Analysis of Triaxial Vibration Data for Health Monitoring of Helicopter Gearboxes

2003 ◽  
Vol 125 (1) ◽  
pp. 120-128 ◽  
Author(s):  
Irem Y. Tumer ◽  
Edward M. Huff
Keyword(s):  
Vibration Monitoring ◽  
False Alarms ◽  
Frequency Content ◽  
Sources Of Information ◽  
Additional Information ◽  
Vibration Data ◽  
Statistical Variation ◽  
Monitoring And Diagnostics ◽  
Helicopter Transmission ◽  
Vibration Signatures

Research on the nature of the vibration data collected from helicopter transmissions during flight experiments has led to several crucial observations believed to be responsible for the high rates of false alarms and missed detections in aircraft vibration monitoring systems. This work focuses on one such finding, namely, the need to consider additional sources of information about system vibrations. In this light, helicopter transmission vibration data, collected using triaxial accelerometers, are explored in three different directions, analyzed for content, and then combined using Principal Components Analysis (PCA) to analyze changes in directionality. The frequency content of the three different directions is compared and analyzed using time-synchronously averaged vibration data. To provide a method for analysis and monitoring purposes, the triaxial data are decorrelated using a mathematical transformation, and compared to the original axes to determine their differences. The benefits of using triaxial data for vibration monitoring and diagnostics are explored by analyzing the changes in the direction of the principal axis of vibration formed using all three axes of vibration. The statistical variation introduced due to the experimental variables is further analyzed using an Analysis of Variance approach to determine the effect of each variable on the overall signature. The results indicate that triaxial accelerometers can provide additional information about the frequency content of helicopter gearbox vibrations, and provide researchers and industry with a novel method of capturing and monitoring triaxial changes in the baseline vibration signatures.

Using Triaxial Accelerometer Data for Vibration Monitoring of Helicopter Gearboxes

2001 ◽  
Author(s):  
Irem Y. Tumer ◽  
Edward M. Huff
Keyword(s):  
Vibration Monitoring ◽  
Monitoring Systems ◽  
Accelerometer Data ◽  
Frequency Content ◽  
Additional Information ◽  
Vibration Data ◽  
Statistical Variation ◽  
Novel Method ◽  
Monitoring And Diagnostics ◽  
Vibration Signatures

Abstract Typical vibration monitoring systems for helicopter gearboxes rely on single-axis accelerometer data. This paper investigates whether triaxial accelerometers can provide crucial flight regime information for helicopter gearbox monitoring systems. The frequency content of the three different directions is compared and analyzed using time-synchronously averaged vibration data. The triaxial data are decorrelated using a mathematical transformation, and compared to the original axes to determine their optimality. The benefits of using triaxial data for vibration monitoring and diagnostics are explored by analyzing the changes in the direction of the principal axis of vibration formed using all three axes of vibration. The statistical variation introduced due to the experimental variables is further analyzed using an Analysis of Variance approach to determine the effect of each variable on the overall signature. The results indicate that triaxial accelerometers can provide additional information about the frequency content of helicopter gearbox vibrations, providing researchers and industry with a novel method of capturing and monitoring changes in the baseline vibration signatures.

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 Monitoring of Industrial Machine Using a Novel Blind Feature Extraction Approach

2021 ◽  
Vol 11 (13) ◽  
pp. 5792
Author(s):  
Siu Ki Ho ◽  
Harish Chandra Nedunuri ◽  
Wamadeva Balachandran ◽  
Jamil Kanfoud ◽  
Tat-Hean Gan
Keyword(s):  
Feature Extraction ◽  
Random Vibration ◽  
Correct Diagnosis ◽  
Ground Truth ◽  
False Alarms ◽  
Optimal Filtering ◽  
Vibration Data ◽  
Reliable Performance ◽  
Vibration Signatures ◽  
Industrial Machine

Machinery with several rotating and stationary components tends to produce non-stationary and random vibration signatures due to the fluctuations in the input loads and process defects due to long hours of operation. Traditional heuristics methods are suitable for the detection of fault signatures, however, they become more complicated when the level of uncertainty or randomness exceeds beyond control. A novel methodology to identify these fault signatures using optimal filtering of vibration data is proposed to eliminate any false alarms and is expected to provide a higher probability of correct diagnosis. In this paper, a detailed pipeline of the algorithms are presented along with the results of the investigation that was carried out. These investigations are performed using open-source vibration data published by the NASA prognostics centre. The performance of these algorithms are evaluated based on the ground truth results published by NASA researchers. Based on the performance of these algorithms several parameters are fine-tuned to ensure generalisation and reliable performance.

