CN109520429B - Few-spectrum sampling point high-speed measurement system and method of white light interference type optical fiber Fabry-Perot sensor - Google Patents
Few-spectrum sampling point high-speed measurement system and method of white light interference type optical fiber Fabry-Perot sensor Download PDFInfo
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Abstract
The invention relates to a few-spectrum sampling point high-speed measurement system and method of a white light interference type optical fiber Fabry-Perot sensor, and belongs to the technical field of optical fiber sensing. The system comprises a broadband light source, an optical circulator, a wavelength division multiplexer, a photoelectric detection group, a high-speed parallel acquisition subsystem and a demodulation calculation subsystem; the method comprises the following steps: s1: decomposing a wide spectrum output by the optical fiber Fabry-Perot sensor into limited N paths of narrow spectrum signals by using a wavelength division multiplexer, a photoelectric detector group and a high-speed acquisition subsystem; s2: and constructing a noise-free N-path ideal interference spectrum signal, and constructing a probability density function by the difference of the noise-free N-path ideal interference spectrum signal and the actual signal obtained in the S1. S3: and solving the estimator which maximizes the probability density function to obtain the maximum likelihood estimator of the cavity length L. The invention starts with spectrum collection and data processing method with less sampling points, software algorithm and hardware, and greatly reduces the resource occupation of data collection and processing, thereby breaking through the bottleneck of measuring speed.
Description
Technical Field
The invention belongs to the technical field of optical fiber sensing, and relates to a few-spectrum sampling point high-speed measurement system and method of a white light interference type optical fiber Fabry-Perot sensor.
Background
For rotating mechanical equipment such as steam turbines and water turbines, generators and engines, centrifuges and machine tools and the like, the high-speed dynamic online monitoring of the micro displacement/clearance of moving parts of the rotating mechanical equipment has important significance for new product research and development and operation safety guarantee. Due to the advantages of small volume, electromagnetic interference resistance, no electricity at the sensor end and the like, the optical fiber sensor is emphasized in the high-speed dynamic online monitoring of the micro displacement/gap. Among various optical fiber sensors, the white light interference type optical fiber sensor has the advantages of high measurement accuracy, strong anti-interference capability and large dynamic range due to the characteristic of carrying larger information quantity by utilizing a wide spectrum, and is one of ideal means for micro-displacement/gap monitoring.
The key of the white light interference type optical fiber Fabry-Perot sensor demodulation is that the cavity length L of the optical fiber Fabry-Perot is solved by using the wide spectrum interference signal, which needs to sample and operate the complete spectrum containing thousands of spectrum data, so that the spectrum sampling and the signal demodulation are faced with the problems of large data volume and low speed. Therefore, the overall measurement speed of the white light interference type optical fiber Fabry-Perot sensing system is difficult to exceed 1 kHz. This has greatly restricted the development of such sensors in high speed dynamic micro-displacement/gap measurements.
1. Status of problem
Obviously, the large data amount spectrum sampling and the large data amount signal demodulation calculation of the wide spectrum interference signal are two major core problems for limiting the demodulation speed of the conventional white light interference type sensing system, so that a breakthrough is sought from two angles of spectrum data sampling and demodulation calculation, namely two major key links for breakthrough of the sensing speed of the white light interference type optical fiber Fabry-Perot sensor and realization of high-speed dynamic measurement.
In the aspect of spectral data sampling, the most conventional method is to collect the spectral data by using a spectrometer, and the most typical micro spectrometer is to spatially separate light beams with various wavelengths by using a light splitting element and then perform spectral sampling by using a linear array detector. Because the output of the photodetector array adopts a serial pixel-by-pixel sampling output mode, the sampling rate is a bottleneck limiting the spectrum sampling speed of the spectrometer; although a series of high-speed spectrometers with frame rates exceeding 1kHz have appeared on the market in recent years with the development of technology, there is little room for improvement and they are expensive. Another kind of spectrum sampling mode is a high-speed frequency-sweeping laser spectrometer which generates wavelength variation by using MEMS mechanical vibration, but the spectrum sampling rate is limited by the MEMS vibration frequency, and is difficult to further increase on the basis of the current commercial product of dozens of kHz level, and the price is also expensive.
In the aspect of demodulation calculation of spectrum signals, a demodulation algorithm based on fast fourier transform is still the mainstream of research and application, and methods such as Bonneman frequency estimation, a fast full-phase method and the like are developed on the basis, and the methods need to carry out calculation with large data volume to achieve the expected demodulation accuracy.
