Secondary Path Estimation by PCA-Compressed Frequency Response Function in Active Vibration Control

2011 ◽  
Vol 66-68 ◽  
pp. 721-726
Author(s):  
Xin Hui Li ◽  
Tie Jun Yang ◽  
Jian Chao Dong ◽  
Ze Qi Lu
Keyword(s):  
Vibration Control ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Active Vibration Control ◽  
Principal Component ◽  
Good Control ◽  
Noise Elimination ◽  
Measured Frequency Response ◽  
Active Vibration

The FXLMS algorithm is widely used in active vibration control system. The estimation of secondary path plays very important roles in such a system. This paper presents an experimental investigation of effective secondary path estimation in active vibration control using measured Frequency Response Function (FRF). Principal component analysis (PCA) is pursued to the measured FRF for noise elimination, and then the PCA-compressed FRF data are used for secondary path estimation. The control results indicate that the proposed method has good control performance.

scholarly journals Active Vibration Control of Rib Stiffened Plate by Using Decentralized Velocity Feedback Controllers with Inertial Actuators

2019 ◽  
Vol 9 (15) ◽  
pp. 3188 ◽  
Author(s):  
Xiyue Ma ◽  
Lei Wang ◽  
Jian Xu
Keyword(s):  
Vibration Control ◽  
Active Vibration Control ◽  
Low Frequency ◽  
Good Control ◽  
Practical Significance ◽  
Stiffened Plate ◽  
Control Performance ◽  
Feedback Controllers ◽  
Velocity Feedback ◽  
Active Vibration

Active control of low frequency vibration and sound radiation from a rib stiffened plate has great practical significance as this structure is widely applied in engineering, such as aircraft or ship fuselage shells. This paper presents an investigation on the performance of active vibration control of the rib stiffened plate by using decentralized velocity feedback controllers with inertial actuators. A simple modeling approach in frequency domain is proposed in this research to calculate the control performance. The theoretical model of vibrating response of the ribbed plate and the velocity feedback controllers is first established. Then, as an important part, the influences of the control gain and the number of the decentralized unit on the control performance are investigated. Results obtained demonstrate that—similar to that of the unribbed plate case—appropriately choosing the number of the unit and their feedback gains can achieve good control results. Too many units or very high feedback gains will not bring further noise reduction.

Damage Detection of Steel Beam Using Frequency Response Function Measurement Data and Fractal Dimension

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Eun-Taik Lee ◽  
Hee-Chang Eun
Keyword(s):  
Fractal Dimension ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Measurement Data ◽  
Fractal Dimensions ◽  
Dynamic Responses ◽  
Steel Beam ◽  
Health State ◽  
Measured Frequency Response

Fractal-dimension-based signal processing has been extensively applied to various fields for nondestructive testing. The dynamic response signal can be utilized as an analytical tool to evaluate the structural health state without baseline data. The fractal features of the dynamic responses with fractal dimensions (FDs) were investigated using the Higuchi, Katz, and Sevcik methods. The waveform FD proposed by these methods was extracted from the measured frequency response function (FRF) data in the frequency domain. Damage was observed within this region, which resulted in an abrupt change in the curvature of the FD. The effectiveness of the methods was investigated via the results of a steel beam test and a numerical experiment to detect damage.

scholarly journals A Novel Method for Fault Diagnosis of the Two-Input Two-Output Nonlinear Mass-Spring-Damper System Based on NOFRF and MBPCA

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jialiang Zhang ◽  
Jie Wu ◽  
Xiaoqian Zhang
Keyword(s):  
Principal Component Analysis ◽  
Fault Diagnosis ◽  
Nonlinear System ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Principal Component ◽  
Component Analysis ◽  
Novel Method ◽  
Mass Spring

