通过深度学习在月球地震数据中新发现与温度相关的长周期信号

IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS
Xin Liu, Zhuowei Xiao, Juan Li, Yosio Nakamura
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引用次数: 0

摘要

月球地震数据对于了解月球内部结构和地质历史至关重要。五十年后,阿波罗数据集仍然是唯一可用的数据集,并继续为当前和未来的月球地震数据分析提供重要价值。人工智能在地震学领域的最新进展已经发现了以前无法识别的地震信号。在我们的研究中,我们利用深度学习对月球地震图进行了无监督聚类,从而发现了一种新型的长周期月球地震信号,这种信号在 1969 年到 1976 年间的每个月夜都存在。随后,我们对这一信号的时间、频率、极化和时间分布特征进行了全面分析,以研究其特性、发生和可能的起源。根据该信号在峰值和平值模式下的振幅以及数字转换器的状态,它是有物理原因的,而不是人为的,如电压变化。根据该信号与月球温度的关系以及阿波罗仪器上的文件,我们得出结论,该信号很可能是由循环加热器引起的,但有几个问题尚未解决,可能会对我们的假设提出质疑。在分析月球地震数据,特别是探测月球自由振荡时,排除这个新发现信号的干扰至关重要。我们的研究为发现新型行星地震信号引入了一种新方法,有助于推进我们对阿波罗地震数据的理解。此外,这一信号的发现对未来行星地震仪的设计也有重要意义,可避免遇到类似问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Newly Discovered Temperature-Related Long-Period Signals in Lunar Seismic Data by Deep Learning

Newly Discovered Temperature-Related Long-Period Signals in Lunar Seismic Data by Deep Learning

Lunar seismic data are essential for understanding the Moon's internal structure and geological history. After five decades, the Apollo data set remains the only available one and continues to offer significant value for current and future lunar seismic data analyses. Recent advances in artificial intelligence for seismology have identified seismic signals that were previously unrecognized. In our study, we utilized deep learning for unsupervised clustering of lunar seismograms, leading to the discovery of a new type of long-period lunar seismic signal that existed every lunar night from 1969 to 1976. We then conducted a thorough analysis covering the timing, frequency, polarization, and temporal distribution characteristics of this signal to study its properties, occurrence, and probable origins. This signal has a physical cause instead of artificial, such as voltage changes, according to its amplitudes during peaked and flat modes, as well as the digital converter status. Based on its relation to the lunar temperature and documents on Apollo instruments, we conclude that this signal is likely induced by the cyclic heater, with several unresolved questions that might challenge our hypothesis. Excluding interference from this newly identified signal is crucial when analyzing lunar seismic data, particularly in detecting lunar free oscillations. Our research introduced a new method for discovering new types of planetary seismic signals and helped advance our understanding of Apollo seismic data. Furthermore, the discovery of this signal holds valuable implications for the design of future planetary seismometers to avoid encountering similar issues.

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来源期刊
Earth and Space Science
Earth and Space Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
5.50
自引率
3.20%
发文量
285
审稿时长
19 weeks
期刊介绍: Marking AGU’s second new open access journal in the last 12 months, Earth and Space Science is the only journal that reflects the expansive range of science represented by AGU’s 62,000 members, including all of the Earth, planetary, and space sciences, and related fields in environmental science, geoengineering, space engineering, and biogeochemistry.
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