Fault diagnosis of squirrel cage induction generator for wind turbine applications using a hybrid deep neural network and decision tree approach

Phase-to-Phase Fault (PPF) and Phase-to-Ground Fault (PGF) are among common electrical faults in wind turbine generators. Detecting and classifying these faults at early stage are hence vital to improving drivetrain reliability and reduce its maintenance cost. In this paper, a hybrid approach based on the Decision Tree (DT) and Deep Neural Network (DNN) is proposed as a high-performance fault diagnosis method to detect and classify PPF and PGF in the squirrel cage induction generator (SCIG). The DT algorithm is used to detect the faulty conditions in the generator by determining special features in the stator current signals. CNN model will then be used to determine the type of fault by analysing the fault signals. Finally, the accuracy of the proposed fault diagnosis approach is evaluated by simulating a 1.7 MW SCIG wind turbine drivetrain at healthy and faulty conditions

A Projection-Based Support Vector Machine Algorithm for Induction Motors’ Bearing Fault Detection

This paper proposes a binary fault detection algorithm for detecting inner raceway bearing faults in a 4KW induction motor. The algorithm uses Support Vector Machine (SVM) and Projection Recurrent Neural Network (PRNN) techniques and is based on data collected experimentally at different speeds and load conditions. Time and frequency contents of the three-phase stator currents are analysed using Discrete Wavelet Transform (DWT), Power Spectral Density (PSD), and cepstrum analysis. A feature set is obtained using various statistical measures, and feature selection algorithms are used to select the most relevant features. The SVM is then trained using these features, and its optimisation problem is formulated as Constrained Nonlinear Programming (NCP). A PRNN is proposed to solve the NCP and obtain the optimal decision boundary of the SVM. The study demonstrates that the accuracy of the algorithm depends on the type of kernel function and the number of relevant features selected. The results suggest that the proposed algorithm is effective in detecting inner raceway bearing faults in induction motors

Wind Turbine Generator Short Circuit Fault Detection Using a Hybrid Approach of Wavelet Transform and Naïve Bayes Classifier

Wind turbines are subjected to several failure modes during their operation. A wind turbine drivetrain generally consists of rotor, bearings, low and high-speed shafts, gearbox, brakes, and generator. Single phase-to-phase and single phase-to-ground faults are among common electrical failure modes in the generator. In this paper, feature extraction has been performed using the Discrete Wavelet Transform (DWT) to detect the electrical faults in the wind turbine generator. A two-stage prediction process is proposed using Naïve Bayes Classifier (NBC), where the healthy and faulty modes are first determined, followed by classifying the types of electrical faults. Three-phase stator currents are used as fault detection signals. The performance of the proposed algorithm has been evaluated in Simulink for a 1659 kW wind turbine drivetrain

Comparison of the Prevalence of Human Papillomaviruses among Fertile and Infertile Women in Mashhad, Northeast of Iran

Background: Human papillomaviruses (HPVs) are the most common viruses which can be sexually transmitted. They can cause different malignancies in asymptomatic women. The association of HPVs with infertility among men and women is controversial. In the current study, the authors compared the frequency of HPVs in fertile and infertile women in the city of Mashhad. Materials and Methods: In the present case-control study, cervical and vaginal smears were collected from infertile and fertile women. HPVs were detected by polymerase chain reaction. Data was analyzed by SPSS v.20 and P-value <0.05 was considered statistically significant. Results: In the current study, 115 infertile women with the mean age of 30.5±5.6 years and 60 fertile women with the mean age of 32.6±9.3 years were included (p=0.07). Among women who were infertile (cases), 121 (52.6%) of 230 smears were positive, while in control group (who were fertile), 50 (41.7%) of 120 smears were positive (p=0.052). Conclusion: Frequency of HPV in both groups was high, which could be due to lack of routine HPV vaccination. HPV can cause placenta abnormality, our infertile women had multiple abortion history and history of abortion had significant differences among infertile and control group. The frequency of HPV had no significant differences between the infertile and control groups

National, sub-national, and risk-attributed burden of thyroid cancer in Iran from 1990 to 2019

An updated exploration of the burden of thyroid cancer across a country is always required for making correct decisions. The objective of this study is to present the thyroid cancer burden and attributed burden to the high Body Mass Index (BMI) in Iran at national and sub-national levels from 1990 to 2019. The data was obtained from the GBD 2019 study estimates. To explain the pattern of changes in incidence from 1990 to 2019, decomposition analysis was conducted. Besides, the attribution of high BMI in the thyroid cancer DALYs and deaths were obtained. The age-standardized incidence rate of thyroid cancer was 1.57 (95% UI: 1.33–1.86) in 1990 and increased 131% (53–191) until 2019. The age-standardized prevalence rate of thyroid cancer was 30.19 (18.75–34.55) in 2019 which increased 164% (77–246) from 11.44 (9.38–13.85) in 1990. In 2019, the death rate, and Disability-adjusted life years of thyroid cancer was 0.49 (0.36–0.53), and 13.16 (8.93–14.62), respectively. These numbers also increased since 1990. The DALYs and deaths attributable to high BMI was 1.91 (0.95–3.11) and 0.07 (0.04–0.11), respectively. The thyroid cancer burden and high BMI attributed burden has increased from 1990 to 2019 in Iran. This study and similar studies’ results can be used for accurate resource allocation for efficient management and all potential risks’ modification for thyroid cancer with a cost-conscious view

