Spectral Coherence Analysis between Grinding Interaction Forces and the Relative Motion of the Workpiece and the Cutting Tool
Grinding operation is performed in order to obtain desired surfaces precisely in machining process. The needed relative motion between the cutting tool and the workpiece is generally created either by the movement of the cutting tool or by the movement of the workpiece or by the movement of both of them as in our case. For all these cases, the coherence level between the movements and the interaction forces is a key influential parameter for efficient grinding. Therefore, in this work, spectral coherence analysis has been performed to investigate the coherence level between grinding interaction forces and the movement of the workpiece on our robotic-grinding experimental setup in METU Mechatronics Laboratory.
Structural Health Monitoring of Buildings and Infrastructure
Structures such as buildings, bridges, dams, wind turbines etc. need to be maintained against various factors such as deterioration, excessive loads, environment, temperature, etc. Choosing an appropriate monitoring system is important for determining any critical damage to a structure and address that to avoid any adverse consequence. Structural Health Monitoring (SHM) has emerged as an effective technique to monitor the health of the structures. SHM refers to an ongoing structural performance assessment using different kinds of sensors attached to or embedded in the structures to evaluate their integrity and safety to help engineers decide on rehabilitation measures. Ability of SHM in identifying the location and severity of structural damages by considering any changes in characteristics of the structures such as their frequency, stiffness and mode shapes helps engineers to monitor the structures and take the most effective corrective actions to maintain their safety and extend their service life. The main objective of this study is to review the overall SHM process specifically determining the natural frequency of an instrumented simply-supported concrete beam using modal testing and finite element model updating.
Energy Detection Based Sensing and Primary User Traffic Classification for Cognitive Radio
As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.
Comparison of Back-Projection with Non-Uniform Fast Fourier Transform for Real-Time Photoacoustic Tomography
Photoacoustic imaging is the imaging technology that combines the optical imaging and ultrasound. This provides the high contrast and resolution due to optical imaging and ultrasound imaging, respectively. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer and digital acquisition (DAQ) board. There are two types of algorithm for reconstructing the photoacoustic signal. One is back-projection algorithm, the other is FFT algorithm. Especially, we used the non-uniform FFT algorithm. To evaluate the performance of our system and algorithms, we monitored two wires that stands at interval of 2.89 mm and 0.87 mm. Then, we compared the images reconstructed by algorithms. Finally, we monitored the two hairs crossed and compared between these algorithms.
Modified Scaling-Free CORDIC Based Pipelined Parallel MDC FFT and IFFT Architecture for Radix 2^2 Algorithm
An innovative approach to develop modified scaling free CORDIC based two parallel pipelined Multipath Delay Commutator (MDC) FFT and IFFT architectures for radix 22 FFT algorithm is presented. Multipliers and adders are the most important data paths in FFT and IFFT architectures. Multipliers occupy high area and consume more power. In order to optimize the area and power overhead, modified scaling-free CORDIC based complex multiplier is utilized in the proposed design. In general twiddle factor values are stored in RAM block. In the proposed work, modified scaling-free CORDIC based twiddle factor generator unit is used to generate the twiddle factor and efficient switching units are used. In addition to this, four point FFT operations are performed without complex multiplication which helps to reduce area and power in the last two stages of the pipelined architectures. The design proposed in this paper is based on multipath delay commutator method. The proposed design can be extended to any radix 2n based FFT/IFFT algorithm to improve the throughput. The work is synthesized using Synopsys design Compiler using TSMC 90-nm library. The proposed method proves to be better compared to the reference design in terms of area, throughput and power consumption. The comparative analysis of the proposed design with Xilinx FPGA platform is also discussed in the paper.
A Fault Analysis Cracked-Rotor-to-Stator Rub and Unbalance by Vibration Analysis Technique
An analytical 4-DOF nonlinear model of a de Laval
rotor-stator system based on Energy Principles has been used
theoretically and experimentally to investigate fault symptoms in a
rotating system. The faults, namely rotor-stator-rub, crack and
unbalance are modeled as excitations on the rotor shaft. Mayes
steering function is used to simulate the breathing behaviour of the
crack. The fault analysis technique is based on waveform signal,
orbits and Fast Fourier Transform (FFT) derived from simulated and
real measured signals. Simulated and experimental results manifest
considerable mutual resemblance of elliptic-shaped orbits and FFT
for a same range of test data.
