Theory And Method Based On Stochastic Resonance For Enhanced Detection Of Transmission State Of Helicopter

Helicopter plays a significant role in national military, economic and social development, which is widely used in modern warfare, military operations other than war and dealing with civil affairs. As a low altitude aircraft, once an abnormality occurs in helicopter transmission, it may cause a catastrophic accident. As a result of helicopter vibration in flight, the transmission works in a harsh environment, which leads the test dynamic signal to a very serious problem of low signal to noise ratio. The appearance of incipient fault or potential failure’s feature is relatively minor with the peculiarity of unobvious symptom and weak characteristic signal. Even if a transmission fault evolves into medium or terminal stage, the characteristic signal may be overwhelmed by strong noise, resulting in comparatively weak characteristics, which is difficult to identify. If the abnormal operating state or the earlier symptom induced by potential failure of the transmission system can be accurately captured or detected, damage evolution should be attracted, and active control should be adopted to prevent the state deterioration, which is urgent and critical to avoid the disaster event caused by helicopter transmission fault.The enhanced detection of incipient fault/damage is a problem of weak characteristic signal detection under strong noise in nature. Recently, more and more researchers are centering their attention on the weak characteristic signal detection technology based on nonlinear enhancement effect because of its promising potential. Stochastic resonance(SR), with its unique advantages, has a valuable contribution to the field of weak signal detection. Aiming at the practical problems, this paper studies the state enhanced detection theory and methods of helicopter transmission system based on nonlinear enhancement effect of SR. The main work in this paper is as follows:(1) Normalized scale transform model implemented by parameter adjustment SR is constructed. And the process of large parameter signal detection is designed. A circuit module of parameter adjustment SR is also designed. Two incipient fault enhanced detection strategies are proposed based on the normalized scale transform model and the constructed circuit module. The effectiveness of the models and strategies are validated by the test results of bearing fault enhanced detection of a test rig and a helicopter transmission. The experiments on bearings with seeded faults and helicopter transmission bearing with rolling element damage indicate that the two strategies are suitable for enhanced fault detection of critical components of transmission.(2) Enhanced detection method of incipient bearing fault is proposed based on signal pre-whitening and SR. The raw vibration signal from gears and bearings of transmission is decomposed by signal pre-whitening based on cepstrum editing. The resulting pre-whitened signal, including white noise and impact signal caused by the damage, is enhanced by the model based on SR. The proposed incipient fault detection method is validated by experiments of seeded fault bearings. And the ability of tracking damage evolution of this method is also proved.(3) The model of multi-scale bistable stochastic resonance array is constructed. And the SR effect of this array model, being composed of bistable SR units, is studied. The model is designed to process the noisy signal with noise intensity beyond the SR resonance region. Based on the enhancement effect of stochastic resonance in this multi-scale bistable array model and the normalized scale transformation, weak signal detection method is proposed. The proposed method’s enhanced detection ability is validated by the numerical simulation signal and fault seeded test data. Finally, the result of the proposed method is compared with that of the detection methods of single SR unit and kurtogram. The comparison shows that the proposed method is better than the two classical methods.(4) Quantitative detection method of weak periodic signal is proposed based on SR. Adding a bias signal to a nonlinear bistable system, which is driven by noise and weak periodic signal, it is found that the mean residence time difference varies monotonously according to the weak periodic signal amplitude in statistical mean. This phenomenon is explained by the concept of resonance trapping. Mean residence time difference is proposed as an indicator to quantitatively characterize amplitude and phase of the weak periodic driving signal. Finally, signal recovery method based on SR is present. The effectiveness of the quantitative detection and the signal recovery method is proved by numerical simulation signal and test data with SR circuit.(5) The weak characteristic signal enhanced detection technology based on SR is integrated in the fault diagnosis system of helicopter transmission. Common vibration features are studied on their sensitivity to damage and ability to track damage size. Enhanced vector, consisting of a variety of common vibration features and features based on SR, is constructed to depict the state of key components of helicopter transmission. The feature enhanced detection technology based on SR is verified and confirmed by the constructed experiment system.In summary, the characteristic signal enhanced detection strategies based on SR via circuit module and software, a key component state enhanced detection method combined SR enhancement and pre-whitening based signal decomposition, a weak signal enhanced detection method based on the constructed multi-scale bistable array model, which expand the array SR theory, a quantitative weak periodic signal detection and recovery method based SR are proposed in this paper. Finally, the resulting model and methods of research are integrated into the status monitoring and fault diagnosis system of helicopter transmission.