According to the complexity and the lack of intelligent analysis method of combine harvester blockage fault , this paper puts forward a method , based on the combination of BP neural network (BPNN)and DS evidence theory , for combine harvester blockage fault diagnosis. Choosing cutting table auger, conveyer trough, threshing cylinder and grain conveying auger as the study, this paper divides the condition of combine harvester into four categories, namely, normal, slightly blocking, blockage, severe blockage, which being as an identification framework for DS evidence theory. BP neural network is used for analysing speed information of monitoring points and distributing basic probability for each proposition in the identification framework. Dempster combination rule converged information at different time to obtain diagnostic results.Test results show that this method can timely and accurately judge the work state of combine harvester, the blocking fault warning time will be increased to 2 seconds and the success probability of blocking fault warning reach more than 90%.
KEYWORDS: Video, Cameras, Video surveillance, Local area networks, Video compression, Embedded systems, Software development, Signal processing, Transplantation, Operating systems
Combine harvester usually works in sparsely populated areas with harsh environment. In order to achieve the remote real-time video monitoring of the working state of combine harvester. A remote video monitoring system based on ARM11 and embedded Linux is developed. The system uses USB camera for capturing working state video data of the main parts of combine harvester, including the granary, threshing drum, cab and cut table. Using JPEG image compression standard to compress video data then transferring monitoring screen to remote monitoring center over the network for long-range monitoring and management. At the beginning of this paper it describes the necessity of the design of the system. Then it introduces realization methods of hardware and software briefly. And then it describes detailedly the configuration and compilation of embedded Linux operating system and the compiling and transplanting of video server program are elaborated. At the end of the paper, we carried out equipment installation and commissioning on combine harvester and then tested the system and showed the test results. In the experiment testing, the remote video monitoring system for combine harvester can achieve 30fps with the resolution of 800x600, and the response delay in the public network is about 40ms.
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