JIANGNan,FENGLi,LINZi-yin,et al.Precise Detection System for Sewage Leakage in Pneumatic Flap Doors Based on Dynamic Mean Perceptron Neural Network[J].China Water & Wastewater,2024,40(17):118-122.
Precise Detection System for Sewage Leakage in Pneumatic Flap Doors Based on Dynamic Mean Perceptron Neural Network
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第40卷
Number:
第17期
Page:
118-122
Column:
Date of publication:
2024-09-01
- Keywords:
- drainage network; flap door; sewage leakage; random error; mean detection; neural network; perceptron
- Abstract:
- Based on the principles of mean detection and perceptron neural network classification, a dynamic mean perceptron neural network classification model was used to develop a precise detection system for sewage leakage in pneumatic flap doors of drainage network. Firstly，pressure was symmetrically increased/decreased by 20 kPa with the inherent critical working pressure P as the center, and the position and state of the flap door 9 times was continuously detected to form a 9-dimensional dynamic feature vector. Then, by weighting and summing with the 9-dimensional mean weight vector, the dynamic mean feature quantity was extracted. Finally, by using a step activation function, the output threshold classification was used to detect the leakage status of the sewage in the flap door, and the output threshold was trained to be 3.6. The on-site application system test of Liede Chong in Guangzhou City showed that the accuracy of the sewage leakage detection of the flap door was 96%. This method effectively solves the problems of the random and systematic errors of detection results, thereby reducing the leakage of sewage in the drainage network.
Last Update:
2024-09-01