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A data-driven fault detection method for marine diesel engines

A marine diesel engine and fault detection technology, applied in the direction of internal combustion engine testing, etc., can solve the problems of low real-time performance and detection efficiency, high time and labor costs, and small application range of the model, so as to solve the difficulty of parameter measurement, reduce dependence, and apply wide range of effects

Active Publication Date: 2021-04-30
PEKING UNIV
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Problems solved by technology

The above technologies either require high-precision monitoring of parameters, which is difficult to measure; or the model constructed has a small scope of application; or requires experienced technicians to perform data analysis, which has high time and labor costs, real-time performance and detection low efficiency

Method used

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  • A data-driven fault detection method for marine diesel engines
  • A data-driven fault detection method for marine diesel engines
  • A data-driven fault detection method for marine diesel engines

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Embodiment Construction

[0059] Below in conjunction with accompanying drawing, further describe the present invention through embodiment, but do not limit the scope of the present invention in any way.

[0060] figure 1 The structure of the diesel engine fault diagnosis system provided for the specific implementation of the present invention mainly includes KPI modeling unit and fault detection unit; KPI modeling and fault detection method flow process are respectively as follows figure 2 , image 3 shown. In specific implementation, the KPI modeling algorithm based on the improved PLS is as follows:

[0061] 1. Collect historical data and construct a data matrix Y∈R m×N and Θ∈R l×N ;

[0062] 2. Use the standard PLS method to solve the regression coefficient M of Θ and Y;

[0063] 3. Implement singular value decomposition:

[0064] 4. Decompose the process variable space into two orthogonal subspaces:

[0065] 5. Design T 2 Statistics: threshold

[0066] 6. Detect faults according...

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Abstract

The invention discloses a data-driven marine diesel engine fault detection method, comprising: adopting the k-nearest neighbor clustering method to cluster the working modes of the historical data of the diesel engine to obtain the working mode type of the diesel engine; adopting partial least squares regression Method PLS establishes the KPI model corresponding to each working mode, calculates the inspection threshold; inputs the real-time data to be detected; judges whether the distance between the real-time data points to be detected and the cluster center of the historical data is less than the preset threshold d for diesel engines The working mode is matched; the data to be detected is input into the KPI model of the corresponding mode, and the fault inspection statistics are calculated to obtain the KPI fault inspection statistics; the data-driven marine diesel engine fault detection is realized through comparison. Sampling the technical scheme of the invention can realize real-time online fault diagnosis with wide application range and high efficiency.

Description

technical field [0001] The invention relates to the field of marine diesel engine detection, in particular to a data-driven marine diesel engine fault detection method based on a partial least squares regression method. Background technique [0002] Diesel engine is the power heart of the ship, once it breaks down, it will inevitably affect the operation and safety of the ship. According to statistics, marine accidents of ships are mainly caused by mechanical failures, and diesel engine failures account for 45% of mechanical failures. Traditional diesel engine fault diagnosis techniques include thermal parameter method, oil analysis method, vibration analysis method and instantaneous speed method. The thermal parameter method mainly uses the change of the thermal parameters (dynamometer diagram, pressure, temperature, etc.) of the marine diesel engine to judge its working state; the oil analysis method is to analyze the performance of the diesel engine's lubricant (or worki...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M15/05
CPCG01M15/05
Inventor 杨莹何志晨李鹤张瑀涵刘瑞杰
Owner PEKING UNIV
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