- 标题
- 摘要
- 关键词
- 实验方案
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FPGA-Based Implementation of an Artificial Neural Network for Measurement Acceleration in BOTDA Sensors
摘要： In recent years, using distributed fiber-optic sensors based on Brillouin scattering, for monitoring pipelines, tunnels, and other constructional structures have gained huge popularity. However, these sensors have a low signal-to-noise ratio (SNR), which usually increases their measurement error. To alleviate this issue, ensemble averaging is used which improves the SNR but in return increases the measurement time. Reducing the noise by averaging requires hundreds or thousands of scans of the optical fiber; hence averaging is usually responsible for a large percent of the entire system latency. In this paper, we propose a novel method based on artificial neural network for SNR enhancement and measurement acceleration in distributed fiber-optic sensors based on the Brillouin scattering. Our method takes the noisy Brillouin spectrums and improves their SNR by 20 dB, which reduces the measurement time significantly. It also improves the accuracy of the Brillouin frequency shift estimation process and its latency by more than 50% in comparison with the state-of-the-art software and hardware solutions.
关键词： Artificial neural network (ANN),digital signal processing,optical fibers,curve fitting,field-programmable gate arrays (FPGAs)
更新于2025-09-23 15:23:52
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Optimization of cleaning frequency and dust accumulation effect on photovoltaic panels
摘要： This Paper introduces a relation between Cleaning Intervals (m), Annual Energy Losses loss(m), Annual Cleaning Cost Ccl(m) and the Total Annual Cost Ct(m) in the PV system. Cost cE As the Dust accumulation reduces the solar transmittance of PV modules subsequently the PV modules will be affected negatively so this work is carried out to investigate the optimum cleaning frequency of PV modules cleaning through monitoring the soiling loss, soiling modeling was obtained in detail. Studying the effect of soiling density on angle of incidence (AOI) based on the obtained soiling rate and cleaning PV scenarios was also investigated with same steps. The main goal behind this study was to compare between the Annual Cleaning Cost and the Annual Energy Losses Cost to meet the optimized Cleaning rate with the minimum Energy Losses and Cost.
关键词： Dust Accumulation,Optimum Interval Energy and Cost Curve Fitting,Photovoltaic,Cleaning Frequency
更新于2025-09-23 15:19:57
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[IEEE 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) - Chongqing, China (2018.10.12-2018.10.14)] 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) - Study on diaphragm Fabry-Perot pressure sensor
摘要： The manufacture method of the diaphragm Fabry-Perot(F-P) pressure sensor was studied. The sensor formed an F-P cavity by welding the hollow fiber on the end face of the single mode fiber, and manufactured a quartz diaphragm by cutting and grinding the single mode fiber. A new fitting demodulation method is proposed, which can obtain the FP cavity’s reflectivity, the diaphragm’s outside reflectivity, the F-P cavity length and the diaphragm thickness at one time. It is highly practical for the parameter monitoring in the sensor manufacturing process. Experiments show that the sensor has high sensitivity and linearity, and has great potential application value in the field of fluid mechanics measurement.
关键词： fiber optics,curve fitting,Pressure measurement,F-P interferometer,fiber sensor
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - Sozopol, Bulgaria (2019.9.6-2019.9.8)] 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - Monte Carlo Evaluation of the Uncertainty in a Calibrated Instrument
摘要： A Monte Carlo procedure is presented for computing the joint state-of-knowledge probability distribution to be assigned to the parameters of a calibration function. The procedure is fully in line with the approach in Supplement 1 to the Guide to the Expression of Uncertainty in Measurement. It consists of propagating the joint probability distribution of the calibration quantities through the mathematical model of the measurement by which the parameters are defined. Usually this model is derived from a least-squares adjustment procedure. When the instrument is in use, we desire to obtain the probability distribution for the stimulus that corresponds to an indicated response. This goal can be accomplished by propagating the distributions for the parameters of the calibration curve, together with the distribution of the indicated response.
关键词： calibration functions,probability distributions,curve fitting,Monte Carlo method
更新于2025-09-19 17:13:59
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Low Complexity Dimensioning of Sustainable Solar-enabled Systems: A Case of Base Station
摘要： Solar-enabled systems are becoming popular for provisioning pollution-free and cost-effective energy solution. Dimensioning of a solar-enabled system requires estimation of appropriate size of photovoltaic (PV) panel as well as storage capacity while satisfying a given energy outage constraint. Dimensioning has strong impact on the user’s quality of experience and network operator’s interest in terms of energy outage and revenue. In this paper, dimensioning problem of solar-enabled communication nodes is analyzed in order to reduce the computation overhead, where stand-alone solar-enabled base station (SS-BS) is considered as a case study. For this purpose, hourly solar data of last ten years has been taken into consideration for analysis. First, the power consumption model of BS is revised to save energy and increase revenue. Using the hourly solar data and power consumption profile, the lower bounds on panel size and storage capacity are obtained using Gaussian mixture model, which provides a reduced search space for cost-optimal system dimensioning. Then, the cost function and energy outage probability are modeled as functions of panel size and number of battery units using curve fitting technique. The cost function is proven to be quasiconvex, whereas energy outage probability is proven to be convex function of panel size and number of battery units. These properties transform the cost-optimal dimensioning problem into a convex optimization framework, which ensures a global optimal solution. Finally, a Computationally-efficient Energy outage aware Cost-optimal Dimensioning Algorithm (CECoDA) is proposed to estimate the system dimension without requiring exhaustive search. The proposed framework is tested and validated on solar data of several cities; for illustration purpose, four cities, New Delhi, Itanagar, Las Vegas, and Kansas, located at diverse geographical regions, are considered. It is demonstrated that, the presented optimization framework determines the system dimension accurately, while reducing the computational overhead up to 94% and the associated energy requirement for computation with respect to the exhaustive search method used in the existing approaches. The proposed framework CECoDA takes advantage of the location-dependent unique solar profile, thereby achieving cost-efficient solar-enabled system design in significantly less time.
