Method and system for predicting service life of electromechanical equipment based on data driving

A technology for electromechanical equipment and life prediction, applied in computer-aided design, design optimization/simulation, calculation, etc., can solve problems such as high data dependence, achieve uniform distribution, increase proportion, and improve adaptability

Active Publication Date: 2022-07-22
TIANJIN UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

The existing technology provides some analysis methods based on data-driven electromechanical life. These methods mainly start from the perspective of how to mine data information, such as increasing the depth of the model, using different feature extraction methods, etc. Then, the data-driven analysis method itself One of the problems is that the dependence on the data is too high. How to make the data random and contain as many actual situations as possible is a problem that needs to be solved in data analysis

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  • Method and system for predicting service life of electromechanical equipment based on data driving
  • Method and system for predicting service life of electromechanical equipment based on data driving
  • Method and system for predicting service life of electromechanical equipment based on data driving

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[0020] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0021] It will be understood that the terms "first", "second" and the like used in the present invention may be used herein to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish a first element from another element. For example, a first xx script could be referred to as a second xx script, and similarly, a second xx script could be referred to as a first xx script, without departing from the scope of the present invention.

[0022] like figure 1 As shown, in one embodiment, a data-driven electr...

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Abstract

The invention relates to the technical field of electromechanical equipment life prediction, in particular to an electromechanical equipment life prediction method and system based on data driving, and the method comprises the steps: obtaining a data set of multiple pieces of equipment; abnormal data are screened out; performing period division according to the distribution of the abnormal data on the time axis; performing cycle combination on cycle division results of different devices to obtain a training set and a test set; inputting the training set into a selected data driving model for training; inputting the test set into the trained data driving model for testing; and after the test is finished, predicting the service life of any electromechanical equipment according to the obtained data driving model. According to the method provided by the invention, the abnormal data are screened, the data of multiple devices are subjected to cycle division and then are recombined to obtain the training set and the test set, the model is trained and tested, the life prediction is completed, and the data are integrated in the data division stage, so that the model is more comprehensive and accurate.

Description

technical field [0001] The invention relates to the technical field of life prediction of electromechanical equipment, in particular to a data-driven life prediction method and system of electromechanical equipment. Background technique [0002] Data-driven is a data processing and analysis method relative to model-driven. The so-called model-driven refers to constructing a model, using the collected data, and analyzing the object according to the constructed model. This method depends on the accuracy of the constructed model. In contrast, under the data-driven analysis method, instead of constructing a fixed model, the collected data is used to train the model to fit the model to the data. [0003] Data-driven analysis methods have a higher dependence on data information, but are also more adaptable to data. In some data analysis with obvious trends and regular fluctuations, data-driven analysis methods have obvious advantages. [0004] Life prediction of electromechanica...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F119/04
CPCG06F30/27G06F2119/04
Inventor 钟炜
Owner TIANJIN UNIVERSITY OF TECHNOLOGY
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