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Abstract Backgrounds This investigation seeks to explore the correlation between nonalcoholic fatty liver disease (NAFLD) and cardiovascular diseases (CVDs), and to to provide evidence for the prevention and treatment of CVDs. Methods This study utilized data from the Jinchang cohort platform, including 19,399 participants without pre-existing major CVDs. Based on the general population and gender stratification, Cox models were used to analyze the risk of NAFLD for CVDs. The combined effect of NAFLD and different obesity indicators on CVDs was analyzed by additive and multiplicative interaction models and subgroups. Results There were 3129 NAFLD patients out of 19399 subjects, and 723 (23.11%) of them had the CVD. After adjusting for multiple confounding factors, the Cox model revealed a 1.17-fold increase in the risk of CVDs among patients with NAFLD compared to those without NAFLD. Moreover, there was no notable disparity in CVDs risk among most NAFLD patients at the same level of obesity. The results indicated no additive interaction between NAFLD and obesity concerning CVDs risk, but rather a positive multiplicative interaction. Using the normal population as a reference, it was found that people with both obesity and NAFLD significantly increased the risk of developing CVDs, with HRs and 95% CIs of 1.790 (1.508, 2.126), 1.356 (1.213, 1.517), and 1.807 (1.503, 2.174), respectively, for BMI, WC, and the combination of BMI and WC. Conclusions NAFLD and obesity are independent risk factors for CVDs. The synergy of obesity and NAFLD implies that NAFLD patients should control weight gain. Larger BMI and WC values may increase the CVDs risk for NAFLD patients, especially women.

Abstract Background Thyroid eye disease (TED) is a vision-threatening autoimmune disorder. Orbital tissue fibrosis leading to intractable complications remains a troublesome issue in TED management. Exploration of novel therapeutic targets and agents to ameliorate tissue fibrosis is crucial for TED. Recent work suggests that Ca2+ signaling participates in tissue fibrosis. However, whether an alteration of Ca2+ signaling has a role in fibrogenesis during TED remains unclear. In this study, we aimed to investigate the role of Ca2+ signaling in the fibrogenesis process during TED and the potential therapeutic effects of a highly selective inhibitor of the L-type calcium channel (LTCC), nimodipine, through a TGF-β1 induced in vitro TED model. Methods Primary culture of orbital fibroblasts (OFs) were established from orbital adipose connective tissues of patients with TED and healthy control donors. Real-time quantitative polymerase chain reaction (RT-qPCR) and RNA sequencing were used to assess the genes expression associated with LTCC in OFs. Flow cytometry, RT-qPCR, 5-ethynyl-2′-deoxyuridine (EdU) proliferation assay, wound healing assay and Western blot (WB) were used to assess the intracellular Ca2+ response on TGF-β1 stimulation, and to evaluate the potential therapeutic effects of nimodipine in the TGF-β1 induced in vitro TED model. The roles of Ca2+/calmodulin-dependent protein kinase II (CaMKII) and signal transducer and activator of transcription 1 (STAT1) in fibrogenesis during TED were determined by immunohistochemistry, WB, flow cytometry and co-immunoprecipitation assay. Selective inhibitors were used to explore the downstream signaling pathways. Results LTCC inhibitor nimodipine blocked the TGF-β1 induced intracellular Ca2+ response and further reduced the expression of alpha-smooth muscle actin (α-SMA), collagen type I alpha 1 (Col1A1) and collagen type I alpha 2 (Col1A2) in OFs. Besides, nimodipine inhibited cell proliferation and migration of OFs. Moreover, our results provided evidence that activation of the CaMKII/STAT1 signaling pathway was involved in fibrogenesis during TED, and nimodipine inhibited the pro-fibrotic functions of OFs by down-regulating the CaMKII/STAT1 signaling pathway. Conclusions TGF-β1 induces an LTCC-mediated Ca2+ response, followed by activation of CaMKII/STAT1 signaling pathway, which promotes the pro-fibrotic functions of OFs and participates in fibrogenesis during TED. Nimodipine exerts potent anti-fibrotic benefits in vitro by suppressing the CaMKII/STAT1 signaling pathway. Our work deepens our understanding of the fibrogenesis process during TED and provides potential therapeutic targets and alternative candidate for TED.

