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Download the full whitepaper “A Sub-1 Hz Resonance Frequency Resonator Enabled by Multi-Step Tuning for Micro-Seismometer” to learn more.
Fig. 3. Block diagram of the multi-domain simulation. Courtesy of Waseda University, Professor Ikehashi laboratory.
In any given year, we expect about 16 major earthquakes worldwide, 15 of which are in the magnitude 7 range and one in the magnitude 8.0 range or greater [1]. As a result, there is high demand for Earthquake Early Warning (EEW) systems. A nationwide EEW system that is managed by the Japanese Meteorological Agency (JMA) has been operating since 2006 [2]. The network is comprised of 1000 seismic stations, spaced 20 to 25km apart. After the 2011 M9.1 Tohoku-Oki earthquake, JMA collected feedback regarding their EEW systems. People were familiar with the earthquake warning systems and found them useful. The participants provided generally positive feedback regarding the JMA EEW system implementation, and were also surprisingly positive about false alarms. The survey respondents were familiar with the technical limitations of the early warning system, and agreed that they preferred having a system that provided false alarms compared to a system that did not issue warnings about an actual earthquake.
Unfortunately, delays can occur between the characterization and detection of a seismic event due to a sparse (or limited) seismic sensor network. One approach to resolve this problem is to supplement traditional sensor networks with MEMS-based seismic sensors. MEMS sensors are small, inexpensive, and suitable for local monitoring, and could be deployed to increase seismic monitoring capabilities. Using MEMS technology and the Internet of Things (IoT), some interesting seismic sensor technologies have already been developed or deployed as part of an early earthquake warning system [3]. The MyShake project in California provides earthquake alerts using smartphones. One of the three EEW systems in Taiwan, the P-alert system developed by National Taiwan University (NTU), uses MEMS sensors to provide onsite warnings more rapidly.
In collaboration with Waseda University, we have recently worked on the design of a sub-1Hz resonance frequency MEMS resonator that can be used in dense seismometer networks [4]. The low resonance frequency of this device is achieved using electrically tunable springs with ultra-small spring constants. For fine-tuning, we have proposed a multi-step electrical tuning method (Fig. 1). The structure of our seismometer is shown in Fig. 2(a), with a top view of the MEMS+® simulated model shown in Figure 2(b). Unfortunately, the small spring constant needed in the design reduces the shock robustness and dynamic range of the seismometer. To improve the shock robustness and enhance the dynamic range, we employ a force-balanced method in which the mass displacement is nulled by a feedback force (Fig. 3). This innovative design has been simulated in MEMS+, and the design can accurately detect input acceleration (a proxy for seismic motion) using a highly compact form factor.
Fig. 1. The basic principle of multi-step electrical tuning. Courtesy of Waseda University, Professor Ikehashi laboratory.
Fig. 2. (a) Schematic of seismometer structure; (b) Top view of the MEMS+ model central structure of the seismometer. Courtesy of Waseda University, Professor Ikehashi laboratory.
Fig. 3. Block diagram of the multi-domain simulation. Courtesy of Waseda University, Professor Ikehashi laboratory.
The goal of this study has been to develop a sensitive and robust MEMS-based seismometer that could be broadly deployed in Earthquake Early Warning systems. This type of MEMS-based seismometer could provide more accurate earthquake detection with fewer false alarms, helping to save lives. We look forward to our future collaboration with Waseda University, and to the eventual deployment of this advanced seismometer into advanced earthquake warning systems.
Download the full whitepaper “A Sub-1 Hz Resonance Frequency Resonator Enabled by Multi-Step Tuning for Micro-Seismometer” to learn more.