Workshop equipment operation and maintenance management method, system and equipment based on industrial Internet of Things

Abstract

The invention discloses a workshop equipment operation and maintenance management method, system and equipment based on the industrial Internet of Things, and relates to the technical field of workshop equipment operation and maintenance, and the method comprises the following steps: obtaining an operation monitoring video of a target conveyor, so as to recognize a product retention condition on the target conveyor; if the product retention condition is recognized, the current rotating speed of a driving motor is obtained to recognize whether motor fault information exists or not; if yes, motor fault information is output, and if not, whether roller rotation abnormal information exists or not is recognized according to the monitoring video; if yes, roller rotation abnormal information is output, and if not, depth images of at least two rollers are obtained based on the visual angle below the rollers; according to the depth image, whether roller depression information exists or not is recognized; if yes, roller depression information is output, and if not, whether product clamping stagnation information exists or not is recognized; the online troubleshooting method and the online troubleshooting device have the advantages that online troubleshooting of the conveyor can be realized, and the troubleshooting efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of workshop equipment operation and maintenance technology, and in particular to a workshop equipment operation and maintenance management method, system and equipment based on industrial Internet of Things. Background Art

[0002] The level of intelligent manufacturing is of great significance to the upgrading and development of my country's industrial production, and smart factories are the core content of intelligent manufacturing. The smart factory industrial Internet of Things is an Internet of Things that combines the new generation of information technology with advanced manufacturing technology. It is oriented to the entire manufacturing process and is built on the "three-system Internet of Things" as the basic architecture. It integrates the perception control platform, sensor network platform, management platform, service platform and user platform to achieve collaborative management and services among the five platforms. It is based on the digital factory and uses the technology and monitoring technology of the Internet of Things to strengthen information collection, management and services. It solves the problem that it is difficult for traditional manufacturing industries to form systematic intelligent management in production and manufacturing, quality management, supply chain, technology research and development, energy management, safety and environmental protection, and park management.

[0003] In the automated assembly line of a smart workshop, the conveyor is the core equipment for conveying and transferring various products. Therefore, the normal operation of the conveyor is the guarantee for the timely delivery of various products. When the conveyor fails and the products pile up and cannot be conveyed normally, the operation and maintenance management personnel need to check the fault information in time. However, for large-scale smart workshops, there are many conveyors running in the production line, and the conveying distance is long, which leads to many reasons for conveyor failure. If the fault information is checked manually one by one, the troubleshooting efficiency is low and the accuracy of manual troubleshooting is also low, which is not conducive to the continuous operation of the assembly line. Summary of the invention

[0004] The main purpose of the present invention is to provide a workshop equipment operation and maintenance management method, system and equipment based on the industrial Internet of Things, aiming to solve the technical problem that the existing workshop conveyor operation and maintenance management is through manual troubleshooting and the troubleshooting efficiency is low.

[0005] To achieve the above object, the present invention provides a workshop equipment operation and maintenance management method based on industrial Internet of Things, comprising the following steps: Obtaining an operation monitoring video of a target conveyor to identify product retention on the target conveyor; wherein the target conveyor includes a frame, and the frame is provided with a plurality of rollers for conveying products and a driving motor for driving the rollers to rotate; If product retention is detected, the current speed of the drive motor is obtained to identify whether there is motor failure information; If yes, the motor fault information is output; if no, the abnormal roller rotation information is identified based on the monitoring video; If yes, the abnormal rotation information of the roller is output; if no, at least two depth images of the roller are acquired based on the viewing angle below the roller; wherein the two depth images respectively contain image information of the upper and lower half shells of the roller; According to the depth image, identify whether there is roller depression information; If yes, then output the roller depression information; if no, then identify whether there is product jam information; wherein the product jam information is information that the product is jammed in the gap between the rollers; If yes, then the product stuck information is output; if no, then the process returns to obtain the current speed of the drive motor.

