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PreAnalysis of extremely low frequency magnetic signals to predict earthquakes

Earthquakes occur due to sudden release of buildup tectonic stresses deep in the Earth. These stresses accumulate over a period of time. The processes that occur in the crustal rocks lead to the activation of highly mobile electronic charge carriers. These charges flow out of the stressed rock into surrounding rocks. Such outflow generates electromagnetic (EM) signals. If the outflow occurs in bursts, it will lead to short EM pulses. If the outflow is continuous, the currents may fluctuate, generating EM emissions over a wide frequency range. Only ultra-low and extremely low frequency (ULF/ELF) waves travel through rock and can reach the Earth surface. Periods of high stress can be detected by monitoring changes in magnetic susceptibility and electrical resistivity. The local magnetic field becomes stronger shortly before an earthquake. It is observed that there is an exceptional increase in the ELF signals (0.01 Hz to 0.5 Hz) three hours prior to the earthquake. In this paper we present an instrumentation system to detect and analyze the changes in the ELF signals prior to an earthquake wirelessly using ZigBee. The ELF antenna acts as a sensor. It converts the variations in the earth's magnetic field to voltage (μv) which is then amplified by the signal conditioning circuit. The signal is further processed by an AVR (Alf Vegard RISC) processor microcontroller and transmitted via ZigBee. An alarm is switched on if the transmitted signal value exceeds the threshold value. The ELF variations are continuously monitored on the hyper terminal. Using a GPS system the value is further sent as an SMS to the mobile phone along with the location.