- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 IEEE SENSORS - New Delhi, India (2018.10.28-2018.10.31)] 2018 IEEE SENSORS - Structural Shape Estimation by Mode Shapes Using Fiber Bragg Grating Sensors: A Genetic Algorithm Approach
摘要： Structural shape estimation is of great interest in many engineering fields. During operation, however, the monitoring of structural displacements is often difficult. This article discuss structural shape estimation using a minimal number of fiber Bragg grating sensors. A strain to displacement transformation matrix is derived using mode shapes, to estimate the global displacement of a structure from measured discrete strain data. The number of sensors and sensor layout for the shape estimation is optimized using genetic algorithm. Static and dynamic displacement experiments are conducted to verify the algorithm. The results show that the estimated displacements match well with those measured displacements.
关键词： Fiber Bragg Grating,Mode shapes,Genetic Algorithm,Sensor,Shape estimation
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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[IEEE 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG) - Sonderborg, Denmark (2019.4.23-2019.4.25)] 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG) - An AN-GA Controlled SEPIC Converter for Photovoltaic Grid Integration
摘要： In this paper, Artificial Neural Network (ANN) optimization with Genetic Algorithm (GA) is implemented. The optimized training to ANN is provide using Bayesian regulation. For this study, a Photovoltaic (PV) system has considered and optimal power tracking been interpreted with proper adjustment of ANN weights using GA approach, which reduces the Root Mean Square Error (RMSE). In this work, the single-ended primary – inductor converter (SEPIC) has been utilized for better power tracking from PV modules. SEPIC Converter accomplish with impedance matching power device and provides utmost PV power tracking. Space vector pulse width modulation-dSPACE interface been utilized as an inverter control. Simulated responses show the potency of the proposed system under sag, swell and varying loading conditions.
关键词： Root Mean Square Error (RMSE),SEPIC.,Grid,Photovoltaic,Artificial neural network (ANN),Genetic Algorithm (GA)
更新于2025-09-19 17:13:59
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[IEEE 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC) - Fukuoka, Japan (2019.7.7-2019.7.11)] 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC) - High-speed RF interconnects beyond 67 GHz in InP photonic integration technology
摘要： Mixed-signal system-on-chip (SoC) devices offer single-chip solutions, but face challenges of hardware-software co-design optimization, device signal range constraints, and limited precision. These issues are addressed by developing a multi-level evolutionary approach to realize complex computational circuits called Embedded-Cascaded Hierarchically Evolved Logic Output Networks (ECHELON). The ECHELON technique utilizes analog evolved building blocks and refines their output using digital fabric to compose power series expansions of transcendental functions which are all routed under intrinsic control on a field-programmable SoC (PSoC). The result for the evolution of seven different powers of the independent variable is a reduction of 31.24% in the overall error as compared to the analog circuits that produce the raw inputs to a differential digital correction phase. Computation blocks developed on a Cypress PSoC-5LP mixed-signal SoC reduced error in the final mathematical approximation to the range of 40–150 mV. In doing so, speedups of roughly 1.4-fold to 6.6-fold with an average of 2.72-fold reduction in function execution times were attained. In particular, this approach achieved a 41.7-fold reduction in error with respect to the largest power of the independent variable used as an input to compute an er(x) function.
关键词： genetic algorithm,programmable logic device,Programmable system on chip (PSoC),power series
更新于2025-09-19 17:13:59
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Towards a Sub-9 fs, 3 mJ, CEP-Stable Multipass Ti:Sapphire Amplifier
摘要： A Taguchi-based genetic algorithm (TBGA) is adopted in an adaptive neuro-fuzzy inference system (ANFIS) to optimize the micro-structure parameters of backlight modules (BLMs) in liquid-crystal displays. The method reduces the number of experiments and accumulates the data that indicate performance quality of the modules. The TBGA selects appropriate membership functions and optimizes the premise and consequent parameters by minimizing the performance criterion of root-mean-squared error. The results indicate that the ANFIS with TBGA is significantly superior to ANFIS with particle swarm optimization, ANFIS with GA, and conventional ANFIS for designing the BLM model. Another role of the TBGA is optimizing micro-structure parameters for the backlight module. The results confirm excellent outcome of the TBGA-based ANFIS approach in terms of prediction accuracy, cost reduction, and luminance uniformity. Far more superior results were obtained when compared with those reported in the literature using conventional trial-and-error design methods and even Taguchi-based design methods. Fuzzy model in nature, our approach is applicable generally to industrial product designs and, thus, offers an effective route to solving problems in various industries.
关键词： backlight module,micro-structure parameter,Taguchi genetic algorithm,Adaptive network fuzzy inference system
更新于2025-09-19 17:13:59
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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) - Interval Methods for Data Fitting Under Imprecision and Uncertainty
摘要： An intelligent hybrid Taguchi-genetic algorithm (IHTGA) is used to optimize bearing offsets and shaft alignment in a marine vessel propulsion system. The objectives are to minimize normal shaft stress and shear force. The constraints are permissible reaction force, bearing stress, shear force, and bending moment in the shaft thrust ?ange under cold and hot operating conditions. Accurate alignment of the shaft for a main propulsion system is important for ensuring the safe operation of a vessel. To obtain a set of acceptable forces and stresses for the bearings and shaft under operating conditions, the optimal bearing offsets must be determined. Instead of the time-consuming classical local search methods with some trial-and-error procedures used in most shipyards to optimize bearing offsets, this paper used IHTGA. The proposed IHTGA performs Taguchi method between the crossover operation of the conventional GA. Incorporating the systematic reasoning ability of Taguchi method in the crossover operation enables intelligent selection of genes used to achieve crossover, which enhances the performance of the IHTGA in terms of robustness, statistical performance, and convergence speed. A penalty function method is performed using the ?tness function as a pseudo-objective function comprising a linear combination of design objectives and constraints. A ?nite-element method is also used to determine the reaction forces and stresses in the bearings and to determine normal stresses, bending moments, and shear forces in the shaft. Computational experiments in a 2200 TEU container vessel show that the results obtained by the proposed IHTGA are signi?cantly better than those obtained by the conventional local search methods with some trial-and-error procedures.