Machine Fault Detection Using Genetic Programming

2005 ◽  
Author(s):  
B. Samanta
Keyword(s):  
Fault Detection ◽  
Genetic Programming ◽  
Vibration Data ◽  
Rotating Machine ◽  
Fault Recognition ◽  
Machine Fault ◽  
Artificial Neural Network Ann ◽  
Monitoring And Diagnostics ◽  
The Time Domain ◽  
Selection Of

Applications of genetic programming (GP) include many areas. However applications of GP in the area of machine condition monitoring and diagnostics is very recent and yet to be fully exploited. In this paper, a study is presented to show the performance of machine fault detection using GP. The time domain vibration signals of a rotating machine with normal and defective gears are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to GP for two class (normal or fault) recognition. The number of features and the features are automatically selected in GP maximizing the classification success. The results of fault detection are compared with genetic algorithm (GA) based artificial neural network (ANN)- termed here as GA-ANN. The number of hidden nodes in the ANN and the selection of input features are optimized using GAs. Two different normalization schemes for the features have been used. For each trial, the GP and GA-ANN are trained with a subset of the experimental data for known machine conditions. The trained GP and GA-ANN are tested using the remaining set of data. The procedure is illustrated using the experimental vibration data of a gearbox. The results compare the effectiveness of both types of classifiers with GP and GA based selection of features.

A Survey of Parental Knowledge of Respiratory Syncytial Virus and Other Respiratory Infections in Preterm Infants

2021 ◽  
Vol 40 (1) ◽  
pp. 14-24
Author(s):  
Marianne Bracht ◽  
Fabiana Bacchini ◽  
Bosco Paes
Keyword(s):  
Respiratory Syncytial Virus ◽  
Preterm Infants ◽  
Disease Risk ◽  
Respiratory Infections ◽  
Parental Knowledge ◽  
Good Knowledge ◽  
Sources Of Information ◽  
Eligibility Criteria ◽  
Additional Information ◽  
Syncytial Virus

PurposeEvaluate parental knowledge of respiratory syncytial virus (RSV) and other respiratory infections in preterm infants.DesignSurvey.SampleFive hundred and eighty-three parents of preterm infants with generalized, Canadian provincial representation.Main OutcomeKnowledge of RSV infection, sources of information, and parental understanding of disease risk.Results97.9 percent (571/583) of the parents had heard about RSV, since they all had a preterm infant. Sixty-one percent reported having good knowledge of RSV; 19.4 percent had very good knowledge; 19.7 percent had little or no awareness of RSV-related infection. Most (86.3 percent) believed that RSV illness was a very serious condition; 13 percent recognized that it could be a major problem for their child. Principal sources of information were the nurse, doctor and pamphlets. Over 480 participants cited 3 or more sources of additional information—Internet, social media platforms, and educational sessions. Respiratory syncytial virus prophylaxis was a priority, but knowledge regarding the eligibility criteria for prophylaxis is essential.

Categorizing Blogs as Information Sources for Libraries and Information Science

2015 ◽  
pp. 4833-4845
Author(s):  
Mark-Shane Scale ◽  
Anabel Quan-Haase
Keyword(s):  
Social Media ◽  
Information Needs ◽  
Information Sources ◽  
Information Science ◽  
Information Source ◽  
Future Research ◽  
Collection Development ◽  
Sources Of Information ◽  
Additional Information ◽  
Source Category

Blogs are important sources of information currently used in the work of professionals, institutions and academics. Nevertheless, traditional information needs and uses research has not yet discussed where blogs fit in the existing typologies of information sources. Blogs and other types of social media have several characteristics that blur the lines of distinction existent between traditional information source categories. This chapter brings this research problem to the fore. Not only do we examine why blogs do not neatly fit into existing information source categories, but we also deliberate the implications for libraries in terms of the need to consider blogs as an information source to be included in collection development. We discuss the opportunities and possibilities for blogs to be integrated into the collection development efforts of academic and public libraries to better serve patrons. In order to accommodate for blogs and other types of social media as information sources, we propose the introduction of an additional information source category. We suggest new avenues of future research that investigate how blogs are being used to meet information needs in various social settings, such as corporations, health care and educational settings (e.g., higher education, and schools). In this chapter, we develop a framework of how blogs may function as information sources to provide libraries with a better understanding of how blogs are integrated into the context of everyday information seeking. By grouping the ways in which people employ blogs to acquire information, we propose that blogs provide information sources along a continuum ranging from non-fiction to fictional information.

