Gas turbine anomaly detection method based on NARX network-box diagram and normal mode extraction

An anomaly detection and boxplot technology, applied in biological neural network models, neural learning methods, special data processing applications, etc., can solve problems such as abnormal detection of gas turbines

CN110532681AActive Publication Date: 2019-12-03HARBIN INST OF TECH +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2019-12-03

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Abstract

The invention discloses a gas turbine anomaly detection method based on an NARX network-box line graph and constant mode extraction, and the method comprises the steps: training an NARX neural networkthrough the data of a training set, and obtaining an exhaust temperature prediction value of training data and a trained NARX neural network model; calculating a residual error between the exhaust temperature prediction value and the corresponding exhaust temperature true value, and inputting the residual error into an improved box line graph algorithm to obtain a residual error detection threshold value; calculating a residual error between a turbine exhaust temperature value predicted by a model obtained by inputting to-be-detected data into a trained NARX neural network model and an actualturbine exhaust temperature value and judging whether the residual error is within a residual error detection threshold value or not. According to the method, the problem that in the prior art, abnormity detection of the gas turbine cannot be achieved under the condition that only a large amount of normal historical data exists is solved, online detection can be achieved, and the method has important significance in safe and reliable operation of the gas turbine.
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Description

technical field

[0001] The invention belongs to the field of gas turbine detection and control, and proposes a gas turbine anomaly detection method based on NARX network-box diagram and normal mode extraction. Background technique

[0002] Gas turbine is a very important power machine, which is widely used in aviation power, ship power, mechanical drive, power system and other fields. Gas turbines work in an environment of high temperature, high pressure, and high-speed rotation for a long time, and the thermal load and mechanical load are large, so they are prone to failure. Gas turbine failures often result in high maintenance costs and huge economic losses. On-line anomaly detection of gas turbine is of great significance to improve the operation safety and reliability of gas turbine.

[0003] In the document "Gas turbine fault diagnosis using probabilistic neural networks (gas turbine fault diagnosis based on probabilistic neural network)" published by Loboda I, Robles...

Examples

Embodiment Construction

[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0027] refer to Figure 10 As shown, the present invention proposes a gas turbine anomaly detection method based on NARX network-box diagram and constant mode extraction, and the gas turbine anomaly detection method includes the following steps:

[0028] Step 1: Use the data of the training set to train the NARX neural network to obtain the predicted exhaust temperature of the training data and the trained NARX neural network model. Through the tra...