Recognition of Human Chef’s Intentions for Incremental Learning of Cookbook by Robotic Salad Chef

Robotic chefs are a promising technology that can bring sizeable health and economic benefits when deployed ubiquitously. This deployment is hindered by the costly process of programming the robots to cook specific dishes while humans learn from observation or freely available videos. In this paper, we propose an algorithm that incrementally adds recipes to the robot’s cookbook based on the visual observation of a human chef, enabling the easier and cheaper deployment of robotic chefs. A new recipe is added only if the current observation is substantially different than all recipes in the cookbook, which is decided by computing the similarity between the vectorizations of these two. The algorithm correctly recognizes known recipes in 93% of the demonstrations and successfully learned new recipes when shown, using off-the-shelf neural networks for computer vision. We show that videos and demonstrations are viable sources of data for robotic chef programming when extended to massive publicly available data sources like YouTube

Exploration of fin stiffness for asymmetric thrust in a swimming robot

Fish commonly combine pectoral fin motion with tail and body motion to create a swimming gait. The rowing pectoral fin motion is characterized by distinct power and recovery strokes where the soft fin bends or rotates significantly to change the hydrodynamic profile of the appendage between the two strokes. In this work, we take inspiration from fish to create an underwater robot that uses a rowing gait to create net forward thrust. We present a mechanical linkage using two cams on a single drive axis to drive both the yawing and rolling rotations of the fin with a single actuated degree of freedom. We also describe the kinematics and geometric constraints of the linkage and how they relate to properties of the cams. We show that a soft fin can create asymmetric thrust in conjunction with the cam-follower transmission and that a fin can produce large spikes in negative force while still creating net forward work throughout the gait cycle.Research Grant from HFSP Ref No: RGP0010/202

Theoretical Investigation into the Mechanism of 3′-dGMP Oxidation by [Pt^IVCl₄(dach)]

The mechanism for the oxidation of 3′-dGMP by [PtCl₄(dach)] (dach = diaminocyclohexane) in the presence of [PtCl₂(dach)] has been investigated using density functional theory. We find that the initial complexation, i.e., the formation of [PtCl₃(dach)­(3′-dGMP)], is greatly assisted by the reaction of the encounter pair [PtCl₂(dach)···3′-dGMP] with [PtCl₄(dach)], leading to migration of an axial chlorine ligand from platinum­(IV) to platinum­(II). A dinuclear platinum­(II)/platinum­(IV) intermediate could not be found, but the reaction is predicted to pass through a platinum­(III)/platinum­(III) transition structure. A cyclization process, i.e., C8–O bond formation, from [PtCl₃(dach)­(3′-dGMP)] occurs through an intriguing phosphate–water-assisted deprotonation reaction, analogous to the opposite of a proton shuttle mechanism. Followed by this, the guanine moiety is oxidized via dissociation of the Pt^IV–Cl_ax bond, and the cyclic ether product is finally formed after deprotonation. We have provided rationalizations, including molecular orbital explanations, for the key steps in the process. Our results help to explain the effect of [PtCl₄(dach)] on the complexation step and the effect of a strong hydroxide base on the cyclization reaction. The overall reaction cycle is intricate and involves autocatalysis by a platinum­(II) species

The Role of Lipid Profile as an Independent Predictor of Non-alcoholic Steatosis and Steatohepatitis in Morbidly Obese Patients

Background and Aims: Obesity is one of the major health problems worldwide. Morbid obesity (body mass index >40 kg/m2 or over 35 with a comorbidity) is associated, apart from other diseases, with an increased risk of non-alcoholic fatty liver disease (NAFLD). Moreover, dyslipidemia is an important comorbidity that is frequently found in NAFLD patients. The aim of this study was to analyze whether serum lipids in morbidly obese patients are associated with the spectrum of NAFLD. ----- Methods: Total serum cholesterol, LDL cholesterol, HDL cholesterol, non-HDL cholesterol, VLDL, and triglycerides were analyzed in 90 morbidly obese patients. The association of lipid profile parameters with histopathological, elastographic, and sonographic indices of NAFLD, non-alcoholic steatohepatitis (NASH), and liver fibrosis were explored. ----- Results: The mean levels of serum total cholesterol, LDL-C, and non-HDL cholesterol in patients with positive histology for liver steatosis and NASH were significantly higher than those in patients with negative histology. None of the indices showed a strong association with NAFLD, NASH, or liver fibrosis after adjustment for potential confounders. ----- Conclusion: A slight predictive value of lipid profile is not sufficiently enough to use solely as a non-invasive test in predicting NASH or liver fibrosis