关键词： computation efficiency,cost-optimal system dimensioning,Sustainable solar-enabled system,solar energy harvesting,energy outage,Gaussian mixture model,convex optimization,curve fitting
更新于2025-09-12 10:27:22
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[IEEE 2018 17th International Conference on Ground Penetrating Radar (GPR) - Rapperswil, Switzerland (2018.6.18-2018.6.21)] 2018 17th International Conference on Ground Penetrating Radar (GPR) - Structural Planes Parameters Extraction Method Based on Borehole Digital Optical Image and GPR
摘要： This paper combines the borehole ground penetrating radar imaging and digital optical borehole imaging, presents an efficient method to recognize and extract the structural planes parameters of rock mass. In this method, it’s necessary to transform the digital optical image in color modeling. Processing such as segmentation and edge refinement are essential steps. Afterwards, matching algorithm is employed by using a transform of sinusoidal curve to extract the fitting parameters. Finally, the image feature data acquired by the borehole GPR image is integrated for verification. With this method, the physical and geometrical characteristics of the rock mass at and around the borehole can be revealed. It can effectively exert the respective characteristics of the two exploration technologies to identify the structural planes in a continuous and rapid way. It has proven highly reliable and efficient.
关键词： structural plane,curve fitting algorithm,borehole digital optical image,identification,borehole GPR image
更新于2025-09-09 09:28:46
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Membership Function-Weighted Non-Linear Fitting Method for Optical-Sensing Modeling and Reconstruction
摘要： Imprecise measurements present universally due to variability in the measurement error. We devised a very simple membership function to evaluate fuzzily the quality of optical sensing with a small dataset, where a normal distribution cannot be assumed. The proposed membership function was further used as a weighting function for non-linear curve fitting under expected mathematical model constraints, namely the membership function-weighted Levenberg–Marquardt (MFW-LM) algorithm. The robustness and effectiveness of the MFW-LM algorithm were demonstrated by an optical-sensing simulation and two practical applications. (1) In laser-absorption spectroscopy, molecular spectral line modeling was greatly improved by the method. The measurement uncertainty of temperature and pressure were reduced dramatically, by 53.3% and 43.5%, respectively, compared with the original method. (2) In imaging, a laser beam-profile reconstruction from heavy distorted observations was improved by the method. As the dynamic range of the infrared camera increased from 256 to 415, the detailed resolution of the laser-beam profiles increased by an amazing 360%, achieving high dynamic-range imaging to capture optical signal details. Therefore, the MFW-LM algorithm provides a robust and effective tool for fitting a proper physical model and precision parameters from low-quality data.
关键词： non-linear curve fitting,sensing modeling and reconstruction,image reconstruction-restoration,optical-sensing signal processing,laser-absorption spectroscopy
更新于2025-09-09 09:28:46
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Sugar Contents and Firmness of Apples Based on Multi-Spectral Imaging Technology
摘要： The paper proposed a prediction method of apple sugar content and firmness based on multi-spectral imaging. Firstly, four characteristic wavelengths (670, 750, 780 and 810 nm) were selected by correlation coefficient method. The gray images of samples at different wavelengths were collected by multi-spectral imaging system, then fitted with Lorenz function, modified Lorenz function, Gaussian function and polynomial function, respectively. It was found that the fitting effect of modified Lorenz function was best. Therefore, the experiment was performed by multiple linear regression and partial least square regression analysis of sugar content and firmness with the fitting parameters of modified Lorenz function. The result showed that the prediction of multiple linear regression model was better than partial least squares regression model. The modeling correction correlation coefficient, calibration standard deviation, the prediction correlation coefficient and predicted standard deviation of sugar content were 0.8568, 0.6736, 0.8395 and 0.7068, respectively. The modeling correction correlation coefficient, calibration standard deviation, the prediction correlation coefficient and the predicted standard deviation of firmness were 0.8660, 0.3275, 0.8407 and 0.3555, respectively. The results also showed that this method was feasible for the prediction of apple sugar content and firmness.
关键词： Firmness,Multi-spectral imaging,Curve fitting,Apple,Multiple linear regression,Sugar content
更新于2025-09-04 15:30:14