A high performance distributed sensor system with multi-intrusions simultaneous detection capability based on phase sensitive OTDR (Φ-OTDR) has been proposed and demonstrated. To improve system performance, three aspects have been investigated. Firstly, a model of one-dimensional impulse response of backscattered light and a Monte Carlo method have been used to study how the laser line width affects the system performance. Theoretical and experimental results show that the performances of the system, especially the signal-noise-ratio (SNR), decrease with the broadening of laser linewidth. Secondly, a temperature-compensated fibre Bragg grating with a 3 dB linewidth of 0.05 nm and a wavelength stability of 0.1 pm has been applied as an optical filter for effective denoising. Thirdly, a novel interrogation method for multi-intrusions simultaneous detection is proposed and applied in data denoising and processing. Consequently, benefiting from the three-in-one improvement, a high performance Φ-OTDR has been realized and four simultaneous applied intrusions have been detected and located at the same time along a 14 km sensing fibre with a spatial resolution of 6m and a high SNR of 16 dB. To the best of our knowledge, this is the most multifunctional Φ-OTDR up to now and it can be used for perimeter and/or pipeline intrusion real-time monitoring.
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An all-fibre multi-parameter sensor for composite structures based on a chirped optical fibre Bragg grating (CFBG) has been studied theoretically and experimentally. The principle of multi-parameters sensing with a single CFBG is based on that the centre wavelength and the FWHM (full width at half maximum) in the reflection spectrum of a CFBG vary linearly with the temperature and/or the axial stress. A wavelength matched optical fibre long period grating (LPG) and another wavelength matched reference CFBG (CFBGR) have been used to interrogate the signal of the sensor CFBG (CFBGS). The temperature and strain of the composite structure have been monitored real-time with one CFBG as a single sensor head. The temperature resolution of 0.12ºC and the strain resolution of 1.1με for a composite structure have been realized in experiments. The experiment results agree well with the theoretical analyses.
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As one of the key techniques for futuristic human computer interaction, facial expression recognition has received much attention in recent years. A method of facial expression recognition based on selective feature extraction and rule matching is presented in this paper. In this method we classify expressions roughly into three kinds according to the deformation of mouth firstly. Then we select some expression features which contribute much to each kind expression according to the rough classification results and extract features for them. Lastly we classify expressions finely using method based on rule matching. Experiments show that facial expression recognition based on selective feature extraction and rule matching can get high recognition rate and has strong robustness.
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