, and the intensity value of each optical signal is input into this model to obtain a compensation intensity value, reducing the impact of vibration on the detection results. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating a method for real-time detection of conveyor belt items based on a grating device, as described in an embodiment of this application.

[0028] Figure 2 This is a flowchart illustrating a system pre-run self-test method in an embodiment of this application.

[0029] Figure 3 This is a schematic diagram of the physical device structure of a real-time conveyor belt item detection system based on a grating device provided in an embodiment of this application. Detailed Implementation

[0030] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0031] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0032] The following is combined with Figure 1 The present application describes a real-time detection method for conveyor belt items based on a grating device: Please see Figure 1 This is a flowchart illustrating a real-time detection method for conveyor belt items based on a grating device in an embodiment of this application.

[0033] S101. Control the transmitting units of each group of grating emitters to cyclically transmit optical signals of different wavelengths according to a preset timing sequence; The system controls the transmitting units of each group of grating transmitters to cyclically transmit optical signals of different wavelengths according to a preset timing sequence. Each group of grating transmitters is contained within a grating device, which also includes a set of grating receivers corresponding to each group of grating transmitters. Specifically, controlling the transmitting units of each group of grating transmitters to cyclically transmit optical signals of different wavelengths according to a preset timing sequence includes: Each group of grating emitters is assigned a unique time slot, the length of which is determined by the conveyor belt speed. Within each unique time slot, the various transmitting units of the control grating emitter sequentially emit optical signals of different wavelengths in a preset order; After one transmission cycle is completed, a preset calibration time slot is inserted. During the preset calibration time slot, each transmission unit is controlled to transmit a preset calibration optical signal. The transmission cycle is when each transmission unit transmits optical signals of different wavelengths in a preset order. Real-time monitoring of the operating parameters of each transmitting unit, including light intensity stability and wavelength accuracy; If a fault is found in a transmitting unit based on the operating parameters, the transmitting unit is marked.

[0034] The grating device contains multiple sets of grating transmitters and corresponding grating receivers. By controlling the transmitting unit to emit light signals of different wavelengths in a specific timing sequence, the system can achieve accurate detection of items on the conveyor belt.

[0035] In practice, the system assigns a unique time slot to each group of grating emitters, the length of which is dynamically determined based on the conveyor belt's operating speed. Within each unique time slot, the system controls each emitting unit of the grating emitter to sequentially emit optical signals of different wavelengths in a preset order. This time-division multiplexing method reduces interference between different grating emitters and improves detection accuracy.

[0036] After a complete transmission cycle, the system inserts a preset calibration time slot. During this time slot, the system controls each transmitting unit to emit a preset calibration optical signal. This calibration process can be used to monitor and adjust the performance of the transmitting units, ensuring the long-term stability of the entire detection system.

[0037] To further improve system reliability, the system monitors the operating parameters of each transmitting unit in real time, including light intensity stability and wavelength accuracy. When the system determines that a transmitting unit has malfunctioned based on the operating parameters, it marks that unit. This real-time monitoring and fault marking mechanism helps the system promptly identify and address problems that may affect detection accuracy.

[0038] The system can employ an adaptive wavelength selection strategy, dynamically adjusting the combination of emitted light signals based on the material properties of the item being detected and environmental conditions. This adaptive strategy can optimize the detection results for different types of items, improving the system's applicability and detection accuracy.

[0039] Furthermore, the system can achieve multispectral fusion detection, that is, simultaneously using light signals of multiple wavelengths for detection and fusing the detection results of different wavelengths through algorithms. This multispectral fusion technology can provide richer information about the object, helping to improve the system's ability to identify complex objects.

[0040] The system can also employ pulse modulation technology to enhance its resistance to ambient light interference and improve detection reliability in complex lighting environments by modulating the pulse width and frequency of the optical signal.

[0041] S102. After confirming that each group of grating receivers has received an optical signal, record the intensity value of the optical signal received by each group of grating receivers. The system first confirms whether each group of grating receivers has received the optical signal emitted from the corresponding grating transmitter. After confirming that each group of grating receivers has received the optical signal, it records the intensity value of the optical signal received by each group of grating receivers. These intensity values ​​are the basic data for subsequently constructing a three-dimensional light intensity distribution matrix. The system can use a high-precision analog-to-digital converter (ADC) to achieve accurate quantization of the optical signal intensity, ensuring that the recorded data has sufficient accuracy and dynamic range.

