scholarly journals A Comparative Study of Regularization Method in Structure Load Identification

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Bingrong Miao ◽  
Feng Zhou ◽  
Chuanying Jiang ◽  
Xiangyu Chen ◽  
Shuwang Yang
Keyword(s):  
Structural Parameters ◽  
Railway Track ◽  
Load Identification ◽  
Noise Levels ◽  
Beam Structure ◽  
Identification Procedure ◽  
Vibration Data ◽  
Vibration Responses ◽  
Curve Method ◽  
Quantitative Indicators

This study aims to correlate the vibration data with quantitative indicators of structural health by comparing and validating the feasibility of identifying unknown excitation forces using output vibration responses. First, numerical analysis was performed to investigate the accuracy, convergence, and robustness of the load identification results for different noise levels, sensors numbers, and initial estimates of structural parameters. Then, the laboratory beam structure experiments were conducted. The results show that using the two identification methods Tikhonov (L-curve) and TSVD (GCV-curve) can successfully and accurately identify the different excitation forces of the external hammer. The TSVD based on GCV method has more advantages than the Tikhonov based on L-curve method. The proposed two kinds of load identification procedure based on vibration response can be applied to the safety performance evaluation of the railway track structure in future inverse problems research.

scholarly journals A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Wei Gao ◽  
Kaiping Yu ◽  
Ying Wu
Keyword(s):  
Inverse Problem ◽  
Regularization Method ◽  
Cross Validation ◽  
Regularization Parameter ◽  
New Method ◽  
Parameter Determination ◽  
Load Identification ◽  
Noise Levels ◽  
Regularization Parameters ◽  
Curve Method

According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM) is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV) method and theL-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.

scholarly journals Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3135 ◽  
Author(s):  
Ying Wang ◽  
Wensheng Lu ◽  
Kaoshan Dai ◽  
Miaomiao Yuan ◽  
Shen-En Chen
Keyword(s):  
Wind Turbine ◽  
Vertical Axis ◽  
Dynamic Responses ◽  
Ambient Vibration ◽  
Structural Vibration ◽  
Vertical Axis Wind Turbine ◽  
Mode Identification ◽  
Stochastic Subspace Identification ◽  
Vibration Data ◽  
Vibration Responses

When constructed on tall building rooftops, the vertical axis wind turbine (VAWT) has the potential of power generation in highly urbanized areas. In this paper, the ambient dynamic responses of a rooftop VAWT were investigated. The dynamic analysis was based on ambient measurements of the structural vibration of the VAWT (including the supporting structure), which resides on the top of a 24-story building. To help process the ambient vibration data, an automated algorithm based on stochastic subspace identification (SSI) with a fast clustering procedure was developed. The algorithm was applied to the vibration data for mode identification, and the results indicate interesting modal responses that may be affected by the building vibration, which have significant implications for the condition monitoring strategy for the VAWT. The environmental effects on the ambient vibration data were also investigated. It was found that the blade rotation speed contributes the most to the vibration responses.

scholarly journals Automated processing of railway track deflection signals obtained from velocity and acceleration measurements

2018 ◽  
Vol 232 (8) ◽  
pp. 2097-2110 ◽  
Author(s):  
David Milne ◽  
Louis L Pen ◽  
David Thompson ◽  
William Powrie
Keyword(s):  
Performance Monitoring ◽  
Low Frequency ◽  
Cumulative Distribution ◽  
Railway Track ◽  
Statistical Process ◽  
Vibration Data ◽  
Rest Position ◽  
Low Frequency Vibration ◽  
Automated Processing ◽  
And Performance

Measurements of low-frequency vibration are increasingly being used to assess the condition and performance of railway tracks. Displacements used to characterise the track movement under train loads are commonly obtained from velocity or acceleration signals. Artefacts from signal processing, which lead to a shift in the datum associated with the at-rest position, as well as variability between successive wheels, mean that interpreting measurements is non-trivial. As a result, deflections are often interpreted by inspection rather than following an algorithmic or statistical process. This can limit the amount of data that can be usefully analysed in practice, militating against widespread or long-term use of track vibration measurements for condition or performance monitoring purposes. This paper shows how the cumulative distribution function of the track deflection can be used to identify the at-rest position and to interpret the typical range of track movement from displacement data. This process can be used to correct the shift in the at-rest position in velocity or acceleration data, to determine the proportion of upward and downward movement and to align data from multiple transducers to a common datum for visualising deflection as a function of distance along the track. The technique provides a means of characterising track displacement automatically, which can be used as a measure of system performance. This enables large volumes of track vibration data to be used for condition monitoring.

