An Introduction to Harmonic Wavelet Analysis of Machine Vibrations

Dogs with rapid ventricular pacing (RVP)-induced congestive heart failure (CHF) have inducible atrial tachycardia, flutter, and fibrillation (AF). We tested the hypothesis that rapid atrial activation in multiple regions and at different rates is responsible for sustained AF in this CHF model. We studied 12 episodes of sustained (>10 minutes) AF induced in 12 dogs with CHF produced by 3-6 weeks of RVP at 230 beats/minute. High-density mapping of AF was performed using 382 unipolar atrial electrograms recorded simultaneously from epicardial electrodes on the right (RA) and left atria (LA) and Bachmann's bundle. AF mechanisms were based on Fast Fourier Transform (FFT) analysis and activation sequence mapping. A driver was defined as a rapid stable activation region with a single dominant frequency peak in FFT analysis. During AF, three FFT and activation patterns were seen: (1) a single LA driver (7.8 +/- 1.1 Hz) near the pulmonary veins (PVs) with irregular activation in the rest of the atria (n = 4); (2) simultaneous, multisite, biatrial drivers at differing frequencies (LA vs RA dominant frequency gradient: 1.3 +/- 0.8 Hz) near the PVs (8.4 +/- 0.3 Hz) and high RA (8.5 +/- 1.5 Hz) (n = 7); and (3) biatrial irregular activation with multiple and/or broadband frequency peaks without a dominant frequency. (LA: 7.1-11.4 Hz; RA: 5.9-7.7 Hz) (n = 1). Atrial drivers had either a focal activation pattern or were due to a macroreentrant circuit around the PVs. In this CHF model, FFT analysis and activation sequence mapping demonstrate that sustained AF is characterized by single and multiple, stable LA and RA drivers with predominant sources in the PVs and high RA causing fibrillatory conduction.

Plastic pipe are widely used in many fields for the fluid or gaseous product conveyance but basic components of a plastic material made it very sensitive to damage, which requires techniques for detecting damage reliable and efficient. Ultrasonic guided wave is a sensitive method based on propagation of low-frequency excitation in solid structures for damage detection. Ultrasonic guided wave method are performed to investigate the effect of crack to the frequency signal using Fast Fourier Transform (FFT) analysis. This paper researched to determine performance of ultrasonic guided wave method in order to detect crack in buried pipeline. It was found that for an uncrack pipe, FFT analysis shows one peak which is the operating frequency by the piezoelectric actuator itself while the FFT analysis for single cracked pipe shows two peak which is the operating frequency by the piezoelectric actuator itself and the resultant frequency from the crack. For multi cracked pipe, the frequency signal shows more than two peak depend the number of crack. The results presented here may facilitate improvements in the accuracy and precision of pipeline crack detection.

In the present work, Heart Rate Variability (HRV) is described by time-frequency representation (TFR), in order to stratify hypertrophic cardiomyopathy (HCM) patients with increasing risk of suffering sudden cardiac death (SCD). TFR and Fast Fourier Transform (FFT) analysis are also compared. The analysis is based on three frequency bands: VLF, 0-0.04 Hz; LF, 0.04-0.15 Hz; and KF, 0.15-0.45 Hz. New variables based on the instantaneous frequency and energy functions using TFR and time-domain analysis allow to discriminate HCM patients with high risk and low risk of SCD (p<0.05). Results shown that TFR analysis of the HRV seems to present more robustness than FFT analysis in order to characterize HRV.