[0042] To improve data reliability, the system can average multiple sampling results from each receiver to reduce the impact of random noise. Simultaneously, the system can implement automatic gain control (AGC) to automatically adjust the receiver sensitivity based on the intensity of the received light signal, adapting to items with different reflectivities and varying ambient light conditions.

[0043] The system can also perform data preprocessing functions, such as removing baseline drift and filtering high-frequency noise, to improve the efficiency and accuracy of subsequent data processing. Furthermore, the system can perform real-time outlier detection on the recorded intensity values, promptly identifying and marking abnormal data points that may be caused by sensor malfunctions or external interference.

[0044] To address potential data loss, the system can implement data interpolation. When a receiver fails to receive a signal, the system can perform interpolation estimation based on data from adjacent receivers to maintain data continuity.

[0045] The system can also perform data compression and storage, reducing the storage space required for raw data through appropriate compression algorithms while ensuring data integrity and recoverability. This is particularly significant for detection systems that operate continuously for extended periods, as it can significantly reduce data storage and transmission costs.

[0046] S103. Construct a three-dimensional light intensity distribution matrix based on intensity values; The system constructs a three-dimensional light intensity distribution matrix based on the intensity value. The three dimensions of the three-dimensional light intensity distribution matrix correspond to the position, height and time on the conveyor belt, respectively.

[0047] In this step, the system uses the light signal intensity values ​​recorded in the previous step to construct a three-dimensional light intensity distribution matrix. The three dimensions of this matrix correspond to the position, height, and time on the conveyor belt, respectively. In this way, the system can capture the spatial distribution of objects on the conveyor belt and how this distribution changes over time.

[0048] During the construction process, the system first needs to map discrete intensity data to specific coordinate points in three-dimensional space. This requires the system to know precisely the spatial location of each grating receiver and the corresponding time point for each set of data. The system can use interpolation algorithms, such as trilinear interpolation or B-spline interpolation, to fill the space between discrete sampling points and generate a continuous three-dimensional light intensity distribution.

[0049] To improve the accuracy and resolution of the matrix, the system can implement an adaptive sampling strategy. In areas with drastic changes in light intensity, such as object edges, the system can increase the sampling density, while in areas with gradual changes in light intensity, the sampling density can be appropriately reduced. This strategy can optimize the use of computational resources while maintaining accuracy.

[0050] The system can also perform multi-scale analysis. By constructing light intensity distribution matrices at different resolutions, the system can simultaneously capture the overall shape and local details of an object, which helps with subsequent object recognition and classification.

[0051] To handle large-scale data, the system can employ a block processing technique. The entire detection area is divided into multiple sub-regions, each with its own sub-matrix, which are then merged into a complete three-dimensional light intensity distribution matrix. This method improves processing speed and allows for parallel computation.

[0052] Taking into account the slight tilt or curvature that may exist in the conveyor belt, the system can perform geometric corrections when constructing the matrix. Using a pre-calibrated conveyor belt surface model, the system can compensate for these geometric deformations, ensuring that the constructed matrix accurately reflects the actual spatial distribution of the items.

[0053] The system also features a dynamic update mechanism. As new intensity data is continuously input, the system can update the three-dimensional light intensity distribution matrix in real time, without having to rebuild the entire matrix each time. This incremental update method can significantly improve the system's real-time performance.

[0054] Finally, while constructing the matrix, the system can calculate some statistical features, such as the mean and variance of light intensity at each spatial point. These statistical features can provide additional useful information for subsequent image segmentation and object recognition.

[0055] S104. Perform image segmentation processing on the three-dimensional light intensity distribution matrix to identify continuous dark areas in the three-dimensional light intensity distribution matrix; The system performs image segmentation on the 3D light intensity distribution matrix, identifying continuous dark areas within the matrix, where each continuous dark area represents the outline of an object. Specifically, the 3D light intensity distribution matrix is ​​denoised to obtain a denoised 3D light intensity distribution matrix. Using a pre-defined segmentation algorithm, the denoised three-dimensional light intensity distribution matrix is ​​binarized to obtain preliminary segmentation results; A three-dimensional connected component analysis algorithm was used to identify preliminary continuous dark areas based on the initial segmentation results; Morphological processing is performed on each initial continuous dark area to obtain continuous dark areas.

[0056] First, the system performs noise reduction on the three-dimensional light intensity distribution matrix to obtain a denoised three-dimensional light intensity distribution matrix. The noise reduction process can employ various filtering algorithms, such as Gaussian filtering, median filtering, or adaptive filtering. The system can select the most suitable filtering method based on the characteristics of the noise, or combine multiple filtering methods to achieve the best noise reduction effect.

