scholarly journals The Method for Determining Optimal Analysis Length of Vibration Data Based on Improved Multiscale Permutation Entropy

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jianwei Zhang ◽  
Ziyu Li ◽  
Peng Yan ◽  
Yang Li ◽  
Jinlin Huang
Keyword(s):  
Data Analysis ◽  
Coarse Grained ◽  
Structural Vibration ◽  
Permutation Entropy ◽  
Standard Entropy ◽  
Vibration Data ◽  
Monitoring Process ◽  
Structure Monitoring ◽  
Length Analysis ◽  
Data Length

Research on damage diagnosis or safety monitoring based on structural vibration response is one of the hot issues in the engineering field. The characteristic information of the structure is obtained by analyzing the structure response data. In the process of data analysis, the choice of data length is very important, which is related to the validity of the structure monitoring results. At present, the selection of data length is usually subjective, which reduces the rigor of the structure monitoring process. Therefore, a method based on improved multiscale permutation entropy (IMPE) is proposed to determine the optimal data analytical length (ODAL) of vibration data. This method creatively applies multiscale permutation entropy (MPE) to the field of data length analysis when processing nonlinear and nonstationary signals and optimizes MPE with the help of the improved coarse-grained method to obtain IMPE. IMPE is sensitive to different data lengths, and the entropy changes with the increase of the data length and tends to be stable. Here, the stable value is defined as a standard entropy. The entropy satisfying 97% of the standard entropy is used as the effective entropy, and the corresponding data length value of the effective entropy is selected as the ODAL of the vibration data. This method is suitable for many fields, provides a reliable data analytical length for data analysis, and has good engineering practicability.

Monitoring Offshore Pipelines Using Forced Transverse Vibration: Data Analysis

1995 ◽  
Author(s):  
Hugh E. M. Hunt
Keyword(s):  
Fluid Flow ◽  
Data Analysis ◽  
Transverse Vibration ◽  
Vibration Amplitude ◽  
Support Condition ◽  
Offshore Pipelines ◽  
Vibration Data ◽  
Wavelet Methods

Abstract Vibration methods are used to identify faults, such as spanning and loss of cover, in long off-shore pipelines. A pipeline ‘pig’, propelled by fluid flow, generates transverse vibration in the pipeline and the measured vibration amplitude reflects the nature of the support condition. Large quantities of vibration data are collected and analysed by Fourier and wavelet methods.

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.

L1 Regularized Model Updating for Structural Damage Detection

2018 ◽  
Vol 18 (12) ◽  
pp. 1850157 ◽  
Author(s):  
Yu-Han Wu ◽  
Xiao-Qing Zhou
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Model Updating ◽  
Regularization Parameter ◽  
Structural Vibration ◽  
Mode Shapes ◽  
Modal Data ◽  
Vibration Data ◽  
Stiffness Reduction ◽  
Regularized Model

Model updating methods based on structural vibration data have been developed and applied to detecting structural damages in civil engineering. Compared with the large number of elements in the entire structure of interest, the number of damaged elements which are represented by the stiffness reduction is usually small. However, the widely used [Formula: see text] regularized model updating is unable to detect the sparse feature of the damage in a structure. In this paper, the [Formula: see text] regularized model updating based on the sparse recovery theory is developed to detect structural damage. Two different criteria are considered, namely, the frequencies and the combination of frequencies and mode shapes. In addition, a one-step model updating approach is used in which the measured modal data before and after the occurrence of damage will be compared directly and an accurate analytical model is not needed. A selection method for the [Formula: see text] regularization parameter is also developed. An experimental cantilever beam is used to demonstrate the effectiveness of the proposed method. The results show that the [Formula: see text] regularization approach can be successfully used to detect the sparse damaged elements using the first six modal data, whereas the [Formula: see text] counterpart cannot. The influence of the measurement quantity on the damage detection results is also studied.

