Gaussian fitting based optimal design of aircraft mission success space using multi-objective genetic algorithm

In order to obtain the optimized aircraft design concept which meets the increasingly complex operation environment at the conceptual design stage,System-of-systems(So S)engineering must be considered.This paper proposes a novel optimization method for the design of aircraft Mission Success Space(MSS)based on Gaussian fitting and Genetic Algorithm(GA)in the So S area.First,the concepts in the design and evaluation of MSS are summarized to introduce the Contribution to System-of-Systems(CSS)by using a conventional effectiveness index,Mission Success Rate(MSR).Then,the mathematic modelling of Gaussian fitting technique is noted as the basis of the optimization work.After that,the proposed optimal MSS design is illustrated by the multiobjective optimization process where GA acts as the search tool to find the best solution(via Pareto front).In the case study,a simulation system of penetration mission was built.The simulation results are collected and then processed by two MSS design schemes(contour and neural network)giving the initial variable space to GA optimization.Based on that,the proposed optimization method is implemented under both schemes whose optimal solutions are compared to obtain the final best design in the case study.

Research on Motion Estimation Algorithm of Star Point Based on Nonlinear Gaussian Fitting

The energy distribution model of motion blurred star point is analyzed.The distribution of the star point approximates to a two-dimensional(2 D) Gaussian distribution under degeneration.Two multi-parameter nonlinear Gaussian fitting methods(GFMs) are proposed,and the relationship between fitting parameters and motion blur parameters is analyzed.Estimation of the parameters of motion blur by fitting parameters is calculated to realize the error compensation of the motion blur.The simulation results show the effectiveness and accuracy.

Vision-based Dynamics Monitoring(VDM)for Diagnosing the Variations of Wind Turbine Tower Foundation Conditions

A slight uneven settlement of the foundation may cause the wind turbine to shake,tilt,or even collapse,so it is increasingly necessary to realize remote condition monitoring of the foundations.At present,the wind turbine foundation monitoring system is incomplete.The current monitoring research of the tower foundation is mainly of contact measurements,using acceleration sensors and static-level sensors for monitoring multiple reference points.Such monitoring methods will face some disadvantages,such as the complexity of monitoring deployment,the cost of manpower,and the load effect on the tower structure.To solve above issues,this paper aims to investigate wind turbine tower foundation variation dynamic monitoring based on machine vision.Machine vision monitoring is a kind of noncontact measurement,which helps to realize comprehensive diagnosis of early foundation uneven settlement and loose faults.The FEA model is firstly investigated as the theoretical foundation to investigate the dynamics of the tower foundation.Second,the Gaussian-based vibration detection is adopted by tracking the tower edge points.Finally,a tower structure with distributed foundation support is tested.The modal parameters obtained from the visual measurement are compared with those from the accelerometer,proving the vision method can effectively monitor the issues with tower foundation changes.

Error Thresholds in Single-Peak Gaussian Distributed Fitness Landscapes

Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gausslan distributed random variables to incorporate the effects of the fluctuations of the fitness landscapes （noise of environments） and investigate the concentration distribution and error threshold of quasispecies by performing an ensemble average within this theoretical framework. We find that a small fluctuation of the fitness landscape causes only a slight change in the concentration distribution and error threshold, which implies that the error threshold is stable against small perturbations. However, for a sizable fluctuation, quite different from the previous deterministic models, our statistical results show that the transition from quasi-species to error catastrophe is not so sharp, indicating that the error threshold is located within a certain range and has a shift toward a larger value. Our results are qualitatively in agreement with the experimental data and provide a new implication for antiviral strategies.

Navigation Method Based on Improved Rapid Exploration Random Tree Star-Smart(RRT^(*)-Smart) and Deep Reinforcement Learning

A large number of logistics operations are needed to transport fabric rolls and dye barrels to different positions in printing and dyeing plants, and increasing labor cost is making it difficult for plants to recruit workers to complete manual operations. Artificial intelligence and robotics, which are rapidly evolving, offer potential solutions to this problem. In this paper, a navigation method dedicated to solving the issues of the inability to pass smoothly at corners in practice and local obstacle avoidance is presented. In the system, a Gaussian fitting smoothing rapid exploration random tree star-smart(GFS RRT^(*)-Smart) algorithm is proposed for global path planning and enhances the performance when the robot makes a sharp turn around corners. In local obstacle avoidance, a deep reinforcement learning determiner mixed actor critic(MAC) algorithm is used for obstacle avoidance decisions. The navigation system is implemented in a scaled-down simulation factory.

