In order to improve the control effect of traditional PID controller on boiler drum water level, the boiler drum water level is simulated and studied by using MATLAB software and integrating fuzzy control algorithm on the basis of traditional PID control. The results show that the time for boiler drum water level control using fuzzy-PID control to reach steady state is better than that of conventional PID control. The maximum overshoot of boiler drum water level control using fuzzy-PID control is also better than conventional PID control. The stability, anti-interference ability and robustness of the system are obviously superior to the traditional PID control.

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The vehicle detection algorithm is an important part of the intelligent transportation system. The accuracy of the algorithm will determine whether accurate vehicle information can be obtained. The system contains several functional modules, including signal amplification, wireless communication, A/D converter, and sensor set/reset functions. To detect all the intersection vehicles, a number of magnetoresistive sensors are connected to the computer system through the wireless communication module, and then, the detected vehicle information will be transferred back to the master host computer. In this paper, two common vehicle detection algorithms, fixed threshold algorithm and adaptive threshold algorithm, were analyzed in the vehicle detection system with magnetoresistive sensors, simultaneously. Finally, an improved multi-intermediate state machine algorithm for vehicle detection was proposed. Using the intermediate state, this algorithm cannot only detect when the vehicle enters the detection area but also decide whether the vehicle leaves the sensor node or not. In this way, it improves the detection accuracy.

Time-frequency analysis is recognized as a dynamic tool to analyze the nonstationary signal. The synchrosqueezing transform is usually applied as a post-processing method to further improve the readability of the time-frequency representation. Synchrosqueezing transform is related to the reassignment method and can be performed in two directions, namely time direction and frequency direction. Frequency-direction reassignment helps to squeeze the slowly changing ridge. However, the time-direction reassignment is efficient to process the signal with rapid variation in instantaneous frequency. Thus, there exists a conflict in most of the time-frequency analysis methods while dealing with a signal containing both of these two components. In this study, a new method called demodulated time-direction synchrosqueezing transform is introduced, which is not only capable of achieving a higher compact TFR but also allow reconstructing the mode. In order to explain demodulated time-direction synchrosqueezing transform, a signal model is established in frequency domain. Then, a demodulated procedure is implemented to eliminate time-frequency analysis diffusion. Finally, time-direction reassignment is carried out to further enhance the energy concentration of the time-frequency analysis. The proposed demodulated time-direction synchrosqueezing transform method is evaluated by both simulation and experimental research. The results reveal that the performance of demodulated time-direction synchrosqueezing transform is better than the conventional time-frequency analysis methods, and it can be applied to the fault diagnosis in a machine.

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