To measure the flow velocity of a fluid without affecting its motion state, a method was proposed based on a polyvinylidene fluoride (PVDF) piezoelectric film sensor. A self-made PVDF piezoelectric sensor placed parallel with the flow direction was used to measure the flow velocity. First, the piezoelectric characteristics of PVDF were obtained theoretically. Next, the relationship between flow velocity and sound pressure was verified numerically. Finally, the relationship between flow velocity and the electrical output of the PVDF piezoelectric film was obtained experimentally. In conclusion, the proposed method was shown to be reliable and effective.

Fluid-filled polyethylene (PE) pipelines have a wide range of applications in, for example, water supply and gas distribution systems, and it is therefore important to understand the characteristics of acoustic propagation in such pipelines in order to detect and prevent pipe ruptures caused by vibration and noise. In this paper, using the appropriate wall parameters, the frequencies of normal waves in a fluid-filled PE pipeline are calculated, and the axial and radial dependences of sound fields are analyzed. An experimental system for investigating acoustic propagation in a fluid-filled PE pipeline is constructed and is used to verify the theoretical results. Both acoustic and mechanical excitation methods are used. According to the numerical calculation, the first-, second-, and third-order cutoff frequencies are 4.6, 10.4, and 16.3 kHz, which are close to the experimentally determined values of 4.7, 10.6, and 16 kHz. Sound above a cutoff frequency is able to propagate in the axial direction, whereas sound below this frequency is attenuated exponentially in the axial direction but can propagate along the wall in the form of vibrations. The results presented here can provide some basis for noise control in fluid-filled PE pipelines.

The Unmanned Surface Vehicle (USV) integrated with an acoustic modem is a novel mobile vehicle for data collection, which has an advantage in terms of mobility, efficiency, and collection cost. In the scenario of data collection, the USV is controlled autonomously along the planning trajectory and the data of underwater nodes are dynamically collected. In order to improve the efficiency of data collection and extend the life of the underwater nodes, a mobile data collection protocol for underwater nodes using the USV was proposed. In the protocol, the stop-and-wait ARQ transmission mechanism is adopted, where the duty cycle is designed considering the ratio between the sleep mode and the detection mode, and the transmission ratio is defined by the duty cycle, wake-up signal cycles, and USV’s speed. According to protocol, the evaluation index for energy consumption is constructed based on the duty cycle and the transmission ratio. The energy consumption of the protocol is simulated and analyzed using the mobile communication experiment data of USV, taking into consideration USV’s speed, data sequence length, and duty cycle. Optimized protocol parameters are identified, which in turn denotes the proposed protocol’s feasibility and effectiveness.

To realize flow field monitoring without interference to the flow field, this study proposes a new passive flow velocity and flow direction measurement system. This method utilizes piezoelectric lead zirconium titanate sensor arrays to measure the flow velocity and direction based on the relevant physical properties of the pressure fluctuation field of the turbulent boundary layer (TBL). Moreover, it can be widely used in flow field monitoring in limited and complex areas with strong interferences. First, the intensity and spatiotemporal characteristics of the TBL pressure fluctuation field are discussed, and the physical principles of three flow velocity measurement methods and two flow direction measurement methods are given according to the different physical characteristics. Second, the effectiveness of each method is verified using numerical simulations. Then, two basic array configurations are given, sensors are produced, and the flow velocity and flow direction measurements under interference environment are conducted in a water tunnel to verify the effectiveness of each measurement method and the noise reduction strategy. The advantages and disadvantages of each measurement method are discussed. Furthermore, neural networks are introduced to reduce the need for manual calibration. Finally, to improve the measurement accuracy and precision, a fusion strategy of the three flow velocity measurement methods is presented. The results prove that the flow velocity and flow direction measurement system can realize effective measurement without interfering with the flow field movement under interference environment.