Normal and abnormal data partitioning method and system for multivariable alarming system

An alarm system and abnormal data technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as failure and unreachability, and achieve the effects of reducing false alarm rate, reducing noise, and high computing speed

Inactive Publication Date: 2018-03-09
北京协同创新智能电网技术有限公司
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Problems solved by technology

[0003] 1. The data segmentation method should not only be able to identify adjacent similar data segments, but also should be able to identify similar data segments that are far apart in time; the methods in the prior art cannot meet the above requirements
[0004] 2. Most of the existing methods focus on the local fitting of the signal
Local mutations caused by strong noise are easily identified as local trends, so such methods may fail when the real signal has strong noise

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  • Normal and abnormal data partitioning method and system for multivariable alarming system
  • Normal and abnormal data partitioning method and system for multivariable alarming system
  • Normal and abnormal data partitioning method and system for multivariable alarming system

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Embodiment Construction

[0036] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0037] like Figure 12 As shown, the embodiment of the present invention provides a method for dividing normal and abnormal data of a multivariable alarm system, comprising the following steps:

[0038] S1, select the minimum time length τ and the minimum deviation Δ for judging whether there is a change in the signal, and construct the change direction combination relationship matrix R of each variable in the normal state.

[0039] Specifically, select the appropriate minimum time length τ and minimum deviation Δ. These two variables are used to define and identify the phase of the signal. That is, the time interval is less than τ and the Euclidean distance ||x(t+Δt)-x(t)|| 2 Two data points less than Δ should b...

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Abstract

The invention relates to normal and abnormal data partitioning method and system for a multivariable alarming system. The method comprises steps: the minimum duration and the minimum deviation are selected, and a variation direction combination relation matrix of variables under a normal condition is constructed; time sequences of variables in data collection are standardized to obtain a standardized matrix; a time dimension is added to the standardized data matrix, primary clustering is carried out in the time dimension, the influence that local mutation caused by strong noise is recognized as a local trend can be eliminated, and the noise can be effectively reduced; and clusters obtained through the primary clustering are merged to recognize adjacent similar data segments; and secondaryclustering is carried out in a variable dimension, and similar data segments at a far time interval can be recognized. The error report rate can be greatly reduced while a high calculation speed is kept. Compared with the traditional method, the method and the system have huge advantages in recognizing the stage and the variation trend of the system.

Description

technical field [0001] The invention relates to the technical field of industrial alarms, in particular to a method and system for dividing normal and abnormal data of a multivariable alarm system. Background technique [0002] The efficient operation of many types of industrial alarm systems relies on a large amount of rich and labeled (such as "normal", "abnormal") historical data. Manually selecting such historical data from massive industrial data is inefficient and only applicable for smaller datasets. Therefore, it is particularly important to develop an algorithm that automatically divides normal / abnormal data segments. The qualitative trend analysis (QTA) method in the existing literature is one way to solve it. It contains three main methods, namely sliding window method (sliding windows), top-down method (top-down) and bottom-up method (bottom-up). However, there are still two unresolved issues: [0003] 1. The data segmentation method should not only be able t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23G06F18/24
Inventor 王建东陈矿杨子江
Owner 北京协同创新智能电网技术有限公司
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