In this article, 180 gastric images taken with Light Microscope help are used. Maximally Stable
Extremal Regions (MSER) features of the images for classification has been calculated. These MSER features
have been applied Discrete Fourier Transform (DFT) method. High-dimensional of these MSER-DFT feature
vectors is reduced to lower-dimensional with Local Tangent Space Alignment (LTSA) and Neighborhood
Preserving Embedding (NPE). When size reduction process was done, properties in 5, 10, 15, 20, 25, 30, 35, 40,
45, and 50 dimensions have been obtained. These low-dimensional data are classified by Random Forest (RF)
classification. Thus, MSER_DFT_LTSA-NPE_RF method for gastric histopathological images have been
developed. Classification results obtained with these methods have been compared. According to the other
methods, classification results for gastric histopathological images have been found to be higher.
An Improved of Multiple Harmonic Sources Identification in Distribution Syste...IAES-IJPEDS
This paper introduces an improved of multiple harmonic sources
identification that been produced by inverter loads in power system using
time-frequency distribution (TFD) analysis which is spectrogram.
The spectrogram is a very applicable method to represent signals in
time-frequency representation (TFR) and the main advantages
of spectrogram are the accuracy, speed of the algorithm and use low memory
size such that it can be computed rapidly. The identification of multiple
harmonic sources is based on the significant relationship of spectral
impedances which are the fundamental impedance (Z1) and harmonic
impedance (Zh) that extracted from TFR. To verify the accuracy of the
proposed method, MATLAB simulations carried out several unique cases
with different harmonic producing loads on IEEE 4-bus test feeder cases. It is
proven that the proposed method is superior with 100% correct identification
of multiple harmonic sources. It is envisioned that the method is very
accurate, fast and cost efficient to localize harmonic sources in distribution
system.
Effective two terminal single line to ground fault location algorithmMuhd Hafizi Idris
This paper presents an effective algorithm to locate Single Line to Ground (SLG) fault at a transmission line. Post fault voltages and currents from both substation terminals were used as the input parameters to the algorithm. Discrete Fourier Transform (DFT) was used to extract the magnitudes and phase angles of three phase voltages and currents. The modeling of the transmission line along with the algorithm was performed using Matlab/Simulink package. The results of fault location for SLG faults along the transmission line demonstrated the validity of the algorithm used even for high resistance earth fault.
Hybrid Algorithm for Dose Calculation in Cms Xio Treatment Planning SystemIOSR Journals
This study aimed at designing an improved hybrid algorithm by explicitly solving the linearized Boltzmann transport equation (LBTE) which is the governing equation that describes the macroscopic behaviour of radiation particles (neutrons, photons, electrons, etc). The algorithm accuracy will be evaluated using a newly designed in-house verification phantom and its results will be compared to those of the other XiO photon algorithms. The LBTE was solved numerically to compute photon transport in a medium. A programming code (algorithm) for the LBTE solution was developed and applied in the treatment planning system (TPS). The accuracy of the algorithm was evaluated by creating several plans for both the designed phantom and solid water phantom using the designed algorithm and other Xio photon algorithms. The plans were sent to a pre-calibrated Eleckta linear accelerator for measurement of absorbed dose.The results for all treatment plans using the hybrid algorithm compared to the 3 Xio photon algorithms were within 4 % limit. Calculation time for the hybrid algorithm was less in plans with larger number of beams compared to the other algorithms; however, it is higher for single beam plans. The hybrid algorithm provides comparable accuracy in treatment planning conditions to the other algorithms. This algorithm can therefore be employed in the calculation of dose in advance techniques such as IMRT and Rapid Arc by a radiotherapy centres with cmsxio treatment planning system as it is easy to implement.
In this article, 180 gastric images taken with Light Microscope help are used. Maximally Stable
Extremal Regions (MSER) features of the images for classification has been calculated. These MSER features
have been applied Discrete Fourier Transform (DFT) method. High-dimensional of these MSER-DFT feature
vectors is reduced to lower-dimensional with Local Tangent Space Alignment (LTSA) and Neighborhood
Preserving Embedding (NPE). When size reduction process was done, properties in 5, 10, 15, 20, 25, 30, 35, 40,
45, and 50 dimensions have been obtained. These low-dimensional data are classified by Random Forest (RF)
classification. Thus, MSER_DFT_LTSA-NPE_RF method for gastric histopathological images have been
developed. Classification results obtained with these methods have been compared. According to the other
methods, classification results for gastric histopathological images have been found to be higher.