[0057] Next, the system uses a preset segmentation algorithm to binarize the denoised 3D light intensity distribution matrix, obtaining preliminary segmentation results. The binarization process can employ a global thresholding method (such as the Otsu method) or a local adaptive thresholding method. The system can dynamically select the most suitable thresholding method based on the characteristics of the light intensity distribution to adapt to different detection environments and object types.

[0058] Then, the system uses a 3D connected component analysis algorithm on the preliminary segmentation results to identify preliminary continuous dark areas. This step groups adjacent dark pixels in the binarized data into a whole, initially defining the outline of each object. The system can use recursive or iterative methods to implement 3D connected component analysis, while considering the continuity of spatial and temporal dimensions.

[0059] Finally, the system performs morphological processing on each initial continuous dark area to obtain the final continuous dark area. Morphological processing can include operations such as dilation, erosion, opening, and closing, used to smooth object boundaries, fill small holes, and remove minute noise. The system can design specific morphological processing sequences based on the characteristics of the object and detection requirements to optimize the extraction effect of the object contour.

[0060] The system can implement a multi-scale segmentation strategy, performing segmentation at different spatial resolutions and then fusing the multi-scale segmentation results to improve the recognition capability of objects of different sizes. Furthermore, the system can employ deep learning-based image segmentation algorithms, such as U-Net or Mask R-CNN, using pre-trained models to improve segmentation accuracy and robustness.

[0061] The system can also implement edge enhancement technology, paying special attention to the edge regions of objects during segmentation to improve the accuracy of edge localization. This is particularly important for subsequent dimensional measurements. Simultaneously, the system can utilize temporal information to implement temporal consistency constraints, ensuring that the segmentation results of the same object remain consistent across different time points.

[0062] For items that are partially occluded or in contact with each other, the system can perform optimized processing after segmentation. By analyzing the shape features and contextual information of the items, the system can attempt to separate adhered items or complete the outline of partially occluded items.

[0063] Finally, the system can assign a unique identifier to each identified continuous dark area and record its basic characteristics such as position and volume in three-dimensional space, providing basic data for subsequent item tracking and analysis.

[0064] S105. Based on the results of identifying changes in the outline of an object at different heights and time points in the continuous dark area, and based on the results of the changes, determine the quantity, size, and relative position of the object to obtain the judgment result; The system first analyzes the contours of each continuous dark area at different height levels. By comparing the contour shapes and areas at different heights, the system can infer the three-dimensional shape features of the object. For example, if the object is a regular cuboid, its contours at different heights should maintain a similar rectangular shape; if it is a cylinder, it will exhibit a circular contour. The system can build a shape feature library for matching and recognizing the shapes of common objects.

[0065] Simultaneously, the system analyzes changes in the outline of items over time. By tracking the positional changes of continuous dark areas at different points in time, the system can calculate the moving speed and trajectory of items on the conveyor belt. This information can be used to predict the future position of items, facilitating real-time tracking and sorting control.

[0066] Based on the spatial and temporal changes in the contours, the system determines the number of items. The system can employ clustering algorithms to group consecutive dark areas with similar motion and shape characteristics into the same item. For partially overlapping or temporarily occluded items, the system can analyze the continuity and consistency of the contours to determine if they are the same item.

[0067] In terms of dimensional measurement, the system utilizes contour information from different heights and time points to construct a 3D model of the object. By calculating parameters such as the volume, surface area, and maximum side length of this 3D model, the system can obtain the object's precise dimensions. The system can also perform automatic calibration, ensuring measurement accuracy by periodically measuring standard objects of known dimensions.

[0068] Regarding the relative positions of objects, the system analyzes the spatial distribution and movement trajectories of different object outlines. The system can establish a dynamic spatial relationship map, recording information such as distance, direction, and relative motion between objects. This is extremely useful for detecting collisions and determining whether objects are stacked.

[0069] The system can implement a multi-hypothesis tracking algorithm, simultaneously maintaining multiple possible object state hypotheses and continuously updating the confidence level of these hypotheses based on subsequent observation data. This method can effectively handle situations where objects are temporarily occluded or sensor data is temporarily lost.

[0070] Furthermore, the system can utilize machine learning algorithms, such as Support Vector Machines (SVM) or Random Forests, to improve the accuracy of item feature recognition and classification. By training the model to learn the features of different types of items, the system can more accurately determine the type and attributes of items.

[0071] Finally, the system integrates all the analysis and judgment results to form a complete judgment result. This result includes information such as the unique identifier, quantity, precise size, location coordinates, speed, and direction of movement for each detected item. This information provides comprehensive data support for the subsequent generation of real-time detection information.

