Because performance parameters of gear have degradation,a method is proposed to recognize and analyze its faults using the hidden Markov model( HMM). In this method,firstly,the delayed correlation-envelope method is u...Because performance parameters of gear have degradation,a method is proposed to recognize and analyze its faults using the hidden Markov model( HMM). In this method,firstly,the delayed correlation-envelope method is used to extract features from vibration signals. Then,HMMs are trained respectively using data under normal condition,gear root crack condition and gear root breaking condition. Further,the trained HMMs are used in pattern recognition and model assessment. Finally,the results from standard HMM and the proposed method are compared, which shows that the proposed methodology is feasible and effective.展开更多
Most proteins adopt an approximate structural symmetry. However, they have no symmetry detectable in their sequences and it is unclear for most of these proteins whether their structural symmetry originates from dupli...Most proteins adopt an approximate structural symmetry. However, they have no symmetry detectable in their sequences and it is unclear for most of these proteins whether their structural symmetry originates from duplication. As one of the six popular folds (super-folds) possessing an approximate structural symmetry, the triosephosphate isomerase barrel (TIM-barrel) domain has been widely studied. Using modified recurrent quantification analysis of primary sequences, we identified the same 2-, 3-, and 4-fold symmetry pattern as their tertiary structures. This result indicates that the symmetry in tertiary structure is coded by symmetry in the primary sequence and that the TIM-barrel adopts a 2-, 3-, or 4-fold repeat pattern during evolution. This discovery will be useful for understanding the evolutionary mechanisms of this protein family and the symmetry pattern that may be a clue into the ancient origin of duplication of half-barrels or the β a unit.展开更多
Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we deve...Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we develop a pure mechanical sensor architecture for intent pattern recognition of lower-limb motion. The sensor system is composed of an accelerometer, a gyroscope mounted on the prosthetic socket, and two pressure sensors mounted under the sole. To compensate the delay in the control of prosthesis, the signals in the stance phase are used to predict the terrain and speed in the swing phase. Specifically, the intent pattern recognizer utilizes intraclass correlation coefficient(ICC) according to the Cartesian product of walking speed and terrain. Moreover, the sensor data are fused via DempsterShafer's theory. And hidden Markov model(HMM) is used to recognize the realtime motion state with the reference of the prior step. The proposed method can infer the prosthesis user's intent of walking on different terrain, which includes level ground,stair ascent, stair descent, up and down ramp. The experiments demonstrate that the intent pattern recognizer is capable of identifying five typical terrain-modes with the rate of 95.8%. The outcome of this investigation is expected to substantially improve the control performance of powered above-knee prosthesis.展开更多
文摘Because performance parameters of gear have degradation,a method is proposed to recognize and analyze its faults using the hidden Markov model( HMM). In this method,firstly,the delayed correlation-envelope method is used to extract features from vibration signals. Then,HMMs are trained respectively using data under normal condition,gear root crack condition and gear root breaking condition. Further,the trained HMMs are used in pattern recognition and model assessment. Finally,the results from standard HMM and the proposed method are compared, which shows that the proposed methodology is feasible and effective.
文摘Most proteins adopt an approximate structural symmetry. However, they have no symmetry detectable in their sequences and it is unclear for most of these proteins whether their structural symmetry originates from duplication. As one of the six popular folds (super-folds) possessing an approximate structural symmetry, the triosephosphate isomerase barrel (TIM-barrel) domain has been widely studied. Using modified recurrent quantification analysis of primary sequences, we identified the same 2-, 3-, and 4-fold symmetry pattern as their tertiary structures. This result indicates that the symmetry in tertiary structure is coded by symmetry in the primary sequence and that the TIM-barrel adopts a 2-, 3-, or 4-fold repeat pattern during evolution. This discovery will be useful for understanding the evolutionary mechanisms of this protein family and the symmetry pattern that may be a clue into the ancient origin of duplication of half-barrels or the β a unit.
基金supported in part by the National Nature Science Fundation(61174009,61203323)Youth Foundation of Hebei Province(F2016202327)+3 种基金the Colleges and Universities in Hebei Province Science and Technology Research Project(ZC2016020)supported in part by Key Project of NSFC(61533009)111 Project(B08015)Research Project(JCYJ20150403161923519)
文摘Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we develop a pure mechanical sensor architecture for intent pattern recognition of lower-limb motion. The sensor system is composed of an accelerometer, a gyroscope mounted on the prosthetic socket, and two pressure sensors mounted under the sole. To compensate the delay in the control of prosthesis, the signals in the stance phase are used to predict the terrain and speed in the swing phase. Specifically, the intent pattern recognizer utilizes intraclass correlation coefficient(ICC) according to the Cartesian product of walking speed and terrain. Moreover, the sensor data are fused via DempsterShafer's theory. And hidden Markov model(HMM) is used to recognize the realtime motion state with the reference of the prior step. The proposed method can infer the prosthesis user's intent of walking on different terrain, which includes level ground,stair ascent, stair descent, up and down ramp. The experiments demonstrate that the intent pattern recognizer is capable of identifying five typical terrain-modes with the rate of 95.8%. The outcome of this investigation is expected to substantially improve the control performance of powered above-knee prosthesis.
