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A wireless sensor network-based distributed measurement system is designed for collecting and monitoring the electric field under the high voltage direct current (HVDC) transmission lines. The proposed system architecture is composed of a group of wireless nodes connected with electric field sensors and a base station. The electric field sensor based on Gauss's law is elaborated and developed. For the design of wireless node, the ARM microprocessor and Zigbee radio frequency module are employed. The proposed system has been used in China's state grid HVDC test base and the in situ power transmission projects. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the transmission lines and can accomplish the accurate, flexible, and stable demands of the electric field measurement.

Support vector machine (SVM) is a machine learning algorithm which has been applied to fault diagnosis of analog circuits. Invasive weed optimization (IWO) is a novel numerical optimization algorithm inspired from weed colonization. An approach that combines IWO and SVM (IWO-SVM) is proposed to fault diagnosis of analog circuits in this paper. The process of fault diagnosis of analog circuits using IWO-SVM approach is introduced in details. A biquadrate filter is used to test the performance of IWO-SVM approach for fault diagnosis. The simulation experiments show that the IWO-SVM approach proposed in this paper has a higher diagnosis accuracy rate than the conventional SVM in fault diagnosis of analog circuits.

For the construction process of striking and rolling to treat the foundation, the traditional compaction test must conduct core sampling and damage detection, which are time-consuming and strenuous. Furthermore, it is difficult to determine the actual overall compaction. Based on acceleration sensor and satellite positioning measurement technology, this paper designs and develops an acceleration information acquisition device for impact construction, which can auto monitor impact construction in large-scale pavement construction. This paper also proposes methods for analyzing the degree of impact acceleration and compaction, including: (1) comprehensive analysis of the functional requirements and structural levels of a device for the acquisition of information about impact acceleration; (2) development of an acquisition system for collecting information about impact acceleration installed on the roller; (3) proposal of a method for the processing and analysis of compaction information based on the collected acceleration information; and (4) proposal of an experimental scheme of to test impact acceleration and application of the whole set of developed equipment to practical engineering.

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