The existing researches on quartz gyroscope mainly focus on the structure design of the tuning fork, which aim at obtaining a better vibration characterization. However, the fabrication of complicated structure is a c...The existing researches on quartz gyroscope mainly focus on the structure design of the tuning fork, which aim at obtaining a better vibration characterization. However, the fabrication of complicated structure is a challenge for present processes, and the imperfect fabrication process seriously affects the performances of the sensors. In this paper, a novel quartz cross-fork structure micromachined gyroscope is proposed. The sensor has a simple structure in x-y plane of quartz crystal. Unlike other quartz gyroscopes, the proposed gyroscope is based on shear stress detection to sense Coriolis’ force rather than normal stress detection. This feature can simplify the sensing electrode patterns and miniaturize the structure easily. Then the mechanical analysis of the structure is discussed. In order to obtain high sensitivities and uniform characteristics between different structures, the sensing beam is designed to be tapered, and the taper should be appreciably greater than 1°. This scheme is validated by finite element analysis software. The dynamic characteristic of the structure is analyzed by lumped parameter model. The dynamic stress in the beam and the detection sensitivity are deduced to optimize the structure parameter of gyroscope. Finally, the gyroscope is fabricated by quartz anisotropic wet etching. The prototype is characterized as follows. The drive mode frequency is 13.38 kHz, and the quality factor is about 900 in air. The scale factor is 1.45 mV/（（°） s –1 ） and the nonlinearity is 3.6% in the dynamic range of ±200°/s. Process and test results show that the proposed quartz gyroscope can achieve a high performance at atmosphere pressure. The research can simplify the fabrication of the quartz gyroscope, and is taken as a novel method for the design of quartz gyroscope.展开更多
Turbopump condition monitoring is a significant approach to ensure the safety of liquid rocket engine （LRE）.Because of lack of fault samples,a monitoring system cannot be trained on all possible condition patterns.T...Turbopump condition monitoring is a significant approach to ensure the safety of liquid rocket engine （LRE）.Because of lack of fault samples,a monitoring system cannot be trained on all possible condition patterns.Thus it is important to differentiate abnormal or unknown patterns from normal pattern with novelty detection methods.One-class support vector machine （OCSVM） that has been commonly used for novelty detection cannot deal well with large scale samples.In order to model the normal pattern of the turbopump with OCSVM and so as to monitor the condition of the turbopump,a monitoring method that integrates OCSVM with incremental clustering is presented.In this method,the incremental clustering is used for sample reduction by extracting representative vectors from a large training set.The representative vectors are supposed to distribute uniformly in the object region and fulfill the region.And training OCSVM on these representative vectors yields a novelty detector.By applying this method to the analysis of the turbopump＇s historical test data,it shows that the incremental clustering algorithm can extract 91 representative points from more than 36 000 training vectors,and the OCSVM detector trained on these 91 representative points can recognize spikes in vibration signals caused by different abnormal events such as vane shedding,rub-impact and sensor faults.This monitoring method does not need fault samples during training as classical recognition methods.The method resolves the learning problem of large samples and is an alternative method for condition monitoring of the LRE turbopump.展开更多
基金supported by National Natural Science Foundation of China(Grant No.51005240)
文摘The existing researches on quartz gyroscope mainly focus on the structure design of the tuning fork, which aim at obtaining a better vibration characterization. However, the fabrication of complicated structure is a challenge for present processes, and the imperfect fabrication process seriously affects the performances of the sensors. In this paper, a novel quartz cross-fork structure micromachined gyroscope is proposed. The sensor has a simple structure in x-y plane of quartz crystal. Unlike other quartz gyroscopes, the proposed gyroscope is based on shear stress detection to sense Coriolis’ force rather than normal stress detection. This feature can simplify the sensing electrode patterns and miniaturize the structure easily. Then the mechanical analysis of the structure is discussed. In order to obtain high sensitivities and uniform characteristics between different structures, the sensing beam is designed to be tapered, and the taper should be appreciably greater than 1°. This scheme is validated by finite element analysis software. The dynamic characteristic of the structure is analyzed by lumped parameter model. The dynamic stress in the beam and the detection sensitivity are deduced to optimize the structure parameter of gyroscope. Finally, the gyroscope is fabricated by quartz anisotropic wet etching. The prototype is characterized as follows. The drive mode frequency is 13.38 kHz, and the quality factor is about 900 in air. The scale factor is 1.45 mV/（（°） s –1 ） and the nonlinearity is 3.6% in the dynamic range of ±200°/s. Process and test results show that the proposed quartz gyroscope can achieve a high performance at atmosphere pressure. The research can simplify the fabrication of the quartz gyroscope, and is taken as a novel method for the design of quartz gyroscope.
基金supported by National Natural Science Foundation of China (Grant No. 50675219)Hu’nan Provincial Science Committee Excellent Youth Foundation of China (Grant No. 08JJ1008)
文摘Turbopump condition monitoring is a significant approach to ensure the safety of liquid rocket engine （LRE）.Because of lack of fault samples,a monitoring system cannot be trained on all possible condition patterns.Thus it is important to differentiate abnormal or unknown patterns from normal pattern with novelty detection methods.One-class support vector machine （OCSVM） that has been commonly used for novelty detection cannot deal well with large scale samples.In order to model the normal pattern of the turbopump with OCSVM and so as to monitor the condition of the turbopump,a monitoring method that integrates OCSVM with incremental clustering is presented.In this method,the incremental clustering is used for sample reduction by extracting representative vectors from a large training set.The representative vectors are supposed to distribute uniformly in the object region and fulfill the region.And training OCSVM on these representative vectors yields a novelty detector.By applying this method to the analysis of the turbopump＇s historical test data,it shows that the incremental clustering algorithm can extract 91 representative points from more than 36 000 training vectors,and the OCSVM detector trained on these 91 representative points can recognize spikes in vibration signals caused by different abnormal events such as vane shedding,rub-impact and sensor faults.This monitoring method does not need fault samples during training as classical recognition methods.The method resolves the learning problem of large samples and is an alternative method for condition monitoring of the LRE turbopump.
