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A loader work condition identification model construction and identification method thereof

A technology of working condition recognition and construction method, applied in character and pattern recognition, construction, computer parts and other directions, can solve the problem of low recognition accuracy, improve the accuracy and efficiency, improve the accuracy, and the preprocessing method is accurate. Effect

Active Publication Date: 2019-02-19
CHANGAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a loader working condition recognition model construction and recognition method to solve the problem of low recognition accuracy of the loader working condition recognition method in the prior art

Method used

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  • A loader work condition identification model construction and identification method thereof
  • A loader work condition identification model construction and identification method thereof
  • A loader work condition identification model construction and identification method thereof

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Embodiment 1

[0031] This embodiment discloses a method for constructing a loader working condition identification model. The method includes the following steps:

[0032] Step 1, collect multiple groups of identification signal data of the loader under different working conditions as the identification signal data set; each group of identification signal data in the identification signal data set corresponds to a working condition label, and obtain the identification working condition label set;

[0033] The working condition of the loader refers to the working condition of the loader under the conditions directly related to its action. Generally, the working condition of the loader includes shoveling, full-load transportation and unloading.

[0034] In this embodiment, the working conditions of the loader are carefully divided to ensure the accuracy of the judgment. The working conditions of the loader include forwarding with no load, digging, retreating with a full load, forwarding with a...

Embodiment 2

[0088] The invention also discloses a loader working condition identification method, the method comprising:

[0089] The working condition recognition model described in Embodiment 1 is used to recognize the signal data to be recognized of the loader that has been processed in Step 1 to Step 3 in Embodiment 1.

[0090]In this embodiment, the signal data to be identified is [loader front axle torque, loader front axle speed, loader rear axle torque, working pump pressure, steering pump pressure, engine speed]=[1450,1280,2870, 8.8, 16.9, 2430], after processing in steps 1-3 of Embodiment 1, the obtained recognition feature set is [front axle torque, rear axle torque, main pump power]=[0.451,0.942,0.287], using After the working condition identification model is identified, the identification result is 2-shoveling.

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Abstract

The invention discloses a loader working condition identification model construction and identification method. Firstly, a corresponding sensor is arranged on the loader to collect multi-source signals such as torque, pressure, gear and brake, and the like, and the data is standardized, the zero floating signal is stripped, the missing value is interpolated and compensated, and the collected signal is processed by noise reduction filter. Secondly, principal component analysis is used to select the feature attributes from the loader's multi-attribute data, and statistical analysis is used to extract the feature of the principal component. Then, the loader working condition samples are established, and the association mapping between the load signal and the pre-classified working condition patterns is established by using the supervised learning data mining algorithm, and the working condition identification model is formed by training a large number of data samples. Combining the feature extraction method of principal component analysis with KNN algorithm, the distance formula of KNN algorithm is improved to make it more consistent with the working condition identification, and theaccuracy and efficiency of the working condition identification algorithm are improved.

Description

technical field [0001] The invention relates to a working condition recognition method, in particular to a loader working condition recognition model construction and recognition method. Background technique [0002] With the development of my country's economy, the production, sales and inventory of construction vehicles have increased rapidly, and construction machinery has developed extremely rapidly. More than 95% of construction machinery products adopt hydraulic transmission in order to obtain high torque and meet the demand of large inertia loads. Due to the harsh working environment, complex and changeable working conditions, and equipment automation, the degree of informatization is constantly improving. How to ensure the reliability of construction machinery , Efficient operation is a technical problem to be solved urgently at present. In order to solve these problems, it is necessary to analyze the load spectrum of the loader operation, including the extraction of...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62E02F9/26
CPCE02F9/26G06F2218/06G06F2218/08G06F18/214
Inventor 张泽宇惠记庄武琳琳雷景媛谷立臣
Owner CHANGAN UNIV
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