- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Macao, Macao (2019.12.1-2019.12.4)] 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Photovoltaic System Performance Model for Output Power Forecasting
摘要： This paper addresses the application of rotor speed signal for the detection and diagnosis of ball bearing faults in rotating electrical machines. Many existing techniques for bearing fault diagnosis (BFD) rely on vibration signals or current signals. However, vibration- or current-based BFD techniques suffer from various challenges that must be addressed. As an alternative, this paper takes the initial step of investigating the efficiency of rotor speed monitoring for BFD. The bearing failure modes are reviewed and their effects on the rotor speed signal are described. Based on this analysis, a novel BFD technique, the rotor speed-based BFD (RSB-BFD) method under variable speed and constant load conditions, is proposed to provide a benefit in terms of cost and simplicity. The proposed RSB-BFD method exploits the absolute value-based principal component analysis (PCA), which improves the performance of classical PCA by using the absolute value of weights and the sum square error. The performance and effectiveness of the RSB-BFD method is demonstrated using an experimental setup with a set of realistic bearing faults in the outer race, inner race, and balls.
关键词： principal component analysis (PCA),Bearing fault diagnosis (BFD),sum square error,variable speed,rotor speed
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE SENSORS - Montreal, QC, Canada (2019.10.27-2019.10.30)] 2019 IEEE SENSORS - AC/DC Millivoltage Sensor by means of ITO-coated Optical Fibers: Towards Monitoring of Biosignals
摘要： Reducing the capacitance of programmable capacitor arrays (PCAs), commonly used in analog integrated circuits, is necessary for low-energy applications. However, limited mismatch data are available for small capacitors. We report mismatch measurement for a 2-fF poly–insulator–poly (PIP) capacitor, which is the smallest reported PIP capacitor to the best of the authors’ knowledge. Instead of using complicated custom on-chip circuitry, direct mismatch measurement is demonstrated and veri?ed using Monte Carlo simulations and experimental measurements. Capacitive test structures composed of 9-bit PCAs are implemented in a low-cost 0.35-μm CMOS process. Measured data are compared to the mismatch of large PIP capacitors, theoretical models, and recently published data. Measurement results indicate an estimated average relative standard deviation of 0.43% for the 2-fF unit capacitor, which is better than the reported mismatch of metal–oxide–metal (MOM) fringing capacitors implemented in an advanced 32-nm CMOS process.
关键词： programmable capacitor array (PCA),capacitor mismatch,mismatch characterization,energy-ef?cient circuits,Analog-to-digital converter (ADC),capacitance-to-digital converter (CDC)
更新于2025-09-23 15:19:57
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Electric field-induced linear electro-optic effect observed in silicon-organic hybrid ring resonator
摘要： Reducing the capacitance of programmable capacitor arrays (PCAs), commonly used in analog integrated circuits, is necessary for low-energy applications. However, limited mismatch data are available for small capacitors. We report mismatch measurement for a 2-fF poly–insulator–poly (PIP) capacitor, which is the smallest reported PIP capacitor to the best of the authors’ knowledge. Instead of using complicated custom on-chip circuitry, direct mismatch measurement is demonstrated and veri?ed using Monte Carlo simulations and experimental measurements. Capacitive test structures composed of 9-bit PCAs are implemented in a low-cost 0.35-μm CMOS process. Measured data are compared to the mismatch of large PIP capacitors, theoretical models, and recently published data. Measurement results indicate an estimated average relative standard deviation of 0.43% for the 2-fF unit capacitor, which is better than the reported mismatch of metal–oxide–metal (MOM) fringing capacitors implemented in an advanced 32-nm CMOS process.
关键词： programmable capacitor array (PCA),Analog-to-digital converter (ADC),energy-ef?cient circuits,mismatch characterization,capacitance-to-digital converter (CDC),capacitor mismatch
更新于2025-09-23 15:19:57
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Synchrotron infrared spectral regions as signatures for foodborne bacterial typing
摘要： Fourier-transform infrared (FTIR) spectroscopy has emerged as a viable alternative to biochemical and molecular biology techniques for bacterial typing with advantages such as short analysis time, low cost and laboratorial simplicity. In this study, synchrotron radiation-based FTIR (SR-FTIR) spectroscopy with higher spectral quality was successfully applied to type 16 foodborne pathogenic bacterial strains. Combined with principal component analysis (PCA) and hierarchical cluster analysis (HCA), we found that the specific spectral region 1300–1000 cm-1, which reflects the information of phosphate compounds and polysaccharides, can be used as the signature region to cluster the strains into groups similar with genetic taxonomic method. These findings demonstrated that FTIR spectra combined with HCA have a great potential in quickly typing bacteria depending on their biochemical signatures.