Abstract Background Studies have found that the ratio of total cholesterol to high‐density lipoprotein cholesterol (TC/HDL‐C) was associated with the development of chronic kidney disease (CKD). However, the relationship in different genders was rarely discussed. The aim of this study was to explore this relationship and assess its predictive power for both males and females. Methods Based on a prospective cohort platform in northwest China, 32,351 participants without CKD were collected in the baseline and followed up for approximately 5 years. Cox proportional hazard model and restricted cubic spline regression analysis were performed to investigate the association between TC, HDL‐C, TC/HDL‐C and CKD in adult female and male. The clinical application value of the indicators in predicting CKD was evaluated by the receiver operator characteristic curve. Results During a mean follow‐up of 2.2 years, 484 males and 164 females developed CKD. After adjusted for relevant confounders, for every one standard deviation increase in TC, HDL‐C and TC/HDL‐C, the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for CKD were 1.17 (1.05–1.31), 0.84 (0.71–0.99), and 1.15 (1.06–1.25) for males, 0.94 (0.78–1.13), 0.58 (0.35–0.95), and 1.19 (1.01–1.40) for females, respectively. The results also showed that TC, HDL‐C, and TC/HDL‐C were associated with CKD in a linear dose–response relationship. The TC/HDL‐C had the largest area under the curve (AUC) compared to TC and HDL‐C, and the AUC among the females was larger than that among males. Conclusions The TC/HDL‐C was significantly associated with CKD in adult males and females and has better clinical value in predicting CKD than TC and HDL‐C, especially in females.

ObjectiveTo understand the incidence of carotid atherosclerosis (CAS) and the association of CAS with stroke incidence in an occupational population of the Jinchang Cohort, and to provide an evidence for the prevention and treatment of CAS and stroke. MethodsThe analysis included 6 262 employees of a nonferrous metal company who participated in the Jinchang Cohort Study and had complete information from the baseline examination, including carotid color Doppler ultrasound, from June 2011 to December 2013 and two rounds of follow-up in 2015 and 2017. The cumulative incidence rates of CAS, carotid intima-media thickening, carotid atherosclerotic plaque, and stroke were calculated among the employees during the follow-up period. A multivariate unconditional logistic regression model was used to analyze the factors associated with CAS, carotid intima-media thickening, and carotid atherosclerotic plaque. A multivariate Cox proportional hazards regression model was used to analyze the risk of stroke incidence and its influencing factors in individuals with CAS, carotid intima-media thickening, and carotid atherosclerotic plaque. ResultsDuring the initial follow-up of a mean of 1.71 ± 0.55 years (ranging from 0.08 to 3.75 years), a total of 1 147 cases of CAS, 287 cases of carotid intima-media thickening, and 860 cases of carotid atherosclerotic plaque were observed, with cumulative incidence rates of 18.32%, 4.58%, and 13.73%, respectively. The results of multivariate unconditional logistic regression analysis showed that age ≥ 45 years, smoking, hypertension, diabetes, abnormal total cholesterol (TC), working as a cadre or technical personnel, and internal staff were risk factors for CAS in the occupational population; whereas education level of college or above was a protective factor; age ≥ 45 years, working as a cadre or technical personnel, smoking, having high-sugar diet, and hypertension were risk factors for carotid intima-media thickening, whereas female gender was a protective factor; females, age ≥ 45 years, working as internal staff, hypertension, diabetes, and abnormal TC were risk factors for carotid atherosclerotic plaque, whereas college education or higher was a protective factor. At the second follow-up of a mean of 2.67 ± 0.55 years (ranging from 0.06 to 4.37 years), a total of 240 stroke cases were identified, with a cumulative incidence of 3.83%. The numbers of stroke cases in subjects with CAS, carotid intima-media thickening, and carotid atherosclerotic plaque were 104, 19, and 85, with cumulative stroke incidences of 9.07%, 6.62%, and 9.88%, respectively. The results of the multivariate Cox proportional hazards regression model analysis showed that after adjusting for gender, age, education level, occupation, smoking, alcohol consumption, physical activity, high-salt diet, high-fat diet, high-sugar diet, hypertension, diabetes, hyperuricemia, body mass index (BMI), abnormal TC, abnormal triglycerides (TG), abnormal high-density lipoprotein cholesterol (HDL-C), abnormal low-density lipoprotein cholesterol (LDL-C), and reduced glomerular filtration rate, the risk of stroke was significantly increased in the individuals with CAS (hazard ratio [HR] = 1.421, 95% confidence interval [95%CI]: 1.030 – 1.961) compared with those without CAS. The results also showed that, age ≥ 45 years, high-salt diet, and overweight were risk factors for stroke incidence in the individuals with CAS; females and hyperuricemia were risk factors for stroke incidence in individuals with carotid intima-media thickening; and high school or technical secondary school education, high-salt diet, and overweight were risk factors for stroke incidence in individuals with carotid atherosclerotic plaque. ConclusionThe cumulative incidence of both CAS and stroke was high during follow-up in the occupational population of the Jinchang Cohort Study and in the occupational population, the individuals with CAS had a higher risk of stroke, and older age, high-salt diet, and overweight were the main risk factors for stroke in the individuals with CAS.