[0072] S106. Based on the judgment result, obtain the real-time detection information of the conveyor belt; Based on the judgment results, the system obtains real-time detection information of the conveyor belt, which includes the number of items, the size and position of each item.

[0073] The system first integrates and formats the judgment results, converting the raw data into a standardized information format. This process involves data filtering, transformation, and organization to ensure that the output information is comprehensive, easy to understand, and easy to use. The system can design various information output templates to suit different application needs and usage scenarios.

[0074] Regarding item quantity information, the system not only provides the total number, but can also classify and count items according to predefined categories (such as size range, shape characteristics, etc.). The system can realize real-time counting function, dynamically updating the counting results as the items move on the conveyor belt.

[0075] Regarding item size information, the system provides three-dimensional dimensional data for each item, including length, width, height, and derived parameters such as volume and surface area. The system can automatically mark items with dimensional abnormalities based on preset tolerance ranges. Furthermore, the system can calculate and output statistical information about item dimensions, such as average value and standard deviation, for quality control during the production process.

[0076] For item location information, the system provides the real-time coordinates of each item on the conveyor belt. These coordinates can be in an absolute coordinate system (such as the distance relative to the start of the conveyor belt) or a relative coordinate system (such as the relative position to other items), allowing the system to predict the future position of the items.

[0077] S107. Real-time monitoring of the conveyor belt's operating speed and vibration parameters; For monitoring the speed of conveyor belts, various technical solutions can be employed. A common method is to use an encoder, mounted on the drive or driven shaft of the conveyor belt. The encoder accurately records the rotational speed of the shaft, thereby calculating the linear speed of the conveyor belt. The system can select either a photoelectric encoder or a magnetic encoder, depending on the specific working environment and accuracy requirements.

[0078] Another method for speed monitoring is to use non-contact sensors, such as laser velocimeters or Doppler radar. These devices can directly measure the speed of movement on the conveyor belt surface, avoiding errors that may be introduced by mechanical connections. The system can install multiple speed sensors at different locations on the conveyor belt and obtain more accurate speed information through data fusion.

[0079] The system can also achieve adaptive sampling rate adjustment. Based on changes in conveyor belt speed, the system dynamically adjusts the sampling frequency of speed data, optimizing system resource utilization while ensuring measurement accuracy.

[0080] For monitoring vibration parameters, the system typically uses accelerometers or vibration sensors. These sensors can be installed at critical locations on the conveyor belt, such as near the drive wheel, at the tensioning device, and on the conveyor belt support structure. The system can simultaneously monitor vibrations in multiple directions, including vertical, horizontal, and axial directions.

[0081] S108. Dynamically adjust the transmission frequency of the grating transmitter and the sampling rate of the grating receiver according to the running speed of the conveyor belt; The system establishes a mapping relationship between operating speed and transmission frequency and sampling rate; When a change in the conveyor belt's running speed is detected, the optimal transmission frequency and optimal sampling rate are recalculated using an interpolation algorithm based on the mapping relationship. Adjustment commands are sent to the grating transmitter and the grating receiver to make the transmitter's transmission frequency the optimal transmission frequency and the receiver's sampling rate the optimal sampling rate.

[0082] First, the system establishes a mapping relationship between operating speed and transmission frequency and sampling rate. This mapping relationship can be based on a combination of theoretical calculations and actual test data. Theoretically, the transmission frequency and sampling rate should increase with the increase of conveyor belt speed to ensure that sufficient information about the items can be captured. The system can use mathematical models, such as linear or polynomial models, to describe this relationship. Simultaneously, the system can optimize and verify this mapping relationship through extensive experimental data.

[0083] When the system detects a change in the conveyor belt's operating speed, it immediately triggers an adjustment process. The system first searches a preset mapping relationship to find the reference point closest to the current speed. Then, the system uses an interpolation algorithm to calculate the optimal transmission frequency and sampling rate. The interpolation algorithm can be linear interpolation, polynomial interpolation, or spline interpolation, etc., depending on the required accuracy and computational complexity.

[0084] The system can implement an adaptive adjustment strategy. In addition to speed, the system can also consider other environmental factors, such as lighting conditions and object type, to comprehensively determine the optimal transmission frequency and sampling rate. This multi-factor adjustment strategy allows the system to better adapt to complex and changing working environments.

[0085] To avoid system instability caused by frequent adjustments, the system can set adjustment thresholds. Parameter adjustments are only triggered when the speed change exceeds the preset threshold. Simultaneously, the system can implement a smooth transition mechanism, using gradual adjustments to avoid abrupt parameter changes.