Although research from two aspects of spectrum sampling and data demodulation and calculation can improve the speed of the conventional white light interference type optical fiber Fabry-Perot sensing demodulation system to a certain extent, the improvement range is limited, and the requirement of high-speed and high-precision measurement cannot be fundamentally met.
2. Root cause of problem
From the data demodulation calculation, since the broad spectrum has thousands of original spectrum data, it is determined that the demodulation calculation needs to process thousands of basic data. In order to ensure the accuracy of demodulation calculation, the algorithm usually needs fourier transform zero padding, spectrum difference, signal phase extraction and other processes, that is, a virtual spectrum data volume needs to be additionally added, so that a large data volume needs corresponding operation hardware and software, and is a key place for restricting the demodulation speed.
From the above problem analysis, it can be seen that, in the white light interference type optical fiber sensor, the original wide spectrum interference data with large data volume and the intensive spectrum signal sampling and processing calculation are required, which is the key to ensure the high-precision demodulation and the key to limit the demodulation speed. Therefore, on the premise of not reducing the demodulation precision, the spectrum sampling intensity is reduced, and the speed bottleneck of a white light interference type optical fiber Fabry-Perot measurement system can be fundamentally broken through by researching the demodulation algorithm and the technical implementation of few spectrum sampling points through a sparse spectrum sampling demodulation algorithm method.
Disclosure of Invention
In view of the above, the present invention provides a method and a system for demodulating fewer spectrum sampling points of a white light interference type optical fiber fabry-perot sensor, which start with hardware systems and software algorithms for spectrum acquisition and data processing of fewer sampling points, respectively, so as to greatly reduce resource occupation of data acquisition and processing, thereby breaking through the speed bottleneck.
In order to achieve the purpose, the invention provides the following technical scheme:
a few-spectrum sampling point demodulation system hardware of a white light interference type optical fiber Fabry-Perot sensor is shown in figure 2 and comprises a broadband light source, an optical circulator, a wavelength division multiplexer, a photoelectric detector group, a high-speed parallel acquisition subsystem, a data demodulation and calculation subsystem and the like; the demodulation system can realize sparse light splitting and collection in a wide spectral range, namely sparse sampling as shown in fig. 1 (b).
The broadband light source, the optical circulator, the wavelength division multiplexer, the photoelectric detector group, the high-speed parallel acquisition subsystem and the data demodulation and calculation subsystem are sequentially connected to form a less-spectrum sampling point demodulation system; the optical fiber Fabry-Perot sensor is connected with the few-spectrum sampling point demodulation system;
the broadband light source is used for providing a high-power stable light source with a wide spectrum and low polarization degree;
the optical circulator is used for transmitting the wide-spectrum optical signal emitted by the light source to the sensor in a one-way mode, and simultaneously transmitting the interference optical signal returned by the optical fiber Fabry-Perot sensor in a one-way mode to the demodulation system;
the wavelength division multiplexer is used for dividing the wide spectrum interference optical signal returned by the optical fiber Fabry-Perot sensor into N paths of narrow band optical signals with different wavelengths;
the photoelectric detector group consists of N photoelectric detectors matched with the wavelength division multiplexer, and each detector independently receives an optical signal with one wavelength to form N paths of parallel analog electric signal outputs;
the high-speed parallel acquisition subsystem is used for amplifying, filtering and converting N paths of electric signals output by the photoelectric detection group into digital signals, and acquiring and caching the digital signals for demodulation calculation of a subsequent system;
the demodulation calculation subsystem is used for carrying out high-speed processing calculation on the N paths of digital signals and realizing high-speed demodulation of the N spectral data.
A high-speed demodulation calculation software algorithm of few spectrum sampling points of a white light interference type optical fiber Fabry-Perot sensor comprises the following steps:
s1: decomposing the output of the optical fiber Fabry-Perot sensor into limited N paths of narrow spectrum signals by using a wavelength division multiplexer, a photoelectric detector group and a high-speed parallel acquisition subsystem, and respectively acquiring and caching the signals;
s2: constructing a noise-free N-path ideal interference spectrum signal, and constructing a probability density function of noise characteristics by using the difference between the noise-free N-path ideal interference spectrum signal and the actual signal obtained in S1;
s3: the estimator that maximizes the probability density function is solved to obtain the maximum likelihood estimator of the cavity length L.
Further, in step S2, the real cosine function form of the ideal interference spectrum signal is:
In＝I0R[1-cos(4πLk)](1)
wherein, I0The light intensity of the light source, k is the central wave number of the wavelength division multiplexer, R is the reflectivity of the reflecting surface of the sensor, and L is the cavity length of the Fabry-Perot sensor. As can be seen from equation (1), solving the cavity length L from the interference spectrum can be converted into a frequency estimation problem of a cosine function, and the interference spectrum signal of a single low-reflectivity interference sensor is a single-frequency real cosine function with a small number of cycles as shown in fig. 1.
