A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibratio...A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares(FLS)-support vector machine(SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.展开更多
The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern ch...The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.展开更多
There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fi...There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.展开更多
In the present study,hydraulic and thermal behavior of an automatic transmission nano-fluid(ATNF) inside a tube with a twisted tape has been investigated.The heat transfer improvement and pressure drop of transmission...In the present study,hydraulic and thermal behavior of an automatic transmission nano-fluid(ATNF) inside a tube with a twisted tape has been investigated.The heat transfer improvement and pressure drop of transmission oil for each of case of using twisted tape and nano-particles were also examined separately and compared with each other.The Cu O nano-particles were used to prepare the ATNF.The effects of different Reynolds numbers and different mass fractions of nano-particle were investigated.The results showed that applying nano-particles and twisted tape simultaneously increases both the pressure drop and Nusselt number,on average by about 53% and 76%,respectively.By using a parameter,namely thermal performance index η,the effect of increasing heat transfer and pressure drop was studied simultaneously.The heat transfer improvement predominates the pressure drop increment in all cases.It was observed that the highest thermal performance of 1.9 was obtained at Re=634 and Φ=2%.Furthermore,regarding the increment of the Nu number,it was shown that the use of twisted tapes individually could increase the average Nu number by 41%,while the max increment arising from individual use of 2% nano-particles is 13%,so using twisted tape is a more effective-technique for this case study.展开更多
Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless...Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless magnetic rotary encoders.Mechanical parts and FPAs are integrated,which reduces the overall size of the finger.Driven by FPA directly,the joint output torque is more accurate and the friction and vibration can be effectively reduced.An improved adaptive genetic algorithm(IAGA) was adopted to solve the inverse kinematics problem of the redundant finger.The statics of the finger was analyzed and the relation between fingertip force and joint torque was built.Finally,the finger force/position control principle was introduced.Tracking experiments of fingertip force/position were carried out.The experimental results show that the fingertip position tracking error is within ±1 mm and the fingertip force tracking error is within ±0.4 N.It is also concluded from the theoretical and experimental results that the finger can be controlled and it has a good application prospect.展开更多
By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite co...By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1,1].Some measures in the optimization algorithm,such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline,were taken to ensure its speediness and veracity in seeking the optimization process.The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision.Furthermore,the average truncated generations,the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally.It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm.展开更多
To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventiona...To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.展开更多
A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An...A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An adaptive genetic algorithm is used to optimize the parameters of the neuron PI controller. The simulation result of the neuron PI control for semi-active suspension system of tracked vehicle indicates that the vertical amplitude,pitch angle and vertical acceleration of the vehicle are well controlled. The root mean square (RMS) of the vertical amplitude decreases by 37.2%,and 45.2% for the pitch angle,38.6% for the vertical acceleration. The research of neuron PI control experiment for the semi-active suspension system of the tracked vehicle model mining in benthal indicates that the RMS of the weight acceleration vibrating along the vertical direction decreases by 29.5%,the power spectral density resonance peak of the acceleration of the car body decreases by 23.8%.展开更多
An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards...An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is Moreover, the proposed method can be useful for software wireless bands. also given, which shows that the QGA tuning algorithm is much faster. defined radio systems using a single antenna for multiple mobile and展开更多
To make heat conduction equation embody the essence of physical phenomenon under study, dimensionless factors were introduced and the transient heat conduction equation and its boundary conditions were transformed to ...To make heat conduction equation embody the essence of physical phenomenon under study, dimensionless factors were introduced and the transient heat conduction equation and its boundary conditions were transformed to dimensionless forms. Then, a theoretical solution model of transient heat conduction problem in one-dimensional double-layer composite medium was built utilizing the natural eigenfunction expansion method. In order to verify the validity of the model, the results of the above theoretical solution were compared with those of finite element method. The results by the two methods are in a good agreement. The maximum errors by the two methods appear when τ（τ is nondimensional time） equals 0.1 near the boundaries of ζ =1 （ζ is nondimensional space coordinate） and ζ =4. As τ increases, the error decreases gradually, and when τ =5 the results of both solutions have almost no change with the variation of coordinate 4.展开更多
A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifet...A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.展开更多
Stack effect is a dominant driving force for building natural ventilation.Analytical models were developed for the evaluation of stack effect in a shaft,accounting for the heat transfer from shaft interior boundaries....Stack effect is a dominant driving force for building natural ventilation.Analytical models were developed for the evaluation of stack effect in a shaft,accounting for the heat transfer from shaft interior boundaries.Both the conditions with constant heat flux from boundaries to the airflow and the ones with constant boundary temperature were considered.The prediction capabilities of these analytical models were evaluated by using large eddy simulation(LES) for a hypothetical shaft.The results show that there are fairly good agreements between the predictions of the analytical models and the LES predictions in mass flow rate,vertical temperatures profile and pressure difference as well.Both the results of analytical models and LES show that the neutral plane could locate higher than one half of the shaft height when the upper opening area is identical with the lower opening area.Further,it is also shown that the analytical models perform better than KLOTE's model does in the mass flow rate prediction.展开更多
The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain inde...The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model.展开更多
In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(S...In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.展开更多
Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal ...Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.展开更多
基金Project(2012BAK09B02-05) supported by the National Key Technology R&D Program of China during the Twelfth Five-year PeriodProject(51274250) supported by the National Natural Science Foundation of China
文摘A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares(FLS)-support vector machine(SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.
基金Projects(51405381,51674188)supported by the National Natural Science Foundation of China
文摘The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.
基金Project(60574030) supported by the National Natural Science Foundation of ChinaKey Project(60634020) supported by the National Natural Science Foundation of China
文摘There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.