Recent Developments in Vibration Monitoring and Diagnostics for Aeroderivative Gas Turbines

1985 ◽  
Author(s):  
James C. Adams
Keyword(s):  
Gas Turbines ◽  
High Efficiency ◽  
Industrial Applications ◽  
Vibration Monitoring ◽  
Monitoring Systems ◽  
Monitoring Methods ◽  
Reliable Monitoring ◽  
Recent Developments ◽  
Monitoring And Diagnostics ◽  
Processing Techniques

Industrial aeroderivative gas turbines are becoming increasingly popular for use in both on-shore and off-shore installations. The characteristics of these machines — high efficiency in simple cycle operation, small size, and light weight — make them ideal for industrial applications. As the aeroderivative gas turbine has become more widely used, the need for more reliable monitoring methods has become increasingly apparent. Traditional velocity transducer based seismic monitoring systems have had several shortcomings when applied to aeroderivative gas turbines. One of these problems was nuisance alarms due to increasing transducer noise output. Another was not detecting increasing casing vibration because of transducer deterioration. Overcoming these problems has required advances in transducer technology as well as changes in signal processing techniques. This paper describes the technology and techniques used in new seismic vibration monitoring systems.

Problems of Optimum Selection

1968 ◽  
Vol 27 (3) ◽  
pp. 715-720
Author(s):  
Gail O'Connor
Keyword(s):  
Factor Analysis ◽  
Multiple Regression ◽  
Sources Of Information ◽  
Additional Information ◽  
Factor Analytic ◽  
Optimum Selection ◽  
Mechanical Ability ◽  
Different Sources ◽  
Selection Of ◽  
Predictive Efficiency

This study examined the selection of different sources of information made by multiple regression, cutting scores, and factor analytic techniques and investigated these procedures in terms of their comparable predictive efficiency. Prior to their job training, 220 Naval winch operator trainees took a battery of seven McQuarrie subtests for mechanical ability. Criterion scores were derived from ratings given subsequent to training. No differences were found among the three methods. However, it is pointed out that the judicious use of factor analysis can provide additional information about the relationships and complexities of the predictors and criterion not available through multiple regression or cutting scores.

Periodic and Continuous Vibration Monitoring for Preventive/Predictive Maintenance of Rotating Machinery

1987 ◽  
Vol 109 (2) ◽  
pp. 159-167 ◽  
Author(s):  
W. C. Laws ◽  
A. Muszynska
Keyword(s):  
Vibration Analysis ◽  
Continuous Monitoring ◽  
Cost Effective ◽  
Predictive Maintenance ◽  
Vibration Monitoring ◽  
Alternative Methods ◽  
Monitoring Systems ◽  
High Quality ◽  
Analysis Techniques ◽  
Vibration Data

The application of vibration monitoring as part of Preventive/Predictive Maintenance programs is discussed. Several alternative methods, including periodic and continuous monitoring techniques, are described. Emphasis is given to the importance of selecting vibration transducers with due regard for the specific machinery type. The equally important need to install monitoring systems which are cost effective and provide genuinely useful information for maintenance engineers and vibration analysts is also highlighted. It is argued that critical machinery should be monitored continuously, and in cases when more detailed investigation is required that high-quality Predictive Maintenance vibration analysis techniques be applied. The need is also emphasized for specialist interpretation of vibration data in order to identify specific machinery malfunctions, of which several examples are given.

Development Solution of Civil Helicopter Transmission Train Vibration Monitoring System

2011 ◽  
Vol 86 ◽  
pp. 342-347
Author(s):  
Su Ning Zhang ◽  
Wen Qiang Ding ◽  
Yong Hong Wang
Keyword(s):  
Monitoring System ◽  
External Environment ◽  
Considerable Improvement ◽  
Maintenance Management ◽  
Vibration Monitoring ◽  
Equipment Failures ◽  
System Vibration ◽  
Critical Components ◽  
Helicopter Transmission ◽  
Train Vibration

Health & Usage Monitoring System (HUMS) is designed for improving airworthiness, reliability and effective maintenance management of helicopter by analysis of detected / diagnosed operation data internal/external environment data collected from the helicopter. Vibration monitoring system plays as an important part of entireness integrated HUMS, which offers a considerable improvement to conventional monitoring techniques. This paper covers development solution of civil helicopter transmission train Vibration monitoring system. Vibration monitoring system (VMS) constantly checks the performance of safety-critical components, provides warnings in advance of potential equipment failures and collects valuable data for routine maintenance of the helicopters.

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