An Improved of Multiple Harmonic Sources Identification in Distribution Syste...IAES-IJPEDS
This paper introduces an improved of multiple harmonic sources
identification that been produced by inverter loads in power system using
time-frequency distribution (TFD) analysis which is spectrogram.
The spectrogram is a very applicable method to represent signals in
time-frequency representation (TFR) and the main advantages
of spectrogram are the accuracy, speed of the algorithm and use low memory
size such that it can be computed rapidly. The identification of multiple
harmonic sources is based on the significant relationship of spectral
impedances which are the fundamental impedance (Z1) and harmonic
impedance (Zh) that extracted from TFR. To verify the accuracy of the
proposed method, MATLAB simulations carried out several unique cases
with different harmonic producing loads on IEEE 4-bus test feeder cases. It is
proven that the proposed method is superior with 100% correct identification
of multiple harmonic sources. It is envisioned that the method is very
accurate, fast and cost efficient to localize harmonic sources in distribution
system.
Effective two terminal single line to ground fault location algorithmMuhd Hafizi Idris
This paper presents an effective algorithm to locate Single Line to Ground (SLG) fault at a transmission line. Post fault voltages and currents from both substation terminals were used as the input parameters to the algorithm. Discrete Fourier Transform (DFT) was used to extract the magnitudes and phase angles of three phase voltages and currents. The modeling of the transmission line along with the algorithm was performed using Matlab/Simulink package. The results of fault location for SLG faults along the transmission line demonstrated the validity of the algorithm used even for high resistance earth fault.
Hybrid Algorithm for Dose Calculation in Cms Xio Treatment Planning SystemIOSR Journals
This study aimed at designing an improved hybrid algorithm by explicitly solving the linearized Boltzmann transport equation (LBTE) which is the governing equation that describes the macroscopic behaviour of radiation particles (neutrons, photons, electrons, etc). The algorithm accuracy will be evaluated using a newly designed in-house verification phantom and its results will be compared to those of the other XiO photon algorithms. The LBTE was solved numerically to compute photon transport in a medium. A programming code (algorithm) for the LBTE solution was developed and applied in the treatment planning system (TPS). The accuracy of the algorithm was evaluated by creating several plans for both the designed phantom and solid water phantom using the designed algorithm and other Xio photon algorithms. The plans were sent to a pre-calibrated Eleckta linear accelerator for measurement of absorbed dose.The results for all treatment plans using the hybrid algorithm compared to the 3 Xio photon algorithms were within 4 % limit. Calculation time for the hybrid algorithm was less in plans with larger number of beams compared to the other algorithms; however, it is higher for single beam plans. The hybrid algorithm provides comparable accuracy in treatment planning conditions to the other algorithms. This algorithm can therefore be employed in the calculation of dose in advance techniques such as IMRT and Rapid Arc by a radiotherapy centres with cmsxio treatment planning system as it is easy to implement.
Path Loss Prediction by Robust Regression Methodsijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
A verification of periodogram technique for harmonic source diagnostic analyt...TELKOMNIKA JOURNAL
A harmonic source diagnostic analytic is vital to identify the root causes and type of harmonic source in power system. This paper introduces a verification of periodogram technique to diagnose harmonic sources by using logistic regression classifier. A periodogram gives a correct and accurate classification of harmonic signals. Signature recognition pattern is used to distinguish the harmonic sources accurately by obtaining the distribution of harmonic and interharmonic components and the harmonic contribution changes. This is achieved by using the significant signature recognition of harmonic producing load obtained from the harmonic contribution changes. To verify the performance of the propose method, a logistic regression classifier will analyse the result and give the accuracy and positive rate percentage of the propose method. The adequacy of the proposed methodology is tested and verified on distribution system for several rectifier and inverter-based loads.
Investigating the performance of various channel estimation techniques for mi...ijmnct
This paper simulates and investigates the performance of four widely-used channel estimation techniques for MIMO-OFDM wireless communication systems; namely, super imposed pilot (SIP), comb-type, spacetime block coding (STBC), and space-frequency block coding (SFBC) techniques. The performance is
evaluated through a number of MATLab simulations, where the bit-error rate (BER) and the mean square
error (MSE) are estimated and compared for different levels of signal-to-noise ratio (SNR). The simulation results demonstrate that the comb-type channel estimation and the SIP techniques overwhelmed the performance of the STFC and STBC techniques in terms of both bit-error rate (BER) and mean square error (MSE).