Objective: The purpose of this study is to compare the capsular structure appearing in follicular adenoma and papillary thyroid carcinoma to differentiate the benign and malignant thyroid nodules. Methods: Second Harmonic Generation (SHG) Microscopy was used to image collagen distribution in the capsules of several types of nodules. The tissue fragments were formalin-fixed, paraffin-embedded but without H&amp;E staining, with 4-5 microns thick sections. From the same sample, two consecutive sections were made. The first was colored with H&amp;E and capsule images were acquired with an optical microscope. The second was not colored with H&amp;E. On the uncolored sample, type I collagen from the capsule was visualized by SHG microscopy. In addition, a parameter was used to study the orientation of collagen fibers, obtained from the Fast Fourier Transform (FFT) analysis of 2D-images. Results: SHG microscopy images were acquired to assess the collagen organization of tumoral capsular thyroid nodules previously diagnosed as benign or malignant by conventional H&amp;E staining. Different degree of collagen fibers orientation was observed from the two kinds of capsules and quantified using FFT analysis. Conclusion: These above described microscopy method can be used to distinguish between benign and malignant thyroid nodules, based on different degree of the capsular collagen fibers orientation.

Objective: The phenomenon of Sub Synchronous Resonance (SSR) on series-compensated long transmission line with steam turbine generator results into adverse oscillations. Therefore, occurrence of SSR should be reduced to the lowest possible level. Method/Analysis: In this paper, the use of STATCOM and subsynchronous damping controller (SSDC) is proposed to alleviate SSR. The rotor speed deviation of generator is being captured and given to the STATCOM. The IEEE second benchmark model (IEEE SBM) on SSR is adopted to analyze and validate the proposed controller. For this, the controller is applied on STATCOM, which in turn is regulating the line. Findings: SSR generates due to the presence of frequency other than the nominal frequency in the system. By calculating frequency response and FFT analysis, the resonant frequency present in the system, is calculated. Then conventional STATCOM is applied, which shows that STATCOM with no auxiliary control is not capable of damping the SSR oscillations. But with auxiliary SSDC on same STATCOM, effectively mitigate the SSR. Novelty/Improvement: The SSR alleviation is done by conducting transient simulations using MATLAB environment on detailed three-phase model, which is non-linear in nature. Fast Fourier Transform (FFT) analysis is also performed to demonstrate the capability of proposed controller.

The most vivacious area of the image processing is image enhancement. Newer techniques and ideas are being routinely incorporated to this field for the proper enhancement to make the original image suitable for some specific purposes. However, the techniques that are suitable for X-ray image enhancement may not necessarily be suitable for enhancement of the Satellite Telescope Transmitted (STT) images. Many times, Medical images especially X-ray images are required to be sharper than its original version for proper information extraction that is necessary for diagnostic purposes. Homomorphic filters that actually belong to the group of the sharpening filters can be employed for finding fine details in the X-ray images. The Homomorphic filters use the Discrete Fourier Transforms (DFT) as the core transform. Presently, more efficient tools for transformations are being used; such as the Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Fast Wavelet Transform (FWT) in digital image processing. In this paper, along with the conventional DFT technique, DCT, DWT, FFT and FWT are incorporated in the image transformation process that consequently modifies the core process of Homomorphic filters. The performance of the resulting modified Homomorphic filters are compared with that of the original filter. The performance enrichment has become evident from the numerical and the visual comparisons.

Continuous Condition Monitoring of the machine is importan to improve efficiency of the machine, to avoid unexpected accidents and financial losses. Condition monitoring using audio signal processing is focused in this paper. The sound of the machine carries information about the machine condition. The change in features of audio signal are observed using the Peak Variation Response (PVR) of the Fast Fourier Transform (FFT) of signal. In this paper, the conventional FFT method has been used to prove that, it is sufficient for the detection of abnormalities due to different loading condition of the machine using audio signature. And a study on PVR of Intrinsic Mode Function (IMF) has been carried out to present the cause of variation in the energy and frequency of the oscillations of audio frequency (AF) modulated signals.