[0086] The system sends adjustment commands to the grating transmitter and receiver to bring their operating parameters to the calculated optimal values. This process requires consideration of the equipment's response time and adjustment accuracy. The system can achieve closed-loop control, using a feedback mechanism to ensure that the actual operating parameters are consistent with the target values.

[0087] S109. Use Fast Fourier Transform to analyze vibration parameters and identify vibration frequency and amplitude; First, the system preprocesses the acquired time-domain vibration signal. This includes removing the DC bias, applying window functions (such as the Hanning or Hamming window) to reduce spectral leakage, and performing necessary filtering to remove high-frequency noise. The purpose of preprocessing is to improve the accuracy and reliability of the FFT analysis.

[0088] The system then performs a Fast Fourier Transform (FFT). The FFT algorithm converts the time-domain signal into a frequency-domain representation, displaying the individual frequency components of the vibration signal and their corresponding amplitudes. The system can select an appropriate number of FFT points to strike a balance between computational efficiency and frequency resolution. For applications requiring higher frequency resolution, the system can employ zero-padding techniques.

[0089] The system analyzes the FFT results to identify the main vibration frequencies and their corresponding amplitudes. This typically involves finding peaks in the spectrum and calculating their frequencies and amplitudes. The system can set thresholds to focus only on frequency components exceeding a certain amplitude, thus filtering out unimportant, weak vibrations.

[0090] S110. Establish a vibration compensation model based on the vibration frequency and vibration amplitude; The system establishes a vibration compensation model based on the vibration frequency and amplitude. This model aims to eliminate or reduce the impact of conveyor belt vibration on light intensity measurement, thereby improving the accuracy of item detection.

[0091] Specifically, the system can establish a vibration compensation model using a polynomial regression method. First, the system collects a large amount of sample data, using vibration frequency and amplitude as independent variables and light intensity measurement error as the dependent variable. Then, the system uses the least squares method to fit a polynomial function, obtaining the mathematical expression of the vibration compensation model.

[0092] S111. Input the intensity value of each optical signal into the vibration compensation model to obtain the compensation intensity value; The system first acquires the raw optical signal intensity values ​​received by the grating receiver. Then, the system inputs these intensity values ​​along with the corresponding vibration parameters (frequency and amplitude) into the vibration compensation model. Based on the input vibration parameters, the vibration compensation model calculates the light intensity deviation caused by the vibration and subtracts this deviation from the raw intensity values ​​to obtain the compensated light intensity value.

[0093] To improve computational efficiency, the system can employ parallel processing technology. The system distributes a large number of optical signal intensity values ​​to multiple processing units for simultaneous processing, with each unit responsible for compensating a portion of the data. This parallel processing method can significantly reduce computation time, enabling the system to process high-frequency acquired optical intensity data in real time.

[0094] Considering that gratings at different locations may be affected by vibration to varying degrees, the system can establish an independent vibration compensation model for each grating receiver. The system adjusts the parameters of the vibration compensation model based on the location of each receiver and the characteristics of its surrounding environment to achieve a more accurate compensation effect.

[0095] S112. Construct a three-dimensional light intensity distribution matrix based on the compensation intensity value.

[0096] A three-dimensional light intensity distribution matrix is ​​constructed based on the compensation intensity value, and image segmentation processing is performed on the three-dimensional light intensity distribution matrix to identify continuous dark areas in the three-dimensional light intensity distribution matrix. That is, step S104 is re-executed, which will not be described in detail here.

[0097] In the above embodiments, light of different wavelengths exhibits different reflection and absorption characteristics for items with different materials and surface properties, enabling better differentiation and identification of various types of items and reducing the probability of false detections and missed detections. The three-dimensional light intensity distribution matrix not only contains the position and height information of the item on the conveyor belt but also records the changes of this information over time, capturing the dynamic characteristics of the item, such as its movement trajectory and shape changes, thereby improving detection accuracy. Image segmentation processing of the three-dimensional light intensity distribution matrix identifies continuous dark areas, transforming complex three-dimensional data into understandable and processable item contour information. This improves the accuracy of identifying the shape and size of items and reduces the adverse effects of overlapping or partial occlusion, enhancing detection capabilities in complex scenes. By analyzing the changes of continuous dark areas at different heights and time points, the accuracy of detecting closely arranged or partially overlapping items is improved.

[0098] Furthermore, before performing step S101 in the above embodiment, the detection system needs to be calibrated to reduce the influence of other factors on the detection results. The following is in conjunction with... Figure 2 The following describes a system pre-operation self-test method in an embodiment of this application: Please see Figure 2 This is a flowchart illustrating a system pre-run self-test method in an embodiment of this application.