Extensive research has established the link between PM2.5 exposure and blood pressure (BP) levels among normal individuals. However, the association between PM2.5 components and BP levels in hypertensive patients has not been fully explored. In this study, 12 971 hypertensive cases from Jinchang cohort (in Jinchang City, China) with nearly 9 years of follow-up were enrolled. Based on the linear mixed-effect model, the effects of fine particulate matter (PM2.5) and five major components [sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), black carbon (BC) and organic matter (OM)]on BP [systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP)]were evaluated by single-component model, component-joint model and component-residual model, respectively. A positive correlation was found between PM2.5 as well as its components (SO42-, NO3-, NH4+, BC and OM) exposure and BP levels. The effects of SO42-, BC and OM on BP were observed to be the most robust among the three models. Based on the results of interaction effects and stratified analysis, the effect of BC exposure on SBP, and the effect of PM2.5 and its five components on PP were greater in female than in males. Compared with elderly hypertensive patients, OM had more significant effects on SBP, DBP and MAP in young and (or) middle-aged hypertensive patients. During the heating season, the effect of PM2.5 and its components on BP was grater compared to the non-heating season. Meanwhile, PM2.5 and its components have a greater influence on BP in patients with hypertension combined with diabetes. Therefore, the findings suggested that both PM2.5 exposure and its components had a significant effect on BP in patients with hypertension. Women and young and middle-aged hypertensive patient were the sensitive population. The implementation of source control and reduction of PM2.5 emission (mainly for SO42-, BC and OM) may be of great significance to control BP level and could reduce the risk of cardiovascular disease in patients with hypertension.

Ensuring the safety of transmission line towers is vital for human safety, power supply, economic development, and environmental protection. This study specifically examines how temperature affects tower inclination. Multifractal detrended cross-correlation analysis (MF-DCCA) is a combination of multifractal detrended fluctuation analysis (MF-DFA) and DCCA that reveals the multifractal features of two cross-correlated non-stationary signals. This paper adopts the MF-DCCA tool to investigate the cross-correlations between the internal temperature of an inclination sensor device and the posture of a transmission line tower. The tilt angle data in the x- and y-axes are used to measure the posture of the transmission line tower. We start by using Pearson correlation to assess the relationship between temperature and two inclination angles, followed by verifying their correlation with a p-value below 0.05 using first-order linear fitting. We initially assess the multifractal features of three time series using MF-DFA before MF-DCCA analysis. All exhibit multifractal traits with H(2)<0.5, indicating negative persistence, especially notable in the temperature series. Finally, we adopt the MF-DCCA approach to examine the multifractal cross-correlation between tilt-angle time series and temperature time series, and the results indicate the negative persistence of the cross-correlation between the time series. Furthermore, the multifractal cross-correlation of temperature and inclination data on the y-axis was also found to be stronger than on the x-axis based on features of the scaling exponent and symmetry exponent.

