This paper describes a new type of latching micro magnetic relay that has recently been demonstrated. The device is based on preferential magnetization of a permalloy cantilever in a permanent external magnetic field. Switching between two stable states is accomplished by a short current pulse through an integrated coil underneath the cantilever. Some key features are summarized as follows. ( 1) Latching (bistable); (2) low energy consumption during switching (593 &I, switching current -60 mA, minimum switching pulse width -0.2 ms); (3) low voltage operation (5.5 V); (4) maximum DC current >500 mA, (5) capable of various switch configurations [single-pole-single-throw (SPST), multi-polesingle-throw (MPST), or multi-pole-double-throw (MPDT)]; (6) low contact resistance (550 mn); (7) operation in ambient environment; ( 8) lifetime expected to be comparable to other micro relays, (9) batch fabrication using planar processing methods.

This research proposes an artificial intelligence (AI) detection model using convolutional neural networks (CNN) to automatically detect gas leaks in a long-distance pipeline. The change of gap pressure is collected when leakage occurs in the pipeline, and thereby the feature of gas leakage is extracted for building the CNN model. The gas leak patterns in the long-distance pipeline are analyzed. A pipeline detection model based on AI technology for automatically monitoring the leaks is proposed by extracting the feature of gas leakage. This model is tested by collecting gas pressure data from an existing natural gas pipeline system starting from Mailiao to Taoyuan in Taiwan. The testing result shows that the reduced model of leak detection can be used to detect the leaks from the upstream and downstream pipelines, and the AI-based pipeline leak detection system can obtain a satisfactory result.