# Method of Suppressing Rayleigh Waves Based on the Technology of Time-Domain Differential Detection
## 5 Conclusions  
The time-domain differential detection method uses characteristics similar to Rayleigh waves recorded between adjacent small-offset traces at common source points to suppress Rayleigh waves. As discussed previously, this suppression is executed independently at the coordinates of two adjacent detectors without depending on or associating with records from other coordinate points, demonstrating its widespread applicability. Other relevant conclusions drawn from empirical observations are as follows:  
1. Rayleigh waves traveling near a free surface exhibit speeds similar to those of direct transverse waves, facilitating effective suppression of both types.
2. Possessing robust energy and persisting over multiple cycles, Rayleigh waves make differential detection a potent method for suppressing Rayleigh wave groups. This requires further investigation into its advantages and potential limitations in signal extraction.
3. The time-domain differential time is the primary factor influencing the effectiveness of Rayleigh wave suppression. Indirect factors include longitudinal and transverse wave speeds, the spacing of differential detectors, and the frequency characteristics of effective signals.
4. The reflection waves retained after differential processing can exhibit amplitude and phase characteristic alterations, necessitating effective restoration in subsequent analyses.
5. The time-domain differential detection method is effective across the broad field of seismic exploration. Practical applications demonstrate that although the differential detection method is widely applicable, the dynamics of longitudinal and transverse wave propagation parameters can vary substantially due to natural or anthropogenic disturbances near the operational site or within shallow medium structures. Hence, it is imperative to progressively enhance the effectiveness of differential detection technology in practical applications to meet these challenges.  
Conceptualization, D.Z. (Debing Zhu), D.Z. (Dazhou Zhang) and T.Y.; methodology, D.Z. (Debing Zhu) and D.Z. ([PERSON]); software, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and T.Y.; validation, [PERSON] ([PERSON]); formal analysis, [PERSON] ([PERSON]); investigation, R.H. and Q.Z.; resources, R.H.; data curation, [PERSON] ([PERSON]); writing--original draft preparation, [PERSON] ([PERSON]); writing--review and editing, [PERSON] ([PERSON]) and [PERSON] ([PERSON]); visualization, [PERSON] ([PERSON]); supervision, [PERSON] ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Science and Technology Research and Development Program Project of China Railway Group Limited (Major Special Project, No. 2022-Special-09); the Natural Science Foundation of Hunan Province, grant No. 2023J[30663; and in part by The Changzhou Science and Technology Support Project, grant No. CE20235069.  
Not applicable.  
Data Availability Statement: The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.