关键词： genetic algorithm,shaft alignment,Marine vessel propulsion system,bearing offsets,optimal design
更新于2025-09-19 17:13:59
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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) - Asymmetric and astigmatic laser beams with orbital angular momentum : (Invited)
摘要： An intelligent hybrid Taguchi-genetic algorithm (IHTGA) is used to optimize bearing offsets and shaft alignment in a marine vessel propulsion system. The objectives are to minimize normal shaft stress and shear force. The constraints are permissible reaction force, bearing stress, shear force, and bending moment in the shaft thrust ?ange under cold and hot operating conditions. Accurate alignment of the shaft for a main propulsion system is important for ensuring the safe operation of a vessel. To obtain a set of acceptable forces and stresses for the bearings and shaft under operating conditions, the optimal bearing offsets must be determined. Instead of the time-consuming classical local search methods with some trial-and-error procedures used in most shipyards to optimize bearing offsets, this paper used IHTGA. The proposed IHTGA performs Taguchi method between the crossover operation of the conventional GA. Incorporating the systematic reasoning ability of Taguchi method in the crossover operation enables intelligent selection of genes used to achieve crossover, which enhances the performance of the IHTGA in terms of robustness, statistical performance, and convergence speed. A penalty function method is performed using the ?tness function as a pseudo-objective function comprising a linear combination of design objectives and constraints. A ?nite-element method is also used to determine the reaction forces and stresses in the bearings and to determine normal stresses, bending moments, and shear forces in the shaft. Computational experiments in a 2200 TEU container vessel show that the results obtained by the proposed IHTGA are signi?cantly better than those obtained by the conventional local search methods with some trial-and-error procedures.
关键词： genetic algorithm,shaft alignment,Marine vessel propulsion system,bearing offsets,optimal design
更新于2025-09-19 17:13:59
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[IEEE 2019 16th China International Forum on Solid State Lighting & 2019 International Forum on Wide Bandgap Semiconductors China (SSLChina: IFWS) - Shenzhen, China (2019.11.25-2019.11.27)] 2019 16th China International Forum on Solid State Lighting & 2019 International Forum on Wide Bandgap Semiconductors China (SSLChina: IFWS) - Research on a Smart LED Lighting Based on Improved Flyback Driver
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： genetic algorithm,forecasting,PCA,echo state network,Time-series,smart grid,electric load prediction,dimensionality reduction
更新于2025-09-19 17:13:59
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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) - Airy Pulse Transformation by an Accelerated Medium Boundary
摘要： Mixed-signal system-on-chip (SoC) devices offer single-chip solutions, but face challenges of hardware-software co-design optimization, device signal range constraints, and limited precision. These issues are addressed by developing a multi-level evolutionary approach to realize complex computational circuits called Embedded-Cascaded Hierarchically Evolved Logic Output Networks (ECHELON). The ECHELON technique utilizes analog evolved building blocks and re?nes their output using digital fabric to compose power series expansions of transcendental functions which are all routed under intrinsic control on a ?eld-programmable SoC (PSoC). The result for the evolution of seven different powers of the independent variable is a reduction of 31.24% in the overall error as compared to the analog circuits that produce the raw inputs to a differential digital correction phase. Computation blocks developed on a Cypress PSoC-5LP mixed-signal SoC reduced error in the ?nal mathematical approximation to the range of 40–150 mV. In doing so, speedups of roughly 1.4-fold to 6.6-fold with an average of 2.72-fold reduction in function execution times were attained. In particular, this approach achieved a 41.7-fold reduction in error with respect to the largest power of the independent variable used as an input to compute an er(cid:102)(x) function.
关键词： Programmable system on chip (PSoC),programmable logic device,genetic algorithm,power series
更新于2025-09-19 17:13:59
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[IEEE 2019 4th International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT) - Sao Paulo, Brazil (2019.8.26-2019.8.30)] 2019 4th International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT) - Normalized Spectral Responsivity Measurement of Photodiode by Direct Method Using a Supercontinuum Laser Source
摘要： A Taguchi-based-genetic algorithm (TBGA) is used in an adaptive neuro-fuzzy inference system (ANFIS) to optimize design parameters for surface acoustic wave (SAW) gas sensors. The Taguchi method is used to reduce the number of experiments and collect performance data for an SAW gas sensor. The TBGA has two optimization roles. In the ANFIS, the TBGA selects appropriate membership functions and optimizes both the premise and the consequent parameters by minimizing the performance criterion of the root mean squared error. Another role of the TBGA is optimizing design parameters for an SAW gas sensor. Simulated experimental application of the proposed TBGA-based ANFIS approach showed that, in terms of both resonant frequency shift and precision performance, this systematic design approach obtains far superior results compared with the conventional trial-and-error design methods and other Taguchi-based design methods.
关键词： Adaptive network fuzzy inference system,Taguchi-genetic algorithm,surface acoustic wave (SAW) gas sensors
更新于2025-09-19 17:13:59