A new apparatus for measuring the dynamic dividing error between hob and worktable in large gear hobbing machines is described in which a pair of small and high sensitive servoaccelerometers are mounted tangentially on a periphery of the large worktable, 180° apart, in order to detect the non-uniformity of rotation of the worktable. Two acceleration signals from the servo-accelerometers are added on the workthble, so as to be additive for the circumferential acceleration and null each other for the rectilinear acceleration of the worktable. After the circumferential acceleration signal transmitted with a telemeter is processed by a pulse signal from the rotary encoder attached to hob shaft in this apparatus, the dynamic dividing error can be obtained. In an experimental use with a large size (3.3 m worktable diameter) gear hobbing machine, the dynamic dividing error has been measured and recorded. By transforming the recorded analogue signal with an FFT (Fast Fourier Transform) analyzer and by consulting to the schematic drawing of the rotational transmission mechanism, specific parts in the mechanism have been identified that cause the dividing error. Also, by transforming the circumferential acceleration of the worktable during quick starting test with an FFT analyzer, rotational natural frequency of the worktable can be obtained easily.

Measuring rectilinear flow within the anterior chamber in phacoemulsification procedures

Flow Analysis of 30 kW Gate Turbine Using Permanent Magnetic Generator

Influence of nanoparticle additives on vibration characteristics in fluid film lubricated journal bearing using real time analysis

Artificial intelligence and condition monitoring and diagnostics of systems are emerging, computer-based transdisciplines. The origins of the theoretical kernels of both transdisciplines can be traced to the last century, but the richly structured theories in the body of knowledge that supports the present work in the cognitive sciences and our recently achieved ability to make real-time decisions related to the operation and maintenance of modern, large-scale, complex mechanical systems are due, in large part, to the explosion of synergistic activity in systems thinking and computers which has occurred in the past three decades. In artificial intelligence one strives to make machines (usually, digital computers) do the sorts of things that the human mind does, including making decisions and problem solving, which is an essential element in condition monitoring and diagnostics as well. Thus there is a strong link between the two transdisciplines. A generic definition of artificialintelligence is given above; however, there is no universally accepted definition of the term conditionmonitoringanddiagnostics, either in its general form or in one of its specific forms, say, the condition monitoring and diagnostics of machines. Nevertheless, it is believed that most practitioners of the condition monitoring and diagnostics art would agree that the activities encompassed by the term can be characterized as a two-phase sequence of processes designed to monitor the condition of an operating, functioning system for the purpose of diagnosing faults in the system. Monitoring is a passive, system-specific, information and data gathering process. Diagnostics is an interactive decision-making process in which the unique, system-specific information and data obtained in the monitoring phase are used by a human or computer-based decision maker to decide if faults exist in the system, where they are located, their criticality and what advisory and/or corrective action should be taken. In the diagnostic phase, computer-based decision making (read ‘‘artificial intelligence’’) can be used to support decisions made by a human or to make and implement decisions automatically. Both cases are discussed here, using the condition monitoring and diagnostics of a gas turbine as an illustrative example.

The fast Fourier transform (FFT) can be used to implement a spectrum analyzer by digitizing the input waveform and performing an FFT on the time domain signal to obtain the frequency domain representation. What seems to be a simple measurement technique often turns out to be much more complicated in practice. Given reasonable computational power, usually in the form of a digital signal processor (DSP), field programmable gate array (FPGA) or custom integrated circuit, the FFT analyzer can provide significant speed improvement over the more traditional swept analyzer. The classic FFT analyzer (also called a dynamic signal analyzer) covers the frequency range from DC up to a few hundred kilohertz. These analyzers are typically applied to audio and mechanical measurements.

An objective evaluation method for woven fabric pilling has been developed using image processing and statistical analysis. Five ASTM photographic standard images were analyzed to determine a characterization method for fabric pilling. Images were filtered by various image analysis techniques such as fast Fourier transformation (FFT) and fast wavelet transformation (FWT). Three parameters including the number of pills, the total pixel area of pilling, and the sum of the gray values of pill images have been defined and extracted automatically from the images. Finally, the relationship between pilling grade and those parameters has been established by a series of statistical analyses.

Neurons as sensors: individual and cascaded chemical sensing