A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfigur...A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfiguration(DNR)followed by DSTATCOM placement.Initially,an optimal DNR is applied to reduce the propagated voltage sags during the test period.The second stage involves optimal placement of the DSTATCOM to assist the already reconfigured network.The gravitational search algorithm is used in the process of optimal DNR and in placing DSTATCOM.Reliability assessment is performed using the well-known indices.The simulation results show that the proposed method is efficient and feasible for improving the level of system reliability.展开更多
One of the most important features of the modern ma ch ining system in an "unmanned" factory is to change tools that have been subjec ted to wear and damage. An integrated tool condition monitoring system co...One of the most important features of the modern ma ch ining system in an "unmanned" factory is to change tools that have been subjec ted to wear and damage. An integrated tool condition monitoring system composed of multi-sensors, signal processing devices and intelligent decision making pla ns is a necessary requirement for automatic manufacturing processes. An intellig ent tool wear monitoring system will be introduced in this paper. The system is equipped with power consumption, vibration, AE and cutting force sensors, signal transformation and collection apparatus and a microcomputer. Tool condition monitoring is a pattern recognition process in which the characte ristics of the tool to be monitored are compared with those of the standard mode ls. The tool wear classification process is composed of the following parts: fea ture extraction; determination of the fuzzy membership functions of the features ; calculation of the fuzzy similarity; learning and tool wear classification. Fe atures extracted from the time domain and frequency domain for the future patter n recognition are as follows. Power consumption signal: mean value; AE-RMS sign al: mean value, skew and kutorsis; Cutting force, AE and vibration signal: mean value, standard deviation and the mean power in 10 frequency ranges. These signa l features can reflect the tool wear states comprehensively. The fuzzy approachi ng degree and the fuzzy distance between corresponding features of different obj ects are combined to describe the closeness of two fuzzy sets more accurately. A unique fuzzy driven neural network based pattern recognition algorithm has bee n developed from this research. The combination of Artificial Neural Networks (A NNs) and fuzzy logic system integrates the strong learning and classification ab ility of the former and the superb flexibility of the latter to express the dist ribution characteristics of signal features with vague boundaries. This methodol ogy indirectly solves the automatic weight assignment problem of the conventiona l fuzzy pattern recognition system and let it have greater representative power, higher training speed and be more robust. The introduction of the two-dimensio nal weighted approaching degree can make the pattern recognition process more re liable. The fuzzy driven neural network can effectively fuse multi-sensor i nformation and successfully recognize the tool wear states. Armed with the advan ced pattern recognition methodology, the established intelligent tool condition monitoring system has the advantages of being suitable for different machini ng conditions, robust to noise and tolerant to faults. Cooperated with the contr ol system of the machine tool, the optimized machining processed can be achieved .展开更多
An alternative method was introduced for voltage sag source location based on S and TT transformed disturbance powers. It is done to avoid the wrong and inconclusive detection of conventional disturbance power method ...An alternative method was introduced for voltage sag source location based on S and TT transformed disturbance powers. It is done to avoid the wrong and inconclusive detection of conventional disturbance power method proposed in the literature. Unlike in the case of the traditional method, the proposed method first transforms the recorded voltage and current during the sag event to some special features before calculating the new version of disturbance powers. The effectiveness of the proposed method has been verified through simulation and actual data from an industrial power system. The results show that the presented method can correctly detect the location of voltage sag source.展开更多
In this study;the effect of the electron density over the Br atoms raising with increasing number of CH_2 group using the results of the K X-ray cross-sections and average fluorescence yields of bromine in quaternary-...In this study;the effect of the electron density over the Br atoms raising with increasing number of CH_2 group using the results of the K X-ray cross-sections and average fluorescence yields of bromine in quaternary-imidazole ring.In the experimental set-up,50 mCi ^(241) Am source and a collimated Ultra-LEGe detector were used.The electron density on the Br atoms raises according to the number of the CH_2 groups on the contrary of the inductive effect.The decreasing of the X-ray fluorescence parameters is interested with the increasing the electron density of Br atoms.展开更多
The measurement of K shell fluorescence parameters is an easy and practical way to investigate the electronic structures of elements in alloys,compounds or complexes.Since the number of valence electrons will change t...The measurement of K shell fluorescence parameters is an easy and practical way to investigate the electronic structures of elements in alloys,compounds or complexes.Since the number of valence electrons will change the screening effect,the measured parameters will be affected from the changes.In this study,the measured parameters were investigated for sulphur element according to the number of CH_2 groups.For the experimental measurements,the samples were excited by 59.5keVγrays from a 241 Am annular radioactive source.The emitted K X-rays from the samples were counted by ab Ultra-LEGe detector with a resolution of 150 eV at 5.9keV.展开更多
基金Project(DIP-2012-30)supported by the Universiti Kebangsaan,Malaysia
文摘A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfiguration(DNR)followed by DSTATCOM placement.Initially,an optimal DNR is applied to reduce the propagated voltage sags during the test period.The second stage involves optimal placement of the DSTATCOM to assist the already reconfigured network.The gravitational search algorithm is used in the process of optimal DNR and in placing DSTATCOM.Reliability assessment is performed using the well-known indices.The simulation results show that the proposed method is efficient and feasible for improving the level of system reliability.
