Capacitive micromachined ultrasound transducers (CMUTs) have broad application prospects in medical imaging, flow monitoring, and nondestructive testing. CMUT arrays are limited by their fabrication process, which seriously restricts their further development and application. In this paper, a vacuum-sealed device for medical applications is introduced, which has the advantages of simple manufacturing process, no static friction, repeatability, and high reliability. The CMUT array suitable for medical imaging frequency band was fabricated by a silicon wafer bonding technology, and the adjacent array devices were isolated by an isolation slot, which was cut through the silicon film. The CMUT device fabricated following this process is a 4 × 16 array with a single element size of 1 mm × 1 mm. Device performance tests were conducted, where the center frequency of the transducer was 3.8 MHz, and the 6 dB fractional bandwidth was 110%. The static capacitance (29.4 pF) and center frequency (3.78 MHz) of each element of the array were tested, and the results revealed that the array has good consistency. Moreover, the transmitting and receiving performance of the transducer was evaluated by acoustic tests, and the receiving sensitivity was −211 dB @ 3 MHz, −213 dB @ 4 MHz. Finally, reflection imaging was performed using the array, which provides certain technical support for the research of two-dimensional CMUT arrays in the field of 3D ultrasound imaging.

This paper presents a simple DFT-based golden section searching algorithm (DGSSA) for the single tone frequency estimation. Because of truncation and discreteness in signal samples, Fast Fourier Transform (FFT) and Discrete Fourier Transform (DFT) are inevitable to cause the spectrum leakage and fence effect which lead to a low estimation accuracy. This method can improve the estimation accuracy under conditions of a low signal-to-noise ratio (SNR) and a low resolution. This method firstly uses three FFT samples to determine the frequency searching scope, then – besides the frequency – the estimated values of amplitude, phase and dc component are obtained by minimizing the least square (LS) fitting error of three-parameter sine fitting. By setting reasonable stop conditions or the number of iterations, the accurate frequency estimation can be realized. The accuracy of this method, when applied to observed single-tone sinusoid samples corrupted by white Gaussian noise, is investigated by different methods with respect to the unbiased Cramer-Rao Low Bound (CRLB). The simulation results show that the root mean square error (RMSE) of the frequency estimation curve is consistent with the tendency of CRLB as SNR increases, even in the case of a small number of samples. The average RMSE of the frequency estimation is less than 1.5 times the CRLB with SNR = 20 dB and N = 512.

The telemetry data are essential in evaluating the performance of aircraft and diagnosing its failures. This work combines the oversampling technology with the run-length encoding compression algorithm with an error factor to further enhance the compression performance of telemetry data in a multichannel acquisition system. Compression of telemetry data is carried out with the use of FPGAs. In the experiments there are used pulse signals and vibration signals. The proposed method is compared with two existing methods. The experimental results indicate that the compression ratio, precision, and distortion degree of the telemetry data are improved significantly compared with those obtained by the existing methods. The implementation and measurement of the proposed telemetry data compression method show its effectiveness when used in a high-precision high-capacity multichannel acquisition system.

Currently, a variety of Low-Power Wide-Area Network (LPWAN) technologies offer diverse solutions for long-distance communication. Among these, Long-Range Wide-Area Network (LoRaWAN) has garnered considerable attention for its widespread applications in the Internet of Things (IoT). Nevertheless, LoRaWAN still faces the challenge of channel collisions when managing dense node communications, a significant bottleneck to its performance. Addressing this issue, this study has developed a novel “time allocation adaptive Data Rate” (TA-ADR) algorithm for network servers. This algorithm dynamically adjusts the spreading factor (SF) and transmission power (TP) of LoRa (Long Range) nodes and intelligently schedules transmission times, effectively reducing the risk of data collisions on the same frequency channel and significantly enhancing data transmission efficiency. Simulations in a dense LoRaWAN network environment, encompassing 1000 nodes within a 480 m × 480 m range, demonstrate that compared to the ADR+ algorithm, our proposed algorithm achieves substantial improvements of approximately 30.35% in data transmission rate, 24.57% in energy consumption, and 31.25% in average network throughput.

Carbon fiber-reinforced polymers (CFRPs) are widely used in the fabrication of solid rocket motor casings due to their exceptional performance. However, the bonding interface between CFRP and viscoelastic materials (rubber) is prone to debonding damage during service and storage under complex environmental conditions, which poses a significant threat to the structural integrity and reliability of the engine. Existing nondestructive testing (NDT) methods, such as X-ray imaging, infrared thermography, and ultrasonic testing, although somewhat effective, exhibit significant limitations in detecting interfacial defects in deep or multilayered composite materials, particularly under the challenging conditions of service and storage. This study proposes an innovative method based on active Lamb wave energy analysis and introduces the Damage Evolution Factor (DEF), specifically designed to detect and evaluate interfacial debonding defects in CFRP–rubber bonded structures within solid rocket motors during service and storage. Through numerical simulations and experimental validation, we selected the A0 mode Lamb wave, which is more sensitive to interfacial damage, as the incident wave and excited it on the surface of the structure. Displacement time-history response signals at observation points under different damage models were extracted and analyzed, and DEF values were calculated. The results show that DEF values increase with the size of the interfacial debonding damage. Similar trends were observed in experimental studies, further validating the effectiveness of this method and demonstrating that DEF can be used for the quantitative evaluation of interfacial debonding defects in CFRP–rubber bilayer bonded structures.

A slot microring resonator acoustic sensor (MRAS) using the PDMS package was proposed to achieve ultra-high sensitivity acoustic detection. The acoustic detection principle of the sensor is analyzed theoretically, the structural parameters are optimized and the performance of the sensor is verified by simulation. The simulation results show that the proposed slot MRAS has a high-quality factor of 1.49 × 10⁶, the sensitivity of the sensor by intensity detection method is up to 3872 mV/kPa, and the 3 dB bandwidth is 210 MHz. The sensor designed in this paper has the advantages of ultra-high sensitivity and wide bandwidth range, which has important value in the field of acoustic detection.