An image recognition-based material transmission online monitoring system

Abstract

This invention relates to the field of material handling monitoring systems, specifically disclosing an online material handling monitoring system based on image recognition. The system includes: a material image acquisition module for acquiring initial placement images and transport process images of the material, both of which include top and side views; a material image analysis module for identifying the boundaries of the initial placement and transport process images to obtain initial distance, transport distance, initial height, and transport height; a movement probability acquisition module for obtaining the material movement probability based on the initial distance, transport distance, initial height, and transport height; and an alarm generation module for determining whether to issue an alarm based on the material movement probability. This invention achieves precise monitoring of material movement by real-time monitoring of changes in the material boundary distance and height, thus improving the accuracy of the detection results.

Description

Technical Field

[0001] This invention relates to the field of material transfer monitoring system technology, specifically an online material transfer monitoring system based on image recognition. Background Technology

[0002] Currently, coal and mineral materials are transported via conveyor belts. However, conveyor belts require a long transport path to reach the loading position. During this path, materials on the conveyor belt are prone to falling, causing material loss and posing a safety hazard to workers. Existing online monitoring systems for material transport only detect the distance between the bottom edge of the material and the side edge of the conveyor belt during transport. This simplistic approach results in low accuracy. Summary of the Invention

[0003] The purpose of this invention is to provide an online monitoring system for material transfer based on image recognition, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] An online monitoring system for material handling based on image recognition, the system comprising:

[0006] The material image acquisition module is used to acquire initial placement images and transmission process images of the material, both of which include top views and side views;

[0007] The material image analysis module is used to identify the boundaries between the initial placement image and the transmission process image, and to obtain the initial distance, the distance during transportation, the initial height, and the height during transportation.

[0008] The movement probability acquisition module is used to obtain the material movement probability based on the initial distance, the distance during transportation, the initial height, and the height during transportation.

[0009] The alarm reminder generation module is used to determine whether to issue an alarm reminder message based on the material movement probability.

[0010] As a further technical solution of the present invention, the material image analysis module includes:

[0011] An image boundary recognition unit is used to identify the boundaries between the initial placement image and the transmission process image;

[0012] The initial distance acquisition unit is used to acquire the initial distance between the initial bottom boundary of the material and the side boundary of the conveyor belt through the top view in the initial placement image;

[0013] An initial height acquisition unit is used to acquire the initial height of the material piled on the conveyor belt relative to the conveyor belt through a side view of the initial placement image;

[0014] The mid-transport distance acquisition unit is used to acquire the mid-transport distance between the bottom boundary and the side boundary of the conveyor belt during the material transportation process through a top view in the image of the transportation process;

[0015] The height acquisition unit during transportation is used to acquire the height of the material piled on the conveyor belt relative to the conveyor belt through a side view of the transportation process image.

[0016] As a further technical solution of the present invention, the movement probability acquisition module includes:

[0017] The variable distance calculation unit is used to compare the initial distance and the distance during transportation in real time at a preset time step to obtain the variable distance;

[0018] The variable height calculation unit is used to compare the initial height and the height during transportation to obtain the variable height.

[0019] The movement probability calculation unit is used to obtain the material movement probability based on the changed distance and changed height.

[0020] As a further technical solution of the present invention, the movement probability calculation unit includes:

[0021] The variable distance comparison subunit is used to compare the variable distance with the distance change movement probability table to obtain the lateral movement probability. In the distance change movement probability table, each variable distance segment and the lateral movement probability are mapped to a pair. The distance change movement probability table contains multiple consecutive variable distance segments.

[0022] The height change comparison subunit is used to compare the height change with the height change movement probability table to obtain the longitudinal movement probability. In the height change movement probability table, each height change segment and the longitudinal movement probability are mapped to a pair. The height change movement probability table contains multiple consecutive height change segments.

[0023] The movement probability acquisition subunit is used to obtain the material movement probability based on the lateral movement probability and the longitudinal movement probability, and to calculate the sum of the lateral movement probability and the longitudinal movement probability to obtain the material movement probability.

[0024] As a further technical solution of the present invention, the alarm reminder generation module includes:

[0025] A probability comparison unit is used to compare the material movement probability with a preset probability threshold.