[0099] S201. Adjust the angles of the transmitting unit and the receiving unit so that the optical axes corresponding to the transmitting unit and the receiving unit are parallel to each other and perpendicular to the direction of movement of the conveyor belt. In this step, the system adjusts the angles of the transmitting and receiving units to ensure the optical axes of the grating devices are aligned. Specifically, the system can employ an automated adjustment mechanism to achieve precise angle control. The system uses high-precision stepper motors to drive the supports of the transmitting and receiving units, achieving optical axis alignment through minute angle adjustments. The system can also integrate sensors such as gyroscopes and accelerometers to monitor the attitude of the transmitting and receiving units in real time, providing accurate feedback data for angle adjustment.

[0100] To ensure the optical axis is perpendicular to the conveyor belt's direction of movement, the system uses a laser rangefinder to measure the distances between the transmitting and receiving units and the conveyor belt surface. The system performs multi-point measurements at different locations on the conveyor belt, calculates the angle between the optical axis and the conveyor belt surface using triangulation principles, and then performs angle correction accordingly.

[0101] The system can also incorporate computer vision technology, using a high-resolution camera to capture the trajectory of the light beam emitted by the transmitting unit. The system analyzes the beam path through image processing algorithms, accurately calculating the deviation between the optical axis and the ideal path, thereby guiding the angle adjustment process.

[0102] To address angular misalignment caused by environmental vibrations and temperature changes, the system employs a dynamic calibration mechanism. The system periodically emits calibration light signals, analyzes the light intensity distribution received by the receiving unit, and automatically triggers a fine-tuning process if an angular misalignment is detected, ensuring the optical axis remains optimally aligned at all times.

[0103] Furthermore, the system can establish a digital twin model to simulate the physical characteristics and optical path propagation of the grating device. The system uses this model to predict the impact of adjustments at different angles on optical axis alignment, thereby optimizing the adjustment strategy, reducing trial-and-error attempts, and improving calibration efficiency.

[0104] S202. When the conveyor belt is unloaded, control the transmitting unit to transmit the initial optical signal and record the initial optical intensity value received by each receiving unit. The system first ensures the conveyor belt is completely empty, which can be achieved through a preset cleaning procedure or visual inspection. Then, the system sequentially activates each transmitting unit according to a predetermined sequence, emitting an initial optical signal of a specific wavelength and intensity. The system precisely controls the transmission timing to ensure that only one transmitting unit is active at any given time, avoiding mutual interference.

[0105] For each transmitting unit, the system records the light intensity values ​​received by all corresponding receiving units. The system uses a high-precision analog-to-digital converter (ADC) to acquire the output signals of the receiving units, ensuring the accuracy of the light intensity measurement. To improve data reliability, the system can perform multiple measurements on each transmitting-receiving unit pair and take the average value as the final initial light intensity value.

[0106] S203. Identify the transmitting and receiving unit pairs whose initial light intensity values ​​are not in the preset range based on the initial light intensity values, and adjust the angles of the transmitting and receiving unit pairs accordingly. The system identifies transmitting and receiving unit pairs whose initial light intensity values ​​are outside the preset range based on the initial light intensity values, and adjusts the angles of the transmitting and receiving unit pairs so that the corresponding initial light intensity values ​​of the transmitting and receiving unit pairs are within the preset range.

[0107] The system first defines a preset interval, which is typically determined based on equipment specifications and historical data. The system compares the initial light intensity value of each transmit-receive unit pair with the preset interval, identifying those unit pairs that are not within the interval. To improve the accuracy of identification, the system can use statistical methods, such as Z-score or interquartile range (IQR), to dynamically determine the anomaly threshold, instead of using a fixed preset interval.

[0108] For any identified abnormal unit pairs, the system initiates an automatic adjustment program. The system uses a precise electric adjustment mechanism to fine-tune the angles of the transmitting and receiving units. The adjustment process employs a closed-loop control strategy; after each minor adjustment, the system immediately measures the light intensity value and compares it with the target value. Based on the difference, it continues to adjust until the light intensity value falls within a preset range.

[0109] S204. Place a standard test object on the conveyor belt, control the conveyor belt to run at different speeds, and record the light intensity changes of each receiving unit at different conveyor belt speeds. The system first selects a set of standard test objects with known geometric dimensions, materials, and optical properties. The system can then use an automated robotic arm or conveyor system to precisely place these standard objects at predetermined positions on a conveyor belt.