Motor Gear Fault Diagnosis by Current, Noise and Vibration on AC Machine Considering Environment
Lots of motors have been being used in industry.
Therefore many researchers have studied about the failure diagnosis of
motors. In this paper, the effect of measuring environment for
diagnosis of gear fault connected to a motor shaft is studied. The fault
diagnosis is executed through the comparison of normal gear and
abnormal gear. The measured FFT data are compared with the normal
data and analyzed for q-axis current, noise and vibration. For bad and
good environment, the diagnosis results are compared. From these, it
is shown that the bad measuring environment may not be able to detect
exactly the motor gear fault. Therefore it is emphasized that the
measuring environment should be carefully prepared.
Vibration Analysis of Gas Turbine SIEMENS 162MW - V94.2 Related to Iran Power Plant Industry in Fars Province
Vibration analysis of most critical equipment is considered as one of the most challenging activities in preventive maintenance. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of these kinds of equipments are developed too much in recent years. On the other hand, there are too much operation factors like inlet and outlet pressures and temperatures that should be monitored. In this paper, some of the most effective concepts and techniques related to gas turbine vibration analysis are discussed. In addition, a gas turbine SIEMENS 162MW - V94.2 vibration case history related to Iran power industry in Fars province is explained. Vibration monitoring system and machinery technical specification are introduced. Besides, absolute and relative vibration trends, turbine and compressor orbits, Fast Fourier transform (FFT) in absolute vibrations, vibration modal analysis, turbine and compressor start up and shut down conditions, bode diagrams for relative vibrations, Nyquist diagrams and waterfall or three-dimensional FFT diagrams in startup and trip conditions are discussed with relative graphs. Furthermore, Split Resonance in gas turbines is discussed in details. Moreover, some updated vibration monitoring system, blade manufacturing technique and modern damping mechanism are discussed in this paper.
, turbine compressor
, vibration data collector
, condition monitoring
, non-contact probe
, Relative Vibration
, Absolute Vibration
, Split Resonance
, Time Wave Form (TWF)
, Fast Fourier transform (FFT).
Vibration, Lubrication and Machinery Consideration for a Mixer Gearbox Related to Iran Oil Industries
In this paper, some common gearboxes vibration analysis methods and condition monitoring systems are explained. In addition, an experimental gearbox vibration analysis is discussed through a critical case history for a mixer gearbox related to Iran oil industry. The case history also consists of gear manufacturing (machining) recommendations, lubrication condition of gearbox and machinery maintenance activities that caused reduction in noise and vibration of the gearbox. Besides some of the recent patents and innovations in gearboxes, lubrication and vibration monitoring systems explained. Finally micro pitting and surface fatigue in pinion and bevel of mentioned horizontal to vertical gearbox discussed in details.
, condition monitoring
, time wave form (TWF)
, fast Fourier transform (FFT)
, gear mesh frequency (GMF)
, Shock Pulse measurement (SPM)
, bearing condition unit (BCU)
, bevel gear
, micro pitting
, surface fatigue.
Detecting Cavitation in a Vertical Sea water Centrifugal Lift Pump Related to Iran Oil Industry Cooling Water Circulation System
Cavitation is one of the most well-known process faults that may occur in different industrial equipment especially centrifugal pumps. Cavitation also may happen in water pumps and turbines. Sometimes cavitation has been severe enough to wear holes in the impeller and damage the vanes to such a degree that the impeller becomes very ineffective. More commonly, the pump efficiency will decrease significantly during cavitation and continue to decrease as damage to the impeller increases. Typically, when cavitation occurs, an audible sound similar to ‘marbles’ or ‘crackling’ is reported to be emitted from the pump. In this paper, the most effective monitoring items and techniques in detecting cavitation discussed in details. Besides, some successful solutions for solving this problem for sea water vertical Centrifugal lift Pump discussed through a case history related to Iran oil industry. Furthermore, balance line modification, strainer choking and random resonance in sea water pumps discussed. In addition, a new Method for diagnosing mechanical conditions of sea water vertical Centrifugal lift Pumps introduced. This method involves disaggregating bus current by device into disaggregated currents having correspondences with operating currents in response to measured bus current. Moreover, some new patents and innovations in mechanical sea water pumping and cooling systems discussed in this paper.