Development of Structural Identification Accuracy Indicators Using Fuzzy Logic

1997 ◽  
Author(s):  
Stanley E. Woodard ◽  
Richard S. Pappa
Keyword(s):  
Data Analysis ◽  
Expert System ◽  
Structural Damage ◽  
Identification Accuracy ◽  
Fuzzy Expert System ◽  
Eigensystem Realization Algorithm ◽  
Automatic Control Systems ◽  
Vibration Data ◽  
Fuzzy Membership Functions ◽  
Degree Of Confidence

Abstract A fuzzy expert system was developed for autonomous in-space identification of spacecraft modal parameters. The in-space identification can be used to validate analytical predictions, detect structural damage, or tune automatic control systems as required. A fuzzy expert system determines accuracy of vibration data analysis performed autonomously using the Eigensystem Realization Algorithm. Evaluation of the data analysis output is imprecise and somewhat subjective. The expert system was developed using the knowledge provided the co-developer of the Eigensystem Realization Algorithm. The accuracy indicator represents the analyst’s degree of confidence in the analysis results. The fuzzy membership functions of the expert system were parameterized and tuned using numerical optimization.

scholarly journals Adaptive Multiscale Symbolic-Dynamics Entropy for Condition Monitoring of Rotating Machinery

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1138
Author(s):  
Chunhong Dou ◽  
Jinshan Lin
Keyword(s):  
Symbolic Dynamics ◽  
Spatial Scales ◽  
Approximate Entropy ◽  
Rotating Machinery ◽  
Temporal Scale ◽  
Permutation Entropy ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Vibration Data ◽  
Temporal Statistics

Vibration data from rotating machinery working in different conditions display different properties in spatial and temporal scales. As a result, insights into spatial- and temporal-scale structures of vibration data of rotating machinery are fundamental for describing running conditions of rotating machinery. However, common temporal statistics and typical nonlinear measures have difficulties in describing spatial and temporal scales of data. Recently, statistical linguistic analysis (SLA) has been pioneered in analyzing complex vibration data from rotating machinery. Nonetheless, SLA can examine data in spatial scales but not in temporal scales. To improve SLA, this paper develops symbolic-dynamics entropy for quantifying word-frequency series obtained by SLA. By introducing multiscale analysis to SLA, this paper proposes adaptive multiscale symbolic-dynamics entropy (AMSDE). By AMSDE, spatial and temporal properties of data can be characterized by a set of symbolic-dynamics entropy, each of which corresponds to a specific temporal scale. Afterward, AMSDE is employed to deal with vibration data from defective gears and rolling bearings. Moreover, the performance of AMSDE is benchmarked against five common temporal statistics (mean, standard deviation, root mean square, skewness and kurtosis) and three typical nonlinear measures (approximate entropy, sample entropy and permutation entropy). The results suggest that AMSDE performs better than these benchmark methods in characterizing running conditions of rotating machinery.

scholarly journals An Approach for Reconstruction of Realistic Economic Data Based on Frequency Characteristics between IMFs

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Hao Du ◽  
Hao Gong ◽  
Suyue Han ◽  
Peng Zheng ◽  
Bin Liu ◽  
...  
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Low Frequency ◽  
Test Method ◽  
Series Data ◽  
Permutation Entropy ◽  
Intrinsic Mode Functions ◽  
Economic Data ◽  
Index Method

Reconstruction of realistic economic data often causes social economists to analyze the underlying driving factors in time-series data or to study volatility. The intrinsic complexity of time-series data interests and attracts social economists. This paper proposes the bilateral permutation entropy (BPE) index method to solve the problem based on partly ensemble empirical mode decomposition (PEEMD), which was proposed as a novel data analysis method for nonlinear and nonstationary time series compared with the T-test method. First, PEEMD is extended to the case of gold price analysis in this paper for decomposition into several independent intrinsic mode functions (IMFs), from high to low frequency. Second, IMFs comprise three parts, including a high-frequency part, low-frequency part, and the whole trend based on a fine-to-coarse reconstruction by the BPE index method and the T-test method. Then, this paper conducts a correlation analysis on the basis of the reconstructed data and the related affected macroeconomic factors, including global gold production, world crude oil prices, and world inflation. Finally, the BPE index method is evidently a vitally significant technique for time-series data analysis in terms of reconstructed IMFs to obtain realistic data.