Influence factors and mechanism of emission of ZnS:Cu nanocrystals

Copper-doped ZnS （ZnS：Cu） nanocrystals are synthesized by the sol-gel method. The average size of the ZnS：Cu nanocrystals is 3.1 nm. The x-ray diffraction indicates that increasing the Cu-dopant concentration results in a large shift in the diffraction angle. The effects of the dopant concentration, the reactant ratio, and aging temperature on the optical properties of the ZnS：Cu nanocrystals are also investigated. The fluorescence emission mechanism is analyzed by peak deconvolution using Gaussian functions. We find that the emission of the ZnS：Cu nanocrystal is composed of different luminescence centers at 430, 470, 490, 526, and 560 nm. The origins of these emissions are discussed and demonstrated by controlled experiments.

Application of Fiber Bragg Grating for Determining Positions of Gas Absorption Lines

Fiber Bragg grating(FBG) is used as a wavelength reference device to calibrate the position of gas absorption peak in the intracavity absorption gas sensor(ICAGS) based on erbium-doped fiberring laser.This system can detect both the reflectance spectrum of FBGs and absorption spectrum of measured gas during a single wavelength sweeping process by linearly varying the driving voltage of optic filter.The voltages corresponding to center wavelength positions of four FBGs in the spectrum are determined through ...

Detection of green apples in natural scenes based on saliency theory and Gaussian curve fitting

Green apple targets are difficult to identify for having similar color with backgrounds such as leaves.The primary goal of this study was to detect green apples in natural scenes by applying saliency detection and Gaussian curve fitting algorithm.Firstly,the image was represented as a close-loop graph with superpixels as nodes.These nodes were ranked based on the similarity to background and foreground queries to generate the final saliency map.Secondly,Gaussian curve fitting was carried out to fit the V-component in YUV color space in salient areas,and a threshold was selected to binarize the image.To verify the validity of the proposed algorithm,55 images were selected and compared with the common used image segmentation algorithms such as k-means clustering algorithm and FCM(Fuzzy C-means clustering algorithm).Four parameters including recognition ratio,FPR(false positive rate),FNR(false negative rate)and FDR(false detection rate)were used to evaluate the results,which were 91.84%,1.36%,8.16%and 4.22%,respectively.The results indicated that it was effective and feasible to apply this method to the detection of green apples in nature scenes.

Vibration properties of low-fraction hydrogen in deuterium ices

Inelastic incoherent neutron scattering spectra of D2O high-density amorphous （hda） ice, ice-Ⅷ and ice-Ⅱ mixed with small amount of H2O （（5%） have been measured recently on high-energy transfer spectrometer at Rutherford Appleton Laboratory （UK）. The hydrogen atom on D2O ice lattices has three distinguished vibrational modes, two bending at low frequencies and one stretching at high frequencies, and their frequencies are slightly different for different phases of ice. It was found that the lower one of the bending modes is located at -95 meⅤ for hda-ice, at -95 meⅤ for ice-Ⅷ and at -96 meⅤ for ice-Ⅱ and they are all lower than the value of 104 meⅤ for ice-Ih. It was also measured that the O-D and O-H covalent bond stretching modes of ice-Ⅷ are at -315 and -425 meⅤ, ice-Ⅱ at 307 and -415 meⅤ, hda-ice at 312 and -418 meⅤ, respectively. They are significantly higher than the values of ice-Ih at -299 and -406 meⅤ, respectively.

Inverse design of mission success space for combat aircraft contribution evaluation

This paper presents a novel design method of the Mission Success Space(MSS) for the evaluation on aircraft contribution effectiveness. MSS concept was proposed for giving success criterion of a mission and judging the success by conventional mission effectiveness with regards to the aircraft capabilities. This space is created by the Mission Success Function(MSF) and the original Effectiveness Index Space(EIS) where empirical equations are usually assumed to be MSFs. Based on this MSS concept, this paper firstly defines the MSS-based evaluation, then further summarizes the evaluation process of the Contribution to System-of-Systems(CSS). More importantly, based on the thought of Inverse Design(ID), a new design method of MSF is presented comprehensively analyzing aircraft's CSS in a combat mission without using any empirical MSF. The definition of MSS based ID is given and the design procedure is sequentially introduced. Two different confrontation cases are depicted with many details as the simulation validation: Air-to-ground and Penetration. There are two design variables considered for designing MSS in the latter case while only one for the former. However, in both cases, the best design is given by evaluating the Gaussian fitting performance of CSS.

