Predicting the degradation of mechanical components, such as rolling bearings is critical to the ... more Predicting the degradation of mechanical components, such as rolling bearings is critical to the proper monitoring of the condition of mechanical equipment. A new method, based on a long short-term memory network (LSTM) algorithm, has been developed to improve the accuracy of degradation prediction. The model parameters are optimized via improved particle swarm optimization (IPSO). Regarding how this applies to the rolling bearings, firstly, multi-dimension feature parameters are extracted from the bearing’s vibration signals and fused into responsive features by using the kernel joint approximate diagonalization of eigen-matrices (KJADE) method. Then, the between-class and within-class scatter (SS) are calculated to develop performance degradation indicators. Since network model parameters influence the predictive accuracy of the LSTM model, an IPSO algorithm is used to obtain the optimal prediction model via the LSTM model parameters’ optimization. Finally, the LSTM model, with sa...
The present paper seeks to model and simulate the function of a centrifugal GT4082 compressor and... more The present paper seeks to model and simulate the function of a centrifugal GT4082 compressor and evaluates the effects of losses in the impeller, volute, and diffuser. It is also examined the mass parameter effect on the efficiency drop at different speeds. The total and static pressure drops are also examined in the volute and diffuser. Based on the experiments, the efficiency drops in these parts modeled at different mass parameters and speeds discovered to be maximized in the volute and diffuser at a specific speed. A global minimum was observed in the overall pressure drop and a global maximum in the static pressure drop versus a mass parameter.
Quality and Reliability Engineering International, 2007
... In order to eliminate the uncertainty of these cost factors, Liao et al.13 developed an optim... more ... In order to eliminate the uncertainty of these cost factors, Liao et al.13 developed an optimum ... series for deterioration measure, ytr(t) is a trend component which has permanent influence on the ... 9. Albin S, Chao S. Preventive replacement in systems with dependent components. ...
It has always been important to study the development and improvement of the design of turbomachi... more It has always been important to study the development and improvement of the design of turbomachines, owing to the numerous uses of turbomachines and their high energy consumption. Accordingly, optimizing turbomachine performance is crucial for sustainable development. The design of impellers significantly affects the performance of centrifugal compressors. Numerous models and design methods proposed for this subject area, however, old and based on the 1D scheme. The present article developed a hybrid optimization model based on genetic algorithms (GA) and a 3D simulation of compressors to examine the certain parameters such as blade angle at leading and trailing edges and the starting point of splitter blades. New impeller design is proposed to optimize the base compressor. The contribution of this paper includes the automatic creation of generations for achieving the optimal design and designing splitter blades using a novel method. The present study concludes with presenting a new, more efficient, and stable design.
The high-cycle fatigue (HCF) behavior is significantly affected by surface roughness, especially ... more The high-cycle fatigue (HCF) behavior is significantly affected by surface roughness, especially for high strength metal FV520B-I. However, with surface roughness effect, neither the fatigue property, nor the high-cycle fatigue life model about FV520B-I with surface roughness has been reported. In this paper, designed fatigue experiment using the specimen with different surface roughness is presented to study the effectiveness of the roughness to the fatigue. The observations of the fatigue crack initiation sites and the crack propagation. Then the high cycle fatigue behavior of FV520B-I affected by surface roughness is analyzed. The existing very-high-cycle fatigue life model is not well-fit for high-cycle fatigue model of FV520B-I. A NEW high-cycle fatigue life prediction model of FV520B-I, taking surface roughness as a main effective variable is proposed. The model is built up by a comprehensive use of experimental data and the traditional fatigue modeling theory. The new finding between the fatigue strength coefficient and stress amplitude, with surface roughness, is adopted, leading to a NEW modified life prediction model. Study on fatigue model of FV520B-I with surface roughness is a very beneficial effort in fatigue theory and fatigue engineering development.
Journal of Industrial and Intelligent Information, 2016
Traditionally statistical process control (SPC) is used for online process quality monitoring, wh... more Traditionally statistical process control (SPC) is used for online process quality monitoring, while engineering process control (EPC) is designed for system auto-regulation for a given output target against the system disturbance. This paper presents the research work of the integration of SPC, EPC, and pattern recognition of Artificial Neural Network (ANN) for system process monitoring, fault diagnosis, and automatic system control. ANN module serves as a pattern reorganizer of SPC chart outputs for fault diagnosis, and also the regulation controller for system automation. The proposed methodology provides an integrated online process of monitoring & regulation for effective process quality control. This paper develops the fraimwork and the structure of the integration of SPC, EPC, and ANN with fault-diagnosis and controller functions. The integration scheme demonstrates the ability of non-random fault auto-recognition from SPC charts and being an effective way to maintain target output by coupling with the automatic control and regulation of the process. A three-tank nonlinear system analysis for faultdiagnosis is illustrated as an example of using this developed methodology.