关键词： FTIR,PCA,Bacterial typing,Spectral signature,HCA,Synchrotron radiation
更新于2025-09-19 17:15:36
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Rapid identification of wood species by near-infrared spatially resolved spectroscopy (NIR-SRS) based on hyperspectral imaging (HSI)
摘要： Conventional near-infrared (NIR) spectroscopy has shown its potential to separate wood species non-destructively based on the aggregate effect of light absorption and scattering values. However, wood has an aligned microstructure, and there is a large refractive index (RI) mismatch between the wood cell wall substance (n≈1.55) and the cell lumen (air≈1.0, water≈1.33). Light scattering is dominant over absorption μ′ (cid:31)( ) a in wood, and this fact can be utilized for complex classification purposes. In this study, an NIR hyperspectral imaging (HSI) camera combined with one focused halogen light source (? 1 mm) was designed to evaluate the light scattering patterns of five softwood (SW) and 10 hardwood (HW) species in the wavelength range from 1002 to 2130 nm. Several parameters were combined to improve the data quality, such as image histogram plots of defined spaced bins (associated with diffuse reflectance values of light), variance calculation on the frequency (the number of pixels in each bin) of each histogram and the principal component analysis (PCA) of all the variance values at each wavelength. The identification accuracy of the quadratic discriminant analysis (QDA) under the five-fold cross-validation method was 94.1%, based on the first three principal component (PC) scores.
关键词： spatially resolved spectroscopy,light scattering characteristics,wood species identification,hardwood,quadratic discriminant analysis (QDA),near-infrared hyperspectral imaging camera,principal component analysis (PCA),softwood,halogen spot-light source
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE Research and Applications of Photonics in Defense Conference (RAPID) - Miramar Beach, FL, USA (2019.8.19-2019.8.21)] 2019 IEEE Research and Applications of Photonics in Defense Conference (RAPID) - Invited Talk: "High Resolution Space/Time Imaging of Shockwaves Generated by Remote Laser Plasmas Produced by Light Filaments"
摘要： In this paper, we approach the problem of forecasting a time series (TS) of an electrical load measured on the Azienda Comunale Energia e Ambiente (ACEA) power grid, the company managing the electricity distribution in Rome, Italy, with an echo state network (ESN) considering two different leading times of 10 min and 1 day. We use a standard approach for predicting the load in the next 10 min, while, for a forecast horizon of one day, we represent the data with a high-dimensional multi-variate TS, where the number of variables is equivalent to the quantity of measurements registered in a day. Through the orthogonal transformation returned by PCA decomposition, we reduce the dimensionality of the TS to a lower number k of distinct variables; this allows us to cast the original prediction problem in k different one-step ahead predictions. The overall forecast can be effectively managed by k distinct prediction models, whose outputs are combined together to obtain the final result. We employ a genetic algorithm for tuning the parameters of the ESN and compare its prediction accuracy with a standard autoregressive integrated moving average model.
关键词： PCA,dimensionality reduction,electric load prediction,smart grid,genetic algorithm,forecasting,echo state network,Time-series
更新于2025-09-19 17:13:59
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Near-Field Radio Holography of Slant-Axis Terahertz Antennas
摘要： Principal component analysis (PCA) and independent component analysis (ICA) for radiated emissions from printed circuits are critically intercompared, revealing similarities and differences of the extracted components between both methods. The input data in this analysis are measured wideband complex-valued magnetic radiated and evanescent fields with quasi-Gaussian spatial distributions. PCA and ICA lead to similar maps of their components when considered as spatial eigenmodes, but independent components exhibit simpler field structure than principal components.