[0006] Optionally, the monitoring video is a video acquired based on a preset viewing angle; wherein the preset viewing angle is a viewing angle parallel to the axial direction of the roller, and the end of the rotating shaft of the roller is provided with a marking line arranged along the radial direction of the rotating shaft; According to the monitoring video, identify whether there is any abnormal information of roller rotation, including: Decomposing the surveillance video based on a preset time interval to obtain two surveillance images; The monitoring images are compared to identify the position information of the marking line, and whether there is abnormal roller rotation information is identified based on the marking line position information.

[0007] Optionally, performing image comparison on the monitoring image to identify the position information of the identification line, and identifying whether there is abnormal roller rotation information according to the position information of the identification line, including: Performing image processing on the two monitoring images to respectively extract two groups of profile features of the end portions of the rotating shafts corresponding to the plurality of rollers; Overlap the two sets of extracted shaft end contour features to obtain a fused image; Identify the angle θ between the two marking lines on each axis in the fused image; Determine whether there is an angle θ that is smaller than a standard angle; wherein the standard angle is the rotation angle of the marking line on the corresponding rotating shaft from the first moment to the second moment after a preset interval time when the roller is running normally; If so, it is identified that there is abnormal roller rotation information, and if not, it is identified that there is no abnormal roller rotation information.

[0008] Optionally, identifying whether there is roller depression information according to the depth image includes: According to the depth image, obtain the three-dimensional point cloud of the roller; Compare the three-dimensional point cloud with the preset standard point cloud to obtain the concavity value; wherein the standard point cloud is the point cloud corresponding to the half shell of the standard roller; Determine whether the depression degree value is greater than a preset defect threshold; If so, it is identified that the roller depression information exists, and if not, it is identified that the roller depression information does not exist.

[0009] Optionally, identifying whether there is product stuck information includes: Obtain the detection pressure values ​​of the rotating shafts at both ends of all rollers; Determine whether the detected pressure value is greater than a preset standard pressure value; wherein the standard pressure value is the corresponding shaft pressure value when the roller is operating normally without blocking the product; If so, it is identified that there is product jam information, and if not, it is identified that there is no product jam information.

[0010] Optionally, the current speed of the drive motor is obtained to identify whether there is motor fault information, including: Get the current speed of the drive motor; Determine whether the current speed is less than a preset standard speed; wherein the standard speed is the speed of the drive motor when it is running normally; If so, it is identified that there is motor fault information, and if not, it is identified that there is no motor fault information.

[0011] Optionally, the method further comprises the following steps: Get the current return number of returning to get the current speed of the driving motor; If the current return times reach the preset times, the call manual alarm information will be output.

[0012] Optionally, the roller rotation abnormality information, roller depression information and product jam information all include roller number information.

[0013] To achieve the above object, the present invention also provides a workshop equipment operation and maintenance management system based on the industrial Internet of Things, including a management platform, a sensor network platform and an object platform that are sequentially connected in communication, and the management platform includes: A video acquisition module is used to acquire the operation monitoring video of the target conveyor to identify the product retention situation on the target conveyor; wherein the target conveyor includes a frame, and the frame is provided with a plurality of rollers for conveying products and a driving motor for driving the rollers to rotate; The motor fault identification module is used to obtain the current speed of the drive motor to identify whether there is motor fault information if the product is stranded; The first data processing module is used to output motor fault information if yes, and if no, identify whether there is abnormal roller rotation information according to the monitoring video; The second data processing module is used for outputting the abnormal rotation information of the roller if yes, and if no, obtaining at least two depth images of the roller based on the viewing angle below the roller; wherein the two depth images respectively contain the image information of the upper and lower half shells of the roller; A roller depression recognition module is used to identify whether there is roller depression information based on the depth image; The third data processing module is used to output roller depression information if yes, and to identify whether there is product jam information if no; wherein the product jam information is information that the product is jammed in the gap between the rollers; The fourth data processing module is used to output product jamming information if yes, and if no, return to obtain the current rotation speed of the driving motor.

[0014] To achieve the above object, the present invention further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above method.

[0015] To achieve the above object, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement the above method.