INVESTIGATING THE PERFORMANCE OF VARIOUS CHANNEL ESTIMATION TECHNIQUES FOR MI...ijmnct
This paper simulates and investigates the performance of four widely-used channel estimation techniques for MIMO-OFDM wireless communication systems; namely, super imposed pilot (SIP), comb-type, spacetime block coding (STBC), and space-frequency block coding (SFBC) techniques. The performance is evaluated through a number of MATLab simulations, where the bit-error rate (BER) and the mean square error (MSE) are estimated and compared for different levels of signal-to-noise ratio (SNR). The simulation results demonstrate that the comb-type channel estimation and the SIP techniques overwhelmed the performance of the STFC and STBC techniques in terms of both bit-error rate (BER) and mean square error (MSE).
The aim of the coupling is to obtain an information-rich detection for both identification and quantification compared to that with a single analytical technique.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Identification of Multiple Harmonic Sources in a Distribution System by Us...journalBEEI
The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances, which are the fundamental impedance (Z1) and harmonic impedance (Zh) that estimate the time-frequency representation (TFR). To verify the performance of the proposed method, an IEEE test feeder with several different harmonic producing loads is simulated. It is shown that the suggested method is excellent with 100% correct identification of MHS. The method is accurate, fast and cost-efficient in the identification of MHS in power distribution arrangement.
Wide Area Fault Location for Power Transmission Network using Reactance Based...Muhd Hafizi Idris
Download here: https://www.researchgate.net/publication/332441499_Wide_Area_Fault_Location_for_Power_Transmission_Network_using_Reactance_Based_Method?_sg=Tkk3ur2Kc3XGh3JHwtJdPM3IdJJx_K42N3Zu9kX_ECutHW5j91ExIMtrJFOui4E-RikSYmuYR0uZWEEVHoSaDTPZuRvC29V6GzZ5g9BS.GnmzKNF1XN22czjk5npta57bMn8D2KxxwQsAMEPlK7abE5qGykkxj8CgUcnYHlzpKEZST1ujqv7avTquOi7Aug
With the advancements in smart grid, communication technology, intelligent electronic device and substation automation, wide area applications for monitoring, protection, control and fault location becoming focused nowadays and improved from time to time. This research focuses on using wide area synchrophasor measurements for fault location in transmission network which acts as a backup to conventional fault location method. Simple reactance based methods together with a developed rules system are used to locate the possible affected line and its fault location. Using the developed rules and algorithm, fault location impedance will be compared at each synchrophasor bus connected lines for different fault types, then between connected lines and finally between synchrophasors buses. Faults at various locations with different fault resistances have been simulated and the results prove that the developed method can be used to locate the fault point and can be used as a backup to main fault location method. Future works also discussed how the method can be improved to get the best and accurate fault location results.
Chebyshev filter applied to an inversion technique for breast tumour detectioneSAT Journals
Abstract Microwave imaging has been extensively studied in the past several years as a new technique for early stage breast cancer detection. The rationale of microwave imaging for breast tumour detection is significant contrast in the dielectric properties of normal tissue and malignant tumours. However, in practice noise present from the environments during screening/examination degrades the quality of the image. Inaccurate reconstructed image caused false/misleading interpretation of the image which leads to inappropriate diagnose or treatment to the patient. In the simulation works, noise is added to imitate the actual environment scenario. The two-dimensional (2D) object that identical to breast model is developed using numerical simulation to imitate the breast model. A filter is integrated with an iterative inversion technique for breast tumour detection to eliminate the noise. To assess the effectiveness of this approach, we consider the reconstruction of the electrical parameter profiles of 2D objects from measurements of the transient total electromagnetic field data contaminated with noise. Additive white Gaussian noise is utilized to mimic the effect of random processes that occur in the nature. This paper presents the filter settings and characteristics that affect the reconstruction of the image in order to obtain the most reliable and closer to the actual image. Selection of filter settings or design is important in order to achieve desired signal, most accurate image and provide reliable information of the object. Chebyshev low pass filter is applied in the Forward-Backward Time-Stepping (FBTS) algorithm to filter the noisy data and to improve the quality of reconstructed image. Keywords: Chebyshev low pass filter, microwave imaging and breast tumour detection
Hyphenated techniques have received ever-increasing attention as the principal means to solve complex analytical problems.