关键词： stochastic fields,principal component analysis (PCA),uncertainty quantification,Independent component analysis (ICA),radiated emissions
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Impact of Transportation on Indian Roads, on PV Modules
摘要： This paper addresses the application of rotor speed signal for the detection and diagnosis of ball bearing faults in rotating electrical machines. Many existing techniques for bearing fault diagnosis (BFD) rely on vibration signals or current signals. However, vibration- or current-based BFD techniques suffer from various challenges that must be addressed. As an alternative, this paper takes the initial step of investigating the efficiency of rotor speed monitoring for BFD. The bearing failure modes are reviewed and their effects on the rotor speed signal are described. Based on this analysis, a novel BFD technique, the rotor speed-based BFD (RSB-BFD) method under variable speed and constant load conditions, is proposed to provide a benefit in terms of cost and simplicity. The proposed RSB-BFD method exploits the absolute value-based principal component analysis (PCA), which improves the performance of classical PCA by using the absolute value of weights and the sum square error. The performance and effectiveness of the RSB-BFD method is demonstrated using an experimental setup with a set of realistic bearing faults in the outer race, inner race, and balls.
关键词： principal component analysis (PCA),rotor speed,sum square error,Bearing fault diagnosis (BFD),variable speed
更新于2025-09-19 17:13:59
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Laser-Induced Breakdown Spectroscopy and Principal Component Analysis for Classification of Spectra from Gold-Bearing Ores
摘要： Laser-induced breakdown spectroscopy (LIBS) and principal component analysis (PCA) were applied to the classification of LIBS spectra from gold ores prepared as pressed pellets from pulverized bulk samples. Obtained for each sample were 5000 single-shot LIBS spectra. Although the gold concentrations in the samples were as high as 7.7 μg/g, Au emission lines were not observed in most single-shot LIBS spectra, rendering infeasible the application of the usual ensemble-averaging approach for spectral processing. Instead, a PCA approach was utilized to analyze the collection of single-shot LIBS spectra. Two spectral ranges of 21 nm and 0.15 nm wide were considered, and LIBS variables (i.e., wavelengths) reduced to no more than three principal components. Single-shot spectra containing Au emission lines (positive spectra) were discriminated by PCA from those without the spectral feature (negative spectra) in a spectral range of less than 1 nm wide around the Au(I) 267.59 nm emission line. Assuming a discrete gold distribution at very low concentration, LIBS sampling of gold particles seemed unlikely, therefore, positive spectra were considered as data outliers. Detection of data outliers was possible using two PCA statistical parameters, i.e., sample residual and Mahalanobis distance. Results from such a classification were compared with a standard database created with positive spectra identified with a filtering algorithm that rejected spectra with an Au intensity below the smallest detectable analytical LIBS signal (i.e., below the LIBS limit of detection). The PCA approach successfully identified 100% of the data outliers when compared with the standard database. False identifications in the multivariate approach were attributed to variations in shot-to-shot intensity and the presence of interfering emission lines.
关键词： gold ores analysis,Laser-induced breakdown spectroscopy,PCA,data outliers,principal component analysis,LIBS
更新于2025-09-19 17:13:59
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Laser-induced fluorescence spectroscopy for early disease detection in grapefruit plants
摘要： Both biotic and abiotic stress causes considerable decrease in chlorophyll content in plant leaves which provide the means of early disease diagnosis. The emergence of disease affects the fluorescence of phenolic compounds and chlorophyll which have been appeared at 530, 686 and 735 nm. It has been found that the intensity of emission band of phenolic compounds at 530 nm increases and that of chlorophyll at 735 nm decreases with the onset of disease. Statistical analysis through principal component analysis (PCA) and partial least square regression (PLSR) has been performed which demonstrated the classification of apparently healthy leaf sites with diseased ones which provide the basis for the detection of disease at early stages. PLSR model was validated through the coefficient of determination (R2), standard error of prediction (SEP) and standard error of calibration (SEC) with the values 0.99, 0.394 and 0.401 which authenticated the model. The prediction accuracy of the model was evaluated through root mean square error in prediction (RMSEP) of 0.14 by predicting 22 unknown emission spectra of different leaf sites. Both PCA and PLSR models produced similar results and proved fluorescence spectroscopy as an excellent tool for early disease detection in plants.
关键词： Early disease diagnosis,Principal component analysis (PCA),Chlorophyll fluorescence,Partial least square regression (PLSR),Phenolic compounds
更新于2025-09-19 17:13:59