Device, method and system for monitoring state of hydraulic system

Abstract

The invention discloses a device, a method and a system for monitoring a state of a hydraulic system. The method comprises the following steps that supervised learning model training is provided, andspecifically, a training set and a test set are divided according to an existing sample data set, and training, verification and optimization processes of the supervised learning model is completed; and the system is initialized, and specifically, the system is started. According to the device, the method and the system for monitoring the state of the hydraulic system, the method comprises the following steps that firstly, data dimensionality reduction is conducted on the large-scale hydraulic measurement original data by using an unsupervised PCA algorithm, the data processing amount is greatly reduced, the training and prediction speed are remarkably improved, the overfitting risk is reduced, the training and prediction speed are remarkably improved, the generalization ability of a modelis improved, and good prediction accuracy is achieved; and the requirement for real-time accurate evaluation of the hydraulic system is met, finally, the prediction accuracy of the hydraulic state can be remarkably improved, and a better application prospect is brought.

Description

technical field [0001] The invention relates to the field of state monitoring of a hydraulic system, in particular to a device, method and system for state monitoring of a hydraulic system. Background technique [0002] Hydraulic systems are the driving force behind a great deal of automation in virtually all heavy industry sectors. The indispensability of hydraulics means that constant attention must be paid to condition monitoring as an essential element in the healthy maintenance of machinery. Recent developments in condition monitoring technology mean that engineers can receive early warning of impending system failures and take remedial action, extending the useful life of machines. [0003] Predictive maintenance technology can reduce unplanned downtime and increase productivity, resulting in significant profit savings in the hydraulic systems market. And with the development of advanced technology, the increase of electrification in hydraulic system components allow...

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Problems solved by technology

[0004] Existing similar studies propose to use the Xgboost algorithm to predict the state of the hydraulic system, and then analyze the important factors affecting each part of the hydraulic system (cooling system, valve status, pump leakage, hydraulic accumulator status), although this method also combines sensor However, it does not normalize and reduce the dimensionality of the original data, which will largely cause the data to retain a lot of noise, cause the model to overfit, and lead to a decrease in the accuracy of the prediction.

At the same time, too large a feature dimension will make the training and prediction of the model occupy too many computing resources, which is not conducive to practical engineering applications.

In addition, similar patents do not combine the label attributes of the target condition value to divide the data, so it is very likely that various data offset prediction problems will occur

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