全光纤马赫-曾德干涉型高精度油罐液位传感器

提出一种用于油罐液位测量的高精度全光纤马赫-曾德干涉型液位传感器及其频谱解调法。基于全反射原理,传感器透射谱条纹对比度随传感光纤周围油液位升高明显下降,油液位变化45 mm,干涉条纹对比度最大变化约8 dB。通过快速傅立叶变换分析滤除零频分量的透射谱发现,特定频率分量随液位升高线性下降。实验结果表明,传感光纤90 mm时,灵敏度311 mm-1,分辨率3μm。该油液液位传感器温度串扰小,在25°C到95℃范围内,被测液位误差小于0.14%。

全分布式光纤应力传感器的研究新进展

全面综述了全分布式光纤应力传感器的发展概况。对光后向散射技术、光学非线性效应、模式耦合技术和光干涉技术的主要研究方案进行了评述,重点介绍和分析了实现高空间分辨率和动态应力测量的新技术。最后展望并讨论了全分布式应力传感器的发展趋势和应用前景。

φ-OTDR全分布式光纤振动传感系统的车辆识别方法改进

相位敏感光时域反射计（φ-OTDR）全分布式光纤振动传感系统,在对车辆信号识别过程中所采用的幅度差分法存在着识别率低的问题。为了克服这一问题,将车辆识别方法改进为基于BP神经网络的识别算法。该算法首先利用φ-OTDR系统采集瑞利后向散射光信号,从中提取出车辆振动信号,然后通过主成分分析法（PCA）对振动信号进行降维和特征提取,最后利用BP神经网络模型对高速公路上的车辆进行识别。实验结果表明：利用BP神经网络算法对车辆进行识别,识别率可以达到98.33%。

基于开槽型DBR光纤激光器拍频的折射率探测

提出一种包层开槽型分布布拉格反射光纤激光器,用于光纤激光折射率探测.该激光器以单纵模双偏振分布布拉格反射光纤激光器为核心传感单元,以结构双折射产生的拍频信号为传感信号对折射率进行探测.实验中应用频率编码,灵敏度高且易于解调.利用二氧化碳激光器的热效应对分布布拉格反射光纤激光器的谐振腔加工开槽,通过控制其扫描范围和功率来制备不同宽度和深度的开槽结构,并研究了不同结构参量对灵敏度特性的影响.实验测得最优灵敏度达-240 MHz/RI-unit.此外,还对该结构的温度传感特性做了测试,相较于未刻槽结构,温度灵敏度提高了21%,达1.73 MHz/℃.该装置结构紧凑、稳定性高、制备简单且成本低廉,可用于进一步研究分布布拉格反射光纤激光器的传感和复用特性.

基于环形腔光纤激光器的相位调制型A混合干涉仪

激光自混合干涉技术是近年来兴起的一种具有很高应用价值的干涉测量技术。为提高自混合干涉的位移测量精度，在环形腔光纤激光器自混合干涉系统中引入正弦相位调制技术。分析了干涉信号的相位调制和基于傅里叶变换的解调算法，讨论了相位调制器的调制噪声和多重反馈等因素对自混合干涉测量精度的影响。使用环形腔掺铒光纤激光器和光纤相位调制器构建了实验系统，对高精度商用微位移平台的振动进行了测量，在频域中获取了自混合干涉信号的相位，并重构了位移平台的位移，获得了λ/20的位移测量精度。实验结果表明，该系统提供了一种可靠的基于全光纤传感应用的高精度位移测量方法。

A distributed optical fiber sensing system for synchronous vibration and loss measurement

We propose a fully distributed fusion system combining phase-sensitive optical time-domain reflectometry(Φ-OTDR) and OTDR for synchronous vibration and loss measurement by setting an ingenious frequency sweep rate(FSR) of the optical source. The relationships between FSR, probe pulse width and repeat period are given to balance the amplitude fluctuation of OTDR traces, the dead zone probability and the measurable frequency range of vibration events. In the experiment, we achieve synchronous vibration and loss measurement with FSR of 40 MHz/s, the proble pulse width of 100 ns and repeat rate of 0.4 ms. The fluctuation of OTDR trace is less than 0.45 dB when the signalto-noise ratio(SNR) is over 12 dB for a captured vibration event located at 9.1 km. The proposed method can be used for not only detection but also early warning of damage events in optical communication networks.

Real-Time Distributed Fiber Optic Sensor for Security Systems： Performance, Event Classification and Nuisance Mitigation

The success of any perimeter intrusion detection system depends on three important performance parameters： the probability of detection （POD）, the nuisance alarm rate （NAR）, and the false alarm rate （FAR）. The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings （LCs） based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder （MZ） interferometer.