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We carried out a petrological, mineralogical, and geochemical study of fragmental and regolith breccia clasts separated from two Chang'e‐5 (CE‐5) soil samples, CE5C0000YJYX03501GP and CE5C0400, which provide an opportunity to investigate the compositional change of regolith at the landing site through time. Fragmental breccia CE‐5‐B3 contains a diverse range of basaltic clasts and basaltic mineral fragments, and some rare Mg‐suite‐like minerals. Regolith breccias CE‐5‐B006, CE‐5‐B007, CE‐5‐B010‐08, CE‐5‐B010‐09, CE‐5‐B011‐07, and CE‐5‐B016‐03 contain mare basaltic fragments, mare vitrophyric clasts, rare Mg‐rich fragments possibly derived from the Mg‐suite rocks, and impact‐derived glass spherules. Pb‐isotope data obtained for baddeleyite grains found both inside some of the basaltic clasts identified in breccia fragments and in the breccia matrices yield Pb/Pb dates similar to the 2 Ga crystallization age of the CE‐5 basalt fragments, extracted directly from the soil sample. Seventy‐four Pb isotope analyses of Ca‐phosphate grains also indicate that the majority of these grains have Pb/Pb dates of 2 Ga, suggesting that they originate from the CE‐5 basalts. In addition, a Pb–Pb isochron drawn through analyses of four Ca‐phosphates in breccia CE5‐B006 yielded an intercept corresponding to a date of 3871 ± 46 Ma, which is the best possible estimate of the formation age of these four grains. Electron probe microanalysis shows that the breccias contain components similar to CE‐5 mare basalt fragments extracted directly from the soil sample, implying that the fragmental and regolith breccia fragments are mostly composed of material sourced from the underlying basalts. The general absence of impact melt breccia clasts, along with the general lack of Fe–Ni metal and absence of added meteoritic debris all suggest that the regolith at the CE‐5 landing site is immature and dominated by material mixed together by small local impact cratering events. Trace element analyses show that the glass beads in the regolith breccias have a Th abundance of 4.06–5.28 μg g−1. This is similar to the Th content of the regolith above the Em4 unit at the landing site as measured from orbit, as well as the estimated bulk Th content of CE‐5 basalts, suggesting that Th of the local regolith is predominantly sourced from the underlying mare basalts, without significant Th addition from Th‐rich exotic clasts sourced from evolved lunar lithologies. [ABSTRACT FROM AUTHOR]

The fault diagnosis of rotating machinery is vital in industry but traditionally depends on manual expertise, requiring substantial resources. To improve diagnostic accuracy, enable effective condition monitoring, and minimize the impact of faults on operations, advanced diagnostic techniques are essential. Hence, we propose an advanced fault diagnosis framework that leverages improved particle swarm optimization (IPSO), variational mode decomposition (VMD), and probabilistic neural networks (PNN) to accurately diagnose faults in rotating machinery using gear and rolling bearing vibration signals. Initially, the vibration signals are decomposed into intrinsic mode functions via VMD, enabling the capture of subtle but critical fault features. To address parameter selection challenges in VMD, we employed IPSO to optimize the VMD parameters, ensuring the optimal decomposition effect. Further, we refined the feature set by applying Laplace fraction optimization and feature dimensionality reduction, isolating sensitive features that serve as input to a PNN-based fault classification model. Experimental results demonstrated that this IPSO-VMD-PNN framework achieves high diagnostic accuracy for various fault types, establishing it as an effective tool for fault identification in rotating machinery. [ABSTRACT FROM AUTHOR]

Logs in the petroleum boreholes indirectly records the sedimentary cycles in the deep burial formation. In order to extract and understand the periodicity and cyclicity, it is necessary to process the data by digital signal analysis method. Taking the gamma ray (GR) log as the primary material, an identification approach of Milankovitch cycles in boreholes is proposed in this paper, which is based on the Maximum Entropy Spectral Analysis (MESA). The first stage chooses the appropriate windows for calculating the frequency spectral properties in a short section of the data. In each depth window, the second stage generates the two-dimension frequency spectrum utilizing the MESA. At each depth point, the third stage finds the potential Milankovitch cycles in the one-dimension frequency spectrum, in which the average amplitude spectrum peak would be matched to the ratio of Milankovitch period. According to the frequency and wavelength of the maximum amplitude in Milankovitch cycles, the fourth stage estimates the sedimentation rate controlled by cyclical factor. Finally, the Milankovitch cycles in Lower Member of Miocene Zhujiang Formation in north slope of Baiyun Sag, Pearl River Mouth Basin, are identified and the cyclical sedimentation rate is estimated. The results demonstrate that the proposed method is feasible and effective to identify Milankovitch cycles in boreholes, which may contribute to the other geological researches.