scholarly journals Entropy Variations of Multi-Scale Returns of Optimal and Noise Traders Engaged in “Bucket Shop Trading”

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 215
Author(s):  
Alejandro Raúl Hernández-Montoya ◽  
Carlos Manuel Rodríguez-Martínez ◽  
Manuel Enríque Rodríguez-Achach ◽  
David Hernández-Enríquez
Keyword(s):  
Data Analysis ◽  
Coarse Grained ◽  
Entropy Measure ◽  
Practical Application ◽  
Noise Traders ◽  
Multi Scale

In this paper a comparative, coarse grained, entropy data analysis of multi-scale log-returns distribution, produced by an ideal “optimal trader” and one thousand “noise traders” performing “bucket shop” trading, by following four different financial daily indices, is presented. A sole optimal trader is assigned to each one of these four analyzed markets, DJIA, IPC, Nikkei and DAX. Distribution of differential entropies of the corresponding multi-scale log-returns of the optimal and noise traders are calculated. Kullback-Leiber distances between the different optimal traders returns distributions are also calculated and results discussed. We show that the entropy of returns distribution of optimal traders for each analyzed market indeed reaches minimum values with respect to entropy distribution of noise traders and we measure this distance in σ units for each analyzed market. We also include a discussion on stationarity of the introduced multi-scale log-returns observable. Finally, a practical application of the obtained results related with ranking markets by their entropy measure as calculated here is presented.

scholarly journals ANALYSIS OF THE IMPLEMENTATION OF THE EVALUATION OF GUIDANCE AND COUNSELLING PROGRAM AT STATE SENIOR HIGH SCHOOLS OF SINGKAWANG

2016 ◽  
Vol 7 (5) ◽  
pp. 1380-1383
Author(s):  
Abd. Basith
Keyword(s):  
High School ◽  
Data Analysis ◽  
Qualitative Methods ◽  
Data Reduction ◽  
Senior High School ◽  
Evaluation Program ◽  
Analysis Techniques ◽  
Monitoring Process ◽  
Evaluation Models ◽  
Counselling Program

The objectives of this research are: (1) to describe and analyze the implementation of the guidance and counsellingprogram at State Senior High School of Singkawang, and (2) to find some factors inhibiting the implementation of the guidance and counselling program at State Senior High School of Singkawang. This study uses qualitative methods; usinginterview data collecting technique, tested its validity through triangulation. The subjects in this study are all teachers of guidance and counselling in the Senior High School of Singkawang as many as 10 people as well as principals and supervisors as the informants with the total of 11 people. The data analysis techniques are in form of data reduction, presentation and conclusion. The results show that: (1) the implementation of evaluation of guidance and counselling program by the teachers still has many weaknesses on each phase of the evaluation, such as not understanding the evaluation models of the guidance and counselling program, how to apply them, and monitoring process that is not done in deeply and in detail (just what it is), (2) Some factors inhibiting the implementation of the evaluation of guidance and counselling program are lack of knowledge and understanding of the evaluation of guidance and counselling program in the schools, lack of interest in developing professional competencies, and lack of guidance to the teachers in implementing the guidance and counselling evaluation program.

A Study on Applicability of Predictive Maintenance and Vibration Data Analysis by Fast Fourier Transform into Major Equipment of Submarine

2021 ◽  
Vol 4 (1) ◽  
pp. 14-21
Author(s):  
Donghoon Kim ◽  
Sang Woo Kang ◽  
Ji Hoon Lee ◽  
Kyung Mo Nam ◽  
Seong Hun Seong ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Data Analysis ◽  
Fast Fourier Transform ◽  
Predictive Maintenance ◽  
Vibration Data ◽  
Major Equipment
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