[0016] The beneficial effects that can be achieved by the present invention are as follows: The present invention first identifies the product retention situation based on the operation monitoring video of the target conveyor. If the product retention situation is identified, it means that the target conveyor may have a fault. According to the probability of the fault and the degree of impact, priority is given to whether the drive motor has a fault. Therefore, it is possible to identify whether there is motor fault information by obtaining the current speed of the drive motor. If so, the motor fault information is directly output to notify the operation and maintenance management personnel to carry out targeted maintenance. If not, the rotation abnormality caused by the roller fault is considered. Here, the monitoring video can continue to be used to identify whether there is roller rotation abnormality information. If so, the roller rotation abnormality information is output. If not, it is considered that the conveyor may be caused by the depression of the roller. The dynamic performance is poor, which eventually leads to the inability to transport some products in time and gradually stranded. Considering the problem that the upper surface of the roller is blocked by the product, at least two depth images of the roller are obtained based on the perspective below the roller to identify whether there is roller depression information. If so, the roller depression information is output. If not, it is considered that the product may be stuck in the gap between the rollers, causing some products to be unable to move forward. Therefore, it can be identified whether there is product jam information in the end. If so, the product jam information is output. If not, considering the influence of the detection error, it returns to the step of obtaining the current speed of the drive motor again, and performs a new round of detection in accordance with the above-mentioned troubleshooting sequence, thereby ensuring the detection accuracy. In summary, the present invention realizes online monitoring of the operating status of the target conveyor, and can quickly troubleshoot according to the probability of occurrence and the degree of impact of the fault, thereby improving the troubleshooting efficiency, and can output the corresponding fault information, which is convenient for the operation and maintenance management personnel to grasp the fault information in time and carry out targeted maintenance, thereby improving the continuity of the workshop assembly line operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0018] Figure 1 It is a flow chart of a workshop equipment operation and maintenance management method based on the industrial Internet of Things in an embodiment of the present invention; Figure 2 is a schematic diagram of a monitoring image obtained in an embodiment of the present invention; Figure 3 is a schematic diagram of a fused image obtained in an embodiment of the present invention; Figure 4 It is a schematic diagram of the connection structure between the rotating shafts at both ends of the roller and the frame in an embodiment of the present invention; Figure 5 Schematic diagram of the framework of the Internet of Things system involved in the embodiments of the present invention.

[0019] Reference numerals: 110-frame, 120-roller, 130-rotating shaft, 140-marking line, 150-pressure sensor.

[0020] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0023] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0024] Example 1 Reference Figure 1-Figure 4 This embodiment provides a workshop equipment operation and maintenance management method based on industrial Internet of Things, including the following steps: Obtaining an operation monitoring video of a target conveyor to identify product retention on the target conveyor; wherein the target conveyor includes a frame 110, and the frame 110 is provided with a plurality of rollers 120 for conveying products and a driving motor for driving the rollers 120 to rotate; If product retention is detected, the current speed of the drive motor is obtained to identify whether there is motor failure information; If yes, the motor fault information is output; if no, the abnormal roller rotation information is identified based on the monitoring video; If yes, the abnormal rotation information of the roller is outputted; if no, at least two depth images of the roller 120 are acquired based on the viewing angle below the roller 120; wherein the two depth images respectively contain image information of the upper and lower half shells of the roller 120; According to the depth image, identify whether there is roller depression information; If yes, the roller depression information is output, if no, whether there is product jam information is identified; wherein the product jam information is information that the product is jammed in the gap between the rollers 120; If yes, then the product stuck information is output; if no, then the process returns to obtain the current speed of the drive motor.