[0026] An alarm reminder generation unit is used to generate alarm reminder information when the probability of material movement exceeds a preset probability threshold.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides an online monitoring system for material transfer based on image recognition. The present invention acquires images of the initial placement of materials and images of the transfer process to obtain the changing distance and changing height. In the present invention, the changing distance and changing height are monitored in real time to obtain the probability of material movement. When the probability of material movement exceeds a preset threshold, an alarm reminder is generated to realize automatic alarm reminder and prevent material from falling. In the present invention, by monitoring the changing distance and changing height of the material boundary in real time, the precise monitoring of material movement is achieved, improving the accuracy of the detection results. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention.

[0029] Figure 1 This is a block diagram of an online monitoring system for material handling based on image recognition.

[0030] Figure 2 This is a block diagram of the material image analysis module in an online monitoring system for material transport based on image recognition.

[0031] Figure 3 This is a block diagram of the movement probability acquisition module in an image recognition-based online monitoring system for material handling.

[0032] Figure 4 This is a block diagram of the alarm generation module in an image recognition-based online monitoring system for material handling. Implementation

[0033] To make the technical problems, solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0034] like Figure 1 As shown in the figure, an embodiment of the present invention provides an online monitoring system for material transfer based on image recognition, the system comprising:

[0035] The material image acquisition module 100 is used to acquire initial placement images and transmission process images of the material, both of which include top views and side views;

[0036] The material image analysis module 200 is used to identify the boundaries between the initial placement image and the transmission process image, and to obtain the initial distance, the distance during transportation, the initial height, and the height during transportation.

[0037] The movement probability acquisition module 300 is used to obtain the material movement probability based on the initial distance, the distance during transportation, the initial height, and the height during transportation.

[0038] The alarm reminder generation module 400 is used to determine whether to issue an alarm reminder message based on the material movement probability.

[0039] In this embodiment of the invention, the material image acquisition module can acquire initial placement images and transmission process images of the material. The material image analysis module identifies the boundaries of the initial placement images and transmission process images to obtain the initial distance, transmission distance, initial height, and transmission height. Then, the movement probability acquisition module obtains the changing distance and changing height based on the initial distance, transmission distance, initial height, and transmission height. The material movement probability is calculated based on the changing distance and changing height. Finally, it is determined whether to issue an alarm reminder based on the material movement probability. In this invention, accurate monitoring of material movement is achieved by real-time monitoring of the changing distance and changing height of the material boundary.

[0040] Please see Figure 2 In a preferred embodiment of the present invention, the material image analysis module 200 includes:

[0041] Image boundary recognition unit 201 is used to recognize the boundary between the initial placement image and the transmission process image;

[0042] The initial distance acquisition unit 202 is used to acquire the initial distance between the initial bottom boundary of the material and the side boundary of the conveyor belt through the top view in the initial placement image;

[0043] The initial height acquisition unit 203 is used to acquire the initial height of the material piled on the conveyor belt relative to the conveyor belt through the side view of the initial placement image;

[0044] The mid-transport distance acquisition unit 204 is used to acquire the mid-transport distance between the bottom boundary and the side boundary of the conveyor belt during the material transportation process through a top view in the image of the transportation process;

[0045] The height acquisition unit 205 during transportation is used to acquire the height of the material piled on the conveyor belt relative to the conveyor belt through a side view of the transmission process image.

[0046] Please see Figure 3 In a preferred embodiment of the present invention, the movement probability acquisition module 300 includes:

[0047] The variable distance calculation unit 301 is used to compare the initial distance and the distance during transportation in real time at a preset time step to obtain the variable distance;

[0048] The variable height calculation unit 302 is used to compare the initial height and the height during transportation to obtain the variable height;

[0049] The movement probability calculation unit 303 is used to obtain the material movement probability based on the changed distance and changed height.

[0050] In a preferred embodiment of the present invention, the movement probability calculation unit includes:

[0051] The variable distance comparison subunit is used to compare the variable distance with the distance change movement probability table to obtain the lateral movement probability. In the distance change movement probability table, each variable distance segment and the lateral movement probability are mapped to a pair. The distance change movement probability table contains multiple consecutive variable distance segments.

[0052] The height change comparison subunit is used to compare the height change with the height change movement probability table to obtain the longitudinal movement probability. In the height change movement probability table, each height change segment and the longitudinal movement probability are mapped to a pair. The height change movement probability table contains multiple consecutive height change segments.

[0053] The movement probability acquisition subunit is used to obtain the material movement probability based on the lateral movement probability and the longitudinal movement probability, and to calculate the sum of the lateral movement probability and the longitudinal movement probability to obtain the material movement probability.

