Abstract Recently, prognostic and health management (PHM) has become a prominent field in modern industry. The rotate vector (RV) reducer is one of the widely used mechanical components industrial systems, specifically robots. RV known for its unique characteristics small size, efficient speed transmission, high torsion. prone to several kinds faults, due continuous operation an robot. To keep smooth steady, timely PHM essential. Previously, fault was diagnosed via various techniques, such...

A robot is essential in many industrial and manufacturing facilities due to its efficiency, accuracy, durability. However, continuous use of the robotic system can result various component failures. The servo motor one critical components, bearing vulnerable parts, hence failure analysis required. Some previous prognostics health management (PHM) methods are very limited considering realistic operating conditions robots based on speeds, loading conditions, motions, because they consider...

ABSTRACT The robotic reducer is prone to failure because of its unique characteristics. Data from vibration and acoustic emission sensors have been used for the prognostics reducer. However, various issues are associated with such traditional techniques. Hence, our research group proposes a novel approach utilize embedded setup electrical current detect mechanical fault in actual industrial robot. Previously, comprehensive feature engineering was proposed classify handcraft-based extraction...

With increasing customer demand, industry 4.0 gained a lot of interest, which is based on smart factories. In factories, robotic components are vulnerable to failure due various industrial operations such as assembly, manufacturing, and product handling. Timely fault detection diagnosis (FDD) important keep the operation smooth. Previously, only unloaded-based FDD algorithms were considered for system. environment, robot working under conditions speeds, loads, motions. Hence, reduce domain...

Recently, the advanced driver assistance system (ADAS) of autonomous vehicles (AVs) has offered substantial benefits to drivers. Improvement passenger safety is one key factors for evolving AVs. An automated provided by ADAS in a salient feature modern vehicles. With an increasing number electronic control units and combination multiple sensors, there are now sufficient computing aptitudes car support deployment. composed various sensors: radio detection ranging (RADAR), cameras, ultrasonic...

Due to their excellent strength-to-weight ratio, composite laminates are gradually being substituted for traditional metallic materials in a variety of industries. However, due orthotropic nature, prone several different types damage, with delamination the most prevalent and serious. Therefore, deep learning-based methods that use sensor data conduct autonomous health monitoring have drawn much interest structural (SHM). direct application these models is restricted by lack training data,...

Due to their precision, compact size, and high torque transfer, Rotate vector (RV) reducers are becoming more popular in industrial robots. However, repetitive operations varying speed conditions mean that these components prone mechanical failure. Therefore, it is important develop effective health monitoring (HM) strategies. Traditional approaches for HM, including those using vibration acoustic emission sensors, encounter such challenges as noise interference, data inconsistency,...

In prognostics and health management (PHM), the majority of fault detection diagnosis is performed by adopting segregated methodology, where electrical faults are detected using motor current signature analysis (MCSA), while mechanical vibration, acoustic emission, or ferrography analysis. This leads to more complicated methods for overall diagnosis. Additionally, involvement several types data makes system difficult, thus increasing computational cost in real-time. Aiming resolve that, this...

Deep learning has helped achieve breakthroughs in a variety of applications; however, the lack data from faulty states hinders development effective and robust diagnostic strategies using deep models. This work introduces transfer framework for autonomous detection, isolation, quantification delamination laminated composites based on scarce low-frequency structural vibration data. Limited response an electromechanically coupled simulation model experimental testing composite coupons were...

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Abstract The aim of this paper is to numerically analyze the hydrothermal behavior different cross-sectional geometries microchannel heat sinks (MCHSs) and conduct a comparative analysis traditional non-traditional designs using ANSYS Fluent. It expected that proposed design discussed in will improve performance MCHSs by maximizing cooling capability minimizing thermal resistance entropy generation rate, thus leading better energy efficiency. channel include rectangular (RMC), circular...