[0025] In this embodiment, the product retention situation is first identified based on the operation monitoring video of the target conveyor (collected by the camera). If the product retention situation is identified, it means that the target conveyor may have a fault. According to the probability of the fault and the degree of impact, priority is given to whether the drive motor has a fault. Therefore, it is possible to identify whether there is motor fault information by obtaining the current speed of the drive motor. If so, the motor fault information is directly output to notify the operation and maintenance management personnel to carry out targeted maintenance. If not, the rotation abnormality caused by the failure of the roller 120 is considered. Here, the monitoring video can continue to be used to identify whether there is abnormal rotation information of the roller 120. If so, the abnormal rotation information of the roller 120 is output. If not, it is considered that the roller 120 may be concave, resulting in poor transmission performance, which ultimately causes some products to fail to be transported in time and gradually. Retention, taking into account the problem of the upper surface of the roller 120 being blocked by the product, at least two depth images of the roller 120 are obtained here based on the viewing angle below the roller 120 (based on depth camera acquisition). The two depth images respectively contain image information of the upper and lower semi-shells of the roller 120, so as to identify the entire roller 120, and whether there is any depression information of the roller 120. If so, the depression information of the roller 120 is output. If not, it is considered that the product may be stuck in the gap between the rollers 120, causing some products to be unable to move forward. Therefore, it can be identified whether there is any product jam information. If so, the product jam information is output. If not, considering the influence of the detection error, it returns to the step of obtaining the current speed of the drive motor, and performs a new round of detection in the above-mentioned troubleshooting sequence, thereby ensuring the detection accuracy. In summary, this embodiment realizes online monitoring of the operating status of the target conveyor, and can quickly troubleshoot according to the probability of fault occurrence and the degree of impact, thereby improving the troubleshooting efficiency, and can output corresponding fault information, which is convenient for operation and maintenance management personnel to grasp the fault information in time and conduct targeted maintenance, thereby improving the continuity of the operation of the workshop assembly line.

[0026] As an optional implementation, the monitoring video is a video acquired based on a preset viewing angle; wherein the preset viewing angle is a viewing angle parallel to the axial direction of the roller 120, and an end of the rotating shaft 130 of the roller 120 is provided with a marking line 140 arranged along the radial direction of the rotating shaft 130; According to the monitoring video, identify whether there is any abnormal information of roller rotation, including: Decomposing the surveillance video based on a preset time interval to obtain two surveillance images; The monitoring images are compared to identify the position information of the marking line, and whether there is abnormal roller rotation information is identified based on the marking line position information.

[0027] In this embodiment, by decomposing the monitoring video acquired based on the axial perspective of the roller 120, two monitoring images with a preset interval time can be obtained, that is, one monitoring image is decomposed at the first moment, and another monitoring image is decomposed at the second moment after the preset interval time. By comparing the position information of the identification line in the two monitoring images, if abnormal rotation of the roller occurs (including the roller not rotating or the actual rotation speed is lower than the normal rotation speed), the abnormal rotation of the roller can be indirectly indicated according to the change in the position of the identification line, thereby realizing non-contact measurement based on machine vision recognition technology, and multiple rollers 120 can be detected at one time. There is no need to set a corresponding sensor at the rotating shaft 130 of each roller 120 to detect the rotation speed, thereby reducing the detection cost. In addition, setting the identification line 140 at the end of the rotating shaft 130 here is not only convenient for identification, but also the identification line 140 located at the end of the rotating shaft 130 will not contact the product, thereby preventing the identification line 140 from being worn during the product transportation process, thereby ensuring the effectiveness of identification.

[0028] As an optional implementation, performing image comparison on the monitoring image to identify the position information of the identification line, and identifying whether there is abnormal roller rotation information according to the position information of the identification line, including: Performing image processing on the two monitoring images to respectively extract two groups of profile features of the ends of the rotating shafts corresponding to the plurality of rollers 120; Overlap the two sets of extracted shaft end contour features to obtain a fused image; Identify the angle θ between the two identification lines 140 on each rotation axis 130 in the fused image; Determine whether there is an angle θ that is smaller than a standard angle; wherein the standard angle is a rotation angle corresponding to the rotation of the marking line 140 on the rotating shaft 130 from a first moment to a second moment after a preset interval when the roller 120 is operating normally; If so, it is identified that there is abnormal roller rotation information, and if not, it is identified that there is no abnormal roller rotation information.

