Industry 4.0 Applications in Wet Wipes Machines (2025)

Review of Traction System, Energy Efficiency and Electrical Design of Automated Guided Vehicles in Automotive Industry

European journal of technique, 2022

2. CONCEPTUAL DEVELOPMENT STEPS OF AN AGV PROJECT 2.1. Specifications and system configuration The list given below refers to an AGV applied in automotive production and can be expanded into other AGV applications as well: Step-1: Specifications and tasks related to the AGV operation environment  Type of AGV  Central or decentral control  Localization and mapping method ARTICLE INFO ABSTRACT

Investigation of Static and Dynamic Analysis of Asynchronous Motors in the Cement Industry

European journal of technique, 2023

condition monitoring and analysis methods [7]. With electrical condition monitoring and analysis methods, unbalanced phase losses, overload, short circuits between phases, short circuit and open windings, tilted rotor faults, broken rotor bars, and insulation faults can be detected [8]. Mechanical condition monitoring and analysis methods can detect faults such as unbalance, bearing failure, mechanical looseness, gear failure, coupling misalignment, and axis disturbance [9].

Evaluation of Vibration Monitoring of HFO Purifiers in the Klaveness Fleet

2019

Electric Motor by using Machine Learning

International Journal of Advanced Research in Science, Communication and Technology, 2024

This research paper addresses the crucial issue of early bearing failure within electric motors, a common problem impacting industrial operations. It begins with a thorough problem identification and historical study of asset failures to pinpoint strategic sensor placement on the motor casing, specifically targeting the bearing area. Time series data acquisition captures the dynamic motor behavior, with LabVIEW software facilitating visualization through frequency plots and spectral graphs. Subsequent preprocessing involves modifying data structure and computing vibration metrics like RRMS and IRRMS to quantify vibration levels. The processing stage consists of condition monitoring using structured supervised datasets transformed into the frequency domain in MATLAB. Interpretation of results enables bearing health assessment and identification of dominant frequency components. Additionally, the remaining useful life of the bearing is estimated using the Support Vector Classifier algorithm, supplemented by RRMS and IRRMS to enhance prediction accuracy. A machine learning model, developed in Python and trained on bearing datasets, predicts the remaining useful life based on sensor-collected data. This comprehensive methodology aims to provide insights into bearing health, facilitating proactive maintenance and optimizing industrial operations

Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data

Sensors

IoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently captured by control devices. In the experimental part, we work on real measurement data and events from a coal fired power plant. The main research objective is to implement a model that detects deviations from the normal operation state based on regression and to check which events or failures can be detected by it. The presented technique allows the creation of a predictive system working on the basis of the available data with a minimal requirement of expert knowledge, in particular the knowledge related to the categorization of failures and the exact time of their occurrence, which is sometimes difficult to identify. The paper shows that with modern technologies, such as the Internet of Things, big ...

Fault diagnosis of mechanical systems based on electrical supply characteristics

2019

Induction motors are the main workhorses of industry. Condition monitoring (CM) of motor based systems plays an important role in the early detection of possible defects, averting adverse operational and financial effects caused by unexpected breakdowns. Limited information has been found which explores the diagnostic abilities of voltage and motor current signals from motors with variable speed drives (VSDs), which are increasingly used in industry to obtain better dynamic response, higher efficiency and lower energy consumption. This study addresses the gap identified by carrying out a systematic review of the monitoring of mechanical systems using induction motors with sensorless VSDs. Specifically, existing techniques often prove ineffective for common internal and external faults that develop in Induction motors. The primary aim is to extract accurate diagnostic information from the power supply parameters of a VSD to monitor IM driven systems for early diagnosis of both mechan...

Analysis of the Induction Motor used in Temperature Controller Machine by Condition Based Monitoring System

Condition monitoring of induction motor have been a challenging task for the engineers and researchers mainly in industries. There are many condition monitoring methods, including visual monitoring, vibration monitoring, thermal monitoring, chemical monitoring, acoustic emission monitoring but all these monitoring methods require expensive sensors or specialized tools whereas current monitoring out of all does not require additional sensors and analyzers. Current monitoring techniques are usually applied to detect the various types of 3-phase induction motor faults such as Rotor fault, short winding fault, air gap eccentricity fault, bearing fault, load fault etc. If any fault and failures occurs in the induction motor in any time can lead to excessive downtimes and causes a great losses in terms of revenue and maintenance. Therefore, condition monitoring for early fault detection of the motor is needed for the protection of the motor. In the present paper, survey of different types of faults in induction motor generate and their diagnosis techniques.

Condition Monitoring of Helical Gear Transmissions Based on Vibration Modelling and Signal Processing

2018

Condition monitoring (CM) of gear transmission has attracted extensive research in recent years. In particular, the detection and diagnosis of its faults in their early stages to minimise cost by maximising time available for planned maintenance and giving greater opportunity for avoiding a system breakdown. However, the diagnostic results obtained from monitored signals are often unsatisfactory because mainstream technologies using vibration response do not sufficiently account for the effect of friction and lubrication. To develop a more advanced and accurate diagnosis, this research has focused on investigating the nonlinearities of vibration generation and transmission with the viscoelastic properties of lubrication, to provide an in-depth understanding of vibration generating mechanisms and hence develop more effective signal processing methods for early detection and accurate diagnosis of gear incipient faults. A comprehensive dynamic model has been developed to study the dyna...

VIBRATION MONITORING AND CONTROL ON A CRUSHING PLANT FOR SMALL SCALE MINING IN SOUTH AFRICA.

Identification and possible modification of mathematical models and equations that govern the dynamics of a crusher……………………………………………………………………………………………………………….57-67 Chapter Four: Results and Discussion………………………………………………………………………………………..69 4.1 Envelope analysis Response…………………………………………………………………………………………………69-74 4.2 System development and enhancement for vibration response using Arduino and Proteus 8 Professional………………………………………………………………………………………………………………………………74-77 4.3 System development and enhance for data ADXL345 Accelerometer data acquisition and processing using wiringPiL2C library and compiler………………………………………………………………………77-81 Chapter Five: Conclusion and Recommendations………………………………………………………………….83-85 Reference……………………………………………………………………………………………………………………………….86-87

Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges

Energies, 2014

As the demand for wind energy continues to grow at exponential rates, reducing operation and maintenance (OM) costs and improving reliability have become top priorities in wind turbine (WT) maintenance strategies. In addition to the development of more highly evolved WT designs intended to improve availability, the application of reliable and cost-effective condition-monitoring (CM) techniques offers an efficient approach to achieve this goal. This paper provides a general review and classification of wind turbine condition monitoring (WTCM) methods and techniques with a focus on trends and future challenges. After highlighting the relevant CM, diagnosis, and maintenance analysis, this work outlines the relationship between these concepts and related theories, and examines new trends and future challenges in the WTCM industry. Interesting insights from this research are used to point out strengths and weaknesses in today's WTCM industry and define research priorities needed for the industry to meet the challenges in wind industry technological evolution and market growth.