Hyphenated techniques are widely used in chemistry and biochemistry and used for both quantitative and qualitative analysis of unknown compounds in complex natural product extracts or fraction and estimation of protein samples also.
Generalized optimal placement of PMUs considering power system observability,...IJECEIAES
This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems.
Maximum likelihood estimation-assisted ASVSF through state covariance-based 2...TELKOMNIKA JOURNAL
The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurement
to the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC).
A Template Matching Approach to Classification of QAM Modulation using Geneti...CSCJournals
The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. Obviously, with no knowledge of the transmitted data and many unknown parameters at the receiver, such as the signal power, carrier frequency and phase offsets, timing information, etc., blind identification of the modulation is a difficult task. This becomes even more challenging in real-world. In this paper modulation classification for QAM is performed by Genetic Algorithm followed by Template matching, considering the constellation of the received signal. In addition this classification finds the decision boundary of the signal which is critical information for bit detection. I have proposed and implemented a technique that casts modulation recognition into shape recognition. Constellation diagram is a traditional and powerful tool for design and evaluation of digital modulations. The simulation results show the capability of this method for modulation classification with high accuracy and appropriate convergence in the presence of noise.
Comparison of signal smoothing techniques for use in embedded system for moni...Dalton Valadares
Paper about the comparison between some signal smoothing techniques for use in an embedded system responsible for monitoring the biofuels quality, specificaly the oxidative stability.
Channel Estimation in MIMO OFDM Systems with Tapped Delay Line ModelIJCNCJournal
The continuous increase in the user demands fornew-generation communication systems, is making the wireless channel more complex and challenging for estimation, developing a simulation model for the channel,and evaluating the performance of different MIMO systems. In this work, a simulation model for multipath fading channels in wireless communication is performed. The model includes a selection of typical Tapped-Delay-Line channel models that can be implemented to reproduce the effects of representative channel distortion and interference. Based on the simulation results, the proposed method exhibits accurate channel estimation performance for frequency-selective fading channels. The proposed work employed LS, MMSE, and ML methods for channel estimation, using 16 and 32 pilots and fixed pilot locations in each frame. Results are obtained for 4x4, 8x8, 16x16, 16x8, and 16x4 MIMO systems and tapped delay line systems.
Path Loss Prediction by Robust Regression Methodsijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
A verification of periodogram technique for harmonic source diagnostic analyt...TELKOMNIKA JOURNAL
A harmonic source diagnostic analytic is vital to identify the root causes and type of harmonic source in power system. This paper introduces a verification of periodogram technique to diagnose harmonic sources by using logistic regression classifier. A periodogram gives a correct and accurate classification of harmonic signals. Signature recognition pattern is used to distinguish the harmonic sources accurately by obtaining the distribution of harmonic and interharmonic components and the harmonic contribution changes. This is achieved by using the significant signature recognition of harmonic producing load obtained from the harmonic contribution changes. To verify the performance of the propose method, a logistic regression classifier will analyse the result and give the accuracy and positive rate percentage of the propose method. The adequacy of the proposed methodology is tested and verified on distribution system for several rectifier and inverter-based loads.
Investigating the performance of various channel estimation techniques for mi...ijmnct
This paper simulates and investigates the performance of four widely-used channel estimation techniques for MIMO-OFDM wireless communication systems; namely, super imposed pilot (SIP), comb-type, spacetime block coding (STBC), and space-frequency block coding (SFBC) techniques. The performance is
evaluated through a number of MATLab simulations, where the bit-error rate (BER) and the mean square
error (MSE) are estimated and compared for different levels of signal-to-noise ratio (SNR). The simulation results demonstrate that the comb-type channel estimation and the SIP techniques overwhelmed the performance of the STFC and STBC techniques in terms of both bit-error rate (BER) and mean square error (MSE).