[0029] In this embodiment, image processing (including grayscale processing and binarization processing) is performed on the two monitoring images to obtain a black-and-white image with clear contour lines, so as to facilitate the extraction of the contour features of the shaft ends corresponding to the multiple rollers 120 in the two monitoring images, and then the two groups of shaft end contour features are overlapped to obtain a fused image (overlapping based on the circular contour formed by the shaft 130). The circular contour of the overlapped shaft 130 should have two identification lines 140 at different positions. Therefore, the angle θ between the two identification lines 140 on each shaft 130 in the fused image can be identified respectively. If it rotates normally, the positions of the identification lines 140 at the first moment and the second moment are different and form a standard angle. If the angle θ is less than the standard angle, it means that the actual rotation speed of the corresponding roller 120 is lower than the normal rotation speed, which means that the transmission mechanism may be loose. If only one identification line 140 is identified, it means that the identification line 140 has not rotated, that is, the roller 120 has not moved at all, which means that there is a hidden danger that the roller 120 is detached from the transmission mechanism. In summary, based on the measurement of the relative angle between the marking lines 140 at different times, the rotation of the roller 120 can be indirectly characterized, and the detection is accurate and effective.

[0030] As an optional implementation, identifying whether there is roller depression information according to the depth image includes: Acquire a three-dimensional point cloud of the roller 120 according to the depth image; Compare the three-dimensional point cloud with a preset standard point cloud to obtain a concavity value; wherein the standard point cloud is a point cloud corresponding to a half shell of the standard roller 120; Determine whether the depression degree value is greater than a preset defect threshold; If so, it is identified that the roller depression information exists, and if not, it is identified that the roller depression information does not exist.

[0031] In this embodiment, the depth image is a grayscale image, which contains the distance information of each pixel from the camera. Therefore, the corresponding coordinate position can be formed according to the distance information of each pixel, and converted into a three-dimensional point cloud of the roller 120 (the three-dimensional point cloud should correspond to the semi-shell of the roller 120) in combination with the existing algorithm. Then, by comparing with the standard point cloud, the spatial volume of the depressed part can be identified and output as a depression degree value. Considering the influence of the depression degree value on the transmission performance, a defect threshold is set here. When the depression degree value is greater than the defect threshold, it indicates that the depression degree of the roller 120 is too large and affects the transmission performance, thereby realizing the detection and identification of the roller depression information.

[0032] As an optional implementation, identifying whether there is product stuck information includes: Obtain the detection pressure values ​​of the rotating shafts 130 at both ends of all rollers 120; Determine whether the detected pressure value is greater than a preset standard pressure value; wherein the standard pressure value is the corresponding pressure value of the rotating shaft 130 when the roller 120 is operating normally without blocking the product; If so, it is identified that there is product jam information, and if not, it is identified that there is no product jam information.

[0033] In this embodiment, when a product is stuck in the gap between the two rollers 120, it is difficult to identify it through machine vision. Therefore, a pressure sensor 150 can be set between the bearing on the rotating shaft 130 and the frame 110. When the product is stuck, the gradual accumulation of products behind the conveyor line will cause a certain degree of squeezing on the stuck product. Therefore, the detection pressure value of the rotating shaft 130 at both ends of all rollers 120 can be obtained. If there is a detection pressure value greater than the standard pressure value, it means that the product is stuck. At this time, the product jam information is output to promptly notify the operation and maintenance management personnel to check. Therefore, this embodiment can indirectly characterize whether there is a product jam through pressure detection, and the detection is accurate and efficient.

[0034] As an optional implementation, obtaining the current rotation speed of the drive motor to identify whether there is motor fault information includes: Get the current speed of the drive motor; Determine whether the current speed is less than a preset standard speed; wherein the standard speed is the speed of the drive motor when it is running normally; If so, it is identified that there is motor fault information, and if not, it is identified that there is no motor fault information.

[0035] In this embodiment, since the frequency of loading products onto the conveyor is basically fixed, the conveyor speed should match the product loading frequency. Therefore, a standard speed is set here. If the motor fails and its current speed is lower than the standard speed, it indicates that there may be a motor failure and the motor failure information is output.

[0036] As an optional implementation, the method further includes the following steps: Get the current return number of returning to get the current speed of the driving motor; If the current return times reach the preset times, the call manual alarm information will be output.

[0037] In this embodiment, when the corresponding fault information is not detected after multiple cycles of detection, taking into account other possible fault conditions that are difficult to detect, in order to ensure the timeliness of fault troubleshooting, a preset number of times is set here. When the current number of returns (i.e., the number of cycle detections) reaches the preset number of times, a call for manual alarm information is output to notify the operation and maintenance management personnel to conduct manual fault troubleshooting.