For fault diagnosis of the two-input two-output mass-spring-damper system, a novel method based on the nonlinear output frequency response function (NOFRF) and multiblock principal component analysis (MBPCA) is proposed. The NOFRF is the extension of the frequency response function of the linear system to the nonlinear system, which can reflect the inherent characteristics of the nonlinear system. Therefore, the NOFRF is used to obtain the original fault feature data. In order to reduce the amount of feature data, a multiblock principal component analysis method is used for fault feature extraction. The least squares support vector machine (LSSVM) is used to construct a multifault classifier. A simplified LSSVM model is adopted to improve the training speed, and the conjugate gradient algorithm is used to reduce the required storage of LSSVM training. A fault diagnosis simulation experiment of a two-input two-output mass-spring-damper system is carried out. The results show that the proposed method has good diagnosis performance, and the training speed of the simplified LSSVM model is significantly higher than the traditional LSSVM.

scholarly journals Dynamic characterizations of underwater structures using noncontact vibration tests based on nanosecond laser ablation in water: evaluation of passive vibration suppression with damping materials

2017 ◽  
Vol 24 (16) ◽  
pp. 3714-3725 ◽  
Author(s):  
Naoki Hosoya ◽  
Itsuro Kajiwara ◽  
Koh Umenai ◽  
Shingo Maeda
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Vibration Suppression ◽  
Pass Filter ◽  
Reliability Factor ◽  
Measured Frequency ◽  
Measured Frequency Response ◽  
Underwater Structure ◽  
Underwater Structures

Recently, the demand for higher performing underwater structures under diverse conditions has increased. Examples include improved precision and speed of the position control of robot manipulators. To prevent the control spillover problems when active controls are used, a control system is typically constituted with a low-pass filter to eliminate all modes except for the target modes. However, experimentally measuring the dynamic properties of an underwater structure in an environment where the structure and a fluid continuously influence each other is difficult. We have recently proposed a noncontact vibration testing method for dynamic characterizations of underwater structures in which the response to a laser ablation excitation force is measured by laser Doppler vibrometer. Integrating passive control using a vibration-damping material affixed onto the underwater structure and active control constituted with the low-pass filter may realize a more cost-effective system. To develop this combined control into a practical method, the reliability of the measured frequency response function must be validated. Additionally, the applicable frequency range must be expanded to encompass the high-frequency region (several tens of kHz) so that the vibration suppression quality of underwater structures can be evaluated. Herein we quantify the effect of random measurement errors on the measured frequency response function with a reliability factor based on the concept of coherence functions. Using the measured frequency response function with a reliability factor, we demonstrated that our method can evaluate passive vibration suppression effect of an underwater structure with a damping material in high-frequency ranges up to 20 kHz.

scholarly journals The Researches on Damage Detection Method for Truss Structures

2018 ◽  
Vol 38 ◽  
pp. 03030
Author(s):  
Meng Hong Wang ◽  
Xiao Nan Cao
Keyword(s):  
Numerical Simulation ◽  
Frequency Response ◽  
Response Function ◽  
Time Domain ◽  
Experimental Analysis ◽  
Frequency Response Function ◽  
Principal Component ◽  
Truss Structures ◽  
Time Domain Signal ◽  
The Time Domain

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Structural damage detection in plates using a deep neural network–couple sparse coding classification ensemble method

2020 ◽  
pp. 107754632092915
Author(s):  
Vahid Bokaeian ◽  
Faramarz Khoshnoudian ◽  
Milad Fallahian
Keyword(s):  
Damage Detection ◽  
Frequency Response ◽  
Response Function ◽  
Sparse Coding ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Principal Component ◽  
Plate Structures ◽  
Feature Extraction Method ◽  
Damage Scenarios

The present study aims at identifying damages in plate structures by applying a pattern recognition–based damage detection technique using the frequency response function. The large number of degrees of freedom is one of the crucial obstacles in the way of accurately identifying damages in plate structures. On the other hand, frequency response functions include many details that dramatically lower the computing speed and enlarge the memory needed for storing data, hampering the application of this method. Furthermore, this study performs principal component analysis as an authoritative feature extraction method with the purpose of reducing the dimensions of the measured frequency response function data and generating distinct feature patterns. Also, because there has been no individual optimal classifier applicable to all problems, an ensemble comprising two powerful classifiers containing couple sparse coding classification and deep neural networks is used to predict the structure damage. This study evaluates the accuracy of damage detection by the proposed method in square-shaped structural plates with the lengths of 1 m and 2 m under different damage scenarios, namely, single and multiple element.

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