INVESTIGATING THE PERFORMANCE OF VARIOUS CHANNEL ESTIMATION TECHNIQUES FOR MI...ijmnct
This paper simulates and investigates the performance of four widely-used channel estimation techniques for MIMO-OFDM wireless communication systems; namely, super imposed pilot (SIP), comb-type, spacetime block coding (STBC), and space-frequency block coding (SFBC) techniques. The performance is evaluated through a number of MATLab simulations, where the bit-error rate (BER) and the mean square error (MSE) are estimated and compared for different levels of signal-to-noise ratio (SNR). The simulation results demonstrate that the comb-type channel estimation and the SIP techniques overwhelmed the performance of the STFC and STBC techniques in terms of both bit-error rate (BER) and mean square error (MSE).
The aim of the coupling is to obtain an information-rich detection for both identification and quantification compared to that with a single analytical technique.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Identification of Multiple Harmonic Sources in a Distribution System by Us...journalBEEI
The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances, which are the fundamental impedance (Z1) and harmonic impedance (Zh) that estimate the time-frequency representation (TFR). To verify the performance of the proposed method, an IEEE test feeder with several different harmonic producing loads is simulated. It is shown that the suggested method is excellent with 100% correct identification of MHS. The method is accurate, fast and cost-efficient in the identification of MHS in power distribution arrangement.
Wide Area Fault Location for Power Transmission Network using Reactance Based...Muhd Hafizi Idris
Download here: https://www.researchgate.net/publication/332441499_Wide_Area_Fault_Location_for_Power_Transmission_Network_using_Reactance_Based_Method?_sg=Tkk3ur2Kc3XGh3JHwtJdPM3IdJJx_K42N3Zu9kX_ECutHW5j91ExIMtrJFOui4E-RikSYmuYR0uZWEEVHoSaDTPZuRvC29V6GzZ5g9BS.GnmzKNF1XN22czjk5npta57bMn8D2KxxwQsAMEPlK7abE5qGykkxj8CgUcnYHlzpKEZST1ujqv7avTquOi7Aug
With the advancements in smart grid, communication technology, intelligent electronic device and substation automation, wide area applications for monitoring, protection, control and fault location becoming focused nowadays and improved from time to time. This research focuses on using wide area synchrophasor measurements for fault location in transmission network which acts as a backup to conventional fault location method. Simple reactance based methods together with a developed rules system are used to locate the possible affected line and its fault location. Using the developed rules and algorithm, fault location impedance will be compared at each synchrophasor bus connected lines for different fault types, then between connected lines and finally between synchrophasors buses. Faults at various locations with different fault resistances have been simulated and the results prove that the developed method can be used to locate the fault point and can be used as a backup to main fault location method. Future works also discussed how the method can be improved to get the best and accurate fault location results.
Chebyshev filter applied to an inversion technique for breast tumour detectioneSAT Journals
Abstract Microwave imaging has been extensively studied in the past several years as a new technique for early stage breast cancer detection. The rationale of microwave imaging for breast tumour detection is significant contrast in the dielectric properties of normal tissue and malignant tumours. However, in practice noise present from the environments during screening/examination degrades the quality of the image. Inaccurate reconstructed image caused false/misleading interpretation of the image which leads to inappropriate diagnose or treatment to the patient. In the simulation works, noise is added to imitate the actual environment scenario. The two-dimensional (2D) object that identical to breast model is developed using numerical simulation to imitate the breast model. A filter is integrated with an iterative inversion technique for breast tumour detection to eliminate the noise. To assess the effectiveness of this approach, we consider the reconstruction of the electrical parameter profiles of 2D objects from measurements of the transient total electromagnetic field data contaminated with noise. Additive white Gaussian noise is utilized to mimic the effect of random processes that occur in the nature. This paper presents the filter settings and characteristics that affect the reconstruction of the image in order to obtain the most reliable and closer to the actual image. Selection of filter settings or design is important in order to achieve desired signal, most accurate image and provide reliable information of the object. Chebyshev low pass filter is applied in the Forward-Backward Time-Stepping (FBTS) algorithm to filter the noisy data and to improve the quality of reconstructed image. Keywords: Chebyshev low pass filter, microwave imaging and breast tumour detection
Hyphenated techniques have received ever-increasing attention as the principal means to solve complex analytical problems.
Hyphenated techniques are widely used in chemistry and biochemistry and used for both quantitative and qualitative analysis of unknown compounds in complex natural product extracts or fraction and estimation of protein samples also.
Generalized optimal placement of PMUs considering power system observability,...IJECEIAES
This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems.
