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Here, in order to calibrate the magnetostrictive liquid-level meter in situ, a set of in-situ calibration device for magnetostrictive liquid-level meter is designed. The structure and working principle of the device are described, and the experimental test and error analysis are carried out for the parts of the in-situ calibration device. Finally, according to the modern instrument and error theory, the accuracy of the calibration device is assessed, and the field calibration experiment of magnetostrictive liquid level gauge is carried out. The theoretical analysis and field experiment results show that the calibrated device can meet the in-situ calibration requirements of the magnetostrictive liquid-level meter with a range of 0–6 m and a precision of 1 mm.

The diode is used as the detection unit to receive the millimetre-wave signal directly. A circuit is made with an operational amplifier OP27 to amplify the signal. The magnification of the OP27 circuit is stable at 100

In this paper, a fiber optic based sensor capable of fault detection in both radial and network overhead transmission power line systems is investigated. Bragg wavelength shift is used to measure the fault current and detect fault in power systems. Magnetic fields generated by currents in the overhead transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). The Fiber Bragg interrogator senses the reflected FBG signals, and the Bragg wavelength shift is calculated and the signals are processed. A broadband light source in the control room scans the shift in the reflected signal. Any surge in the magnetic field relates to an increased fault current at a certain location. Also, fault location can be precisely defined with an artificial neural network (ANN) algorithm. This algorithm can be easily coordinated with other protective devices. It is shown that the faults in the overhead transmission line cause a detectable wavelength shift on the reflected signal of FBG and can be used to detect and classify different kind of faults. The proposed method has been extensively tested by simulation and results confirm that the proposed scheme is able to detect different kinds of fault in both radial and network system.