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Accurately and sensitively detecting and locating the partial discharge (PD) inside transformers is of great significance for ensuring the safe operation of transformers. Due to the obstruction of the ultrasonic signal by the transformer casing and electromagnetic interference in the field, the PD detection accuracy and sensitivity of piezoelectric ultrasonic sensors are limited. This study, based on a real 110-kV transformer, explored the installation method of the fiber-optic Fabry–Perot (F–P) sensor array and the localization method for PD and compared the detection performance of fiber-optic F–P sensors and piezoelectric sensors. In response to optical and acoustic noise present in the field, an adaptive Wiener filter-based noise reduction method was proposed to enhance the accuracy of arrival time extraction. Based on the time-difference-of-arrival (TDOA) principle, a localization equation considering ultrasonic time delay increment was constructed. A PD localization method based on the SOGWO was introduced, and the localization accuracy and its fluctuations were analyzed under conditions considering and not considering the ultrasonic time delay increment. The research results indicate that fiber-optic F–P sensors have higher sensitivity and better resistance to electromagnetic noise and external acoustic noise interference. The solid structure inside the transformer has a significant impact on ultrasonic localization accuracy. Considering the ultrasonic time delay increment can improve localization accuracy, but it may lead to greater fluctuations in the accuracy. The research findings of this article highlight the advantages of fiber-optic F–P sensors in detecting PD in transformers.

Realizing reliable online detection of characteristic gases (H2, C2H4, CO, and CO2) in lithium-ion batteries is crucial to maintain the safe and stable operation of power equipment and new energy storage power plants. In this study, transition metal Ptn(n= 1, 3, and 4) clusters are attached to MoSe2nanosheets for the first time based on density functional theory using the perfect crystalline facet modification method, and the adsorption characteristics and electronic behaviors of H2, C2H4, CO, and CO2are investigated and enhanced. The results show that Ptn(n= 1, 3, and 4) is reliably chemically connected to the substrate without any significant deformation of the geometry. The adsorption properties as well as the band gap, DOS, and LUMO–HOMO are optimized for the modified Gas/Ptn(n= 1, 3, and 4)-MoSe2system. The large electronic states near the Fermi level are further activated by the modification process, and Pt-MoSe2and Pt4-MoSe2can serve as battery state characteristic gas sensors suitably according to the detection needs of specific target gases, whereas Pt3-MoSe2can be used as a good adsorbent for effective and reliable scavenging of battery state characteristic gases and is further applied to energy and power equipment and new energy storage power plants.

Lung adenocarcinoma (LUAD) is a common malignant tumor. Identification of biomarkers and understanding their potential functions will facilitate the treatment and diagnosis in LUAD patients. The yellow module (cor = 0.31, P = 2e-6) was selected as the core module based on weighted gene co-expression network analysis (WGCNA) by integrating RNA-seq data and tumor stage. Two upregulated genes (PLAU and GREM1) in yellow module were identified to be biomarkers. Kaplan–Meier curve analysis displayed that high expression levels of them had a poor overall survival (OS). And, their high expression levels revealed higher tumor stage and relapse possibility in LUAD patients, and could be a prognostic parameter. Both biomarkers showed similar immune cell expression profiles in low- and high-expression groups. Strongly positive correlation between both biomarkers and biomarkers of tumor-infiltrating lymphocytes were also clarified in TCGA-LUAD cohort. Importantly, single gene GSEA showed that transcriptional mis-regulation in cancer and microRNAs in cancer were enriched in LUAD patients. Therefore, a miRNA-mRNA-transcription factors (TFs) co-expression regulatory networks was constructed for each biomarker, various miRNAs and TFs were related to PLAU and GREM1. Among which, 6 downstream TFs were overlapped genes for both biomarkers. Notably, 2 of these TFs (FOXF1 and TFAP2A) exhibited significantly abnormal expression levels. Among which, FOXF1 was downregulated and TFAP2A was upregulated in TCGA-LUAD cohort. Both TFs showed a significantly positive correlation with the expression level of PLAU. In conclusion, we identified 2 biomarkers related to immune response and achieved a good accuracy in predicting OS in patients with LUAD.