Developments in data storage and sensor technologies have allowed the cumulation of a large volume of data from industrial systems.Both structural and non-structural data of industrial systems are collected,which cove...Developments in data storage and sensor technologies have allowed the cumulation of a large volume of data from industrial systems.Both structural and non-structural data of industrial systems are collected,which covers data formats of time-series,text,images,sound,etc.Several researchers discussed above were mostly qualitative,and ceratin techniques need expert guidance to conclude on the condition of gearboxes.But,in this study,an improved symbiotic organism search with deep learning enabled fault diagnosis(ISOSDL-FD)model for gearbox fault detection in industrial systems.The proposed ISOSDL-FD technique majorly concentrates on the identification and classification of faults in the gearbox data.In addition,a Fast kurtogram based time-frequency analysis can be used for revealing the energy present in the machinery signals in the time-frequency representation.Moreover,the deep bidirectional recurrent neural network(DBiRNN)is applied for fault detection and classification.At last,the ISOS approach was derived for optimal hyperparameter tuning of the DL method so that the classification performance will be improvised.To illustrate the improvised performance of the ISOSDL-FD algorithm,a comprehensive experimental analysis can be performed.The experimental results stated the betterment of the ISOSDLFD algorithm over current techniques.展开更多
Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monito...Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model gen展开更多
An optical flequency comb phase-locked on an iodine frequency stabilized diode laser at 634 nm is constructed to transfer the accuracy and stability from the optical domain to the radio frequency domain. An external-c...An optical flequency comb phase-locked on an iodine frequency stabilized diode laser at 634 nm is constructed to transfer the accuracy and stability from the optical domain to the radio frequency domain. An external-cavity diode laser is frequency-stabilized on the Doppler-free absorption signals of the hyperfine transition R（80）8-4 using the third-harmonic detection technique. The instability of the ultra-stable optical oscillator is determined to be 7 ×10^-12 by a cesium atomic clock via the optical frequency comb＇s mass frequencv dividing technique.展开更多
In this paper, we utilized villared rectifier technique to harvest wireless energy to overcome previously used RF-WEH rectenna. Our design focuses mainly on a multiple-stage Villard voltage multiplier model to rectify...In this paper, we utilized villared rectifier technique to harvest wireless energy to overcome previously used RF-WEH rectenna. Our design focuses mainly on a multiple-stage Villard voltage multiplier model to rectify the output voltage of the rectenna and transferred it to a dc load. As a starting point, optimization and parameter analysis offer a novel and small antenna for the 2.45 GHz ISM band that precisely matched. Moreover, the fabricated prototype has measured and simulated results have confirmed the antenna’s accuracy in the reflection coefficient. Second, a highly efficient antenna may effectively harvest the electrical energy by combining with the two-stage voltage multiplier circuit presented at the ISM band. Furthermore, the proposed rectenna has the optimum performance compared to state of art rectennas in terms of efficiency, power range, and impedance bandwidth showing pronounced achievement and increasing the DC output power significantly. The prototype is fabricated and experimentally tested to confirm the concept. Measurement results show that the proposed rectenna can be used for RF energy harvesting applications.展开更多
文摘Developments in data storage and sensor technologies have allowed the cumulation of a large volume of data from industrial systems.Both structural and non-structural data of industrial systems are collected,which covers data formats of time-series,text,images,sound,etc.Several researchers discussed above were mostly qualitative,and ceratin techniques need expert guidance to conclude on the condition of gearboxes.But,in this study,an improved symbiotic organism search with deep learning enabled fault diagnosis(ISOSDL-FD)model for gearbox fault detection in industrial systems.The proposed ISOSDL-FD technique majorly concentrates on the identification and classification of faults in the gearbox data.In addition,a Fast kurtogram based time-frequency analysis can be used for revealing the energy present in the machinery signals in the time-frequency representation.Moreover,the deep bidirectional recurrent neural network(DBiRNN)is applied for fault detection and classification.At last,the ISOS approach was derived for optimal hyperparameter tuning of the DL method so that the classification performance will be improvised.To illustrate the improvised performance of the ISOSDL-FD algorithm,a comprehensive experimental analysis can be performed.The experimental results stated the betterment of the ISOSDLFD algorithm over current techniques.
文摘Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model gen
基金supported by the National"973"Program of China(No.2006CB921401 and 2006CB921402)the Major Program of National Natural Science Foundation of China(No.60490280)the National Natural Science Foundation of China(No.10574005)
文摘An optical flequency comb phase-locked on an iodine frequency stabilized diode laser at 634 nm is constructed to transfer the accuracy and stability from the optical domain to the radio frequency domain. An external-cavity diode laser is frequency-stabilized on the Doppler-free absorption signals of the hyperfine transition R（80）8-4 using the third-harmonic detection technique. The instability of the ultra-stable optical oscillator is determined to be 7 ×10^-12 by a cesium atomic clock via the optical frequency comb＇s mass frequencv dividing technique.
文摘In this paper, we utilized villared rectifier technique to harvest wireless energy to overcome previously used RF-WEH rectenna. Our design focuses mainly on a multiple-stage Villard voltage multiplier model to rectify the output voltage of the rectenna and transferred it to a dc load. As a starting point, optimization and parameter analysis offer a novel and small antenna for the 2.45 GHz ISM band that precisely matched. Moreover, the fabricated prototype has measured and simulated results have confirmed the antenna’s accuracy in the reflection coefficient. Second, a highly efficient antenna may effectively harvest the electrical energy by combining with the two-stage voltage multiplier circuit presented at the ISM band. Furthermore, the proposed rectenna has the optimum performance compared to state of art rectennas in terms of efficiency, power range, and impedance bandwidth showing pronounced achievement and increasing the DC output power significantly. The prototype is fabricated and experimentally tested to confirm the concept. Measurement results show that the proposed rectenna can be used for RF energy harvesting applications.
