Fernando S Schlindwein | University of Leicester (original) (raw)
Papers by Fernando S Schlindwein
… Congress on Sound …, Jan 1, 2005
Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity o... more Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity of such pumps has grown over the years but little research has been done in the area of condition-monitoring of dry-vacuum pumps. Fault detection of one such pump through the use of AutoRegressive (AR) modelling technique and spectral analysis of vibration and acoustic data has been studied. The testing environment is a 5-stage Roots-and-Claw dry-vacuum pump. Usage of spectral analysis for fault prediction in real-time has been conservative due to concerns over large processing requirements especially when large sample sizes and high sampling frequencies are used. In this study it is shown how such concerns can be allayed, to a large extent, by AR modelling, as the AR method has enhanced resolution capabilities compared to the FFT technique even when small sample sizes are used and requires a sampling rate just slightly above Nyquist rate to give good parameter estimates. The AR spectra of both the vibration and acoustic data produced are highly correlated and the frequencies of the maximum peaks are found at the pump's shaft rotational speed and multiples of it. The disadvantage of the AR method is that optimum model order is not known a priori. It was desired to keep the model order low as smaller orders translate to smaller processing requirements for spectral estimation. Several methods of order selection criteria such as AIC (Akaike Information Criterion), FPE (Final Prediction Error), MDL (Minimum Description Length), CAT (Criterion Autoregressive Transfer-function) and the more recent FSIC (Finite Sample Information Criterion) were investigated to find the true order. All the criteria selected approximately the same order. For the vibration data, initial results show that the minimum order required can be as low as 25 and for 90% of the frames the model order does not exceed 45.
Mechanical Systems and Signal Processing, Jan 1, 2009
Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monit... more Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monitoring. The new quantifiers construct a complete quantitative time-frequency analysis: the Wavelet packets relative energy measures the normalized energy of the wavelet packets node; the Total wavelet packets entropy measures how the normalized energies of the wavelet packets nodes are distributed in the frequency domain; the Wavelet packets node entropy describes the uncertainty of the normalized coefficients of the wavelet packets node. Unlike the feature extraction methods directly using the amplitude of wavelet coefficients, the new quantifiers are derived from probability distributions and are more robust in diagnostic applications. By applying these quantifiers to Acoustic Emission signals from faulty bearings of rotating machines, our study shows that both localized defects and advanced contamination faults can be successfully detected and diagnosed if the appropriate quantifier is chosen. The Bayesian classifier is used to quantitatively analyse and evaluate the performance of the proposed quantifiers. We also show that reducing the Daubechies wavelet order or the length of the segment will deteriorate the performance of the quantifiers. A twodimensional diagnostic scheme can also help to improve the diagnostic performance but the improvements are only significant when using lower wavelet orders.
A five stage "Roots and Claw" dry vacuum pump is a typical ind of quasi-steady stat e high speed ... more A five stage "Roots and Claw" dry vacuum pump is a typical ind of quasi-steady stat e high speed rotating machine. The research using the novel Acoustic Emission measureme nt and Wavelet technique aims to develop advanced detection methods for dry vacuum pump s to prevent pumps' failure. In this paper, denoising problem of Acoustic Emission sign al is studied by using Discrete Wavelet Transform thresholding methods. The Donoho-Johnstone t hreshold method and parameter method are studied and compared. The Birgé-Massart strategy outperforms other estimators in our case. The denoised Acoustic Emission signals enable detection of the defect and identification of the type of bearing defect. Care h as to be ta en on proper selecting wavelet basis to reduce the bias and error. The study shows us the Discrete Wavelet Transform-based thresholding method is suitable for Acoustic Emission si gnals to detect bearing defect of rotating machines.
This paper presents a QRS-T subtraction approach for atrial fibrillation (AF) intracardiac atrial... more This paper presents a QRS-T subtraction approach for atrial fibrillation (AF) intracardiac atrial electrograms (AEG). It also presents a comparison between the proposed method and two alternative ventricular subtraction techniques: average beat subtraction (ABS) using a fixed length window and an approach based on flat interpolation for QRS cancellation. Areas of the atrium close to the mitral valve showed stronger ventricular influence on the AEGs when compared with the remaining atrial regions. Ventricular influence affects the spectral power distribution of the AEG and can also affect the estimation of the dominant frequency unless the whole ventricular activity influence (QRS-T) is removed. The average power after QRS-T subtraction is significantly reduced for frequencies above 10 Hz (mostly associated with QRS complexes), as well as for frequencies between 3 and 5.5 Hz, (mostly related to T waves). The results indicate that the proposed approach removes ventricular influence on the AF AEGs better than the QRS cancellation method. Spectral analysis showed that both the ABS and the proposed method do well and no method should be preferred to the other. In the time domain the proposed approach is matched to the lengths and timings of onset and offset for individual QRS-T segments while the ABS approach uses an arbitrary length around the QRS for the pattern used for QRS-T removal.
Atrial fibrillation is the most common cardiac arrhythmia, and it is associated with increased ri... more Atrial fibrillation is the most common cardiac arrhythmia, and it is associated with increased risk of stroke, heart failure and mortality. In this work we describe spectral analysis techniques that are being used in conjunction with visualization algorithms to help guide catheter ablation procedures that aim at treating patients with the arrhythmia.
Physiological …, Jan 1, 2002
Heart rate variability (HRV) has been used as a non-invasive marker of the activity of the autono... more Heart rate variability (HRV) has been used as a non-invasive marker of the activity of the autonomic nervous system and its spectrum analysis gives a measure of the sympatho-vagal balance. If short segments are used in an attempt to improve temporal resolution, autoregressive spectral estimation, where the model order must be estimated, is preferred. In this paper we compare four criteria for the estimation of the 'optimum' model order for an autoregressive (AR) process applied to short segments of tachograms used for HRV analysis. The criteria used were Akaike's final prediction error, Akaike's information criterion, Parzen's criterion of autoregressive transfer function and Rissanen's minimum description length method, and they were first applied to tachograms to verify (i) the range and distribution of model orders obtained and (ii) if the different techniques suggest the same model order for the same frames.
Ultrasound in medicine & biology, Jan 1, 1990
Ultrasound in medicine & biology, Jan 1, 1989
CITATIONS 36 READS 96 3 authors, including:
…, Jan 1, 2001
Cole-Cole model parameters are widely used to interpret electrical geophysical methods and are ob... more Cole-Cole model parameters are widely used to interpret electrical geophysical methods and are obtained by inverting the induced polarization (IP) spectrum. This paper presents a direct inversion method for parameter estimation based on multifold least-squares estimation. Two algorithms are described that provide optimal parameter estimation in the least-squares sense. Simulations demonstrate that both algorithms can provide direct apparent spectral parameter inversion for complex resistivity data. Moreover, the second algorithm is robust under reasonably high noise.
Medical and Biological …, Jan 1, 2002
The long-term aims of this study are to find a parameter derived from the ECG that has a high sen... more The long-term aims of this study are to find a parameter derived from the ECG that has a high sensitivity and specificity to asphyxia and, once we know or suspect that asphyxia occurred, to estimate how severe it was. We carried out a pilot study in which 24 adult Wistar rats were anaesthetised and subjected to controlled asphyxia for specified durations. We measured the pH, 'neurological score' and the ECG, extracting from this heart rate and heart rate variability (HRV). We have developed a technique capable of detecting asphyxia in less than 1 min, based on monitoring the ECG and estimating HRV by measuring the standard deviation of normal RR intervals (the RR interval is the time interval between two consecutive R-points of the QRS complex). In all cases the heart rate decreased and HRV increased, by an average of 46 AE 33 ms in relation to the baseline, at the onset of asphyxia. The comparison of the base level of HRV after and before asphyxia shows promise for the estimation of the severity of the episode; however, the limitations of this study should be noted as they include the small size of the cohort and the methods of analysis.
An investigation into the vibration characteristics of a 'Roots and Claws' based dry vacuum pump ... more An investigation into the vibration characteristics of a 'Roots and Claws' based dry vacuum pump under different operating conditions was conducted. An AutoRegressive (AR)-based condition monitoring algorithm was developed and tested on both a fault-free and a pump with an implanted ceramic bearing with an inner race defect at the High Vacuum (HV) end. The investigation provided some in-depth understanding of the effects of different operating conditions such as speed and load on the vibration of the pump. The first key step in the fault detection scheme was accurate determination of the running speed of the pump. It was observed that the rotating speed of the pump's rotor shaft on which the bearing case was directly connected to was often less than the set speed of the pump due to rotor slip. The second step was envelope demodulation of the time domain vibration signals where the resonance excited by the faultinduced impacts was identified and the vibration signal were bandpass filtered around the resonant peak. The third step is spectral estimation using parametric-based method of AR modelling. The advantage of the AR method is that it can work with smaller sample sizes and sampling rates compared to the more traditional approach of FFT (Fast Fourier Transform) and achieve far superior resolution capabilities. The analysis results showed that the effect of actual speed was predominant in the detection of bearing faults as this was the speed that was used in the calculations of the bearing defect frequencies and had to be determined very accurately. Initial results show that the fault diagnostic scheme is very promising and the bearing fault could be accurately determined at all speeds.
Proceedings of the …, Jan 1, 2007
A Morlet-like wavelet cluster-based method for band-pass filtering and envelope demodulation is d... more A Morlet-like wavelet cluster-based method for band-pass filtering and envelope demodulation is described. Via appropriate choice of wavelet parameters, a wavelet cluster combined with multi-Morlet-like wavelets can be used as a band-pass filter with zero phase shift, flat topped pass-band and rapid attenuation in the transition band. It can be used to extract high frequency natural vibration components. The imaginary part of the Morlet-like wavelet cluster is the Hilbert transformation of its real part. This can be used to implement envelope demodulation and extract the envelope component of the high frequency resonance band. The method is applied for fault diagnosis relating to bearing defects in a dry vacuum pump. It is shown that the fault characteristic frequencies can be extracted effectively. The efficacy of the method is demonstrated in experimental studies.
… Congress on Sound …, Jan 1, 2005
Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity o... more Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity of such pumps has grown over the years but little research has been done in the area of condition-monitoring of dry-vacuum pumps. Fault detection of one such pump through the use of AutoRegressive (AR) modelling technique and spectral analysis of vibration and acoustic data has been studied. The testing environment is a 5-stage Roots-and-Claw dry-vacuum pump. Usage of spectral analysis for fault prediction in real-time has been conservative due to concerns over large processing requirements especially when large sample sizes and high sampling frequencies are used. In this study it is shown how such concerns can be allayed, to a large extent, by AR modelling, as the AR method has enhanced resolution capabilities compared to the FFT technique even when small sample sizes are used and requires a sampling rate just slightly above Nyquist rate to give good parameter estimates. The AR spectra of both the vibration and acoustic data produced are highly correlated and the frequencies of the maximum peaks are found at the pump's shaft rotational speed and multiples of it. The disadvantage of the AR method is that optimum model order is not known a priori. It was desired to keep the model order low as smaller orders translate to smaller processing requirements for spectral estimation. Several methods of order selection criteria such as AIC (Akaike Information Criterion), FPE (Final Prediction Error), MDL (Minimum Description Length), CAT (Criterion Autoregressive Transfer-function) and the more recent FSIC (Finite Sample Information Criterion) were investigated to find the true order. All the criteria selected approximately the same order. For the vibration data, initial results show that the minimum order required can be as low as 25 and for 90% of the frames the model order does not exceed 45.
This paper provides a practical rule for determining the minimum model order for Autoregressive (... more This paper provides a practical rule for determining the minimum model order for Autoregressive (AR) based spectrum analysis of data from rotating machinery. The use of parametric methods for spectral estimation, though having superior frequency resolution than Fast Fourier Transform (FFT) based methods, has remained less favoured mainly because of the difficulties in estimating the model order. The minimum model order p min required is the ratio of the sampling rate and the rotating speed of the machine. This is the number of samples in one shaft revolution. Traditional model order selection criteria, Akaike Information Criterion (AIC), Finite Information Criterion (FPE), Minimum Description Length (MDL), Criterion Autoregressive Transfer-function (CAT), and Finite Information Criterion (FIC) are used to estimate the optimal order. These asymptotic criteria for model order estimation are functions of the prediction error and the optimal order of an AR model is chosen as the minimum of this function. Experimental results, using vibration data taken from a dry vacuum pump at different sampling rates and rotating speeds, show that at there is a marked reduction in the prediction error. p min For low speed rotating machinery, the optimal order is . As the speed of the rotating machine increases, p min there is some advantage in using twice or thrice , to produce more accurate frequency estimates. The Box-p min Jenkins method of order determination using autocorrelation and partial autocorrelations plots are also used for justification of the selection of this minimal order. † Member of the International Institute of Acoustics and Vibration (IIAV) (pp @-@)
Mechanical Systems and Signal Processing, Jan 1, 2009
Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monit... more Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monitoring. The new quantifiers construct a complete quantitative time-frequency analysis: the Wavelet packets relative energy measures the normalized energy of the wavelet packets node; the Total wavelet packets entropy measures how the normalized energies of the wavelet packets nodes are distributed in the frequency domain; the Wavelet packets node entropy describes the uncertainty of the normalized coefficients of the wavelet packets node. Unlike the feature extraction methods directly using the amplitude of wavelet coefficients, the new quantifiers are derived from probability distributions and are more robust in diagnostic applications. By applying these quantifiers to Acoustic Emission signals from faulty bearings of rotating machines, our study shows that both localized defects and advanced contamination faults can be successfully detected and diagnosed if the appropriate quantifier is chosen. The Bayesian classifier is used to quantitatively analyse and evaluate the performance of the proposed quantifiers. We also show that reducing the Daubechies wavelet order or the length of the segment will deteriorate the performance of the quantifiers. A twodimensional diagnostic scheme can also help to improve the diagnostic performance but the improvements are only significant when using lower wavelet orders.
Transactions of the …, Jan 1, 2003
Advances in Medical, …
The MIT-BIH arrhythmia database (48 ECG records of 30 min each) was used to find out, experimenta... more The MIT-BIH arrhythmia database (48 ECG records of 30 min each) was used to find out, experimentally, which combination of centre frequency and bandwidth is 'optimal' for a pre-emphasis digital Finite Impulse Response (FIR) band-pass filter for QRS detection. An exhaustive search was performed for centre frequencies ranging from 13 to 20 Hz and for bandwidths from 5 to 12 Hz, at integer values of 1 Hz for both. The criterion for optimality was simply the filter that, coupled with a simple threshold detector, produced the minimum number of errors (defined as the sum of false-positives and false-negatives). For the whole MIT-BIH database the 'optimum' point was found to be that where centre frequency, f c =19 Hz and bandwidth, BW=9 Hz.
Journal of Biomedical Science, Jan 1, 2010
Dominant frequency (DF) of electrophysiological data is an effective approach to estimate the act... more Dominant frequency (DF) of electrophysiological data is an effective approach to estimate the activation rate during Atrial Fibrillation (AF) and it is important to understand the pathophysiology of AF and to help select candidate sites for ablation. Frequency analysis is used to find and track DF. It is important to minimize the catheter insertion time in the atria as it contributes to the risk for the patients during this procedure, so DF estimation needs to be obtained as quickly as possible. A comparison of computation times taken for spectrum estimation analysis is presented in this paper. Fast Fourier Transform (FFT), Blackman-Tukey (BT), Autoregressive (AR) and Multiple Signal Classification (MUSIC) methods are used to obtain the frequency spectrum of the signals. The time to produce DF was measured for each method. The method which takes the shortest time for analysis is selected for real time application purpose.
In this paper a novel approach is proposed for vibration based fault detection studies by the tra... more In this paper a novel approach is proposed for vibration based fault detection studies by the tracking of pole movements in the complex z domain. Vibration signals obtained from the ball bearings from a High Vacuum (HV) and Low Vacuum (LV) ends of a dry vacuum pump run in normal and fault conditions are modeled as time variant AR (Autoregressive) series.
… Congress on Sound …, Jan 1, 2005
Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity o... more Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity of such pumps has grown over the years but little research has been done in the area of condition-monitoring of dry-vacuum pumps. Fault detection of one such pump through the use of AutoRegressive (AR) modelling technique and spectral analysis of vibration and acoustic data has been studied. The testing environment is a 5-stage Roots-and-Claw dry-vacuum pump. Usage of spectral analysis for fault prediction in real-time has been conservative due to concerns over large processing requirements especially when large sample sizes and high sampling frequencies are used. In this study it is shown how such concerns can be allayed, to a large extent, by AR modelling, as the AR method has enhanced resolution capabilities compared to the FFT technique even when small sample sizes are used and requires a sampling rate just slightly above Nyquist rate to give good parameter estimates. The AR spectra of both the vibration and acoustic data produced are highly correlated and the frequencies of the maximum peaks are found at the pump's shaft rotational speed and multiples of it. The disadvantage of the AR method is that optimum model order is not known a priori. It was desired to keep the model order low as smaller orders translate to smaller processing requirements for spectral estimation. Several methods of order selection criteria such as AIC (Akaike Information Criterion), FPE (Final Prediction Error), MDL (Minimum Description Length), CAT (Criterion Autoregressive Transfer-function) and the more recent FSIC (Finite Sample Information Criterion) were investigated to find the true order. All the criteria selected approximately the same order. For the vibration data, initial results show that the minimum order required can be as low as 25 and for 90% of the frames the model order does not exceed 45.
Mechanical Systems and Signal Processing, Jan 1, 2009
Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monit... more Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monitoring. The new quantifiers construct a complete quantitative time-frequency analysis: the Wavelet packets relative energy measures the normalized energy of the wavelet packets node; the Total wavelet packets entropy measures how the normalized energies of the wavelet packets nodes are distributed in the frequency domain; the Wavelet packets node entropy describes the uncertainty of the normalized coefficients of the wavelet packets node. Unlike the feature extraction methods directly using the amplitude of wavelet coefficients, the new quantifiers are derived from probability distributions and are more robust in diagnostic applications. By applying these quantifiers to Acoustic Emission signals from faulty bearings of rotating machines, our study shows that both localized defects and advanced contamination faults can be successfully detected and diagnosed if the appropriate quantifier is chosen. The Bayesian classifier is used to quantitatively analyse and evaluate the performance of the proposed quantifiers. We also show that reducing the Daubechies wavelet order or the length of the segment will deteriorate the performance of the quantifiers. A twodimensional diagnostic scheme can also help to improve the diagnostic performance but the improvements are only significant when using lower wavelet orders.
A five stage "Roots and Claw" dry vacuum pump is a typical ind of quasi-steady stat e high speed ... more A five stage "Roots and Claw" dry vacuum pump is a typical ind of quasi-steady stat e high speed rotating machine. The research using the novel Acoustic Emission measureme nt and Wavelet technique aims to develop advanced detection methods for dry vacuum pump s to prevent pumps' failure. In this paper, denoising problem of Acoustic Emission sign al is studied by using Discrete Wavelet Transform thresholding methods. The Donoho-Johnstone t hreshold method and parameter method are studied and compared. The Birgé-Massart strategy outperforms other estimators in our case. The denoised Acoustic Emission signals enable detection of the defect and identification of the type of bearing defect. Care h as to be ta en on proper selecting wavelet basis to reduce the bias and error. The study shows us the Discrete Wavelet Transform-based thresholding method is suitable for Acoustic Emission si gnals to detect bearing defect of rotating machines.
This paper presents a QRS-T subtraction approach for atrial fibrillation (AF) intracardiac atrial... more This paper presents a QRS-T subtraction approach for atrial fibrillation (AF) intracardiac atrial electrograms (AEG). It also presents a comparison between the proposed method and two alternative ventricular subtraction techniques: average beat subtraction (ABS) using a fixed length window and an approach based on flat interpolation for QRS cancellation. Areas of the atrium close to the mitral valve showed stronger ventricular influence on the AEGs when compared with the remaining atrial regions. Ventricular influence affects the spectral power distribution of the AEG and can also affect the estimation of the dominant frequency unless the whole ventricular activity influence (QRS-T) is removed. The average power after QRS-T subtraction is significantly reduced for frequencies above 10 Hz (mostly associated with QRS complexes), as well as for frequencies between 3 and 5.5 Hz, (mostly related to T waves). The results indicate that the proposed approach removes ventricular influence on the AF AEGs better than the QRS cancellation method. Spectral analysis showed that both the ABS and the proposed method do well and no method should be preferred to the other. In the time domain the proposed approach is matched to the lengths and timings of onset and offset for individual QRS-T segments while the ABS approach uses an arbitrary length around the QRS for the pattern used for QRS-T removal.
Atrial fibrillation is the most common cardiac arrhythmia, and it is associated with increased ri... more Atrial fibrillation is the most common cardiac arrhythmia, and it is associated with increased risk of stroke, heart failure and mortality. In this work we describe spectral analysis techniques that are being used in conjunction with visualization algorithms to help guide catheter ablation procedures that aim at treating patients with the arrhythmia.
Physiological …, Jan 1, 2002
Heart rate variability (HRV) has been used as a non-invasive marker of the activity of the autono... more Heart rate variability (HRV) has been used as a non-invasive marker of the activity of the autonomic nervous system and its spectrum analysis gives a measure of the sympatho-vagal balance. If short segments are used in an attempt to improve temporal resolution, autoregressive spectral estimation, where the model order must be estimated, is preferred. In this paper we compare four criteria for the estimation of the 'optimum' model order for an autoregressive (AR) process applied to short segments of tachograms used for HRV analysis. The criteria used were Akaike's final prediction error, Akaike's information criterion, Parzen's criterion of autoregressive transfer function and Rissanen's minimum description length method, and they were first applied to tachograms to verify (i) the range and distribution of model orders obtained and (ii) if the different techniques suggest the same model order for the same frames.
Ultrasound in medicine & biology, Jan 1, 1990
Ultrasound in medicine & biology, Jan 1, 1989
CITATIONS 36 READS 96 3 authors, including:
…, Jan 1, 2001
Cole-Cole model parameters are widely used to interpret electrical geophysical methods and are ob... more Cole-Cole model parameters are widely used to interpret electrical geophysical methods and are obtained by inverting the induced polarization (IP) spectrum. This paper presents a direct inversion method for parameter estimation based on multifold least-squares estimation. Two algorithms are described that provide optimal parameter estimation in the least-squares sense. Simulations demonstrate that both algorithms can provide direct apparent spectral parameter inversion for complex resistivity data. Moreover, the second algorithm is robust under reasonably high noise.
Medical and Biological …, Jan 1, 2002
The long-term aims of this study are to find a parameter derived from the ECG that has a high sen... more The long-term aims of this study are to find a parameter derived from the ECG that has a high sensitivity and specificity to asphyxia and, once we know or suspect that asphyxia occurred, to estimate how severe it was. We carried out a pilot study in which 24 adult Wistar rats were anaesthetised and subjected to controlled asphyxia for specified durations. We measured the pH, 'neurological score' and the ECG, extracting from this heart rate and heart rate variability (HRV). We have developed a technique capable of detecting asphyxia in less than 1 min, based on monitoring the ECG and estimating HRV by measuring the standard deviation of normal RR intervals (the RR interval is the time interval between two consecutive R-points of the QRS complex). In all cases the heart rate decreased and HRV increased, by an average of 46 AE 33 ms in relation to the baseline, at the onset of asphyxia. The comparison of the base level of HRV after and before asphyxia shows promise for the estimation of the severity of the episode; however, the limitations of this study should be noted as they include the small size of the cohort and the methods of analysis.
An investigation into the vibration characteristics of a 'Roots and Claws' based dry vacuum pump ... more An investigation into the vibration characteristics of a 'Roots and Claws' based dry vacuum pump under different operating conditions was conducted. An AutoRegressive (AR)-based condition monitoring algorithm was developed and tested on both a fault-free and a pump with an implanted ceramic bearing with an inner race defect at the High Vacuum (HV) end. The investigation provided some in-depth understanding of the effects of different operating conditions such as speed and load on the vibration of the pump. The first key step in the fault detection scheme was accurate determination of the running speed of the pump. It was observed that the rotating speed of the pump's rotor shaft on which the bearing case was directly connected to was often less than the set speed of the pump due to rotor slip. The second step was envelope demodulation of the time domain vibration signals where the resonance excited by the faultinduced impacts was identified and the vibration signal were bandpass filtered around the resonant peak. The third step is spectral estimation using parametric-based method of AR modelling. The advantage of the AR method is that it can work with smaller sample sizes and sampling rates compared to the more traditional approach of FFT (Fast Fourier Transform) and achieve far superior resolution capabilities. The analysis results showed that the effect of actual speed was predominant in the detection of bearing faults as this was the speed that was used in the calculations of the bearing defect frequencies and had to be determined very accurately. Initial results show that the fault diagnostic scheme is very promising and the bearing fault could be accurately determined at all speeds.
Proceedings of the …, Jan 1, 2007
A Morlet-like wavelet cluster-based method for band-pass filtering and envelope demodulation is d... more A Morlet-like wavelet cluster-based method for band-pass filtering and envelope demodulation is described. Via appropriate choice of wavelet parameters, a wavelet cluster combined with multi-Morlet-like wavelets can be used as a band-pass filter with zero phase shift, flat topped pass-band and rapid attenuation in the transition band. It can be used to extract high frequency natural vibration components. The imaginary part of the Morlet-like wavelet cluster is the Hilbert transformation of its real part. This can be used to implement envelope demodulation and extract the envelope component of the high frequency resonance band. The method is applied for fault diagnosis relating to bearing defects in a dry vacuum pump. It is shown that the fault characteristic frequencies can be extracted effectively. The efficacy of the method is demonstrated in experimental studies.
… Congress on Sound …, Jan 1, 2005
Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity o... more Oil-free dry-vacuum pumps are prevalent in semiconductor plants worldwide today. The popularity of such pumps has grown over the years but little research has been done in the area of condition-monitoring of dry-vacuum pumps. Fault detection of one such pump through the use of AutoRegressive (AR) modelling technique and spectral analysis of vibration and acoustic data has been studied. The testing environment is a 5-stage Roots-and-Claw dry-vacuum pump. Usage of spectral analysis for fault prediction in real-time has been conservative due to concerns over large processing requirements especially when large sample sizes and high sampling frequencies are used. In this study it is shown how such concerns can be allayed, to a large extent, by AR modelling, as the AR method has enhanced resolution capabilities compared to the FFT technique even when small sample sizes are used and requires a sampling rate just slightly above Nyquist rate to give good parameter estimates. The AR spectra of both the vibration and acoustic data produced are highly correlated and the frequencies of the maximum peaks are found at the pump's shaft rotational speed and multiples of it. The disadvantage of the AR method is that optimum model order is not known a priori. It was desired to keep the model order low as smaller orders translate to smaller processing requirements for spectral estimation. Several methods of order selection criteria such as AIC (Akaike Information Criterion), FPE (Final Prediction Error), MDL (Minimum Description Length), CAT (Criterion Autoregressive Transfer-function) and the more recent FSIC (Finite Sample Information Criterion) were investigated to find the true order. All the criteria selected approximately the same order. For the vibration data, initial results show that the minimum order required can be as low as 25 and for 90% of the frames the model order does not exceed 45.
This paper provides a practical rule for determining the minimum model order for Autoregressive (... more This paper provides a practical rule for determining the minimum model order for Autoregressive (AR) based spectrum analysis of data from rotating machinery. The use of parametric methods for spectral estimation, though having superior frequency resolution than Fast Fourier Transform (FFT) based methods, has remained less favoured mainly because of the difficulties in estimating the model order. The minimum model order p min required is the ratio of the sampling rate and the rotating speed of the machine. This is the number of samples in one shaft revolution. Traditional model order selection criteria, Akaike Information Criterion (AIC), Finite Information Criterion (FPE), Minimum Description Length (MDL), Criterion Autoregressive Transfer-function (CAT), and Finite Information Criterion (FIC) are used to estimate the optimal order. These asymptotic criteria for model order estimation are functions of the prediction error and the optimal order of an AR model is chosen as the minimum of this function. Experimental results, using vibration data taken from a dry vacuum pump at different sampling rates and rotating speeds, show that at there is a marked reduction in the prediction error. p min For low speed rotating machinery, the optimal order is . As the speed of the rotating machine increases, p min there is some advantage in using twice or thrice , to produce more accurate frequency estimates. The Box-p min Jenkins method of order determination using autocorrelation and partial autocorrelations plots are also used for justification of the selection of this minimal order. † Member of the International Institute of Acoustics and Vibration (IIAV) (pp @-@)
Mechanical Systems and Signal Processing, Jan 1, 2009
Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monit... more Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monitoring. The new quantifiers construct a complete quantitative time-frequency analysis: the Wavelet packets relative energy measures the normalized energy of the wavelet packets node; the Total wavelet packets entropy measures how the normalized energies of the wavelet packets nodes are distributed in the frequency domain; the Wavelet packets node entropy describes the uncertainty of the normalized coefficients of the wavelet packets node. Unlike the feature extraction methods directly using the amplitude of wavelet coefficients, the new quantifiers are derived from probability distributions and are more robust in diagnostic applications. By applying these quantifiers to Acoustic Emission signals from faulty bearings of rotating machines, our study shows that both localized defects and advanced contamination faults can be successfully detected and diagnosed if the appropriate quantifier is chosen. The Bayesian classifier is used to quantitatively analyse and evaluate the performance of the proposed quantifiers. We also show that reducing the Daubechies wavelet order or the length of the segment will deteriorate the performance of the quantifiers. A twodimensional diagnostic scheme can also help to improve the diagnostic performance but the improvements are only significant when using lower wavelet orders.
Transactions of the …, Jan 1, 2003
Advances in Medical, …
The MIT-BIH arrhythmia database (48 ECG records of 30 min each) was used to find out, experimenta... more The MIT-BIH arrhythmia database (48 ECG records of 30 min each) was used to find out, experimentally, which combination of centre frequency and bandwidth is 'optimal' for a pre-emphasis digital Finite Impulse Response (FIR) band-pass filter for QRS detection. An exhaustive search was performed for centre frequencies ranging from 13 to 20 Hz and for bandwidths from 5 to 12 Hz, at integer values of 1 Hz for both. The criterion for optimality was simply the filter that, coupled with a simple threshold detector, produced the minimum number of errors (defined as the sum of false-positives and false-negatives). For the whole MIT-BIH database the 'optimum' point was found to be that where centre frequency, f c =19 Hz and bandwidth, BW=9 Hz.
Journal of Biomedical Science, Jan 1, 2010
Dominant frequency (DF) of electrophysiological data is an effective approach to estimate the act... more Dominant frequency (DF) of electrophysiological data is an effective approach to estimate the activation rate during Atrial Fibrillation (AF) and it is important to understand the pathophysiology of AF and to help select candidate sites for ablation. Frequency analysis is used to find and track DF. It is important to minimize the catheter insertion time in the atria as it contributes to the risk for the patients during this procedure, so DF estimation needs to be obtained as quickly as possible. A comparison of computation times taken for spectrum estimation analysis is presented in this paper. Fast Fourier Transform (FFT), Blackman-Tukey (BT), Autoregressive (AR) and Multiple Signal Classification (MUSIC) methods are used to obtain the frequency spectrum of the signals. The time to produce DF was measured for each method. The method which takes the shortest time for analysis is selected for real time application purpose.
In this paper a novel approach is proposed for vibration based fault detection studies by the tra... more In this paper a novel approach is proposed for vibration based fault detection studies by the tracking of pole movements in the complex z domain. Vibration signals obtained from the ball bearings from a High Vacuum (HV) and Low Vacuum (LV) ends of a dry vacuum pump run in normal and fault conditions are modeled as time variant AR (Autoregressive) series.