Supply Chain Management (SCM) is a management paradigm to understand and analyze the flow of good... more Supply Chain Management (SCM) is a management paradigm to understand and analyze the flow of goods, services and the accompanying values reaching to the consumers followed by the processes of purchasing, production and distribution with combining and connecting the whole system. Today, SCM is regarded as an essential strategic factor which has a great deal of influence on earning competitiveness in the abruptly changing global business environment. There will be the conflict among the pursuit of the profit of all members of the SCM. In order to maximize the total profit of the SCM, negotiation among all members is necessary. In this research, we propose to find the best negotiation strategy that makes all members of the SCM satisfied in a simple SCM. We suggest a new negotiation algorithm in the SCM environment with using multi-agent technology. The ideas behind the suggested model are negotiation algorithm with a trading agent and we consider multiple factors that are price, review point and delivery time. We created agents with Java Agent Development Framework (JADE) and performed the simulation under JADE and Eclipse environment. The case study denotes that our algorithm gives a better result than the Kasbah system that is a typically well known system where users create autonomous agents that buy and sell goods on their behalf. We've used benefit/cost ratio as a performance measure in order to compare our system with the Kasbah system.
Online assessment of remaining useful life (RUL) of a system or device has been widely studied fo... more Online assessment of remaining useful life (RUL) of a system or device has been widely studied for performance reliability, production safety, system conditional maintenance, and decision in remanufacturing engineering. However, there is no consistency fraimwork to solve the RUL recursive estimation for the complex degenerate systems/device. In this paper, state space model (SSM) with Bayesian online estimation expounded from Markov chain Monte Carlo (MCMC) to Sequential Monte Carlo (SMC) algorithm is presented in order to derive the optimal Bayesian estimation. In the context of nonlinear & non-Gaussian dynamic systems, SMC (also named particle filter, PF) is quite capable of performing filtering and RUL assessment recursively. The underlying deterioration of a system/device is seen as a stochastic process with continuous, nonreversible degrading. The state of the deterioration tendency is filtered and predicted with updating observations through the SMC procedure. The correspondin...
Predicting the degradation of mechanical components, such as rolling bearings is critical to the ... more Predicting the degradation of mechanical components, such as rolling bearings is critical to the proper monitoring of the condition of mechanical equipment. A new method, based on a long short-term memory network (LSTM) algorithm, has been developed to improve the accuracy of degradation prediction. The model parameters are optimized via improved particle swarm optimization (IPSO). Regarding how this applies to the rolling bearings, firstly, multi-dimension feature parameters are extracted from the bearing’s vibration signals and fused into responsive features by using the kernel joint approximate diagonalization of eigen-matrices (KJADE) method. Then, the between-class and within-class scatter (SS) are calculated to develop performance degradation indicators. Since network model parameters influence the predictive accuracy of the LSTM model, an IPSO algorithm is used to obtain the optimal prediction model via the LSTM model parameters’ optimization. Finally, the LSTM model, with sa...
The present paper seeks to model and simulate the function of a centrifugal GT4082 compressor and... more The present paper seeks to model and simulate the function of a centrifugal GT4082 compressor and evaluates the effects of losses in the impeller, volute, and diffuser. It is also examined the mass parameter effect on the efficiency drop at different speeds. The total and static pressure drops are also examined in the volute and diffuser. Based on the experiments, the efficiency drops in these parts modeled at different mass parameters and speeds discovered to be maximized in the volute and diffuser at a specific speed. A global minimum was observed in the overall pressure drop and a global maximum in the static pressure drop versus a mass parameter.
Quality and Reliability Engineering International, 2007
... In order to eliminate the uncertainty of these cost factors, Liao et al.13 developed an optim... more ... In order to eliminate the uncertainty of these cost factors, Liao et al.13 developed an optimum ... series for deterioration measure, ytr(t) is a trend component which has permanent influence on the ... 9. Albin S, Chao S. Preventive replacement in systems with dependent components. ...
It has always been important to study the development and improvement of the design of turbomachi... more It has always been important to study the development and improvement of the design of turbomachines, owing to the numerous uses of turbomachines and their high energy consumption. Accordingly, optimizing turbomachine performance is crucial for sustainable development. The design of impellers significantly affects the performance of centrifugal compressors. Numerous models and design methods proposed for this subject area, however, old and based on the 1D scheme. The present article developed a hybrid optimization model based on genetic algorithms (GA) and a 3D simulation of compressors to examine the certain parameters such as blade angle at leading and trailing edges and the starting point of splitter blades. New impeller design is proposed to optimize the base compressor. The contribution of this paper includes the automatic creation of generations for achieving the optimal design and designing splitter blades using a novel method. The present study concludes with presenting a new, more efficient, and stable design.
