In order to improve the efficiency and accuracy of fault diagnosis of power supply and distribution system in intelligent buildings, a fault diagnosis method based on Bayesian network and wavelet transform was proposed. Firstly, the topological structure of power supply and distribution network in intelligent buildings was analyzed in detail in theory. Secondly, the switching and electrical quantities in fault information were filtered and reorganized by wavelet transform. Finally, the fault information after the reorganization was modeled and analyzed by Bayesian network, and the fault diagnosis results were obtained. In this paper, the process of extracting electrical and switching quantities from fault information was introduced in detail. According to the fault characteristics of the existing intelligent building power supply and distribution system, the corresponding recovery strategy was given. IEEE⁃39 multi⁃node complex power fault system is taken as an example, the simulation results show fault diagnosis result of the proposed method is fast and accurate. The research results have important reference value for fault diagnosis research of intelligent building power supply and distribution network.

A single terminal fault location method for overhead transmission lines in general interconnected power system with n⁃bus was proposed. High accuracy in fault location was achieved by using both an accurate distributed parameters model for the faulted transmission line, and a two⁃bus Thevenin equivalent network model for the power system that accurately accounted for its inter connectivity. The method was tested by using transient fault data obtained from MATLAB simulations of an 11⁃bus interconnected power system. The results show that the method is capable of estimating the fault distance with high accuracy for various fault conditions. And it is sensitive to errors in the value of the local bus impedance, but insensitive to errors in the value of the remote bus impedance.

In the gathering pipeline, the velocity and pressure of the oil-water two-phase flow through the elbow will change, which will increase the corrosion degree of the elbow and lead to frequent accidents caused by corrosion of the elbow. Taking water as discrete phase, the flow state in pipeline is numerically simulated by the combination of RNG turbulence model and DPM model. The variation law of pipeline corrosion influence factor is obtained, and the simulation data is processed by origin software and analyzed by orthogonal test method. The results show that the different pipeline parameters have different effects on cavitation corrosion rate. Among them, the pipe diameter has the greatest influence, the mass flow rate of water droplet particles, the inlet velocity of the fluid, and the bending angle of the pipe are the second, and the bending diameter ratio has the least influence on the cavitation corrosion rate.The research results can provide the technical support for the design and operation management of the gathering pipeline.