Grain cleaning loss detection method for combined harvester and device thereof

Abstract

The invention discloses a grain cleaning loss detection method for a combined harvester and a device thereof. An array type piezoeletric quartz sensor is installed at the outlet of a cleaning sieve, the signal output from the array type piezoeletric quartz sensor is transmitted into a charge amplifier and a gain adjustable circuit to be processed and converted into a voltage signal with a certain amplitude value; a high pass filtering circuit and a sensitivity regulating circuit are used to respectively separate out the features of the vibration noise and the grain signals from the frequency domain and the time domain; the separated vibration noise and grain signals are rectified into standard pulse signals which can be executed by a micro monolithic processor through a pulse shaping circuit; the grain cleaning loss is detected by the method of full-width distribution of multi-lamella piezoelectric detection array, information is acquired from multiple areas and multiple angles, thereby enhancing the grain impact signals, improving the grain-grass identification precision and improving the testing reliability of the system; the detecting device has the advantages of good integral dynamic performance, strong anti-jamming capability, and high measurement precision, thereby realizing online measurement of the cleaning loss in the field.

Description

technical field [0001] The invention relates to a combine harvester among agricultural machinery, in particular to a performance test of the combine harvester, which is used for intelligent detection of grain cleaning loss. Background technique [0002] In the performance test of the combine harvester, the grain cleaning loss rate is an important index, which directly affects the production efficiency and operation quality of the harvester. In grain harvesting operations, when the moisture content of the stalks is low, a large number of broken stalks produced during the threshing process will increase the cleaning load, reduce the cleaning quality, and the cleaning loss rate is as high as about 4%, which greatly reduces the operating cost. quality. For a long time, the detection of this index has been using manual counting and manual calculation of the loss rate. The disadvantages are: low work efficiency, large errors, and inability to guide the harvesting operation of the...

AI Technical Summary

Problems solved by technology

In grain harvesting operations, when the moisture content of the stalks is low, a large number of broken stalks produced during the threshing process will increase the cleaning load, reduce the cleaning quality, and the cleaning loss rate is as high as about 4%, which greatly reduces the operating cost. quality

For a long time, the detection of this indicator has been using manual counting and manual calculation of the loss rate. The disadvantages are: low work efficiency, large errors, and inability to guide the harvesting operation of the unit in real time

[0003] Since there are very few grains in the sieve throws compared to the stalks and grass, the grain loss signal detected by the sensor is very weak, almost drowned in the strong vibration noise of the combine harvester and the sieve, combined with the stalk and grass. Signal interference makes it extremely difficult to identify and extract grain signals

In addition, when the grain-grass mixture is discharged from the cleaning sieve, it continuously hits the sensitive element of the sensor installed at the back of the sieve. The traditional structure is to fix a single piezoelectric substrate on a flat plate. The grain obtained by this structure The information is incomplete and inaccurate, and is also affected by its own performance and noise. The collected data has a large uncertainty

[0004] At present, when the cleaning loss automatic monitoring system based on single-chip microcomputer is actually used, the overall function, quantitative index and reliability of the whole machine are not high.

The array piezoelectric crystal grain cleaning loss sensor is only a theoretical study, there is no specific implementation plan, and it cannot solve the sensitivity consistency problem of the array structure

Images