文摘In the present study,hydraulic and thermal behavior of an automatic transmission nano-fluid(ATNF) inside a tube with a twisted tape has been investigated.The heat transfer improvement and pressure drop of transmission oil for each of case of using twisted tape and nano-particles were also examined separately and compared with each other.The Cu O nano-particles were used to prepare the ATNF.The effects of different Reynolds numbers and different mass fractions of nano-particle were investigated.The results showed that applying nano-particles and twisted tape simultaneously increases both the pressure drop and Nusselt number,on average by about 53% and 76%,respectively.By using a parameter,namely thermal performance index η,the effect of increasing heat transfer and pressure drop was studied simultaneously.The heat transfer improvement predominates the pressure drop increment in all cases.It was observed that the highest thermal performance of 1.9 was obtained at Re=634 and Φ=2%.Furthermore,regarding the increment of the Nu number,it was shown that the use of twisted tapes individually could increase the average Nu number by 41%,while the max increment arising from individual use of 2% nano-particles is 13%,so using twisted tape is a more effective-technique for this case study.
基金Project(2009AA04Z209) supported by the National High Technology Research and Development Program of ChinaProject(R1090674) supported by the Natural Science Foundation of Zhejiang Province,ChinaProject(51075363) supported by the National Natural Science Foundation of China
文摘Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless magnetic rotary encoders.Mechanical parts and FPAs are integrated,which reduces the overall size of the finger.Driven by FPA directly,the joint output torque is more accurate and the friction and vibration can be effectively reduced.An improved adaptive genetic algorithm(IAGA) was adopted to solve the inverse kinematics problem of the redundant finger.The statics of the finger was analyzed and the relation between fingertip force and joint torque was built.Finally,the finger force/position control principle was introduced.Tracking experiments of fingertip force/position were carried out.The experimental results show that the fingertip position tracking error is within ±1 mm and the fingertip force tracking error is within ±0.4 N.It is also concluded from the theoretical and experimental results that the finger can be controlled and it has a good application prospect.
基金Project(60874114) supported by the National Natural Science Foundation of China
文摘By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1,1].Some measures in the optimization algorithm,such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline,were taken to ensure its speediness and veracity in seeking the optimization process.The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision.Furthermore,the average truncated generations,the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally.It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm.
基金Project(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject (60874070) supported by the National Natural Science Foundation of China
文摘To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.
基金Project(2010GK3091) supported by Industrial Support Project in Science and Technology of Hunan Province, ChinaProject(10B058) supported by Excellent Youth Foundation Subsidized Project of Hunan Provincial Education Department, China
文摘A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An adaptive genetic algorithm is used to optimize the parameters of the neuron PI controller. The simulation result of the neuron PI control for semi-active suspension system of tracked vehicle indicates that the vertical amplitude,pitch angle and vertical acceleration of the vehicle are well controlled. The root mean square (RMS) of the vertical amplitude decreases by 37.2%,and 45.2% for the pitch angle,38.6% for the vertical acceleration. The research of neuron PI control experiment for the semi-active suspension system of the tracked vehicle model mining in benthal indicates that the RMS of the weight acceleration vibrating along the vertical direction decreases by 29.5%,the power spectral density resonance peak of the acceleration of the car body decreases by 23.8%.
基金Projects(61102039, 51107034) supported by the National Natural Science Foundation of ChinaProject(2011FJ3080) supported by the Planned Science and Technology Project of Hunan Province ChinaProject supported by Fundamental Research Funds for the Central Universities, China
文摘An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is Moreover, the proposed method can be useful for software wireless bands. also given, which shows that the QGA tuning algorithm is much faster. defined radio systems using a single antenna for multiple mobile and
基金Projects(50576007,50876016) supported by the National Natural Science Foundation of ChinaProjects(20062180) supported by the National Natural Science Foundation of Liaoning Province,China
文摘To make heat conduction equation embody the essence of physical phenomenon under study, dimensionless factors were introduced and the transient heat conduction equation and its boundary conditions were transformed to dimensionless forms. Then, a theoretical solution model of transient heat conduction problem in one-dimensional double-layer composite medium was built utilizing the natural eigenfunction expansion method. In order to verify the validity of the model, the results of the above theoretical solution were compared with those of finite element method. The results by the two methods are in a good agreement. The maximum errors by the two methods appear when τ（τ is nondimensional time） equals 0.1 near the boundaries of ζ =1 （ζ is nondimensional space coordinate） and ζ =4. As τ increases, the error decreases gradually, and when τ =5 the results of both solutions have almost no change with the variation of coordinate 4.
基金Projects(61101104,61100213) supported by the National Natural Science Foundation of ChinaProject(NY211050) supported by Fund of Nanjing University of Posts and Telecommunications,China
文摘A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.
基金Project(50838009) supported by the National Natural Science Foundation of ChinaProject(2010DFA72740-03) supported by the National Key Technology Research and Development Program of China
文摘Stack effect is a dominant driving force for building natural ventilation.Analytical models were developed for the evaluation of stack effect in a shaft,accounting for the heat transfer from shaft interior boundaries.Both the conditions with constant heat flux from boundaries to the airflow and the ones with constant boundary temperature were considered.The prediction capabilities of these analytical models were evaluated by using large eddy simulation(LES) for a hypothetical shaft.The results show that there are fairly good agreements between the predictions of the analytical models and the LES predictions in mass flow rate,vertical temperatures profile and pressure difference as well.Both the results of analytical models and LES show that the neutral plane could locate higher than one half of the shaft height when the upper opening area is identical with the lower opening area.Further,it is also shown that the analytical models perform better than KLOTE's model does in the mass flow rate prediction.
文摘The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model.
基金Projects(61471370,61401479)supported by the National Natural Science Foundation of China
文摘In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.
基金Project(1390/2)supported by Khuzestan Gas Company,Iran
文摘Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.