文摘One of the most important features of the modern ma ch ining system in an "unmanned" factory is to change tools that have been subjec ted to wear and damage. An integrated tool condition monitoring system composed of multi-sensors, signal processing devices and intelligent decision making pla ns is a necessary requirement for automatic manufacturing processes. An intellig ent tool wear monitoring system will be introduced in this paper. The system is equipped with power consumption, vibration, AE and cutting force sensors, signal transformation and collection apparatus and a microcomputer. Tool condition monitoring is a pattern recognition process in which the characte ristics of the tool to be monitored are compared with those of the standard mode ls. The tool wear classification process is composed of the following parts: fea ture extraction; determination of the fuzzy membership functions of the features ; calculation of the fuzzy similarity; learning and tool wear classification. Fe atures extracted from the time domain and frequency domain for the future patter n recognition are as follows. Power consumption signal: mean value; AE-RMS sign al: mean value, skew and kutorsis; Cutting force, AE and vibration signal: mean value, standard deviation and the mean power in 10 frequency ranges. These signa l features can reflect the tool wear states comprehensively. The fuzzy approachi ng degree and the fuzzy distance between corresponding features of different obj ects are combined to describe the closeness of two fuzzy sets more accurately. A unique fuzzy driven neural network based pattern recognition algorithm has bee n developed from this research. The combination of Artificial Neural Networks (A NNs) and fuzzy logic system integrates the strong learning and classification ab ility of the former and the superb flexibility of the latter to express the dist ribution characteristics of signal features with vague boundaries. This methodol ogy indirectly solves the automatic weight assignment problem of the conventiona l fuzzy pattern recognition system and let it have greater representative power, higher training speed and be more robust. The introduction of the two-dimensio nal weighted approaching degree can make the pattern recognition process more re liable. The fuzzy driven neural network can effectively fuse multi-sensor i nformation and successfully recognize the tool wear states. Armed with the advan ced pattern recognition methodology, the established intelligent tool condition monitoring system has the advantages of being suitable for different machini ng conditions, robust to noise and tolerant to faults. Cooperated with the contr ol system of the machine tool, the optimized machining processed can be achieved .
基金the financial support from the Universiti Kebangsaan Malaysia under the research grant UKM-DLP-2011-059
文摘An alternative method was introduced for voltage sag source location based on S and TT transformed disturbance powers. It is done to avoid the wrong and inconclusive detection of conventional disturbance power method proposed in the literature. Unlike in the case of the traditional method, the proposed method first transforms the recorded voltage and current during the sag event to some special features before calculating the new version of disturbance powers. The effectiveness of the proposed method has been verified through simulation and actual data from an industrial power system. The results show that the presented method can correctly detect the location of voltage sag source.
文摘In this study;the effect of the electron density over the Br atoms raising with increasing number of CH_2 group using the results of the K X-ray cross-sections and average fluorescence yields of bromine in quaternary-imidazole ring.In the experimental set-up,50 mCi ^(241) Am source and a collimated Ultra-LEGe detector were used.The electron density on the Br atoms raises according to the number of the CH_2 groups on the contrary of the inductive effect.The decreasing of the X-ray fluorescence parameters is interested with the increasing the electron density of Br atoms.
基金The financial support from research foundation of Mustafa Kemal University(grant no:13121)is also gratefully acknowledged
文摘The measurement of K shell fluorescence parameters is an easy and practical way to investigate the electronic structures of elements in alloys,compounds or complexes.Since the number of valence electrons will change the screening effect,the measured parameters will be affected from the changes.In this study,the measured parameters were investigated for sulphur element according to the number of CH_2 groups.For the experimental measurements,the samples were excited by 59.5keVγrays from a 241 Am annular radioactive source.The emitted K X-rays from the samples were counted by ab Ultra-LEGe detector with a resolution of 150 eV at 5.9keV.