Maximum likelihood estimation-assisted ASVSF through state covariance-based 2...TELKOMNIKA JOURNAL
The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurement
to the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC).
A Template Matching Approach to Classification of QAM Modulation using Geneti...CSCJournals
The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. Obviously, with no knowledge of the transmitted data and many unknown parameters at the receiver, such as the signal power, carrier frequency and phase offsets, timing information, etc., blind identification of the modulation is a difficult task. This becomes even more challenging in real-world. In this paper modulation classification for QAM is performed by Genetic Algorithm followed by Template matching, considering the constellation of the received signal. In addition this classification finds the decision boundary of the signal which is critical information for bit detection. I have proposed and implemented a technique that casts modulation recognition into shape recognition. Constellation diagram is a traditional and powerful tool for design and evaluation of digital modulations. The simulation results show the capability of this method for modulation classification with high accuracy and appropriate convergence in the presence of noise.
Comparison of signal smoothing techniques for use in embedded system for moni...Dalton Valadares
Paper about the comparison between some signal smoothing techniques for use in an embedded system responsible for monitoring the biofuels quality, specificaly the oxidative stability.
Channel Estimation in MIMO OFDM Systems with Tapped Delay Line ModelIJCNCJournal
The continuous increase in the user demands fornew-generation communication systems, is making the wireless channel more complex and challenging for estimation, developing a simulation model for the channel,and evaluating the performance of different MIMO systems. In this work, a simulation model for multipath fading channels in wireless communication is performed. The model includes a selection of typical Tapped-Delay-Line channel models that can be implemented to reproduce the effects of representative channel distortion and interference. Based on the simulation results, the proposed method exhibits accurate channel estimation performance for frequency-selective fading channels. The proposed work employed LS, MMSE, and ML methods for channel estimation, using 16 and 32 pilots and fixed pilot locations in each frame. Results are obtained for 4x4, 8x8, 16x16, 16x8, and 16x4 MIMO systems and tapped delay line systems.
Channel Estimation in MIMO OFDM Systems with Tapped Delay Line ModelIJCNCJournal
The continuous increase in the user demands fornew-generation communication systems, is making the wireless channel more complex and challenging for estimation, developing a simulation model for the channel,and evaluating the performance of different MIMO systems. In this work, a simulation model for multipath fading channels in wireless communication is performed. The model includes a selection of typical Tapped-Delay-Line channel models that can be implemented to reproduce the effects of representative channel distortion and interference. Based on the simulation results, the proposed method exhibits accurate channel estimation performance for frequency-selective fading channels. The proposed work employed LS, MMSE, and ML methods for channel estimation, using 16 and 32 pilots and fixed pilot locations in each frame. Results are obtained for 4x4, 8x8, 16x16, 16x8, and 16x4 MIMO systems and tapped delay line systems.
Instantaneous Frequency Estimation Based On Time-Varying Auto Regressive Mode...CSCJournals
Time-varying autoregressive (TVAR) model is used for modeling non stationary signals, Instantaneous frequency (IF) and time-varying power spectral density are then extracted from the TVAR parameters. TVAR based Instantaneous frequency (IF) estimation has been shown to perform very well in realistic scenario when IF variation is quick, non-linear and has short data record. In TVAR modeling approach, the time-varying parameters are expanded as linear combinations of a set of basis functions .In this article, time poly nominal is chosen as basis function. Non stationary signal IF is estimated by calculating the angles of the roots (poles) of the time-varying autoregressive polynomial at every sample instant. We propose modified covariance method that utilizes both the time varying forward and backward linear predictors for estimating the time-varying parameters and then IF estimate. It is shown that performance of proposed modified covariance method is superior than existing covariance method which uses only forward linear predictor for estimating the time-varying parameters. The IF evaluation based on TVAR modeling requires efficient estimation of the time-varying coefficients by solving a set of linear equations referred as the general covariance equations. When covariance matrix is of high order, usual approach such as Gaussian elimination or direct matrix inversion is computationally incompetent for solving such a structure of equations. We apply recursive algorithm to competently invert the covariance matrix, by means of Wax-Kailath algorithm which exploits the block-Toeplitz arrangement of the covariance matrix for its recursive inversion, which is the central part of this article. The order determination of TVAR model is addressed by means of the maximum likelihood estimation (MLE) algorithm.