Distributed Load Identification for Uncertain Structure Based on LHS-GA and Improved L-Curve Method

2020 ◽  
Vol 18 (01) ◽  
pp. 2050022
Author(s):  
Haitao Zhao ◽  
Xiaowang Li ◽  
Ji’an Chen
Keyword(s):  
Latin Hypercube Sampling ◽  
Upper And Lower Bounds ◽  
Sampling Point ◽  
Load Identification ◽  
Noise Performance ◽  
Force Amplitude ◽  
Comprehensive Method ◽  
Distributed Load ◽  
Uncertain Structure ◽  
Curve Method

In order to identify the upper and lower bounds of distributed force exciting on an uncertain structure, a comprehensive approach combining genetic algorithm based on Latin hypercube sampling (LHS-GA) and improved L-curve method is built up in this paper. For uncertain parameter expressed by interval form, LHS-GA is presented to seeking the maximum and minimum amplitudes of distributed load in the interval. Aiming at distributed load reconstruction for a specific sampling point in the interval, which is the objective function of LHS-GA, the traditional L-curve method is improved to weaken the ill-posedness problem and obtain accurate distributed force amplitude. Numerical example results indicate the comprehensive method is able to acquire precise bounds of distributed load. Meanwhile, it possesses a strong anti-noise performance.

scholarly journals Modelling a Cracked Beam Structure Using the Finite Element Displacement Method

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Hui Long ◽  
Yilun Liu ◽  
Changzheng Huang ◽  
Weihui Wu ◽  
Zhaojun Li
Keyword(s):  
Finite Element ◽  
Dynamic Model ◽  
Structural Parameters ◽  
Element Model ◽  
Beam Element ◽  
The Finite Element Method ◽  
Displacement Method ◽  
Beam Structure ◽  
Cracked Beam ◽  
Local Flexibility

A new model is presented for studying the effects of crack parameters on the dynamics of a cracked beam structure. The model is established by the finite element displacement method. In particular, the stiffness matrix of the cracked beam element is firstly derived by the displacement method, which does not need the flexibility matrix inversion calculation compared with the previous local flexibility approaches based on the force method. Starting with a finite element model of cracked beam element, the equation of strain energy of a cracked beam element is formed by the displacement method combined with the linear fracture mechanics. Then, based on the finite element method, the dynamic model of the cracked beam structure is obtained. The results show that the dynamic model discovers the internal relation between the dynamic characteristics of cracked beam structure and structural parameters, material parameters, and crack parameters. Finally, an example is presented to validate the proposed dynamic model.

WSN-Based Vibration Characteristic Research for Various Railway Track Structures for Pattern Classification

2016 ◽  
Vol 30 (10) ◽  
pp. 1650020 ◽  
Author(s):  
Guo-dong Yue ◽  
Zheng Xu ◽  
Liding Wang ◽  
Chong Liu ◽  
Tongqun Ren
Keyword(s):  
Pattern Classification ◽  
Wavelet Transforms ◽  
Railway Track ◽  
Frequency Bands ◽  
Vibration Data ◽  
Power Spectral ◽  
Acceleration Data ◽  
Curve Track ◽  
Instantaneous Frequencies

To effectively study vibration characteristics of tracks under different track structures, wavelet transforms of the vibration data are used for pattern classification of vibration feature. First, acceleration data of the track are collected with running speed of 150[Formula: see text]km/h at 26 positions respectively on a slab tangent track, ballast tangent track and ballast curve track by a wireless sensor network (WSN). Then they are analyzed using the power spectral densities (PSDs) and wavelet-based energy spectrum analysis. The paper elaborates on the reasons for the differences of vibration energy and excitation frequencies due to the mechanism of different frequency bands and the corresponding track structures. Based on these, the instantaneous frequencies, vibration energies and durations in the low, medium, and high frequency bands are selected as the features for three track structures. A function curve representing the features is proposed to detect the abnormal track structure by a correlation analysis. Finally, the proposed method of pattern classification has been validated by experimental testings.

