The Application of Adaptive Kalman Filter Technology in Aspheric Surface Machining and Detection

2012 ◽  
Vol 192 ◽  
pp. 42-45
Author(s):  
Xue Chen Zhang ◽  
Guo Hua Cao ◽  
Feng Ming Nie
Keyword(s):  
Random Error ◽  
Simulation Analysis ◽  
Processing Technique ◽  
Second Order ◽  
Recursive Identification ◽  
Surface Element ◽  
Machining Parameters ◽  
Aspheric Surface ◽  
Online Detection ◽  
Stationary Characteristic

The grinding machining parameters of large-caliber aspherics ultra-precision grinding processing depend on the analysis of online profile accuracy detection data .and the detection data has the second order of non-stationary characteristic . The research of second order of non-stationary data processing technique and isolate and reduce the random error of online detection data is key technology of ensure the precision of aspheric surface grinding accuracy . This paper proposed a parallel recursive identification of improved adaptive kalman filtering method , the simulation analysis and φ500mm aspheric surface element grinding experiment proved this method can real-time process second order of non-stationary data of online detection data , isolate and reduce the random error , make a best estimate of time-varying signal, provide correction parameter of grinding process , processed aspherical face proflie accuracy≤4μm.

NSCT and focus measure optimization based multi-focus image fusion

2021 ◽  
pp. 1-13
Author(s):  
N. Aishwarya ◽  
C. BennilaThangammal ◽  
N.G. Praveena
Keyword(s):  
Simulation Analysis ◽  
Structural Information ◽  
Research Area ◽  
Processing Technique ◽  
The Novel ◽  
Phase Congruency ◽  
Focus Measure ◽  
Fused Image ◽  
Focus Image ◽  
Image Pairs

Getting a complete description of scene with all the relevant objects in focus is a hot research area in surveillance, medicine and machine vision applications. In this work, transform based fusion method called as NSCT-FMO, is introduced to integrate the image pairs having different focus features. The NSCT-FMO approach basically contains four steps. Initially, the NSCT is applied on the input images to acquire the approximation and detailed structural information. Then, the approximation sub band coefficients are merged by employing the novel Focus Measure Optimization (FMO) approach. Next, the detailed sub-images are combined using Phase Congruency (PC). Finally, an inverse NSCT operation is conducted on synthesized sub images to obtain the initial synthesized image. To optimize the initial fused image, an initial decision map is first constructed and morphological post-processing technique is applied to get the final map. With the help of resultant map, the final synthesized output is produced by the selection of focused pixels from input images. Simulation analysis show that the NSCT-FMO approach achieves fair results as compared to traditional MST based methods both in qualitative and quantitative assessments.

scholarly journals A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kai Wei ◽  
Xuwen Jing ◽  
Bingqiang Li ◽  
Chao Kang ◽  
Zhenhuan Dou ◽  
...  
Keyword(s):  
Vibration Signal ◽  
Rotating Machinery ◽  
Second Order ◽  
Variable Speed ◽  
Short Time Fourier Transform ◽  
Stationary Characteristic ◽  
Nonstationary Signals ◽  
Time Frequency ◽  
Effective Technology ◽  
Short Time

AbstractIn recent years, considerable attention has been paid in time–frequency analysis (TFA) methods, which is an effective technology in processing the vibration signal of rotating machinery. However, TFA techniques are not sufficient to handle signals having a strong non-stationary characteristic. To overcome this drawback, taking short-time Fourier transform as a link, a TFA methods that using the generalized Warblet transform (GWT) in combination with the second order synchroextracting transform (SSET) is proposed in this study. Firstly, based on the GWT and SSET theories, this paper proposes a method combining the two TFA methods to improve the TFA concentration, named GWT–SSET. Secondly, the method is verified numerically with single-component and multi-component signals, respectively. Quantized indicators, Rényi entropy and mean relative error (MRE) are used to analyze the concentration of TFA and accuracy of instantly frequency (IF) estimation, respectively. Finally, the proposed method is applied to analyze nonstationary signals in variable speed. The numerical and experimental results illustrate the effectiveness of the GWT–SSET method.

scholarly journals Mitigating impact of spatial variance of turbulence in wind energy applications

2020 ◽  
Vol 5 (2) ◽  
pp. 439-450
Author(s):  
Jonas Kazda ◽  
Jakob Mann
Keyword(s):  
Wind Turbine ◽  
Random Error ◽  
Wind Farm ◽  
Second Order ◽  
Mitigation Measures ◽  
Order Moment ◽  
Spatial Variance ◽  
Turbine Performance ◽  
The Difference ◽  
The Impact

