# Application of Acoustic Emission Technique in Landslide Monitoring and Early Warning: A Review
## 3 Fundamentals of Acoustic Emission Technique
### Instrumentation for Acoustic Emission Monitoring  
Critical AE instrumentation components encompass sensors as transducers, pre-amplifiers, main amplifiers, filters, and an analog-to-digital converter linked to a data acquisition system for parameter extraction and analysis [88]. Figure 4 summarizes the schematic illustration of AE instrumentation.  
Highly sensitive broadband sensors are favored for capturing a broad range of frequencies. Piezoelectric wafers made from lead zirconate titanate (PZT) and polarized during manufacturing are widely utilized because they convert mechanical strains induced by elastic waves into voltage signals through crystal deformations [89]. Sensors vary in  
Figure 4: Schematic illustration of AE instrumentation.  
their frequency ranges, spanning from 0.1 kHz to over 1 MHz, with resonance frequencies adjusted according to specific applications and the properties of the monitored materials.  
Sensors must establish effective coupling with monitored structures, either by direct mounting on surfaces or through waveguides, especially in media with high attenuation such as soils [90]. The skin effect, arising from the wavelength of AE exceeding crystal thickness, leads to surface responses that benefit from flush mounting on surfaces to ensure contact with a coupled fluid layer that resonates with the structure for optimal transmission. Coupling materials should possess acoustic impedance similar to that of both sensors and structures to minimize reflections that could weaken signal penetration into the test structures and enhance sensitivity [91].  
Signals typically remain weak at nano- and microvolt levels, necessitating pre-amplification to enhance amplitudes before transmission through coaxial cables to main amplifiers positioned at a distance from the sensors to mitigate electromagnetic interferences [92]. Pre-amplifiers with gains ranging between 20 and 40 dB amplify signals to microvolt and millivolt levels, making them suitable for further amplification by main multi-channel amplifiers located far from the sensors. In comparison to traditional cable sensors, optical fiber AE sensors offer several advantages, including high sensitivity, broad frequency response, immunity to electromagnetic interference, capability to operate in extreme temperatures, remote monitoring, and intrinsic safety [93].  
Filtering cleans signals from electromagnetic noise, environmental disturbances, and high/low frequency artifacts, respectively, before digitization [94]. High pass filters above 20-30 kHz eliminate seismic/acoustic noises, while low pass filters under 1 MHz attenuate resonance peaks centered at sensor natural frequencies to retrieve genuine signals. Adjustable gain amplifiers regulate final signal amplitudes before analog-to-digital conversion.  
Multi-channel data acquisition systems connect amplifiers to computers running customized software for additional processing, event discrimination, and parameter extraction [95]. Fast Fourier transformations are used to analyze frequency domain spectra from time-domain signals, while continuous wavelet transforms extract time-frequency information by converting signals into coded digital bitstream formats [96]. Data analysis provides parameters such as amplitudes, energy levels, rise times, counts, and event rates for empirical correlations with mechanical and failure responses observed through reference techniques [97].  
Overall, well-designed AE systems enhance sensitivity by combining components that work together effectively as integrated units to account for the unique attenuation characteristics of geological materials. This ensures signal integrity throughout the entire process, from detection to analysis. Furthermore, the incorporation of automated algorithms for pattern recognition and machine learning modeling improves the interpretation of data from growing datasets collected during continuous monitoring periods.