[0038] As an optional implementation, the roller rotation abnormality information, roller depression information and product jam information all include roller number information. The operation and maintenance manager can quickly find the location of the roller 120 with the corresponding fault according to the roller number information, so as to facilitate rapid maintenance and improve efficiency.

[0039] Example 2 Based on the same inventive idea as the above embodiment, Figure 1-Figure 5 This embodiment also provides a workshop equipment operation and maintenance management system based on the industrial Internet of Things, including a management platform, a sensor network platform and an object platform that are sequentially connected in communication, and the management platform includes: A video acquisition module is used to acquire the operation monitoring video of the target conveyor to identify the product retention situation on the target conveyor; wherein the target conveyor includes a frame 110, and the frame 110 is provided with a plurality of rollers 120 for conveying products and a driving motor for driving the rollers 120 to rotate; The motor fault identification module is used to obtain the current speed of the drive motor to identify whether there is motor fault information if the product is stranded; The first data processing module is used to output motor fault information if yes, and if no, identify whether there is abnormal roller rotation information according to the monitoring video; The second data processing module is used for outputting the abnormal rotation information of the roller if yes, and if no, obtaining at least two depth images of the roller 120 based on the viewing angle below the roller 120; wherein the two depth images respectively contain the image information of the upper and lower half shells of the roller 120; A roller depression recognition module is used to identify whether there is roller depression information based on the depth image; The third data processing module is used to output roller depression information if yes, and to identify whether there is product jam information if no; wherein the product jam information is information that the product is jammed in the gap between the rollers 120; The fourth data processing module is used to output product jamming information if yes, and if no, return to obtain the current rotation speed of the driving motor. It should be noted that the workshop equipment operation and maintenance management system based on the industrial Internet of Things in this embodiment also includes a user platform and a service platform that are connected to each other in communication, and the service platform is connected to the management platform in communication, thereby forming a standard five-platform structure of the Internet of Things. Among them, the physical entity of the user platform includes various user terminals, such as mobile phones, computers, special terminals, etc., and the user-side services are realized by combining with the user information system software. The service platform is a functional platform for realizing service communication. The management platform is a functional platform for realizing the operation and management of the Internet of Things system. In some embodiments, the management platform may include multiple management sub-platforms, and the management sub-platforms are respectively connected to the above-mentioned sensor network platform, and each management sub-platform corresponds to a video acquisition module, a motor fault identification module, a first data processing module, a second data processing module, a roller depression identification module, a third data processing module and a fourth data processing module. The sensor network platform is a functional platform for realizing sensor communication. The object platform is a functional platform for realizing perception control, and the object platform includes target conveyors, cameras, depth cameras and other equipment.

[0040] The relevant explanations and examples of each module in the device of this embodiment can refer to the method of the aforementioned embodiment, and will not be repeated here.

[0041] Example 3 Based on the same inventive concept as the above-mentioned embodiment, this embodiment provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned method.

[0042] Example 4 Based on the same inventive concept as the aforementioned embodiment, this embodiment provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement the aforementioned method.

[0043] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. The workshop equipment operation and maintenance management method based on industrial Internet of Things is characterized by: The following steps are involved: Obtaining an operation monitoring video of a target conveyor to identify product retention on the target conveyor; wherein the target conveyor includes a frame, and the frame is provided with a plurality of rollers for conveying products and a driving motor for driving the rollers to rotate; If product retention is detected, the current speed of the drive motor is obtained to identify whether there is motor failure information; If yes, the motor fault information is output; if no, the abnormal roller rotation information is identified based on the monitoring video; If yes, the abnormal rotation information of the roller is output; if no, at least two depth images of the roller are acquired based on the viewing angle below the roller; wherein the two depth images respectively contain image information of the upper and lower half shells of the roller; According to the depth image, identify whether there is roller depression information; If yes, then output the roller depression information, if no, then identify whether there is product jam information; wherein the product jam information is information that the product is jammed in the gap between the rollers; If yes, then the product stuck information is output; if no, then the process returns to obtain the current speed of the drive motor.

2. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 1 is characterized in that: The monitoring video is a video acquired based on a preset viewing angle; wherein the preset viewing angle is a viewing angle parallel to the axial direction of the roller, and the end of the rotating shaft of the roller is provided with a marking line arranged along the radial direction of the rotating shaft; According to the monitoring video, identify whether there is any abnormal information of roller rotation, including: Decomposing the surveillance video based on a preset time interval to obtain two surveillance images; The monitoring images are compared to identify the position information of the marking line, and whether there is abnormal roller rotation information is identified based on the marking line position information.

3. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 2 is characterized in that: The monitoring images are compared to identify the position information of the identification line, and whether there is abnormal roller rotation information based on the identification line position information, including: Performing image processing on the two monitoring images to respectively extract two groups of profile features of the end portions of the rotating shafts corresponding to the plurality of rollers; Overlap the two sets of extracted shaft end contour features to obtain a fused image; Identify the angle θ between the two marking lines on each axis in the fused image; Determine whether there is an angle θ that is smaller than a standard angle; wherein the standard angle is the rotation angle of the marking line on the corresponding rotating shaft from the first moment to the second moment after a preset interval time when the roller is running normally; If so, it is identified that there is abnormal roller rotation information, and if not, it is identified that there is no abnormal roller rotation information.

4. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 1 is characterized in that: According to the depth image, identify whether there is roller depression information, including: According to the depth image, obtain the three-dimensional point cloud of the roller; Compare the three-dimensional point cloud with the preset standard point cloud to obtain the concavity value; wherein the standard point cloud is the point cloud corresponding to the half shell of the standard roller; Determine whether the depression degree value is greater than a preset defect threshold; If so, it is identified that the roller depression information exists, and if not, it is identified that the roller depression information does not exist.

5. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 1 is characterized in that: Identify if there is any product stuck information, including: Obtain the detection pressure values ​​of the rotating shafts at both ends of all rollers; Determine whether the detected pressure value is greater than a preset standard pressure value; wherein the standard pressure value is the corresponding shaft pressure value when the roller is operating normally without blocking the product; If so, it is identified that there is product jam information, and if not, it is identified that there is no product jam information.

6. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 1 is characterized in that: Get the current speed of the drive motor to identify whether there is motor fault information, including: Get the current speed of the drive motor; Determine whether the current speed is less than a preset standard speed; wherein the standard speed is the speed of the drive motor when it is running normally; If so, it is identified that there is motor fault information, and if not, it is identified that there is no motor fault information.

7. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 1 is characterized in that: The following steps are also included: Get the current return number of returning to get the current speed of the driving motor; If the current return times reach the preset times, the call manual alarm information will be output.

8. The workshop equipment operation and maintenance management method based on industrial Internet of Things according to claim 1 is characterized in that: The roller number information is included in the roller rotation abnormality information, roller depression information and product jam information.

9. The workshop equipment operation and maintenance management system based on industrial Internet of Things is characterized by: It includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication, and the management platform includes: A video acquisition module is used to acquire the operation monitoring video of the target conveyor to identify the product retention situation on the target conveyor; wherein the target conveyor includes a frame, and the frame is provided with a plurality of rollers for conveying products and a driving motor for driving the rollers to rotate; The motor fault identification module is used to obtain the current speed of the drive motor to identify whether there is motor fault information if the product is stranded; The first data processing module is used to output motor fault information if yes, and if no, identify whether there is abnormal roller rotation information according to the monitoring video; The second data processing module is used for outputting the abnormal rotation information of the roller if yes, and if no, obtaining at least two depth images of the roller based on the viewing angle below the roller; wherein the two depth images respectively contain the image information of the upper and lower half shells of the roller; A roller depression recognition module is used to identify whether there is roller depression information based on the depth image; The third data processing module is used to output roller depression information if yes, and to identify whether there is product jam information if no; wherein the product jam information is information that the product is jammed in the gap between the rollers; The fourth data processing module is used to output product jamming information if yes, and if no, return to obtain the current rotation speed of the driving motor.

10. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the workshop equipment operation and maintenance management method based on the industrial Internet of Things as described in any one of claims 1 to 8.

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