It is wildly known that the grain direct harvest can improve the corn harvest efficiency effectively. However, in the process of grain direct harvest, incomplete threshing and cleaning loss will lead to the loss of corn grain. Among them, the grain loss caused by the cleaning process can be controlled and reduced by adjusting the opening extent of the cleaning sieve, fan speed and other parameters. In traditional operation process, the operator had to adjust the cleaning mechanism based on their experience, which directly leads to low efficiency as well as high rate of grain loss. The grain loss rate sensor proposed in this paper provides the feedback parameters to control the above actuators, which makes the intelligent cleaning of the harvester possible. By comparing the existing research results, the PVDF piezoelectric film was used as the sensitive material. A sensor test platform and a real machine test platform were built and the corresponding software system of the sensor was designed and developed. The software system includes data acquisition module, filtering algorithm, wave shaped module, counting module, data processing module and wireless transmission module. Moreover, an algorithm was proposed to calibrate the error caused by misidentification of the grains and residues. After the testing and debugging, the final identification error of the laboratory tests was decreased from 12% to 3% and the error of the real machine test was under 6%, which is acceptable.The research results of this paper provided the basis for the development of intelligent control system of grain harvesting machinery, and it is of great significance to reduce the cleaning loss rate of harvesting machinery.
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