SAR tomography imaging based on high-order spectrum analysis

2007 ◽  
Author(s):  
Wang Jinfeng ◽  
Zhou Peng ◽  
Pi Yiming
Keyword(s):  
Spectrum Analysis ◽  
High Order ◽  
Tomography Imaging ◽  
Order Spectrum

Studying on the Magnetorheological Fluids and its Rheometer

2011 ◽  
Vol 230-232 ◽  
pp. 1396-1401 ◽  
Author(s):  
Bing San Chen ◽  
Ji Bin Jiang ◽  
Fu Jiang Zhang
Keyword(s):  
Dynamic Characteristics ◽  
Spectrum Analysis ◽  
Computer Software ◽  
High Order ◽  
Step Motor ◽  
Order Analysis ◽  
Analysis Process ◽  
Mr Fluids ◽  
Order Spectrum ◽  
Measurement And Analysis

This paper presents a magnetorheological(MR) rheometer which consists of a pair of rotating parallel disc, step motor, the signal collecting device, computer software for dynamic analysis etc.. In order to assess the performance of the MR rheometer, high-order spectrum analysis tools are used. The theoretical and experimental results indicate that the rheometer is useful to test the dynamic charicteristics of the MR fluids and the high-order analysis might be helpful to describe MR rheometer dynamic characteristics. The measurement and analysis process based on virtual instruments are automatically controlled by computer in this paper.

Analysis of Statistical Characteristics of the Laser Vibrometer’s Static Signal Noise

2014 ◽  
Vol 986-987 ◽  
pp. 2048-2051
Author(s):  
Jing Yang ◽  
Jian Long Tang ◽  
Jun Hui Hou ◽  
Xue Zhang ◽  
Zhi Shan Wu
Keyword(s):  
Power Spectrum ◽  
Frequency Spectrum ◽  
Spectrum Analysis ◽  
Noise Signal ◽  
High Order ◽  
Random Signal ◽  
Statistical Characteristics ◽  
Signal Noise ◽  
Order Spectrum ◽  
Laser Signal

The static signal is collected through the experiment, and the probability density function model is established. The static random signal noise is analyzed by frequency spectrum, power spectrum and high order spectrum analysis. It is found that the third order spectrum of the laser static signal is zero by the high order spectrum analysis. Noise signal is only to analyze on the frequency spectrum and power spectrum. The results show that the static laser signal has the characteristics of stationary Gauss random signal.

Investigation on Energy Loss in Centrifugal Pump Based on Entropy Generation and High-Order Spectrum Analysis

2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Baoling Cui ◽  
Chenliang Zhang
Keyword(s):  
Energy Loss ◽  
Internal Energy ◽  
Centrifugal Pump ◽  
Entropy Generation ◽  
Spectrum Analysis ◽  
Pressure Pulsation ◽  
High Order ◽  
Energy Losses ◽  
Fundamental Characteristic ◽  
Order Spectrum

Abstract Full-open, straight-blade centrifugal pumps have the advantages of simple structure and high stability at high speeds. However, this type of centrifugal pump has a large internal energy loss and low efficiency. The flow loss caused by unstable flow accounts for most of the internal energy loss of a centrifugal pump, and this energy dissipates mainly to the surroundings of the pump in the form of pressure pulsation and vibration. In this study, to effectively understand the hydraulic behavior and energy loss in a centrifugal pump, the energy losses in the pump were numerically analyzed by the entropy generation method, the distribution of the energies of pressure pulsation and vibration was evaluated based on experimental results at different flowrates, and the correlation between flow and energy loss at 20% of the design flowrate (Qd) was investigated by high-order spectrum analysis. The energies of pressure pulsation and vibration in the experiment were evaluated by the root-mean-square (RMS) value. The distribution of the entropy generation rate (EGR) indicated large energy losses at the diffusion section of the volute, clearance, tongue, and blade inlet. At 20% of the design flowrate (Qd), the energy loss was caused by the backflow near the tongue, and the EGR at EP2 had a nonlinear fundamental characteristic frequency of 0.44fn. By bispectrum and coherence analysis, the nonlinear fundamental characteristic frequencies generated by the unforced flow were analyzed, and it was found that unforced flow was transmitted to one another in the near-tongue region.

Structural Damage Identification Based on Moving Load and High-Order Spectrum Analysis

2012 ◽  
Vol 594-597 ◽  
pp. 1082-1085
Author(s):  
Bu Yu Wang
Keyword(s):  
Neural Network ◽  
Spectrum Analysis ◽  
Structural Damage ◽  
Damage Identification ◽  
Moving Load ◽  
High Order ◽  
Structural Vibration ◽  
Order Spectrum ◽  
Nonlinear Character ◽  
Non Stationary Signal

Moving load could enhance damage-structural nonlinear character. High-order statistical analysis described character of non-stationary signal more exactly than traditional fourier spectrum based on second-order statistics analysis. The result of high-order spectrum analysis was two-dimensional，and spectrum entropy of different frequency can extract its intrinsic information and characters from it. Using these characters, the structural damage pattern could be recognized by neural network. The validity of this method was reviewed by a beam under moving load. When structure has damage, its state information can be extracted availably from high-order spectrum entropy of structural vibration, and it isn’t sensitive to noise. It can be used as eigenvectors of pattern recognition based on neural network.

High Order Spectrum Characteristics of the Elevator Fault

2012 ◽  
Vol 605-607 ◽  
pp. 739-743
Author(s):  
Yue Kun Zheng ◽  
Yi Jian Huang
Keyword(s):  
High Order ◽  
Normal Operation ◽  
Signal Spectrum ◽  
Analysis Tool ◽  
Analysis Method ◽  
Vibration Acceleration ◽  
Acceleration Signal ◽  
Order Spectrum ◽  
Spectrum Characteristics ◽  
Acceleration Signals

Used the high order spectrum and slice analysis method, studied the elevator running vibration acceleration signals and calculated the trispectrum two dimensional slices, bispectrum and theirs diagonal slices, under different running conditions. The results show that: when the elevator normal operation the acceleration signal spectrum peaks concentration, otherwise the acceleration signal peaks dispersion; in fault condition, compared to bispectrum peaks trispectrum peaks is sharper. High order spectrum contains abundant information of different fault elevator running details. It is a suitable analysis tool for diagnosing the faults of elevator.

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