[0054] Please see Figure 4 In a preferred embodiment of the present invention, the alarm reminder generation module 400 includes:

[0055] The probability comparison unit 401 is used to compare the material movement probability with a preset probability threshold.

[0056] The alarm reminder generation unit 402 is used to generate alarm reminder information when the probability of material movement exceeds a preset probability threshold.

[0057] All the functions of the above-mentioned image recognition-based online material transfer monitoring system are performed by computer equipment, which includes one or more processors and one or more memories. The one or more memories store at least one piece of program code, which is loaded and executed by the one or more processors to realize the functions of the image recognition-based online material transfer monitoring system.

[0058] The processor fetches instructions from memory one by one, analyzes the instructions, and then performs the corresponding operations according to the instructions, generating a series of control commands to enable the various parts of the computer to act automatically, continuously, and in a coordinated manner, forming an organic whole. This enables the input of programs and data, as well as the calculation and output of results. The arithmetic or logical operations generated in this process are all performed by the arithmetic unit. The memory includes a read-only memory (ROM), which is used to store computer programs. The memory is equipped with external protection devices.

[0059] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0060] Those skilled in the art will understand that the above description of the service equipment is merely an example and does not constitute a limitation on the terminal equipment. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0061] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the terminal device, connecting various parts of the user terminal via various interfaces and lines.

[0062] The aforementioned memory can be used to store computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned terminal device by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as information collection template display function, product information publishing function, etc.); the data storage area may store data created based on the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to publish, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0063] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the modules / units in the systems of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the functions of the various system embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0064] It should be noted that, in this document, the term "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0065] The above are merely preferred embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An online monitoring system for material transfer based on image recognition, characterized in that, The system includes: The material image acquisition module is used to acquire initial placement images and transmission process images of the material, both of which include top views and side views; The material image analysis module is used to identify the boundaries between the initial placement image and the transmission process image, and to obtain the initial distance, the distance during transportation, the initial height, and the height during transportation. The movement probability acquisition module is used to obtain the material movement probability based on the initial distance, the distance during transportation, the initial height, and the height during transportation. An alarm reminder generation module is used to determine whether to issue an alarm reminder message based on the material movement probability; The material image analysis module includes: An image boundary recognition unit is used to identify the boundaries between the initial placement image and the transmission process image; The initial distance acquisition unit is used to acquire the initial distance between the initial bottom boundary of the material and the side boundary of the conveyor belt through the top view in the initial placement image; An initial height acquisition unit is used to acquire the initial height of the material piled on the conveyor belt relative to the conveyor belt through a side view of the initial placement image; The mid-transport distance acquisition unit is used to acquire the mid-transport distance between the bottom boundary and the side boundary of the conveyor belt during the material transportation process through a top view in the image of the transportation process; The height acquisition unit during transportation is used to acquire the height of the material piled on the conveyor belt relative to the conveyor belt through a side view of the transportation process image; The movement probability acquisition module includes: The variable distance calculation unit is used to compare the initial distance and the distance during transportation in real time at a preset time step to obtain the variable distance; The variable height calculation unit is used to compare the initial height and the height during transportation to obtain the variable height. A movement probability calculation unit is used to obtain the material movement probability based on the changed distance and changed height. The movement probability calculation unit includes: The variable distance comparison subunit is used to compare the variable distance with the distance change movement probability table to obtain the lateral movement probability. In the distance change movement probability table, each variable distance segment and the lateral movement probability are mapped to a pair. The distance change movement probability table contains multiple consecutive variable distance segments. The height change comparison subunit is used to compare the height change with the height change movement probability table to obtain the longitudinal movement probability. In the height change movement probability table, each height change segment and the longitudinal movement probability are mapped to a pair. The height change movement probability table contains multiple consecutive height change segments. The movement probability acquisition subunit is used to obtain the material movement probability based on the lateral movement probability and the longitudinal movement probability, and to calculate the sum of the lateral movement probability and the longitudinal movement probability to obtain the material movement probability.

2. The online monitoring system for material transfer based on image recognition according to claim 1, characterized in that, The alarm notification generation module includes: A probability comparison unit is used to compare the material movement probability with a preset probability threshold. An alarm reminder generation unit is used to generate alarm reminder information when the probability of material movement exceeds a preset probability threshold.

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