# An Earthquake Forecast Model Based on Multi-Station PCA Algorithm
## 3 AETA System  
### AETA System Structure  
Previous research works have found a variety of precursor anomalies, and we focus on the electromagnetic radiation anomaly in the earthquake preparation period and occurrence period, and we call it earthquake electromagnetism. [PERSON]'s work [16] shows that different electromagnetic radiation anomalies include changes of the geoelectric field, electromagnetic field, electromagnetic disturbance signal, and the charge concentration in the space ionosphere often appears before an earthquake. These electromagnetic signals may come from the piezomagnetic effect, piezoelectric effect, induced magnetic effect, dynamic electromagnetic effect, thermal magnetic effect, and other subsurface processes. [PERSON]'s work [17] and [PERSON]'s work [18] observed electromagnetic anomalies in the ultra-low frequency band before the Wenchuan earthquake, Minxian Zhangxian earthquake, and Izu Islands earthquake; the seismic electromagnetic anomalies are mainly concentrated in the ultra-low frequency band below 30 Hz.  
Although the ultra-low frequency electromagnetic anomalies have shown significant relation with earthquakes, there is still no work to monitor it in the long term and over a large area. However, earthquake precursor anomalies are generally long-term processes, so there is a large space in such a research area. To explore the possibility of ultra-low frequency electromagnetic anomalies in the long term, we designed the AETA system and set about four hundred monitor stations around Sichuan and Yunan, and the area is about 800,000 km\({}^{2}\). Figure 1 shows the whole system of AETA. One station of AETA consists of a probe and station devices, which are responsible for data processing tasks and data uploading tasks. The probe collects acoustic and magnetic signals and sends them to the station for the next step. The station will do some processing work that contains down-sampling and wave filtering; then, it sends them to the cloud server. Everyone could gain data through the webpage and API. (To access the public data, just view the website aeta.cn or [[https://dtvs.aeta.net/stations](https://dtvs.aeta.net/stations)]([https://dtvs.aeta.net/stations](https://dtvs.aeta.net/stations)), or send an email to [EMAIL_ADDRESS]. The last access of the database is 6 December 2021.) Figure 2 shows the distribution of AETA stations. The stations follow the distribution of fault zones in this area to catch anomalies as much as possible.  
The electromagnetic disturbance probe has a frequency response range of 0.1 Hz\(\sim\)10 kHz with an intensity range of 0.1 nT\(\sim\)1000 nT. Its sensitivity is 20 mV/nT in the range of 0.1 Hz\(\sim\)10 kHz, the data resolution is 18 bit, and the voltage resolution is 19.073 \(\mu\)V. The high-frequency sampling rate of the probe is 30 kHz.  
The energy of magnetic abnormal concentrates in ultra-low frequency [19; 20; 21]. According to this, we use a Butterworth filter to down-sample the raw data of 30 kHz to reduce the cost of data transmission and storage. The signal energy is concentrated below 250 Hz. According to the Nyquist sampling theorem [22], a sample rate \(f_{s}\) could perfectly reconstruct a signal whose band limit is \(f_{s}/2\), and the raw data will be down-sampled to 500 Hz, and this process saves information in the raw data under 250 Hz. The difference between the full frequency signal and the low-frequency signal is not obvious, and the signal energy is concentrated below 250 Hz. The seismic electromagnetic phenomenon is related to the rock fracture caused by the accumulation of underground stress and the electromagnetic radiation generated during the development of microcracks. This is more related to the ultra-low frequency signal below 30 Hz, and this frequency is less interfered with by other electromagnetic sources, so this frequency range is more valuable.