Key Takeaways & Executive Findings
- •• A novel microseismic source location method integrates particle swarm optimization with multi-sensor arrays, adaptively weighting P-wave arrivals to enhance accuracy. • The method reduces location error by up to 97.51% in synthetic tests with high noise, and by 48.95%, 26.40%, and 55.84% in pencil-lead break experiments on rock surfaces. • In mining applications, dual sensor arrays jointed method lowers average location error by 54.32% and 14.29% compared to single arrays, demonstrating robustness and practical value. • The approach offers a compelling solution for accurate microseismic monitoring in deep mining, improving risk assessment and stability evaluation.
Abstract
Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joints the P-wave first arrival data. This method adaptively adjusts the preference for “superior” arrays and leverages “inferior” arrays to escape local optima, thereby improving the location accuracy. The effectiveness and stability of this method were validated through synthetic tests, pencil-lead break (PLB) experiments, and mining engineering applications. Specifically, for synthetic tests with 1 µs Gaussian noise and 100 µs large noise in rock samples, the location error of the multi-sensor arrays jointed location method is only 0.30 cm, which improves location accuracy by 97.51% compared to that using a single sensor array. The average location error of PLB events on three surfaces of a rock sample is reduced by 48.95%, 26.40%, and 55.84%, respectively. For mine blast event tests, the average location error of the dual sensor arrays jointed method is 62.74 m, 54.32% and 14.29% lower than that using only sensor arrays 1 and 2, respectively. In summary, the proposed multi-sensor arrays jointed location method demonstrates good noise resistance, stability, and accuracy, providing a compelling new solution for MS location in relevant mining scenarios.
1. Introduction
The depletion of shallow resources has driven mining operations to advance into deeper levels gradually. However, due to factors such as mining methods, geological conditions, and mining technologies, deep mining operations under high-stress environments face increasingly severe challenges, such as underground water inrushes and rockburst.
Microseismic (MS) monitoring has provided crucial insights and breakthroughs in understanding rock mass activity, stress distribution, and underground structures [1]. As the fundamental basis of MS technology, MS source location has been widely implemented in risk assessment and stability evaluation of underground engineering structures, such as deep mines [2], caverns [3, 4], and tunnels [5]. Moreover, highly accurate MS locations can be further employed in velocity structure imaging and source mechanism inversion [6, 7]. In mining engineering, the accuracy of MS location directly influences the planning of mining activity. Therefore, it is essential to develop a robust and highly accurate location method for MS events.
Loading authentic research manuscript (Pages 1–5)...
LIU Ling-hao, SHANG Xue-yi, WANG Yi, LI Xi-bing, FENG Fan (2025). Microseismic source location based on multi-sensor arrays and particle swarm optimization algorithm. Journal of Central South University. https://doi.org/10.1007/s11771-025-6059-3
Research & Educational Purpose Only:The translations, structured abstracts, analytical annotations, and data reports provided by SinoTechIntel are intended exclusively for academic research, internal corporate R&D, and educational benchmarking. They do not constitute formal engineering, chemical safety, legal, or professional advice.
Copyright & Intellectual Property Notice: Original copyright of the underlying source articles and experimental data remains with the respective authors, institutions, and original publishing journals. SinoTechIntel claims intellectual property only over its proprietary translations, analytical syntheses, and AEO structured enhancements in accordance with international fair use and academic citation principles.
Frequently Asked Questions
What is the main contribution of this paper?
The paper proposes a microseismic source location method that combines particle swarm optimization with multi-sensor arrays, using a free weight to jointly process P-wave first arrivals. This adaptive approach improves location accuracy by leveraging superior arrays and using inferior arrays to escape local optima.
How does the proposed method improve location accuracy?
The method improves accuracy by adaptively weighting multiple sensor arrays, which reduces the influence of noise and local optima. In synthetic tests, it achieved a 97.51% improvement over single-array methods, and in field tests, it reduced average location errors by up to 54.32% compared to single arrays.
What experiments were conducted to validate the method?
The method was validated through synthetic tests with Gaussian noise, pencil-lead break (PLB) experiments on rock samples, and mining engineering applications involving blast events. These tests demonstrated its noise resistance, stability, and accuracy.