FAULT IDENTIFY OF BEARING USING ENHANCED HILBERT-HUANG TRANSFORMADEIJ Journal
Today the maintenance and repair based on condition monitoring techniques of rotating equipment is one
of the most important tools to prevent stopping of production and reduce the cost of maintenance and
repair and the vibration analysis according to the width of identifiable defects scope has a specific
importance. In this paper, we discuss about rolling bearings defects detection with using of normalized
Hilbert huang approach.
Diagnosis of broken bars fault in induction machines using higher order spect...ISA Interchange
Detection and identification of induction machine faults through the stator current signal using higher order spectra analysis is presented. This technique is known as motor current signature analysis (MCSA). This paper proposes two higher order spectra techniques, namely the power spectrum and the slices of bi-spectrum used for the analysis of induction machine stator current leading to the detection of electrical failures within the rotor cage. The method has been tested by using both healthy and broken rotor bars cases for an 18.5 kW-220 V/380 V-50 Hz-2 pair of poles induction motor under different load conditions. Experimental signals have been analyzed highlighting that bi-spectrum results show their superiority in the accurate detection of rotor broken bars. Even when the induction machine is rotating at a low level of shaft load (no-load condition), the rotor fault detection is efficient. We will also demonstrate through the analysis and experimental verification, that our proposed proposed-method has better detection performance in terms of receiver operation characteristics (ROC) curves and precision-recall graph.
Conditioning Monitoring of Gearbox Using Different Methods: A ReviewIJMER
Gears are important element in a variety of industrial applications such as machine tool
and gearboxes. An unexpected failure of the gear may cause significant economic losses. For that
reason, fault diagnosis in gears has been the subject of intensive research. Vibration signal analysis
has been widely used in the fault detection of rotation machinery. Fault diagnosis plays an important
role in condition monitoring to enhance the machine time. In view of this, the present investigation
focused on the development of Fault diagnosis system of gearboxes based on the vibration signatures
and Artificial Neural Networks. In the present investigation to generate the vibration signatures an
experimental set-up has been fabricated with sensing and measuring equipment. The prominent faults,
wear, crack, broken tooth and insufficient lubrication of the gear were practically induced in the
present investigation. Vibration signatures of the gearbox were collected by transmitting the motion at
constant speed with gears having no fault, without applying any load. By inducing one fault at a time,
vibration signatures were collected with different degrees of wear on a gear tooth, a gear with a
broken tooth, tooth with crack and with insufficient lubrication. As the vibration data of maximum
amplitudes was found to be inseparable, fault diagnosis based on this data was not possible. Five
prominent statistical features were extracted based on data pertaining to maximum amplitudes of
vibration and used fault diagnosis. Due overlapping of this data, it was decided to use ANN based
fault diagnosis system for the present investigation. The set of statistical features were extracted based
on data pertaining to maximum amplitudes of vibration and used them as input parameters to the
ANN based fault diagnosis system designed.
Transmission line is one the important compnent in protection of electric power system because the transmission line connects the power station with load centers.
The fault includes storms, lightning, snow, damage to insulation, short circuit fault [1].
Fault needs to be predicted earlier in order to be prevented before it occur
At present, the research on fault detection and diagnosis technology is very significant to improve the reliability of the equipment, which can greatly improve the safety and efficiency of the equipment. This paper proposes a new fault detection and diagnosis means based on the FOA-LSSVM algorithm. Experimental results demonstrate that the algorithm is effective for the detection and diagnosis of analog circuit faults. In addition, the model also demonstrate good generalization ability.
BEARINGS PROGNOSTIC USING MIXTURE OF GAUSSIANS HIDDEN MARKOV MODEL AND SUPPOR...IJNSA Journal
Prognostic of future health state relies on the estimation of the Remaining Useful Life (RUL) of physical
systems or components based on their current health state. RUL can be estimated by using three main
approaches: model-based, experience-based and data-driven approaches. This paper deals with a datadriven
prognostics method which is based on the transformation of the data provided by the sensors into
models that are able to characterize the behavior of the degradation of bearings.
For this purpose, we used Support Vector Machine (SVM) as modeling tool. The experiments on the
recently published data base taken from the platform PRONOSTIA clearly show the superiority of the
proposed approach compared to well established method in literature like Mixture of Gaussian Hidden
Markov Models (MoG-HMMs).
