Feedwater pump fault detection method based on minimum sufficient statistics pattern analysis
A technology of pattern analysis and fault detection, applied in computing, data processing applications, instruments, etc., can solve problems such as performance degradation, difficulty in obtaining fault samples, and failure to detect faults, and achieve the effect of high detection accuracy
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0091] A fault detection method for feedwater pumps based on minimum sufficient statistics pattern analysis, including the following steps:
[0092] Step 1: Collect steam-driven feedwater pump operation and related state data from the DCS of a 300MW unit in a power plant. The sampling time is 1s. The specific state variables are shown in Table 1. Collect 5000 groups in normal state, and then standardize the mean value to 0 and the standard deviation to 1 to form the training data set X∈R m×n . Among them, m=11 is the number of state variables, and n=5000 is the number of training samples. In addition, 900 sets of data on the transition from normal state to fault state of two common faults of fluid cavitation and abnormal wear of the steam-driven feedwater pump were collected to test the effect of the method.
[0093] Table 1 Status Data
[0094] Feed water pump inlet flow Feed water pump inlet temperature Feed water pump radial shaft vibration X direction ...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