A topographic parameter inversion method based on laser altimetry

A topographic parameter inversion method based on laser altimetry is developed in this paper, which can be used to deduce the surface vertical profile and retrieve the topographic parameters within the laser footprints by analyzing and simulating return waveforms. This method comprises three steps. The first step is to build the numerical models for the whole measuring procedure of laser altimetry, construct digital elevation models for surfaces with different topographic parameters, and calculate return waveforms. The second step is to analyze the simulated return waveforms to obtain their characteristics parameters, summarize the effects of the topographic parameter variations on the characteristic parameters of simulated return waveforms, and analyze the observed return waveforms of laser altimeters to acquire their characteristic parameters at the same time. The last step is to match the characteristic parameters of the simulated and observed return waveforms, and deduce the topographic parameters within the laser footprint. This method can be used to retrieve the topographic parameters within the laser footprint from the observed return waveforms of spaceborne laser altimeters and to get knowledge about the surface altitude distribution within the laser footprint other than only getting the height of the surface encountered firstly by the laser beam, which extends laser altimeters' function and makes them more like radars.

Robustness of ventilation systems in the control of walking-induced indoor fluctuations: Method development and case study

Walking-induced fluctuations have a significant influence on indoor airflow and pollutant dispersion.This study developed a method to quantify the robustness of ventilation systems in the control of walking-induced fluctuation control.Experiments were conducted in a full-scale chamber with four different kinds of ventilation systems:ceiling supply and side return(CS),ceiling supply and ceiling return(CC),side supply and ceiling return(SC),and side supply and side return(SS).The measured temperature,flow and pollutant field data was(1)denoised by FFT filtering or wavelet transform;(2)fitted by a Gaussian function;(3)feature-extracted for the range and time scale disturbance;and then(4)used to calculate the range scale and time scale robustness for different ventilation systems with dimensionless equations developed in this study.The selection processes for FFT filtering and wavelet transform,FFT filter cut-off frequency,wavelet function,and decomposition layers are also discussed,as well as the threshold for wavelet denoising,which can be adjusted accordingly if the walking frequency or sampling frequency differs from that in other studies.The results show that for the flow and pollutant fields,the use of a ventilation system can increase the range scale robustness by 19.7%-39.4% and 10.0%-38.8%,respectively;and the SS system was 7.0%-25.7% more robust than the other three ventilation systems.However,all four kinds of ventilation systems had a very limited effect in controlling the time scale disturbance.

Study on low noise cryogenic charge readout electronics for liquid xenon time projection chamber

Background Liquid xenon time projection chamber(LXe TPC)is widely used in high-energy physics experiments such as particle detection and neutrino(or neutrinoless)double beta decay.The charge readout accuracy of the LXeTPCdirectly affects the measurement results and success of the experiments.Because liquid xenon needs to maintain a cryogenic temperature between 162 and 165 K at atmospheric pressure,the charge generated in the LXe TPC always needs to be read out in the cryogenic environment for minimizing the input capacitance,which has effect in determining the output noise of the charge amplifier.Purpose Design a charge readout electronics system applicable to LXe TPC and research a data analysis method to get the exact amount of charge by analyzing the waveform at that output of the designed electronics system.Methods Design a multi-channel charge-reading application specific integrated circuit(ASIC)that can operate in the cryogenic environment.The signals and power supply of the ASIC are connected to an electronics system at room temperature through micro-coaxial cables.The electronics at room temperature complete the sampling of the ASIC output.A data acquisition device receives the sampled waveform data and calculates the charge measurement resolution by Gaussian fitting.Results The designed ASIC and selected micro-coaxial cable can work in stable condition under the cryogenic environment of 165 K.The analyzed integral nonlinearity of the charge measurement of the chip is 0.83%in the range from 1 to 50 fC,and the charge measurement resolution of the chip is lower than 900 e−RMS.Conclusion In this paper,a preliminary study of the charge readout method based on the system structure of self-developed ASIC,micro-coaxial cable,and data readout electronics is completed for LXe TPC.The system test results indicate that the designed ASIC can work normally in the cryogenic temperature of 165 K with a high dynamic range and good linearity of the charge measurement.Further work can be done to reduce the charge measurement resolution of the system to 200 e−RMS.

A Comprehensive Method to Reject Detection Outliers by Combining Template Descriptor with Sparse 3D Point Clouds

We are using a template descriptor on the image in order to try and find the object. However, we have a sparse 3D point clouds of the world that is not used at all when looking for the object in the images. Considering there are many false alarms during the detection, we are interested in exploring how to combine the detections on the image with the 3D point clouds in order to reject some detection outliers. In this experiment we use semi-direct-monocular visual odometry (SVO) to provide 3D points coordinates and camera poses to project 3D points to 2D image coordinates. By un-projecting points in the tracking on the selection tree (TST) detection box back to 3D space, we can use 3D Gaussian ellipsoid fitting to determine object scales. By ruling out different scales of detected objects, we can reject most of the detection outliers of the object. © 2017, Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg.