A Harmonic Tracking Technique for Recovery of Gear Motion From Non-Stationary Vibration Signals

1995 ◽  
Author(s):  
Christopher A. Lerch ◽  
Richard H. Lyon
Keyword(s):  
Diagnostic System ◽  
Time Spectrum ◽  
Time Dependent ◽  
Invasive Technique ◽  
Signal Distortion ◽  
Vibration Signals ◽  
Tracking Method ◽  
Non Invasive ◽  
Stationary Vibration ◽  
Short Time

Abstract A method termed harmonic tracking is developed to recover time dependent gear motion from machine casing vibration. The harmonic tracking method uses short-time spectral generation and a subsequent set of algorithms to locate and track gear meshing frequencies as functions of time. The meshing frequencies are then integrated with respect to time to obtain the rotation of individual gears. More specifically, spectral generation is performed using the discrete Fourier transform, and the locating and tracking algorithms involve locating tones in each short-time spectrum and tracking them through successive spectra to recover gear meshing harmonics. The harmonic tracking method is found to be more robust than demodulation-based methods in the presence of measurement noise and signal distortion from the structural transfer function between gears and the casing. The harmonic tracking method is tested, both through simulation and experiments involving motor-operated valves (MOV’s) as part of the development of a diagnostic system for MOV’s. In all cases, the harmonic tracking method is found to recover gear motion with sufficient accuracy to perform diagnostics. The harmonic tracking method should be generally applicable to situations in which a non-invasive technique is required for determining the time-dependent angular speeds and displacements of gearbox input, intermediary, and output shafts.

scholarly journals Biospeckle Optical Coherence Tomography (bOCT) in the Speedy Assessment of the Responses of the Seeds of Raphanus sativus L. (Kaiware Daikon) to Acid Mine Drainage (AMD)

2021 ◽  
Vol 12 (1) ◽  
pp. 355
Author(s):  
Danyang Li ◽  
Uma Maheswari Rajagopalan ◽  
Y. Sanath K. De Silva ◽  
Fenwu Liu ◽  
Hirofumi Kadono
Keyword(s):  
Optical Coherence Tomography ◽  
Acid Mine Drainage ◽  
Mine Drainage ◽  
Mineral Resources ◽  
Vital Role ◽  
Invasive Technique ◽  
Optical Coherence ◽  
Non Invasive ◽  
Acid Mine ◽  
Short Time

The extraction of mineral resources from mines plays a vital role in global socio-economic development. However, acid mine drainage (AMD) has been one of the major pollutants, and a vast area of the agricultural fields has been polluted. Therefore, techniques for monitoring the response of plants to AMD that arise during mineral extraction are necessary. In addition, such a technique becomes especially valuable to understand how the plants could play a role in the phytoremediation of AMD. We propose the use of biospeckle Optical Coherence Tomography (bOCT) to investigate the response of Kaiware daikon seeds under the exposure to simulated AMD at two different concentrations of 40 mL/L and 80 mL/L. OCT images of the Kaiware daikon seed were obtained at a speed of 10 frames per second (1 frame: 512 × 2048 pixels) for a few tens of seconds. For each pixel of the OCT structural images, the contrast across the temporal axis was calculated to give biospeckle contrast OCT images (bOCT images). It was found that bOCT images clearly distinguished the changes due to 40 mL/L and 80 mL/L of AMD treatments from the control within a short time of around an hour, compared to the conventional OCT images that failed to show any changes. This variation was found to be statistically significant and could reflect the internal activity of the seeds. The proposed bOCT method could be a rapid, non-invasive technique for screening suitable plants in AMD phytoremediation applications.

scholarly journals Some results for analyzing time-dependent frequencies of vibration signals

2002 ◽  
Vol 24 (1) ◽  
pp. 51-64
Author(s):  
Tran Duong Tri
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Wavelet Transform ◽  
Time Dependent ◽  
Short Time Fourier Transform ◽  
Vibration Signals ◽  
Short Time

This paper provides some results for analyzing relations between frequencies and time of vibration signals. These results have been obtained by studying the properties of wavelet transform, the spectral analysis, the Short-time Fourier transform and by using the toolboxes in the software parked MATLAB. We have created the corresponding PC programs in order to realize algorithms and for the illustration of results by exploring examples.

USING DOPPLER TO ASSESS THE FETAL HEALTH FOR THE PREDICTION OF GESTATIONAL OUTCOME

2014 ◽  
pp. 9-18
Author(s):  
Thi Linh Giang Truong ◽  
Vu Quoc Huy Nguyen
Keyword(s):  
Middle Cerebral Artery ◽  
Cerebral Artery ◽  
Umbilical Artery ◽  
Functional Method ◽  
Invasive Technique ◽  
Routine Practice ◽  
Fetal Health ◽  
Uterine Arteries ◽  
Non Invasive ◽  
Key Words Doppler

Background: Assessment of fetal health plays the most important role in prenatal care because of influence of the prediction of gestational outcome. One of the main aims of routine antenatal care is to identify the ‘ at risk ‘ fetus in order to apply clinical interventions which could results in reduced perinatal morbidity and mortality. Doppler ultrasound is a non invasive technique whereby the movement of blood is studied by detecting the change in frequence of reflected sound, Doppler blood flow velocity waves form of fetal side (umbilical artery, middle cerebral artery ...) and maternal side ( uterine arteries) are discussed and monograms for routine practice are presented. Recently this method is important tool for qualifying high risk pregnancies and help early forecasts the health of the babies and mothers disorder. Doppler sonography in obstetrics is a widely accepted functional method of examining the prediction of gestational outcome. Key words: Doppler, umbilical artery, middle cerebral artery, uterine arteries

scholarly journals Deep Learning Approach for Vibration Signals Applications

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3929
Author(s):  
Han-Yun Chen ◽  
Ching-Hung Lee
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Parameters Optimization ◽  
Frequency Spectra ◽  
Vibration Signals ◽  
Bearing Faults ◽  
Time Frequency ◽  
And Performance ◽  
The One ◽  
Short Time

This study discusses convolutional neural networks (CNNs) for vibration signals analysis, including applications in machining surface roughness estimation, bearing faults diagnosis, and tool wear detection. The one-dimensional CNNs (1DCNN) and two-dimensional CNNs (2DCNN) are applied for regression and classification applications using different types of inputs, e.g., raw signals, and time-frequency spectra images by short time Fourier transform. In the application of regression and the estimation of machining surface roughness, the 1DCNN is utilized and the corresponding CNN structure (hyper parameters) optimization is proposed by using uniform experimental design (UED), neural network, multiple regression, and particle swarm optimization. It demonstrates the effectiveness of the proposed approach to obtain a structure with better performance. In applications of classification, bearing faults and tool wear classification are carried out by vibration signals analysis and CNN. Finally, the experimental results are shown to demonstrate the effectiveness and performance of our approach.

scholarly journals Thermal Liquid Biopsy (TLB) Focused on Benign and Premalignant Pancreatic Cyst Diagnosis

2020 ◽  
Vol 11 (1) ◽  
pp. 25
Author(s):  
Sonia Hermoso-Durán ◽  
Guillermo García-Rayado ◽  
Laura Ceballos-Laita ◽  
Carlos Sostres ◽  
Sonia Vega ◽  
...  
Keyword(s):  
Liquid Biopsy ◽  
Pancreatic Cyst ◽  
Point Of View ◽  
Invasive Technique ◽  
Background Current ◽  
Interesting Point ◽  
Pancreatic Lesion ◽  
Non Invasive ◽  
Patient Diagnosis ◽  
New Biomarkers

Background: Current efforts in the identification of new biomarkers are directed towards an accurate differentiation between benign and premalignant cysts. Thermal Liquid Biopsy (TLB) has been previously applied to inflammatory and tumor diseases and could offer an interesting point of view in this type of pathology. Methods: In this work, twenty patients (12 males and 8 females, average ages 62) diagnosed with a pancreatic cyst benign (10) and premalignant (10) cyst lesions were recruited, and biological samples were obtained during the endoscopic ultrasonography procedure. Results: Proteomic content of cyst liquid samples was studied and several common proteins in the different groups were identified. TLB cyst liquid profiles reflected protein content. Also, TLB serum score was able to discriminate between healthy and cysts patients (71% sensitivity and 98% specificity) and between benign and premalignant cysts (75% sensitivity and 67% specificity). Conclusions: TLB analysis of plasmatic serum sample, a quick, simple and non-invasive technique that can be easily implemented, reports valuable information on the observed pancreatic lesion. These preliminary results set the basis for a larger study to refine TLB serum score and move closer to the clinical application of TLB providing useful information to the gastroenterologist during patient diagnosis.

Modeling of non-stationary vibration signals based on the modified Kronecker sequences

PAMM ◽  
2015 ◽  
Vol 15 (1) ◽  
pp. 195-196 ◽  
Author(s):  
Iulian Girip ◽  
Ligia Munteanu
Keyword(s):  
Vibration Signals ◽  
Stationary Vibration
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