[0110] The system then controls the conveyor belt to operate according to a preset speed sequence. This speed sequence typically covers the entire operating speed range of the system, from the lowest to the highest speed, including multiple intermediate speed points. The system uses a high-precision frequency converter or servo control system to ensure the accuracy and stability of the conveyor belt speed.

[0111] At each velocity point, the system activates all transmitting units and records the changes in light intensity received by each receiving unit. The system employs a high-speed data acquisition card to capture instantaneous changes in light intensity at a sufficiently high sampling rate. To improve data reliability, the system repeats the measurement multiple times at each velocity point and calculates statistical characteristics such as the mean and standard deviation.

[0112] S205. Based on the recorded changes in light intensity, calculate the system's response time and detection sensitivity, and adjust the parameters accordingly.

[0113] The system first analyzes the recorded light intensity change data to extract key features. For response time, the system calculates the time interval from when an object enters the detection area until the light intensity reaches a stable value. The system can use methods such as threshold detection or curve fitting to accurately locate the start and end points of light intensity changes. For detection sensitivity, the system calculates the ratio of the magnitude of the light intensity change to the object size to evaluate the system's ability to detect objects of different sizes.

[0114] The system can implement an adaptive thresholding algorithm. Based on the light intensity variation characteristics at different speeds, the system dynamically adjusts the detection threshold to maximize system sensitivity while ensuring detection accuracy. The system can use machine learning algorithms, such as decision trees or support vector machines, to establish a mapping relationship between speed, object features, and the optimal threshold.

[0115] To improve computational efficiency, the system can employ parallel processing techniques. The system distributes a large amount of light intensity data across multiple processing units for simultaneous analysis, with each unit responsible for calculating the response time and detection sensitivity of a portion of the data. This parallel processing method can significantly reduce computation time, enabling the system to quickly complete performance evaluation.

[0116] The system can also perform comprehensive optimization of multiple indicators. In addition to response time and detection sensitivity, the system can also consider indicators such as false detection rate and false negative rate. The system uses multi-objective optimization algorithms, such as genetic algorithms or particle swarm optimization, to find the best balance point among various performance indicators and determine the optimal combination of system parameters.

[0117] In the above embodiments, adjusting the angles of the transmitting and receiving units so that their optical axes are parallel to each other and perpendicular to the direction of conveyor belt movement reduces signal attenuation and distortion caused by angular deviations, thereby improving the signal-to-noise ratio. By identifying transmitting and receiving unit pairs whose initial light intensity values ​​are outside the preset range and making corresponding adjustments, the performance differences caused by manufacturing errors, installation deviations, or environmental factors are reduced. Using standard test objects to conduct tests at different conveyor belt speeds allows for the evaluation of performance in dynamic environments. Based on recorded light intensity changes, the system's response time and detection sensitivity are calculated, and necessary parameter adjustments are made to enable the system to adapt to different operating conditions.

[0118] The system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of a real-time detection system for conveyor belt items based on a grating device, provided in an embodiment of this application.

[0119] It should be noted that, Figure 3 The structure of the system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0120] like Figure 3 As shown, the system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 302 or a program loaded from storage portion 308 into Random Access Memory (RAM) 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0121] The following components are connected to I / O interface 305: input section 306 including a camera, infrared sensor, etc.; output section 307 including a liquid crystal display (LCD) and speakers, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0122] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0123] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. The transmitted data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0124] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a 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 indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0125] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist independently and not assembled into the system. The storage medium carries one or more computer programs that, when executed by a processor of a system, cause the system to implement the methods provided in the above embodiments.

[0126] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0127] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0128] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0129] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for real-time detection of conveyor belt items based on a grating device, characterized in that, include: The transmitting units of each group of grating transmitters are controlled to cyclically transmit optical signals of different wavelengths according to a preset timing sequence. Each group of grating transmitters is included in the grating device, and the grating device also includes a group of grating receivers that correspond one-to-one with each group of grating transmitters. If it is determined that each group of grating receivers has received the optical signal, the intensity value of the optical signal received by each group of grating receivers is recorded; A three-dimensional light intensity distribution matrix is ​​constructed based on the intensity value, and the three dimensions of the three-dimensional light intensity distribution matrix correspond to the position, height and time on the conveyor belt, respectively. The three-dimensional light intensity distribution matrix is ​​subjected to image segmentation processing to identify continuous dark areas in the three-dimensional light intensity distribution matrix, and each continuous dark area represents the outline of an object; Based on the changes in the outline of the object at different heights and time points identified by the continuous dark area, and based on the changes, the quantity, size and relative position of the object are determined to obtain the judgment result; Based on the judgment result, the real-time detection information of the conveyor belt is obtained, including the number of items, the size and position of each item.

