Best Time Domain Features for Early Detection of Faults in Rotary Machines Using RAT and ANN

The common mechanical defect of rotating machinery is bearing failure which is considered the most common failure mode in rotating machinery. This kind of failure can lead to large losses as financial during work. Early detection of different faults in rotating machines such as bearing fault, misalignment, and others is considered one of the techniques in which is achieved by further signal processing techniques. Thus, using statistical methods such as reverse arrangement tests (RAT) to obtain the best a feature associated with these different faults is the perfect solution to find the failure which is widespread in the early detection of a fault. This type of feature will be used in Artificial Neural networks (ANN) as input for auto diagnosis. These characteristics are independently associated with different types of fault. Using RAT is considered very important in the process of linking different kinds of failures with the most important features.

Investigation of the operation of a ship’s synchronous generator based on a numerical model

The article presents the results of modeling a ship’s synchronous generator. Based on preliminary design calculations, a geometric model of the generator was built. The static and overclocking processes of the generator are investigated. For static modes, the frequency response of the process is obtained. A numerical model was used to identify a mechanical defect. On the example of a simulated defect of an electrical machine - the eccentricity of the generator rotor, the signature of the defect signal is obtained. The study revealed that the presence of rotor eccentricity leads to the appearance of a harmonic component in the spectrum of the force of large amplitude with a maximum value at a low frequency. Transient analysis was carried out using wavelet transformations. The results of the study of dynamics show how the rotor speed increases. The simulation revealed three frequency regions of the signal under study: the region of the increase in speed, the achievement of the critical speed (between the second and third seconds), and the exit to the steady-state. A diagram of a system for diagnosing defects in an electrical machine using a digital twin - a numerical model is proposed. Generator defects (mechanical and electromechanical) can be identified based on model data. Databases of defect signatures in a static mode and a diagnostic model, which contains algorithms for deciding on the presence of a defect, can serve as the basis of information for an operator to decide.

Vibration Feature Analysis for Gas-Insulated Switchgear Mechanical Fault Detection under Varying Current

As a key component to ensure the safe operation of the power grid, mechanical defect diagnosis technology of gas-insulated switchgear (GIS) during operation is often neglected. At present, GIS mechanical fault detection based on vibration information has not been developed. The main reason is that the excitation current is considerable but uncontrollable in the actual operation of GIS. It is difficult to eliminate the influence of excitation on the vibration amplitude and form an effective vibration feature description technology. Therefore, this paper proposes a unified feature-extraction method for GIS vibration information that reduces the influence of current amplitude for mechanical fault diagnosis. Starting from the GIS mechanical analysis, the periodicity of vibration excitation and the influence of amplitude are discussed. Then, combined with the non-linear characteristics of GIS systems and non-linear vibration theory, the multiplier frequency energy ratio (MFER) is designed to extract vibration-unified features of GIS for diagnosing the mechanical fault under different current levels. The diagnosis results of the experimental data with different feature-extraction methods show the applicability and superiority of the proposed method in the GIS’s mechanical fault-detection field based on vibration information.

THE RESEARCH FOR AN IDENTIFICATION OF CRACK – LIKE CORROSION – MECHANICAL DEFECT BY ACOUSTIC IN-LINE INSPECTION TOOLS

Problem of an identification of cracks in dents or corrosion damage, which is considered as a crack – like corrosion – mechanical defect type, is considered for acoustic in – line inspection tools during an in – line inspection of oil pipelines. For this purpose, a theoretical model has been provided and considered as a vertical notch with a convex base. For modeling an interaction of acoustic waves with the defect model there has been used a corresponded formula of an acoustic equation at a ray – acoustic approximation. Considering used simplifying assumptions there have obtained certain boundary conditions for acoustic equation of the crack – like corrosion mechanical defect. Based on this theoretical model here an experimental research were provided at specially manufactured test specimen which contained vertical notches with base of different curvature. At the specimen there are has been obtained a difference of echo signals amplitude from convex and flat surface based notches. Obtained results showed a sufficient agreement with provided by theoretical modeling and approve an adequacy of the proposed model for a theoretical description of considered interaction shear waves with the defect imitation. According to obtained trend of an echo – signal amplitude variation a method for identification of cracks in dents or corrosion damage during an oil pipeline inspection by inline inspection tools has been provided.

Mechanical defect detection of porcelain column high-voltage disconnector based on operating torque

Currently, there is no effective detection and diagnosis technology for the frequently happened mechanical defects of disconnectors. A porcelain column high-voltage disconnector is taken as the object to study the influence of mechanical defects, including bearing jamming, axle pin jamming, and three-phase position asynchrony on the operating torque through geometric mechanics deduction. An operating torque detection technology is proposed, which could accurately measure the operating torque of the disconnector without destroying its original shafting. Using this technology, the operating torque curves of the disconnector in normal state and typical mechanical defect simulation states are measured and compared. The results indicate that the operating torque changes with the mechanical state of disconnector, and these changes could be quantified through the proposed detection technology. And the types of mechanical defects can be distinguished according to their different effects on the operating torque curve. Based on this, a practical mechanical defects diagnosis method is summarized to provide reference for maintainers to diagnose the mechanical defects of disconnectors.