Environmental Intelligent Control of Underground Integrated Pipe Gallery Based on Equipment Failure Rate

Abstract

As a comprehensive infrastructure, urban integrated pipe gallery has numerous risk factors and various types, and once an accident occurs, it will have a major impact on urban public safety. At present, the comprehensive management of the underground integrated pipe gallery in China is still in the stage of regular inspection of the appointed personnel. Risks cannot be foreseen in advance, and they cannot be prevented. Based on the environmental data and equipment maintenance data in the pipe gallery, this paper proposes an intelligent regulation algorithm for underground integrated pipe gallery based on equipment failure rate. The fusion of heterogeneous data is included in the specific modules, meanwhile, the feature of device failure rate is extracted based on machine learning, and the multi-objective optimization environment is intelligently regulated by energy consumption and equipment failure rate. The algorithm can effectively reduce the probability of equipment failure by intelligent regulation of the environment, and improve the safety and economy of the underground integrated pipe gallery. INDEX TERMS Equipment failure rate, intelligent control, pipe gallery.

Data Asset Management and Visualization Based on Intelligent Algorithm: Taking Power Equipment Data as An Example

“…This phase describes the specification of the tree structure [21][22][23]. The maximum tree depth is set to 3 levels and the saliency values for split nodes and merge categories are set to 0.05.…”

“…In the second stage, the labeled data are used to supervise the DNN final stage prediction. In this paper, a deep neural network based on the SAE-DNN model is built to identify suspicious anomalies [23]. As shown in Fig.…”