2. The method according to claim 1, characterized in that, Before the transmitting units of each group of grating emitters cyclically transmit optical signals of different wavelengths according to a preset timing sequence, the method further includes: Adjust the angles of the transmitting unit and the receiving unit so that the optical axes corresponding to the transmitting unit and the receiving unit are parallel to each other and perpendicular to the direction of movement of the conveyor belt; When the conveyor belt is unloaded, the transmitting unit is controlled to emit an initial light signal, and the initial light intensity value received by each receiving unit is recorded. Based on the initial light intensity value, the transmitting unit and receiving unit pair whose initial light intensity value is not in the preset range are identified, and the angle of the transmitting unit and receiving unit pair is adjusted so that the initial light intensity value corresponding to the transmitting unit and receiving unit pair is within the preset range; A standard test object was placed on a conveyor belt, and the conveyor belt was controlled to run at different speeds. The light intensity changes of each receiving unit were recorded at different conveyor belt speeds. Based on the recorded changes in light intensity, the system's response time and detection sensitivity are calculated, and parameters are adjusted accordingly.

3. The method according to claim 1, characterized in that, The control unit for each group of grating emitters to cyclically emit optical signals of different wavelengths according to a preset timing sequence specifically includes: Each group of grating emitters is assigned a unique time slot, the length of which is determined based on the conveyor belt speed. Within each unique time slot, the various transmitting units of the grating emitter are controlled to sequentially emit optical signals of different wavelengths in a preset order.

4. The method according to claim 3, characterized in that, After the method controls the various transmitting units of the grating emitter to sequentially emit optical signals of different wavelengths in a preset order, the method further includes: After a transmission cycle is completed, a preset calibration time slot is inserted. During the preset calibration time slot, each transmission unit is controlled to transmit a preset calibration optical signal. The transmission cycle is when each transmission unit transmits optical signals of different wavelengths in the preset order. Real-time monitoring of the operating parameters of each emitting unit, including light intensity stability and wavelength accuracy; If a fault is determined to exist in a transmitting unit based on the operating parameters, the transmitting unit is marked.

5. The method according to claim 1, characterized in that, The step of performing image segmentation processing on the three-dimensional light intensity distribution matrix to identify continuous dark areas in the three-dimensional light intensity distribution matrix specifically includes: The three-dimensional light intensity distribution matrix is ​​denoised to obtain a denoised three-dimensional light intensity distribution matrix. Using a preset segmentation algorithm, the denoised three-dimensional light intensity distribution matrix is ​​binarized to obtain preliminary segmentation results; The preliminary segmentation results were analyzed using a three-dimensional connected component analysis algorithm to identify preliminary continuous dark areas. Morphological processing is performed on each of the initial continuous dark areas to obtain the continuous dark areas.

6. The method according to claim 1, characterized in that, After obtaining the real-time detection information of the conveyor belt based on the judgment result, the method further includes: The operating speed and vibration parameters of the conveyor belt are monitored in real time. The transmission frequency of the grating transmitter and the sampling rate of the grating receiver are dynamically adjusted according to the operating speed of the conveyor belt. The vibration parameters were analyzed using Fast Fourier Transform to identify the vibration frequency and amplitude. A vibration compensation model is established based on the vibration frequency and the vibration amplitude. The intensity value of each optical signal is input into the vibration compensation model to obtain the compensation intensity value; A three-dimensional light intensity distribution matrix is ​​constructed based on the compensation intensity value, and the steps of performing image segmentation processing on the three-dimensional light intensity distribution matrix and identifying continuous dark areas in the three-dimensional light intensity distribution matrix are performed.

7. The method according to claim 6, characterized in that, The step of dynamically adjusting the transmission frequency of the grating transmitter and the sampling rate of the grating receiver according to the operating speed of the conveyor belt specifically includes: Establish the mapping relationship between the operating speed and the transmission frequency and sampling rate; When a change in the operating speed of the conveyor belt is detected, the optimal transmission frequency and optimal sampling rate are recalculated using an interpolation algorithm based on the mapping relationship. An adjustment command is sent to the grating transmitter and the grating receiver to make the transmission frequency of the grating transmitter the optimal transmission frequency and the sampling rate of the grating receiver the optimal sampling rate.

8. A real-time detection system for conveyor belt items based on grating equipment, characterized in that, The system includes: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the system, the system performs the method as described in any one of claims 1-7.

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