Microbial degradation of petroleum hydrocarbons plays a vital role in mitigating petroleum contamination and heavy oil extraction. In this study, a Saccharomyces cerevisiae capable of degrading hexadecane has been successfully engineered, achieving a maximum degradation rate of up to 20.42%. However, the degradation ability of this strain decreased under various pressure conditions such as high temperature, high osmotic pressure, and acidity conditions. Therefore, a S. cerevisiae with high tolerance to these conditions has been constructed. And then, we constructed an “anti-stress hydrocarbon-degrading” consortium comprising engineered yeast strain SAH03, which degrades hexadecane, and glutathione synthetic yeast YGSH10, which provides stress resistance. This consortium was able to restore the degradation ability of SAH03 under various pressure conditions, particularly exhibiting a significant increase in degradation rate from 5.04% to 17.04% under high osmotic pressure. This study offers a novel approach for improving microbial degradation of petroleum hydrocarbons.

Abstract Objective To explore the effect of temperature variability (TV) on admissions and deaths for cardiovascular diseases (CVDs). Method The admissions data of CVDs were collected in 4 general hospitals in Jinchang City, Gansu Province from 2013 to 2016. The monitoring data of death for CVDs from 2013 to 2017 were collected through the Jinchang City Center for Disease Control and Prevention. Distributed lag nonlinear model (DLNM) was combined to analyze the effects of TV (daily temperature variability (DTV) and hourly temperature variability (HTV)) on the admissions and deaths for CVDs after adjusting confounding effects. Stratified analysis was conducted by age and gender. Then the attribution risk of TV was evaluated. Results There was a broadly linear correlation between TV and the admissions and deaths for CVDs, but only the association between TV and outpatient and emergency room (O&ER) visits for CVDs have statistically significant. DTV and HTV have similar lag effect. Every 1 ℃ increase in DTV and HTV was associated with a 3.61% (95% CI: 1.19% ~ 6.08%), 3.03% (95% CI: 0.27% ~ 5.86%) increase in O&ER visits for CVDs, respectively. There were 22.75% and 14.15% O&ER visits for CVDs can attribute to DTV and HTV exposure during 2013–2016. Males and the elderly may be more sensitive to the changes of TV. Greater effect of TV was observed in non-heating season than in heating season. Conclusion TV was an independent risk factor for the increase of O&ER visits for CVDs, suggesting effective guidance such as strengthening the timely prevention for vulnerable groups before or after exposure, which has important implications for risk management of CVDs.

BackgroundPerfluorinated alkyl substances (PFAS) are a class of synthetic organic fluorides, which have adverse health effects on brain function, and limited research has been conducted on their effects on depression. ObjectiveTo assess potential correlation between serum PFAS and depression. MethodsUsing the 2015—2016 and 2017—2018 National Health and Nutrition Examination Survey (NHANES) datasets, 2626 subjects with complete relevant information in people ≥20 years old were selected. Logistic regression and restricted cubic splines were used to analyze the association and dose-response relationship between serum PFAS concentration and depression. Subgroup analysis was performed on sex, age, race, education level, marital status, family income to poverty ratio, moderate exercise, body mass index, and drinking status. ResultsAmong the 2626 subjects, there were 666 patients (25.4%) with mild or above depression. After adjusting for race, education level, marital status, body mass index, moderate exercise, drinking history, cotinine, and other types of PFAS, serum perfluorooctane sulfonate (PFOS) was positively associated with the risk of depression (OR=1.85, 95%CI: 1.14, 3.02), and showed a nonlinear dose-response relationship (χ2=6.37, Pnonlinear=0.012). Perfluorononanoic acid (PFNA) was inversely associated with the risk of depression (OR=0.23, 95%CI: 0.14, 0.39), and showed a linear dose-response relationship (Ptrend

