Here we propose a novel quartz micromachined gyroscope. The sensor has a simple cross-fork structure in the x-y plane of quartz crystal. Shear stress rather than normal stress is utilized to sense Coriolis’ force generated by the input angular rate signal. Compared to traditional quartz gyroscopes, which have two separate sense electrodes on each sidewall, there is only one electrode on each sidewall of the sense beam. As a result, the fabrication of the electrodes is simplified and the structure can be easily miniaturized. In order to increase sensitivity, a pair of proof masses is attached to the ends of the drive beam, and the sense beam has a tapered design. The structure is etched from a z-cut quartz wafer and the electrodes are realized by direct evaporation using the aperture mask method. The drive mode frequency of the prototype is 13.38 kHz, and the quality factor is approximately 1,000 in air. Therefore, the gyroscope can work properly without a vacuum package. The measurement ability of the shear stress detection design scheme is validated by the Coriolis’ force test. The performance of the sensor is characterized on a precision rate table using a specially designed readout circuit. The experimentally obtained scale factor is 1.45 mV/°/s and the nonlinearity is 3.6% in range of ±200 °/s.

This paper proposes a novel embedded surface acoustic wave (SAW) pressure sensor for monitoring civil engineering structures. The sensor consists of a pressure cell and a sensing chip in a metal housing. The whole interior of the sensor is filled with silicone oil for pressure transfer. The sensing chip is a SAW die packaged in a seal cavity to monitor the pressure of the silicone oil. Therefore, the external pressure applied to the cell can be detected by this method. In order to optimize the structure, the strain behavior and pressure measurement of the SAW device are analyzed in detail. The positions of the inter-digital transducer (IDT) and reflectors on the SAW substrate are designed deliberately. The SAW device is fabricated by a lift-off process. The sensor is characterized by a network analyzer. The pressure sensitivity tested is 0.4°/kPa and the nonlinearity is 1.02%. The maximum absolute error is 2.9° in the range of 0-500 kPa.

Existing microelectro mechanical systems (MEMSs) electric field sensors have movable parts and electronic components. The movable parts are susceptible to external vibration, and the electronic components distort the distribution of the measured electric field. Therefore, we proposed a novel MEMS electric field sensor based on surface acoustic wave (SAW) technology. The SAW electric field sensor is a delay line device with an interdigital transducer and a reflector. The substrate of the device is a ZnO/SiO ₂ /Si multilayer structure. The ZnO piezoelectric layer is not only used as the propagation medium of SAW, but also used as the sensing film of the external electric field. Then, the external electric field could be detected by analyzing the change of the eigenfrequency of the SAW. The multilayer structure of the substrate was prepared by MEMS process. The interdigital transducer and the reflector are fabricated by the lift-off process. The SAW sensor is characterized at different external electric field strengths by a network analyzer. The sensitivity of the sensor was 0.23 kHz/(kV m ⁻¹ ) and the nonlinearity was 6.8%.

Digital twins (DTs) have seen widespread application across industries, enabling deep integration of cyber–physical systems. However, previous research has largely focused on domain-specific DTs and lacks a universal, cross-industry modeling framework, resulting in high development costs and low reusability. To address these challenges, this study proposes a DT modeling method based on hierarchical decoupling and topological connections. First, the system is decomposed top–down into three levels—system, subsystem, and component—through hierarchical functional decoupling, reducing system complexity and supporting independent component development. Second, a method for constructing component-level DTs using standardized information sets is introduced, employing the JSON-LD language to uniformly describe and encapsulate component information. Finally, a topological connection mechanism abstracts the relationships between components into an adjacency matrix and assembles components and subsystems bottom–up using graph theory, ultimately forming the system-level DT. The effectiveness of the proposed method was validated using a typical surface water purification system as a case study, where the system was decomposed into four functional subsystems and 12 types of components. Experimental results demonstrate that the method efficiently enables automated integration of DTs from standardized components to subsystems and the complete system. Compared with conventional monolithic modeling approaches, it significantly reduces system complexity, supports efficient component development, and accelerates system integration. For example, when the number of components exceeds 300, the proposed method generates topology connections 44.69% faster than direct information set traversal. Consequently, this approach provides a novel and effective solution to the challenges of low reusability and limited generality in DT models, laying a theoretical foundation and offering technical support for establishing a universal cross-industry DT modeling framework.