Embedded harvester header integrated control system

Abstract

The invention belongs to the technical field of harvesters, and discloses an embedded harvester header integrated control system and control method. The embedded harvester header integrated control system comprises: a power monitoring module, a feed amount monitoring module, a grain component monitoring module, a main control module, a positioning module, an air blowing module, a data storage module, and a display module. The high-efficiency fuel consumption of the engine is facilitated, and the energy-saving and emission-reducing effect is improved; under the echo interference in rainy days,foggy days and the like, the harvester header integrated control system is accurately positioned; and the temperature compensation of an air blower is realized, so that the air blower is not affectedby the external temperature. The embedded harvester header integrated control system is used for the unsupervised multi-target radar radiation source signal feature selection problem; and the fast convergence of the multi-objective particle swarm optimization algorithm is preserved, and the solution set has good diversity.

Description

technical field [0001] The invention belongs to the technical field of harvesters, and in particular relates to an integrated control system based on an embedded harvester header. Background technique [0002] Harvester It is an integrated machine for harvesting crops. Harvesting, conveying, threshing, and cleaning are completed at one time, and the grains are concentrated into the grain tank, and then the grain is transported to the transport vehicle through the grain unloading auger. Manual harvesting can also be used to spread the stalks of rice, wheat and other crops in the field, and then use grain harvesting machinery to pick up and threshing. Crop harvesting machinery for harvesting grains and stalks of cereal crops such as rice and wheat. Including harvesters, windrowers, balers, grain combines and grain threshers, etc. Grain harvesting machinery is developed on the basis of various harvesting and threshing tools; however, the existing harvesters cannot accurately...

AI Technical Summary

Problems solved by technology

In addition, the multi-objective feature selection algorithm finally obtains a series of compromise solutions, from which it is necessary to select a solution with excellent performance, but currently there are few unsupervised methods available

The main difficulty lies in: the designed feature subset evaluation function and search strategy fail to consider the redundancy and correlation of feature subsets; the evaluation criteria also do not consider the influence of the dimension selection of feature subsets on classification effectiveness; The unsupervised way to extract the feature dimension and the importance ranking of feature subsets in the Pareto solution set of the multi-objective optimization algorithm has not yet been resolved

The engine power data monitoring error rate is high, and the service life of the engine cannot be effectively guaranteed

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