This paper proposes a multifractal least squares support vector machine detrended fluctuation analysis (MF-LSSVM-DFA) model. The system is an extension of the traditional MF-DFA model. To address potential overfitting or underfitting caused by the fixed-order polynomial fitting in MF-DFA, LSSVM is employed as a superior alternative for fitting. This approach enhances model accuracy and adaptability, ensuring more reliable analysis results. We utilize the p model to construct a multiplicative cascade time series to evaluate the performance of MF-LSSVM-DFA, MF-DFA, and two other models that improve upon MF-DFA from recent studies. The results demonstrate that our proposed modified model yields generalized Hurst exponents h(q) and scaling exponents τ(q) that align more closely with the analytical solutions, indicating superior correction effectiveness. In addition, we explore the sensitivity of MF-LSSVM-DFA to the overlapping window size s. We find that the sensitivity of our proposed model is less than that of MF-DFA. We find that when s exceeds the limited range of the traditional MF-DFA, h(q) and τ(q) are closer than those obtained in MF-DFA when s is in a limited range. Meanwhile, we analyze the performances of the fitting of the two models and the results imply that MF-LSSVM-DFA achieves a better outstanding performance. In addition, we put the proposed MF-LSSVM-DFA into practice for applications in the medical field, and we found that MF-LSSVM-DFA improves the accuracy of ECG signal classification and the stability and robustness of the algorithm compared with MF-DFA. Finally, numerous image segmentation experiments are adopted to verify the effectiveness and robustness of our proposed method.

The transmission line is an important channel for the electric energy transmission in the power system. Whether the stable transmission of electric energy is related to key issues such as people’s livelihood and industry, so it is of great significance to evaluate the operation status of the transmission line. Aiming at the shortcomings of the current evaluation methods for the operation status of transmission lines, this paper proposes a comprehensive evaluation method for the operation status of transmission lines based on the improved combination weighting evaluation model. By constructing a transmission line status indication system based on transmission line standards and specifications, comprehensively considering subjective weights and objective weights, the operational health status of the 6 transmission lines in actual operation is calculated, and the calculation results are compared with the evaluation results of the national grid industry standards. In contrast, this method fully combines the advantages of the improved AHP method and the CRITIC method. While retaining the subjective opinions of experts, it can well avoid the phenomenon of unbalanced weights. Compared with the traditional standard evaluation method, it is more in line with objective reality. The evaluation and early warning of the operation status of transmission lines are of great guiding significance.

Currently few studies have explored the relationship between exposure to gaseous pollutants and metabolic health indicators in patients, especially in patients with metabolic syndrome (Mets). This study collected 15,520 patients with Mets in a prospective cohort of nearly 50,000 people with 7 years of follow-up from 2011 to 2017, and matched air pollutants and meteorological data during the same period. The mixed effects model was used to analyze the relationship between different short exposure windows (1-week, 1-month, 2-month, and 3-month) of gaseous pollutants (SO2, NO2, and O3) and the metabolic health indicators of patients after controlled the confounding factors. Stratified analysis was performed by demographic characteristics and behavioral factors. The effects of gaseous pollutants on patients with different Met components were also analyzed. The results showed that the short-term exposure to SO2, NO2, and O3 had a certain effect on the metabolic health indicators of patients with Mets in different exposure windows, and with the extension of the exposure window period, the effects increased. The stratified analysis showed that gender, age, and life behaviors might modify these detrimental effects. In addition, the effects of gaseous pollutants on metabolic health indicators in G4 and G7 were more obvious than other Met components, and the effects of gaseous pollutants on the level of LDL-C were found to be statistically significant in most components. Therefore, patients with Mets should pay more attention to the influence of gaseous pollutants to take appropriate protection to reduce potential health risk.

In a national power grid system, it is necessary to keep transmission lines secure. Detection and identification must be regularly performed for transmission tower components. In this paper, we propose a defect recognition method for key components of transmission lines based on deep learning. First, based on the characteristics of the transmission line image, the defect images are preprocessed, and the defect dataset is created. Then, based on the TensorFlow platform and the traditional Faster R-CNN based on the R-CNN model, the concept-ResNet-v2 network is used as the basic feature extraction network to improve the network structure adjustment and parameter optimization. Through feature extraction, target location, and target classification of aerial transmission line defect images, a target detection model is obtained. The model improves the feature extraction on transmission line targets and small target component defects. The experimental results show that the proposed method can effectively identify the defects of key components of the transmission lines with a high accuracy of 98.65%.

