Abnormity detection and diagnosis method for non-gaussian dynamic high-sulfur natural gas purification process
A process abnormality and diagnostic method technology, applied in the direction of electrical testing/monitoring, testing/monitoring control systems, instruments, etc., can solve problems such as failure to detect failures in time
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[0049] Such as figure 1 As shown, a non-Gaussian dynamic high-sulfur natural gas purification process abnormal detection and diagnosis method is carried out according to the following steps:
[0050] Step 1: Randomly collect n groups of high-sulfur natural gas purification process data to form the original measurement sample set X=[x 1 ,x 2 ,...,x n ]∈R m×N , each sample contains N independent high-sulfur natural gas purification process parameter sampling values.
[0051] Step 2: Preprocess the sample data and select the effective data that can best reflect the actual characteristics of the production process; specifically: eliminate samples with missing parameters in the collected data, and ensure that the samples meet the company's purification gas technical indicators, and the obtained data is X *=[x 1 ,x 2 ,...,x n ]∈R m×n , n is the number of samples collected after processing, n<N.
[0052] Step 3: Analyze the autoregressive model of the data X* obtained in st...
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