Abstract. For the first time an analytical solution for the quantification of the spatial variance of the second-order moment of correlated wind speeds was developed in this work. The spatial variance is defined as random differences in the sample variance of wind speed between different points in space. The approach is successfully verified using simulation and field data. The impact of the spatial variance on three selected applications relevant to the wind energy sector is then investigated including mitigation measures. First, the difference of the second-order moment between front-row wind turbines of Lillgrund wind farm is investigated. The variance of the difference ranges between 25 % and 48 % for turbulence intensities ranging from 7 % to 10 % and a sampling period of 10 min. It is thus suggested to use the second-order moment measured at each individual turbine as input to flow models of wind farm controllers in order to mitigate random error. Second, the impact of the spatial variance of the measured second-order moment on the verification of wind turbine performance is investigated. Misalignment between the mean wind direction and the line connecting the meteorological mast and wind turbine is observed to result in an additional random error in the observed second-order moment of wind speed. In the investigated conditions the random error was up to 34 %. Such a random error adds uncertainty to the turbulence intensity-based classification of the fatigue loads and power output of a wind turbine. To mitigate the random error, it is suggested to either filter the measured data for low angles of misalignment or quantify wind turbine performance using the ensemble-averaged measurements of the same wind conditions. Third, the verification of sensors in wind farms was investigated with respect to the impact of distant reference measurements. In the case of a misalignment between the wind direction and the line connecting sensor and reference, an increased random error will hamper the comparison of the measured second-order moments. The suggested mitigation measures are equivalent to those for the verification of turbine performance.

Quantification Evaluation of Continuous Fiber Composite Microstructure with Assistance of Image Processing Technique

2012 ◽  
Vol 622-623 ◽  
pp. 743-746
Author(s):  
Jiang Sun ◽  
Qi Xiao
Keyword(s):  
Image Processing ◽  
Fiber Composite ◽  
Processing Technique ◽  
Intensity Function ◽  
Second Order ◽  
Image Processing Technique ◽  
Two Phase ◽  
Structural Morphology ◽  
Composite Microstructure ◽  
Processing Techniques

The paper first introduced the method of analyzing the micro-structural morphology, then with assistance of image processing techniques and a second-order intensity function, simulated the two-phase composite micro-structure and selected its RVE. By an object function based on the second-order intensity function and using genetic algorithm, the RVE of original composite microstructure was created and its elastic moduli were analyzed. Numerical calculations showed that the represent volume element can well represent the original composite microstructure.

Research and Transformation of Rotary Surface Discharge Machining Equipment of Engineering Ceramic

2014 ◽  
Vol 941-944 ◽  
pp. 529-533
Author(s):  
Li Xin Zhang
Keyword(s):  
Surface Quality ◽  
Processing Technique ◽  
Surface Discharge ◽  
Machining Parameters ◽  
Main Shaft ◽  
Engineering Ceramic ◽  
Electrode Wire ◽  
Machining Test ◽  
Main Factor

This paper introduces a kind of rotary surface processing technique which is realized through installing a main shaft on common digital control wire-electrode cutter to drive rotary workpiece. Then the discharge machining test is conducted to study the surface roughness which is the main factor influences the surface quality, and then it comes to a test conclusion that installing electrode wire restrainer and auxiliary electrode device can improve the machining surface quality of rotary surface discharge. It has also provided the basis for further optimizing machining parameters in later study.

Application of Object-Based Image Processing Technique in Printing Defect Online Detection

2015 ◽  
Vol 731 ◽  
pp. 210-213
Author(s):  
Shu Feng Liu ◽  
Shao Hong Shen
Keyword(s):  
Image Processing ◽  
Detection Method ◽  
Main Idea ◽  
Color Difference ◽  
Processing Technique ◽  
Experimental Results ◽  
Image Processing Technique ◽  
Online Detection ◽  
Multi Scale ◽  
Color Printing

In this paper ,a color printing defect automatic online detection method based on digital image processing technique is proposed. The main idea of this method is comparison of defect product and template and it makes up of following key models. Firstly, multi-scale segmentation is applied to composed image which is overlaid by detecting product and template image. Secondly, an automatic region similarity analysis calculation is taken to segmentation obtained in multi-scale segmentation. The color difference between detecting product and template can be calculated accurately. Thirdly, defect detection results can be obtained according to threshold segmentation. Finally, the characteristics and advantages are approved by experimental analysis and discussion. Algorithm parameters are adjusted and modified to improve the stability and effectiveness. Experimental results approve that color printing defect automatic detection method in this paper has the characteristics of effectiveness and applicability. And experimental results indicate that this method has the advantage of judging the defect types automatically.