Vibration Analysis of an Alstom Typhoon Gas Turbine Power Plant Related to Iran Oil Industry
Vibration analysis is the most important factor in preventive maintenance. Gas turbine vibration analysis is also one of the most challenging categories in most critical equipment monitoring systems. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of this kind of equipment developed too much in recent years. On the other hand, too much operation condition consideration in this kind of equipment should be adjusted properly like inlet and outlet pressure and temperature for both turbine and compressor. In this paper the most important tools and hypothesis used for analyzing of gas turbine power plants discussed in details through a real case history related to an Alstom Typhoon gas turbine power plant in Iran oil industries. In addition, the basic principal of vibration behavior caused by mechanical unbalance in gas turbine rotor discussed in details.
Hydraulic Unbalance in Oil Injected Twin Rotary Screw Compressor Vibration Analysis (A Case History Related to Iran Oil Industries)
Vibration analysis of screw compressors is one of the most challenging cases in preventive maintenance. This kind of equipment considered as vibration bad actor facilities in industrial plants. On line condition monitoring systems developed too much in recent years. The high frequency vibration of ball bearings, gears, male and female caused complex fast Fourier transform (FFT) and time wave form (TWF) in screw compressors. The male and female randomly are sent to balance shop for balancing operation. This kind of operation usually caused some bending in rotors during the process that could cause further machining in such equipment. This kind of machining operation increased the vibration analysis complexity beside some process characteristic abnormality like inlet and out let pressure and temperature. In this paper mechanical principal and different type of screw compressors explained. Besides, some new condition monitoring systems and techniques for screw compressors discussed. Finally, one of the common behavior of oil injected twin rotary screw compressors called hydraulic unbalance that usually occurred after machining operation of male or female and have some specific characteristics in FFT and TWF discussed in details through a case history related to Iran oil industries.
High-Frequency Spectrum Analysis of VFTO Generated inside Gas Insulated Substations
Worldwide many electrical equipment insulation
failures have been reported caused by switching operations, while
those equipments had previously passed all the standard tests and
complied with all quality requirements. The problem is mostly
associated with high-frequency overvoltages generated during
opening or closing of a switching device. The transients generated
during switching operations in a Gas Insulated Substation (GIS) are
associated with high frequency components in the order of few tens
The frequency spectrum of the VFTO generated in the 220/66 kV
Wadi-Hoff GIS is analyzed using Fast Fourier Transform technique.
The main frequency with high voltage amplitude due to the operation
of disconnector (DS5) is 5 to 10 MHz, with the highest amplitude at 9
MHz. The main frequency with high voltage amplitude due to the
operation of circuit breaker (CB5) is 1 to 25 MHz, with the highest
amplitude at 2 MHz.
Mitigating techniques damped the oscillating frequencies
effectively. The using of cable terminal reduced the frequency
oscillation effectively than that of OHTL terminal. The using of a
shunt capacitance results in vanishing the high frequency
components. Ferrite rings reduces the high frequency components
effectively especially in the range 2 to 7 MHz. The using of RC and
RL filters results in vanishing the high frequency components.
Texture Feature-Based Language Identification Using Wavelet-Domain BDIP and BVLC Features and FFT Feature
In this paper, we propose a texture feature-based
language identification using wavelet-domain BDIP (block difference
of inverse probabilities) and BVLC (block variance of local
correlation coefficients) features and FFT (fast Fourier transform)
feature. In the proposed method, wavelet subbands are first obtained
by wavelet transform from a test image and denoised by Donoho-s
soft-thresholding. BDIP and BVLC operators are next applied to the
wavelet subbands. FFT blocks are also obtained by 2D (twodimensional)
FFT from the blocks into which the test image is
partitioned. Some significant FFT coefficients in each block are
selected and magnitude operator is applied to them. Moments for each
subband of BDIP and BVLC and for each magnitude of significant
FFT coefficients are then computed and fused into a feature vector. In
classification, a stabilized Bayesian classifier, which adopts variance
thresholding, searches the training feature vector most similar to the
test feature vector. Experimental results show that the proposed
method with the three operations yields excellent language
identification even with rather low feature dimension.
