## 2 Materials and Methods
### Microseismic Monitoring Signals
#### 2.1.2 Waveform Features  
Microseismic events manifest in various forms of waveform images, each possessing unique characteristics. To comprehensively analyze and classify microseismic events, researchers can employ methods for extracting relevant features from these waveform images. Figure 3 illustrates different types of microseismic event waveform images, encompassing microseismic events (commonly referred to as rock microfracture events), blasting events, rock drilling events, power interference events, and other noise events. The diversity in these images reflects the waveform features of different events; thus, feature extraction from these images can aid in better understanding and distinguishing various types of microseismic events.  
Microseismic event classification can typically be based on triggering mechanisms, waveform characteristics, and occurrence locations [27]. Common classifications of microseismic events include naturally occurring microseismic events, which are triggered by natural processes such as underground structural movement and rock deformation; human-induced microseismic events, which are caused by human activities such as mining operations and blasting; and rock burst events, which are caused by the rupture or collapse  
Figure 3: Various types of microseismic event waveform images. (**a**) Different waveforms of rock microfracture (**b**) Different waveforms of blasting (**c**) Drilling (**d**) Orepass blasting (**e**) Electrical noise (**f**) Background noise.  
of rocks. Based on different triggering mechanisms, monitored microseismic events can be divided into the following categories:  
1. Rock microfracture microseismic events, which are usually associated with stress changes and cracks in underground rock formations. The waveform characteristics of these events show small amplitude, high frequency, short duration, and may display certain periodicity.
2. Blasting events are seismic signals generated by blasting activities in mines or underground projects. The waveform characteristics are usually high amplitude, low frequency, longer duration, and specific spectral features.
3. Rock drilling events, which originate from mechanical activities such as rock gouging and drilling in mines and other sites, produce noisy signals. Although these signals may appear in microseismic monitoring, they are unrelated to seismic activity and need to be distinguished from microseismic events. Their waveform characteristics are generally characterized by high amplitude noise, broad bandwidth, transient signals, and lack of significant periodicity.
4. Other noise events, which refer to noise sources other than rock drilling events, such as unloading, equipment operation, power interference, and groundwater flow, may interfere with the monitoring and identification of MS. The waveform characteristics of these noise events are usually random, irregular, and without obvious frequency and amplitude patterns.  
Extracting features from waveform images is a critical step in microseismic event analysis because these features can be used to characterize the event in both the time and frequency domains. These features may include amplitude, frequency, energy distribution, waveform shape, etc. By quantitatively analyzing these features, researchers can establish models for microseismic event recognition and classification [28]. These models can assist mining and underground engineering monitoring systems in more accurately identifying and responding to potential microseismic events, thereby enhancing the safety and sustainability of underground operations. Figure 3 provides a visual reference, emphasizing the diversity of waveform images and underscoring the necessity of feature extraction from these images. By subdividing microseismic events based on different classification criteria, we can gain a more accurate understanding of different types of underground activities and their potential impacts, thus better safeguarding the safety of mines and projects.