The Modeling and Finite Elements Simulation for Pressure Field of Abrasive Jet Precision Finishing With Grinding Wheel as Restraint

2007 ◽  
Vol 359-360 ◽  
pp. 474-478
Author(s):  
Suo Xian Yuan ◽  
Xi Ying Liu ◽  
Guang Qi Cai ◽  
Jin Ping Shao
Keyword(s):  
Finite Elements ◽  
Simulation Analysis ◽  
Three Dimensional ◽  
Hydrodynamic Pressure ◽  
Processing Technique ◽  
Grinding Wheel ◽  
Abrasive Jet Machining ◽  
Conventional Grinding ◽  
Finite Elements Simulation ◽  
Precision Finishing

It is innovative to combine abrasive jet machining and conventional grinding together in this thesis. And it realizes a new sort of grinding wheel restricted with abrasive jet processing. The three-dimensional mathematical model of hydrodynamic pressure of wedge-like grinding zone between grinding wheel and workpiece on abrasive jet finishing with wheel as restraint was established, and the finite elements simulation analysis for the hydrodynamic pressure was implemented. This paper investigated the liquid hydrodynamic pressure, the regularities of distributing of velocity, influencing factors and the affection for processing technique.

Dynamic Modeling and Simulation Analysis for Rotary Ultrasonic Machining of SiCp/Al Thin-Walled Structure

2013 ◽  
Vol 568 ◽  
pp. 15-20 ◽  
Author(s):  
Ming Wang ◽  
Guo Jun Dong ◽  
Ming Zhou
Keyword(s):  
Simulation Analysis ◽  
Time Domain Analysis ◽  
Machining Parameters ◽  
Ultrasonic Machining ◽  
Analysis Method ◽  
Rotary Ultrasonic Machining ◽  
Al Composite ◽  
Machining Allowance ◽  
Thin Walled ◽  
Simulation Results

SiCp/Al thin-walled structure is processed by rotary ultrasonic machining (RUM). Machining allowance of thin-walled structure is large, manufacturability is bad, and it is vulnerable to vibration to reduce processing quality in machining. Based on analysis of chatter mechanism of RUM, a dynamic model for chatter analyzing and a stability judgment criterion are established and the simulation is conducted for a typical thin-walled component of SiCp/Al composite with time domain analysis method. The simulation results show that machining parameters of RUM could be optimized selected with this model, chatter could be prevented effectively and a good processing effect achieved.

scholarly journals Mitigating Impact of Spatial Variance of Turbulence in Wind Energy Applications

2019 ◽  
Author(s):  
Jonas Kazda ◽  
Jakob Mann
Keyword(s):  
Wind Turbine ◽  
Random Error ◽  
Wind Farm ◽  
Second Order ◽  
Mitigation Measures ◽  
Order Moment ◽  
Spatial Variance ◽  
Turbine Performance ◽  
The Difference ◽  
The Impact

Abstract. The first analytical solution for the quantification of the spatial variance of the second-order moment of correlated wind speeds was developed in this work. The spatial variance is defined as random differences in the sample variance of wind speed between different points in space. The approach is successfully verified using simulation and field data. The impact of the spatial variance on three selected applications relevant to the wind energy sector is then investigated including mitigation measures. First, the difference of the second-order moment between front-row wind turbines of Lillgrund wind farm is investigated. The variance of the difference ranges between 25 % and 48 % for turbulence intensities ranging from 7 % to 10 % and a sampling period of 10 min. It is thus suggested to use the second-order moment measured at each individual turbine as input to flow models of wind farm controllers in order to mitigate random error. Second, the impact of the spatial variance of the measured second-order moment on the verification of wind turbine performance is investigated. Misalignment between the mean wind direction and the line connecting the meteorological mast and wind turbine is observed to result in an additional random error in the observed second-order moment of wind speed. In the investigated conditions the random error was up to 34 %. Such random error adds uncertainty to the turbulence intensity-based classification of the fatigue loads and power output of a wind turbine. To mitigate the random error it is suggested to either filter the measured data for low angles of misalignment, or to quantify wind turbine performance using the ensemble averaged measurements of the same wind conditions. Third, the verification of sensors in wind farms was investigated with respect to the impact of distant reference measurements. In case of a misalignment between the wind direction and the line connecting sensor and reference, an increased random error will hamper the comparison of the measured second-order moments. The suggested mitigation measures are equivalent to those for the verification of turbine performance.

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