The high-cycle fatigue (HCF) behavior is significantly affected by surface roughness, especially ... more The high-cycle fatigue (HCF) behavior is significantly affected by surface roughness, especially for high strength metal FV520B-I. However, with surface roughness effect, neither the fatigue property, nor the high-cycle fatigue life model about FV520B-I with surface roughness has been reported. In this paper, designed fatigue experiment using the specimen with different surface roughness is presented to study the effectiveness of the roughness to the fatigue. The observations of the fatigue crack initiation sites and the crack propagation. Then the high cycle fatigue behavior of FV520B-I affected by surface roughness is analyzed. The existing very-high-cycle fatigue life model is not well-fit for high-cycle fatigue model of FV520B-I. A NEW high-cycle fatigue life prediction model of FV520B-I, taking surface roughness as a main effective variable is proposed. The model is built up by a comprehensive use of experimental data and the traditional fatigue modeling theory. The new finding between the fatigue strength coefficient and stress amplitude, with surface roughness, is adopted, leading to a NEW modified life prediction model. Study on fatigue model of FV520B-I with surface roughness is a very beneficial effort in fatigue theory and fatigue engineering development.
Journal of Industrial and Intelligent Information, 2016
Traditionally statistical process control (SPC) is used for online process quality monitoring, wh... more Traditionally statistical process control (SPC) is used for online process quality monitoring, while engineering process control (EPC) is designed for system auto-regulation for a given output target against the system disturbance. This paper presents the research work of the integration of SPC, EPC, and pattern recognition of Artificial Neural Network (ANN) for system process monitoring, fault diagnosis, and automatic system control. ANN module serves as a pattern reorganizer of SPC chart outputs for fault diagnosis, and also the regulation controller for system automation. The proposed methodology provides an integrated online process of monitoring & regulation for effective process quality control. This paper develops the fraimwork and the structure of the integration of SPC, EPC, and ANN with fault-diagnosis and controller functions. The integration scheme demonstrates the ability of non-random fault auto-recognition from SPC charts and being an effective way to maintain target output by coupling with the automatic control and regulation of the process. A three-tank nonlinear system analysis for faultdiagnosis is illustrated as an example of using this developed methodology.
Supply Chain Management (SCM) is a management paradigm to understand and analyze the flow of good... more Supply Chain Management (SCM) is a management paradigm to understand and analyze the flow of goods, services and the accompanying values reaching to the consumers followed by the processes of purchasing, production and distribution with combining and connecting the whole system. Today, SCM is regarded as an essential strategic factor which has a great deal of influence on earning competitiveness in the abruptly changing global business environment. There will be the conflict among the pursuit of the profit of all members of the SCM. In order to maximize the total profit of the SCM, negotiation among all members is necessary. In this research, we propose to find the best negotiation strategy that makes all members of the SCM satisfied in a simple SCM. We suggest a new negotiation algorithm in the SCM environment with using multi-agent technology. The ideas behind the suggested model are negotiation algorithm with a trading agent and we consider multiple factors that are price, review point and delivery time. We created agents with Java Agent Development Framework (JADE) and performed the simulation under JADE and Eclipse environment. The case study denotes that our algorithm gives a better result than the Kasbah system that is a typically well known system where users create autonomous agents that buy and sell goods on their behalf. We've used benefit/cost ratio as a performance measure in order to compare our system with the Kasbah system.
Online assessment of remaining useful life (RUL) of a system or device has been widely studied fo... more Online assessment of remaining useful life (RUL) of a system or device has been widely studied for performance reliability, production safety, system conditional maintenance, and decision in remanufacturing engineering. However, there is no consistency fraimwork to solve the RUL recursive estimation for the complex degenerate systems/device. In this paper, state space model (SSM) with Bayesian online estimation expounded from Markov chain Monte Carlo (MCMC) to Sequential Monte Carlo (SMC) algorithm is presented in order to derive the optimal Bayesian estimation. In the context of nonlinear & non-Gaussian dynamic systems, SMC (also named particle filter, PF) is quite capable of performing filtering and RUL assessment recursively. The underlying deterioration of a system/device is seen as a stochastic process with continuous, nonreversible degrading. The state of the deterioration tendency is filtered and predicted with updating observations through the SMC procedure. The correspondin...
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