Petroleum hydrocarbons are relatively recalcitrant compounds, and as contaminants, they are one of the most serious environmental problems. n-Alkanes are important constituents of petroleum hydrocarbons. Advances in synthetic biology and metabolic engineering strategies have made n-alkane biodegradation more designable and maneuverable for solving environmental pollution problems. In the microbial degradation of n-alkanes, more and more degradation pathways, related genes, microbes, and alkane hydroxylases have been discovered, which provide a theoretical basis for the further construction of degrading strains and microbial communities. In this review, the current advances in the microbial degradation of n-alkanes under aerobic condition are summarized in four aspects, including the biodegradation pathways and related genes, alkane hydroxylases, engineered microbial chassis, and microbial community. Especially, the microbial communities of “Alkane-degrader and Alkane-degrader” and “Alkane-degrader and Helper” provide new ideas for the degradation of petroleum hydrocarbons. Surfactant producers and nitrogen providers as a “Helper” are discussed in depth. This review will be helpful to further achieve bioremediation of oil-polluted environments rapidly.

PurposeInflammation triggers the activation of CD4+T cells and the breakdown of blood–retinal barrier, thus contributing to the pathology of experimental autoimmune uveitis (EAU). We explored the anti-inflammatory effect of hydroxychloroquine (HCQ) on EAU and the potential mechanisms active in T cells and retinal vascular endothelial cells (RVECs).MethodsC57BL/6J mice were immunized with interphotoreceptor retinoid binding protein 1-20 (IRBP1–20) to induce EAU and then treated with the vehicle or HCQ (100 mg/kg/day). On day 7, 14, 21, 30 and 60 after immunization, clinical scores were evaluated. On day 14, histopathological scores were assessed, and retinas, spleens, and lymph nodes were collected for quantitative polymerase chain reaction or flow cytometry analysis. RVEC dysfunction was induced by tumor necrosis factor α (TNF-α) stimulation. The expression of cytokines, chemokines, adhesion molecules, and lectin-like oxidized LDL receptor-1 (LOX-1)/nuclear factor κB (NF-κB) was measured in RVECs with or without HCQ.ResultsHCQ treatment protected mice from uveitis, evidenced by reduced expression of inflammatory factors, chemokines, and adhesion molecules in the retina. In systemic immune response, HCQ inhibited the activation of naïve CD4+T cells and frequencies of T effector cells, and promoted T regulatory cells. HCQ decreased IRBP1-20–specific T cell responses and proliferation of CD4+T cells in vitro. Further studies established that TNF-α induced RVECs to express inflammatory cytokines, chemokines, and adhesion molecules, whereas HCQ alleviated the alterations via the LOX-1/NF-κB pathways.ConclusionsHCQ alleviates EAU by regulating the Teff/Treg balance and ameliorating RVECs dysfunction via the LOX-1/NF-κB axis. HCQ may be a promising therapeutic candidate for uveitis.

The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors that influence dynamic key evaluation indices such as grounding resistance, sag, and wire corrosion, establishes the evaluation criteria of the ETL operation state, and proposes five ETL status levels and seven principles for selecting evaluation indices. Nine grade I evaluation indices and twenty-nine grade II evaluation indices, including passageway and meteorological environments, are determined. The cloud model theory is embedded and used to propose a warning technology for the operation state of ETLs based on inspection defect parameters and the cloud model. Combined with the inspection defect parameters of a line in the Baicheng district of Jilin Province and the critical evaluation index data such as grounding resistance, sag, and wire corrosion, which are used to calculate the timeliness of the data, the solid line is evaluated. The research shows that the dynamic evaluation model is correct and that the ETL status evaluation and early warning method have reasonable practicability.