BEARINGS PROGNOSTIC USING MIXTURE OF GAUSSIANS HIDDEN MARKOV MODEL AND SUPPOR...IJNSA Journal
Prognostic of future health state relies on the estimation of the Remaining Useful Life (RUL) of physical systems or components based on their current health state. RUL can be estimated by using three main approaches: model-based, experience-based and data-driven approaches. This paper deals with a data driven prognostics method which is based on the transformation of the data provided by the sensors into
models that are able to characterize the behavior of the degradation of bearings.
For this purpose, we used Support Vector Machine (SVM) as modeling tool. The experiments on the recently published data base taken from the platform PRONOSTIA clearly show the superiority of the proposed approach compared to well established method in literature like Mixture of Gaussian Hidden Markov Models (MoG-HMMs).
1. 6th
National Congress on Civil Engineering,
April 26-27, 2011, Semnan University, Semnan, Iran
A new wavelet-based method for determination of mode shapes:
Experimental Results
M. R. Ashory1
, M. Jaafari2
, M. M. Khatibi3
, A. Malekjafarian4
1- Assistant professor, School of Mechanical Engineering, Semnan University
2, 4- MSc of Mechanical Engineering, School of Mechanical Engineering, Semnan University
3- MSc of Mechanical Engineering, Islamic Azad University-Semnan Branch
m.m.khatybi@gmail.com
Abstract
In this article a new method is proposed to determine the mode shapes of linear dynamic systems
from the results of wavelet analysis. A previously proposed method based on a modified Morlet
wavelet function with an adjusting parameter is used to identify the natural frequencies and
damping ratios of system. The mode shapes are obtained from the time signal of responses and the
extracted natural frequencies from wavelet transform of response signals. The method is applied to
a steel real beam excited by an impact force. It is shown that the extracted mode shapes are not
scaled. Therefore, the mass change method is used for scaling of the mode shapes.
Keywords: Mode shapes, Wavelet transform, Natural frequency, Free responses.
1. INTRODUCTION
Estimation of the modal parameters in terms of natural frequencies, damping coefficients and mode
shapes from experimental data is a fundamental problem in structural dynamics. The modal
parameter identification methods may be categorized in to Single Degree Of Freedom (SDOF) methods
and Multi Degrees Of Freedom (MDOF) methods. Pick peaking method, circle fit method and line fit
method are the classical methods for modal parameter identification [1]. The recent method of three
point finite difference method [2] gives more accurate results compared to the traditional methods.
Least square complex exponential method [3], poly-reference time domain method [4], Ibrahim time
domain method [5], automated parameter identification and order reduction for discrete time series
[6] are among the MDOF methods for modal parameter determination [7]. The basis of most of these
methods is Fourier analysis which transforms the time data to the frequency data. However, Fourier
analysis cannot determine the modal parameters accurately in the noisy environments. Some methods
consist of pre-filtering of the input signals can improve the results. Moreover, close modes may hardly
be identified using the techniques based on the Fourier analysis. Recently, wavelet analysis has
attracted researchers in applied physics and engineering as well as the other branches of science due to
its powerful capability in analyzing a signal [8]. In contrast to the Fourier transform which has a
uniform resolution in frequency domain, the wavelet transform has the property of double resolution
in both the time and frequency domain. By using this property, the wavelet transform can be adjusted
to analyze the non-stationary signals. Also, the strongly coupled modes can be identified by tuning the
wavelets. Moreover, the inherent ability of wavelet transform in filtering out the noise contaminating a
signal is an important advantage for identifying the modal parameters. In previous years, some
researches have been conducted for identification of modal parameter using wavelet transform [9-13].
The input signals to these wavelet techniques are mostly the ambient time records without the
knowledge of input force and consequently these methods are comparable to output-only techniques in
modal testing.
Three methods for estimating the damping ratios based on the Continuous Wavelet Transform (CWT)
were proposed in [14]. A procedure of identification of natural frequencies and damping ratios of the
system from its free decays using wavelet transform was proposed in [15]. A modified Morlet wavelet
function with adjusting parameter was proposed in [16] to improve the accuracy of identification. A
modal parameter identification procedure using continuous wavelet transform including the mode
shape identification has been proposed in [17]. An identification method for natural frequencies and
damping ratios based on a modulated Gaussian wavelet transform from impulse response function is