What are the practical implications of this research?
The proposed method provides a reliable solution for accurate microseismic source location in deep mining environments, which is crucial for risk assessment, stability evaluation, and early warning of rockburst and other hazards.
What is the significance of using multi-sensor arrays?
Multi-sensor arrays provide redundant information that can be jointly processed to reduce location errors. The method adaptively weights arrays based on their quality, allowing superior arrays to dominate while inferior arrays help escape local optima, leading to more robust and accurate locations.
Related Technical Papers & Translations
Direct Repair of the Crystal Structure and Coating Surface of Spent LiFePO4 Materials Enables Superfast Li-Ion Migration
The rapid accumulation of spent LiFePO4 (LFP) cathodes from retired lithium-ion batteries necessitates the development of effective and environmental-friendly recycling strategies. In this context, direct regeneration has emerged as a promising approach for reclaiming LFP cathode materials, offering a streamlined pathway to restore their electrochemical functionality. We report an integrated regeneration protocol that simultaneously repairs the degraded crystal structure and reconstructs the damaged carbon coating in spent LFP. The regenerated cathode material had superfast lithium-ion diffusion kinetics and a stable cathode–electrolyte interface, giving a remarkable rate capability with specific capacities of 122 mAh g−1 at 5C and 106 mAh g−1 at 10C (1C = 170 mA g−1). It also maintained capacities of 110.7 mAh g−1 (5C) and 84.1 mAh g−1 (10C) after 400 cycles. It could be used in harsh environments and could be stably cycled at subzero temperatures (−10 and −20 °C) and in solid-state electrolyte batteries. Life cycle assessment combined with economic evaluation using the EverBatt model reveals that this direct regeneration approach has high economic and environmental benefits.
Oxide Semiconductor for Advanced Memory Architectures: Atomic Layer Deposition, Key Requirement and Challenges
Oxide semiconductors (OSs), introduced by the Hosono group in the early 2000s, have evolved from display backplane materials to promising candidates for advanced memory and logic devices. The exceptionally low leakage current of OSs and compatibility with three-dimensional (3D) architectures have recently sparked renewed interest in their use in semiconductor applications. This review begins by exploring the unique material properties of OSs, which fundamentally originate from their distinct electronic band structure. Subsequently, we focus on atomic layer deposition (ALD), a core technique for growing excellent OS films, covering both basic and advanced processes compatible with 3D scaling. The basic surface reaction mechanisms—adsorption and reaction—and their roles in film growth are introduced. Furthermore, material design strategies, such as cation selection, crystallinity control, anion doping, and heterostructure engineering, are discussed. We also highlight challenges in memory applications, including contact resistance, hydrogen instability, and lack of p-type materials, and discuss the feasibility of ALD-grown OSs as potential solutions. Lastly, we provide an outlook on the role of ALD-grown OSs in memory technologies. This review bridges material fundamentals and device-level requirements, offering a comprehensive perspective on the potential of ALD-driven OSs for next-generation semiconductor memory devices.
Laser powder bed fusion of biodegradable Zn-4Cu alloy: Processing, microstructure and properties
Zn's natural degradability and biocompatibility make it a promising candidate for implants, however, its mechanical properties remain insufficient for bone applications. In this study, the performance of Zn was enhanced by developing Zn-Cu alloys via laser powder bed fusion (LPBF). Optimal LPBF parameters for forming stable tracks were achieved by adjusting laser power and scanning speed. Under optimized conditions of 100 W and 100 mm/s, high-density (99.58%) Zn-Cu alloys with improved hardness (68.2HV) and yield strength (160 MPa) were achieved. These improvements are attributed to solid solution strengthening, segregation strengthening, and grain refinement. The Zn-Cu alloys also demonstrated favorable degradation behavior, with a rate of 0.16 mm/year. This degradation is primarily driven by micro-galvanic corrosion between the CuZn5 phase and Zn matrix, along with refined grains and increased grain boundary density. This work demonstrates a viable strategy for fabricating Zn-based implants with enhanced structural integrity and mechanical performance via LPBF.