Vibration and Noise Characteristics of an Aircraft-Type Gas Turbine Used in a Marine Propulsion System

1969 ◽  
Author(s):  
R. E. Harper
Keyword(s):  
Gas Turbine ◽  
Vibration Isolation ◽  
Propulsion System ◽  
Noise Levels ◽  
Vibration Data ◽  
Noise Characteristics ◽  
Marine Propulsion ◽  
Antisubmarine Warfare ◽  
Aircraft Type ◽  
Marine Propulsion System

Sound and vibration data measured on a combination diesel gas turbine propulsion system in a 2000-ton antisubmarine warfare ship are presented. The data can be considered representative of the noise levels, both structureborne and airborne, that can be expected in an installation of this or a similar type. Examples of the attenuation of structureborne noise through selected structural joints illustrate the vibration isolation attainable through the use of lightweight aircraft-type structures.

scholarly journals Vibrational Diagnostics of Rotating Machinery Malfunctions

1995 ◽  
Vol 1 (3-4) ◽  
pp. 237-266 ◽  
Author(s):  
Agnes Muszynska
Keyword(s):  
Rotating Machinery ◽  
Vibration Monitoring ◽  
Process Data ◽  
Vibration Data ◽  
Machine Monitoring ◽  
Vibration Responses ◽  
Actual Field ◽  
Vibrational Diagnostics ◽  
Monitoring And Diagnostics ◽  
Machinery Diagnostics

This paper outlines rotating machinery malfunction diagnostics using vibration data in correlation with operational process data. The advantages of vibration monitoring systems as a part of preventive/predictive maintenance programs are emphasized. After presenting basic principles of machinery diagnostics, several specific malfunction symptoms supported by simple mathematical models are given. These malfunctions include unbalance, excessive radial load, rotor-to-stator rubbing, fluid-induced vibrations, loose stationary and rotating parts, coupled torsional/lateral vibration excitation, and rotor cracking. The experimental results and actual field data illustrate the rotor vibration responses for individual malfunctions. Application of synchronous and nonsynchronous perturbation testing used for identification of basic dynamic characteristics of rotors is presented. Future advancements in vibration monitoring and diagnostics of rotating machinery health are discussed. In the Appendix, basic instrumentation for machine monitoring is outlined.

scholarly journals Simultaneous identification of the load and unknown parameters of the structure based on the perturbation method

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880566 ◽  
Author(s):  
Chongwen Wang ◽  
Chengbin Du ◽  
Shouyan Jiang
Keyword(s):  
Perturbation Method ◽  
Structural Parameters ◽  
Structural Parameter ◽  
Load Identification ◽  
Response Matrix ◽  
Parameter Perturbation ◽  
Unknown Parameters ◽  
Simply Supported ◽  
Shear Frame ◽  
Simultaneous Identification

For when a structure is both subjected to unknown loads and characterized by unknown parameters and structural parameter identification and load identification algorithms cannot be applied under these circumstances, this article proposes a new algorithm based on the perturbation method for the simultaneous identification of the load and unknown structural parameters using a few response points. The impulse response matrix is expanded with respect to the unknown parameters, and then the load term is combined with the unknown parameter perturbation term to generate the parameter–load term; finally, the load and unknown parameters can be simultaneously identified by iteration. The proposed algorithm is verified by an example of a 10-storey shear frame, and the effect of noise level, the number of response points, and the truncation ratio, which is a parameter introduced to improve the accuracy of the proposed algorithm, are studied. Moreover, the effect of the distribution of response points is discussed for another example of a simply supported beam, and the results show that when the response points are distributed over the full beam, the error is obviously smaller than when the response points are distributed over only part of the beam.

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