Velocity Filter Banks using 3-D FFT
In this paper a bank of velocity filters is devised to be
used for isolating a moving object with specific velocity in a sequence of frames. The approach used is a 3-D FFT based experimental procedure without applying any theoretical concept
from velocity filters. Accordingly, velocity filters are built using the
spectral signature of each separate moving object. Experimentation
reveals the capabilities of the constructed filter bank to separate moving objects as far as the amplitude as well as the direction of the
velocity are concerned.
OFDM and Fingerprint Authentication for Efficient Airport Security
This paper presents an idea to improve the efficiency
of security checks in airports through the active tracking and
monitoring of passengers and staff using OFDM modulation
technique and Finger print authentication. The details of the
passenger are multiplexed using OFDM .To authenticate the
passenger, the fingerprint along with important identification
information is collected. The details of the passenger can be
transmitted after necessary modulation, and received using various
transceivers placed within the premises of the airport, and checked at
the appropriate check points, thereby increasing the efficiency of
checking. OFDM has been employed for spectral efficiency.
Localizing Acoustic Touch Impacts using Zip-stuffing in Complex k-space Domain
Visualizing sound and noise often help us to determine
an appropriate control over the source localization. Near-field acoustic
holography (NAH) is a powerful tool for the ill-posed problem.
However, in practice, due to the small finite aperture size, the discrete
Fourier transform, FFT based NAH couldn-t predict the activeregion-
of-interest (AROI) over the edges of the plane. Theoretically
few approaches were proposed for solving finite aperture problem.
However most of these methods are not quite compatible for the
practical implementation, especially near the edge of the source. In
this paper, a zip-stuffing extrapolation approach has suggested with
2D Kaiser window. It is operated on wavenumber complex space
to localize the predicted sources. We numerically form a practice
environment with touch impact databases to test the localization of
sound source. It is observed that zip-stuffing aperture extrapolation
and 2D window with evanescent components provide more accuracy
especially in the small aperture and its derivatives.
Simulation of Irregular Waves by CFD
Wave generation methodology has been developed
and validated by simulating wave in CFD. In this analysis, Flap type
wave maker has been modeled numerically with wave basin to
generate waves for marine experimental analysis. Irregular waves are
arrived from the wave spectrum, and this wave has been simulated in
CFD. Generated irregular wave has been compared with an analytical
wave. Simulated wave has been processed for FFT analysis, and the
wave spectrum is validated with original wave spectrum.
Parallel-computing Approach for FFT Implementation on Digital Signal Processor (DSP)
An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.
Sub-Image Detection Using Fast Neural Processors and Image Decomposition
In this paper, an approach to reduce the computation steps required by fast neural networksfor the searching process is presented. The principle ofdivide and conquer strategy is applied through imagedecomposition. Each image is divided into small in sizesub-images and then each one is tested separately usinga fast neural network. The operation of fast neuralnetworks based on applying cross correlation in thefrequency domain between the input image and theweights of the hidden neurons. Compared toconventional and fast neural networks, experimentalresults show that a speed up ratio is achieved whenapplying this technique to locate human facesautomatically in cluttered scenes. Furthermore, fasterface detection is obtained by using parallel processingtechniques to test the resulting sub-images at the sametime using the same number of fast neural networks. Incontrast to using only fast neural networks, the speed upratio is increased with the size of the input image whenusing fast neural networks and image decomposition.
EEG Waves Classifier using Wavelet Transform and Fourier Transform
The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field due to its rich information about human tasks. In this work EEG waves classification is achieved using the Discrete Wavelet Transform DWT with Fast Fourier Transform (FFT) by adopting the normalized EEG data. The DWT is used as a classifier of the EEG wave's frequencies, while FFT is implemented to visualize the EEG waves in multi-resolution of DWT. Several real EEG data sets (real EEG data for both normal and abnormal persons) have been tested and the results improve the validity of the proposed technique.
High-Speed Pipeline Implementation of Radix-2 DIF Algorithm
In this paper, we propose a new architecture for the implementation of the N-point Fast Fourier Transform (FFT), based on the Radix-2 Decimation in Frequency algorithm. This architecture is based on a pipeline circuit that can process a stream of samples and produce two FFT transform samples every clock cycle. Compared to existing implementations the architecture proposed achieves double processing speed using the same circuit complexity.