| With China’s coal production capacity continues to increase, coal handling speed gradually speeding. Large capacity belt conveyor has become the main tool of mine transport, the belt conveyors are used in the mine more and more widely. Longitudinal tear of the conveyor belt is one of the major failures of the belt conveyor. Because of More steel cord conveyor belts are used in belt conveyors in few kilometers or even hundreds of kilometers of conveyor chains of coal mine, after the use of this type of conveyor belt, the tensile performance is greatly improved, but resisting tear performance has not improved. Because of the monomer length of Steel cord conveyor belt is long, if longitudinal tear can not be found timely, it is possible to cause the entire conveyor belt scrapped, resulting in a serious accident and huge economic losses. Therefore, it is necessary to detect longitudinal tear on the conveyor belt. This paper analyzes the resulting conveyor belt longitudinal tear reason and a number of existing techniques and methods, these techniques and methods contain two type, they are contact and non-contact,in addition, the research in domestic and foreign are not synchronized, the research level of domestic behind foreign. Some existing methods have complicated structure, and some can cause false positives, and some can damage conveyor belt covers. Now, some universities and research institutes began to study the machine vision for conveyor belt longitudinal tear detection, the advantages of machine vision are non-contact and getting the tear image intuitively, it can visually achieve maximum near real-time detection and instead mechanical equipment and the human eye to detect, it can greatly reduce the economic losses of the coal mine and effectively protect the safety of staff.With the development of virtual instrument technology in recent years, it brings a revolution to the field of instrumentation, its modular hardware and portable chassis provide hardware support to the application of conveyor belt longitudinal tear detection. The past20years, the virtual instrument launched its corresponding machine vision technology, namely NI machine vision technology. This paper applies NI machine vision technology to conveyor belt longitudinal tear analog detection in laboratory conditions, the research is mainly focused on the simulation machine vision detection platform composed by the NI1764Smart Camera and NI PS-15power supply and the light source of the backlight board and host computer, where the host computer with NI PMA-1115Portable PXI LCD Monitor and Keyboard Accessory and NI PXIe-10828-Slot PXI Express Chassis for PXI and PXI Express Modules and NI PXIe-8133PXI platform embedded controller. The advantages of the host computer contain stable performance and strong anti-interference ability, in theory, it suitable for complex and harsh environment of coal mine. This article also focuses on machine vision detection and feature extraction method of virtual instrument. This paper studies how to use NI VBAI write conveyor belt longitudinal tear simulation detecting procedures and use NI VA prepare conveyor belt longitudinal tear image processing and analysis program. In additional, this paper researches the method of tear image feature extraction and propose the theoretical method of tear fracture feature extraction based on the generalized Hough transform. By experiment and simulation detecting, the platform can be used to capture and process image, the speed of image processing is faster, processing results would be better, it able to achieve a signal of simulation alarm and parking. Therefore, it is theoretical and feasible that use the machine vision technology of virtual instrument for coal mine conveyor belt longitudinal tear detection. |
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