Dissertation
Dissertation > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation components,parts > Transmitter ( converter),the sensor > Physical sensors > Light sensor

Study on Signal Processing Scheme for Fiber-Optic Interferometric Sensors Based on Software Interrogation Method

Author ChenZuoYing
Tutor LiXinWan
School Shanghai Jiaotong University
Course Electromagnetic Field and Microwave Technology
Keywords Interferometric fiber-optic magnetic field sensor Signal detection Minimum detectable phase System noise Adaptive Line Enhancer Software demodulation Sensitivity
CLC TP212.14
Type Master's thesis
Year 2007
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Interferometric fiber-optic magnetic field sensors involving optoelectronics, materials science, signal processing, processing technology, and other disciplines. Interferometric fiber-optic magnetic field sensor with high sensitivity, large dynamic range, anti-interference ability, low cost, broad application prospects and development potential, is a popular direction of the magnetic field sensor technology research areas today. Interferometric Fibre weak magnetic field sensing probe sensitivity is high, so the signal processing module. A well-designed signal processing module should be able to well restore the signals detected by the sensor probe, and less noise introduced. Usually used hardware signal detection method having a flexible and limitations, in particular the additional introduction of the electrical noise, so this article consider the signal detection is performed by means of software. The optical signal on the sensor output due to system noise will produce a phase drift, so how to suppress the system noise is the crux of the signal detection. The interference type optical fiber magnetic field sensor system noise includes the noise and light noise, the fiber thermal noise, shot noise, and the photoelectric detector noise, the background noise such as the introduction of the external environment. This article is a detailed analysis and evaluation of these sources of noise and affect the mechanism of the phase of the output signal. Fiber thermal noise, scattering noise sensing system affect most of the ups and downs of noise sensitivity (minimum detectable phase) To this end, this paper presents a filtering scheme based on adaptive line enhancement technology, the magnetic field pass interferometric the differential output signal obtained by the sense probe site to be sampled, the sampled data by the adaptive line enhancer filtering, the use of the three phase point of the waveform to determine the DC, fundamental and second harmonic components, and other parameters, the measured magnetic field signals software demodulation. The adaptive line enhancement technology is a time delay and the number of iterations to achieve noise filtering method can effectively filter out the white noise of the system broadband fiber thermal noise and shot noise. Meanwhile, in the frequency domain, it is a narrowband filter of adjustable bandwidth, can dynamically track the resonance operating point of the optical fiber sensor, and to overcome the hardware implementation of the bandpass filter center frequency is limited by the weaknesses. The experiments show that the adaptive line enhancement modules have a good inhibition of the system the noise floor compared to the module is not used, a decrease of 13dB. The same time, we found that the demodulation of linearity better than without the results of the filtering module, the optical fiber sensor sensitivity reached 5.22 × 10? The 3mV nT. The method of signal processing software only design parameters, flexible and easy to adjust, and can suppress the influence of noise of the system. In this paper, a sensor network trend of interferometric fiber-optic sensor signal processing system software demodulation method of virtual instrument thought, combined with high-performance processing power of the computer, the signal processing system is a remote monitoring center The real-time measurement, a reference for the future research direction.

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