In response to the difficulty of weak detection of early bearing damage, resonance demodulation technology and the principle of fiber Bragg grating sensing strain were combined to design a fiber Bragg grating generalized resonance sensor, which can extract the weak pulse signal of weak detection of early bearing’s early damage from rolling bearing. First, a principle of resonance dynamics of second-order mechanical systems based on fiber Bragg grating and generalized resonance principles is proposed. Second, the basic structure of the sensor is designed. Then, ANSYS finite element simulation is used to analyze the natural frequency of the sensor. Finally, the natural frequency value of the sensor was obtained through experiments. The experimental results of proof-of-principle show that the experimental results are consistent with the theoretical predictions. The theoretical model is accurate, which verifies the feasibility of the sensor.

No abstract

No abstract

Aiming at the problems of weak dynamic response and difficulty in diagnosis of early damage of rolling bearings, a diagnosis method for early damage of rolling bearings is proposed. Taking radial rolling bearings as the main research object, the load symmetric structure of deep groove ball bearings is analyzed. Based on the mechanical second-order system theory, the sensor monitoring structure is constructed. The generalized resonance principle is used to identify weak signals, and the fiber Bragg grating is used for signal sensing. The signal is obtained through the fiber Bragg grating high-speed demodulator. When a continuous periodic generalized resonance wave appears in the amplitude–frequency analysis of the signal, and there is a high-frequency resonance frequency, it can be proved that the bearing is faulty. The diagnosis method can effectively avoid the interference of low-frequency signals, the frequency spectrum is pure and there is no electromagnetic interference. It fully shows that the fiber Bragg grating sensor is suitable for the monitoring and diagnosis of the early weak fault of the bearing.

The traditional MFP (matched field processing, MFP) methods of underwater acoustic target often have poor estimation performance or get inaccurate estimation result on the constrain of spatial sparse observation. Considering the problem, this paper proposed a new high-accuracy MFP estimation algorithm of underwater acoustic target based on compressed sensing by analyzing the space sparsity of underwater target location. The algorithm established the spatial sparse description model of underwater target, and compressed sensing the underwater target in spatial domain, then used the joint sparse reconstruction algorithm to achieve the MFP estimation of underwater acoustic target. The simulation results show that the method can increase the DOA estimation accuracy of underwater acoustic target at less array elements and less snapshots.