Fig. 1(a) shows a section of interference spectrum obtained by a low-reflectivity fiber Fabry under an ideal wide-spectrum light source, and a spectrum signal obtained by a general spectrometer after intensive sampling. Dense spectral sampling leads to problems of large data size, slow speed, etc. If the spectrum shown in fig. 1(a) is sparsely sampled under the condition that the nyquist sampling rate is satisfied, a spectrum signal as shown in fig. 1(b) can be obtained.
For signals with a small number of cycles, a sampling point number very close to the nyquist sampling rate, and a single frequency component as shown in fig. 1(b), the general spectrum analysis method cannot provide a result with high accuracy due to the fence effect, spectrum leakage, and the like. And the parameter estimation method taking the Fabry-Perot cavity length L as the unknown frequency can provide high frequency estimation accuracy. Among the many kinds of cosine parameter estimation methods, maximum likelihood estimation has proven to be one of the best algorithms for estimation accuracy and performance.
Further, in step S2, the probability density function of the interference spectrum signal is:
wherein S isnActual interference spectral signals, I, collected for system hardwarenFor the ideal interference spectrum signal obtained by the formula (1), σ is the noise variance, N is the independent variable of the spectrum signal, and N is the number of channels (i.e. the number of spectrum sampling points) of the wavelength division multiplexer and the photoelectric detector group.
Further, in step S3, the maximum likelihood estimator of the cavity length L is:
where g is the maximum likelihood estimate argument, knIs the wavenumber independent variable. According to the maximum likelihood estimator calculated by the formula (3), the cavity length result with the accuracy close to the Clalmelo limit can be obtained by using the few-point sampling spectrum shown in FIG. 1(b), so that the high-accuracy cavity length demodulation can be realized under the condition of greatly reducing the number N of the spectrum sampling points.
The invention has the beneficial effects that: the invention starts from two aspects of spectrum acquisition and data processing methods and software algorithms with few sampling points and spectrum data acquisition and processing hardware with few sampling points, reduces the data volume of spectrum sampling and processing from thousands to tens of data volume, greatly reduces the resource occupation of data acquisition and processing, and breaks through the speed bottleneck.
Drawings
In order to make the object, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
FIG. 1 is a schematic diagram of spectrum and digital spectrum signals of a white light interference type Fabry-Perot sensor;
FIG. 2 is a system structure diagram of the high-speed demodulation system with few spectrum sampling points according to the present invention;
FIG. 3 is a structural diagram of a few-spectrum sampling point white light interference fiber Fabry-Perot high-speed measurement system based on multipath DWDM;
fig. 4 is a flow chart of core steps of a high-speed demodulation algorithm.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in FIG. 2, the high-speed measurement system with few spectrum sampling points of the white light interference type optical fiber Fabry-Perot sensor comprises a broadband light source, an optical circulator, a wavelength division multiplexer, a photoelectric detector group, a high-speed parallel acquisition subsystem, a data demodulation and calculation subsystem and the like.
1. Spectral sampling hardware system embodiment:
the wavelength division multiplexer (DWDM) can realize the spectrum light splitting with the center frequency equal interval and the constant bandwidth, and is a mature product in the communication field. The 100GHz array waveguide grating type DWDM is selected to form a spectrum sampling hardware system as shown in figure 3.
The photoelectric detector adopts a discrete InGaAs photodiode detector with a tail fiber and is used for converting interference light intensity of each channel into a voltage signal, the signal processing circuit is used for amplifying a mu A level current signal output by the photodiode into a voltage signal in a range of 0-5V, synchronous acquisition is carried out by an FPGA through an analog-to-digital converter (ADC), and the acquired signal is operated and demodulated in the high-speed FPGA.
The system measurement speed is determined by the minimum value of the bandwidth of each device in the system. Wherein the bandwidth of the photoelectric detector can reach GHz level generally; the analog conditioning circuit can realize the amplification and conditioning of MHz-level signals; the FPGA needs to realize multi-channel synchronous analog-digital conversion and data acquisition, and researches show that the speed can reach 1 MHz. The frame rate of the data communication adopting the gigabit network for transmitting the optical spectrum signal can reach 1.5 MHz. The overall speed of the spectral sampling hardware system can reach 1 MHz.
2. Embodiment of demodulation algorithm
The spectrum data with few sampling points in the graph 4 can be read through various hardware platforms and interface software, and subsequent demodulation calculation can be realized through various software algorithms.