Aiming at the difficulty of fault location of multi-source transmission lines, this paper proposes a fault location method for multi-terminal transmission lines based on a fault branch judgment matrix. The fault traveling wave signal is decomposed by Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the IMFs sensitive components that can characterize the fault characteristics of the target signals are selected by constructing a correlation-rearrangement entropy function. The arrival time of fault signals at the endpoint has been accurately calibrated by combining them with the Teager Energy Operator (TEO). To eliminate the influence of wave velocity and fault time on the location results, this paper proposes a two-terminal location method based on the line mode component to improve the location accuracy. On this basis, combined with the fault branch judgment matrix, the accurate location of multi-terminal transmission line faults is realized. This method has been shown to have high accuracy in detecting traveling wave heads, accurately judging fault branches, and producing a small error in fault location results. Compared with the existing multi-terminal transmission line fault location algorithm, it has obvious advantages and meets the needs of actual working conditions.

Due to the barely resonant earthed system used in the transmission line, it is more challenging to identify faults at a 66 kV voltage level because of insufficient fault identification techniques. In this paper, a 66 kV transmission line fault identification method based on a fault characteristic matrix and an improved particle swarm optimization (IPSO)-wavelet neural network (WNN) is proposed to address the difficulties in extracting and detecting characteristic parameters. The maximum matrix of the dbN wavelet was used to determine its decomposition scale and construct the fault characteristic matrix based on the energy values of frequency bands. The decomposition scale of the dbN wavelet was determined by the modulus maximum matrix to ensure the integrity of fault information. The fault feature matrix was then constructed based on the energy values of frequency bands and the fault feature was accurately extracted. In this research, aiming at the problems such as slow convergence speed and a tendency to fall into local minima, the WNN algorithm is enhanced with the IPSO algorithm. This significantly increased the convergence speed of the identification model and its ability to discover the global optimal solution. The simulation results demonstrate that this method can effectively and accurately identify the fault type with high identification accuracy, quick identification, and robust adaptability. Under challenging working conditions, it is capable of accurately identifying the fault type of 66 kV transmission lines.

Transmission lines are primarily deployed overhead, and the transmission tower, acting as the fulcrum, can be affected by the unbalanced force of the wire and extreme weather, resulting in the transmission tower tilt, deformation, or collapse. This can jeopardize the safe operation of the power grid and even cause widespread failures, resulting in significant economic losses. Given the limitations of current tower tilt detection methods, this paper proposes a tower tilt detection and analysis method based on monocular vision images. The monocular camera collects the profile and contour features of the tower, and the tower tilt model is combined to realize the calculation and analysis of the tower tilt. Through this improved monocular visual monitoring method, the perception accuracy of the tower tilt is improved by 7.5%, and the axial eccentricity is accurate to ±2 mm. The method provides real-time reliability and simple operation for detecting tower inclination, significantly reducing staff inspection intensity and ensuring the power system operates safely and efficiently.

In order to safely operate the electric transmission lines, to monitoring the crossed span distance of the overhead lines is one of the key measures. Since the current measurement methods of crossed span distance of overhead line has high cost, low accuracy, and traditional measurement methods has low efficiency, the monitoring model of overhead line in three-dimensional space is constructed, and based on oblique parabola equation. The algorithm for detecting the crossed span distance based on three-dimensional inclination under the windless and windy conditions is studied, which are applied to the on-line monitoring system. Through actual measurement, the accuracy and practicability of the three-dimensional model and algorithm are verified which provides reliable algorithm support for traverse crossing distance measurement and on-line monitoring system, and improves work efficiency.

The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission. The tower's tilt and severe deformation will cause the building to collapse. Many small changes caused the tower's collapse, but the early staff often could not intuitively notice the changes in the tower's state. In the current tower online monitoring system, terminal equipment often needs to replace batteries frequently due to premature exhaustion of power. According to the need for real-time measurement of power line tower, this research designed a real-time monitoring device monitoring the transmission tower attitude tilting and foundation state based on the inertial sensor, the acceleration of 3 axis inertial sensor and angular velocity raw data to pole average filtering pre-processing, and then through the complementary filtering algorithm for comprehensive calculation of tilt angle, the system meets the demand for inclined online monitoring of power line poles and towers regarding measurement accuracy, with low cost and power consumption. The optimization multi-sensor cooperative detection and correction measured tilt angle result relative accuracy can reach 1.03%, which has specific promotion and application value since the system has the advantages of unattended and efficient calculation. [ABSTRACT FROM AUTHOR]