Improved data cleaning method for stack noise reduction auto-encoder

An auto-encoder and data cleaning technology, applied in the data cleaning field of stack noise reduction auto-encoder, can solve the problems of evaluating equipment operating conditions, destroying data continuity and integrity, ignoring correlations, etc.
CN109978079AInactive Publication Date: 2019-07-05NORTHEAST DIANLI UNIVERSITY
3 Cites 17 Cited by

Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
NORTHEAST DIANLI UNIVERSITY
Publication Date
2019-07-05
Estimated Expiration
Not applicable Β· inactive patent

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses an improved data cleaning method for a stack noise reduction auto-encoder, which comprises the following steps of firstly, introducing an Adam and SGD hybrid algorithm to continuously adjust the network parameters of a stack noise reduction auto-encoder model; secondly, training the normal state data by using the model, obtaining the hidden characteristics of the data, andobtaining a reconstruction error in a normal state; thirdly, using the model for detecting the abnormal state data, analyzing the influence of various types of data on the model according to reconstruction errors of the abnormal state data, and rapidly classifying, cleaning and repairing the dirty data and the abnormal data reflecting the equipment faults. The AS-SDAE can directly and intelligently analyze the monitoring data, can better mine the high-order characteristics hidden in the data, guarantees the high efficiency of cleaning the dirty data, retains the useful data reflecting the abnormal condition of the equipment, and improves the data analysis efficiency.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the field of data processing, in particular to an improved data cleaning method of a stack noise reduction autoencoder. Background technique

[0002] With the development of electric power enterprises, the demand for national electricity is increasing. As one of the main equipment for electric energy production, the boiler's condition monitoring data increases in series during the production process, which conforms to the characteristics of big data and contains rich potential. Resource value, mining and analysis of these data is helpful to understand the overall operation law of the power system. However, the operating conditions of the power plant are complex and diverse, and the boiler is subject to various external interferences during the actual operation process, such as the environment is changeable, the sensor is abnormal for a short time, and the data transmission chain is blocked, etc., resulting in the monitoring dat...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More