Because the fast Fourier transform has speed advantage in the aspect of frequency estimation algorithm, and the maximum likelihood estimation algorithm has precision advantage, the fast Fourier transform method is firstly used for obtaining a coarse cavity length estimation quantity by combining the fast Fourier transform algorithm and the maximum likelihood estimation algorithm, and then the maximum likelihood estimation method is used for calculating the fine estimation quantity near the coarse estimation quantity. Since the fine estimation is completed in only a small frequency range, the speed of the maximum likelihood method in the fine estimation is greatly improved, so that the demodulation with high speed and high precision can be realized, and a flow chart of the algorithm is shown in fig. 4.
The software algorithm can be realized on a conventional desktop computer, and can also be realized by developing a special high-speed embedded system. The demodulation algorithm speed is expected to be improved to 1MHz through algorithm optimization and multi-step parallel operation.
Finally, it is noted that the above-mentioned preferred embodiments illustrate rather than limit the invention, and that, although the invention has been described in detail with reference to the above-mentioned preferred embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention as defined by the appended claims.
Claims (5)
1. A few-spectrum sampling point high-speed measurement method of a white light interference type optical fiber Fabry-Perot sensor is characterized by comprising the following steps of:
s1: decomposing the output of the optical fiber Fabry-Perot sensor into limited N paths of narrow spectrum signals by using a wavelength division multiplexer, a photoelectric detector group and a high-speed parallel acquisition subsystem, and respectively acquiring and caching the signals;
s2: constructing a noise-free N-path ideal interference spectrum signal, and constructing a probability density function with the difference of the actual signal obtained by S1;
s3: and solving the estimator which maximizes the probability density function so as to obtain the maximum likelihood estimator of the cavity length L and complete the high-speed demodulation of the N spectral sampling data.
2. The few-spectrum sampling point high-speed measurement method according to claim 1, wherein in step S2, the real cosine function form of the ideal interference spectrum signal is:
In＝I0R[1-cos(4πLk)](1)
wherein, I0The light intensity of the light source, k is the central wave number of the wavelength division multiplexer, R is the reflectivity of the reflecting surface of the sensor, and L is the cavity length of the Fabry-Perot sensor.
3. The few-spectrum sampling point high-speed measurement method according to claim 2, wherein in step S2, the probability density function of the interference spectrum signal is:
wherein S isnFor measuring the resulting interference spectral signal, InFor the ideal interference spectrum signal obtained by the formula (1), sigma is the noise variance, N is the independent variable of the spectrum signal, and N is the number of channels of the wavelength division multiplexer and the photoelectric detector group, namely the number of spectrum sampling points.
4. The few-spectrum sampling point high-speed measurement method according to claim 3, wherein in step S3, the maximum likelihood estimator of the cavity length L is:
where g is the maximum likelihood estimate argument, knIs the wavenumber independent variable.
5. The few-spectrum sampling point high-speed measurement method according to any one of claims 1 to 4, characterized in that the method is applied to a high-speed measurement system, and the system comprises a broadband light source, an optical circulator, a wavelength division multiplexer, a photoelectric detector group, a high-speed parallel acquisition subsystem and a data demodulation and calculation subsystem;
the broadband light source, the optical circulator, the wavelength division multiplexer, the photoelectric detector group, the high-speed parallel acquisition subsystem and the data demodulation and calculation subsystem are sequentially connected to form a less-spectrum sampling point demodulation system; the optical fiber Fabry-Perot sensor is connected with the few-spectrum sampling point demodulation system;
the broadband light source is used for providing a high-power stable light source with a wide spectrum and low polarization degree;
the optical circulator is used for transmitting the wide-spectrum optical signal emitted by the light source to the sensor in a single direction, and simultaneously transmitting the interference optical signal returned by the optical fiber Fabry-Perot sensor to the wavelength division multiplexer in a single direction;
the wavelength division multiplexer is used for dividing the wide spectrum interference optical signal returned by the optical fiber Fabry-Perot sensor into N paths of narrow band optical signals with different wavelengths;
the photoelectric detector group consists of N photoelectric detectors matched with the wavelength division multiplexer, and each detector independently receives an optical signal with one wavelength to form N paths of parallel analog electric signal outputs;
the high-speed parallel acquisition subsystem is used for amplifying, filtering and converting N paths of electric signals output by the photoelectric detection group into digital signals, and acquiring and caching the digital signals for demodulation calculation of a subsequent system;
the demodulation calculation subsystem is used for carrying out high-speed processing calculation on the N paths of digital signals to realize high-speed demodulation of the signals.
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