Design of Smart CMS for Rotary Machines

Description

A Smart Condition Monitoring System (SCMS) is a system that uses IIoT sensors and AI-based monitoring to detect the condition of mechanical equipment, such as pumps, compressors or gearboxes. It can help to prevent expensive plant downtimes by reliably detecting imminent failures before they occur and enable predictive maintenance.

Benefits of SCMS for Learners are:

• SCMS can help Learners understand the principles and applications of condition monitoring, predictive maintenance, artificial intelligence and Internet of Things in various industrial settings.

• SCMS can provide learners with real-time data and plain text information from multiple sensors that can be used for analysis, diagnosis and decision making.

• SCMS can enhance learners’ problem-solving skills and critical thinking by challenging them to identify and resolve abnormal operating conditions of Machines.

• SCMS can improve learners’ safety awareness and risk management by showing them how SCMS can prevent expensive plant downtimes and reduce unscheduled maintenance.

"Learn and Master the Most Popular Predictive Maintenance Technologies in this Comprehensive Course".

• Learn the Supervised Data Aquisition Methodologies

• Learn the Complex Data Analytics in a simple way by using Data Ensemble Techniques.

• Learn the Data Preprocessing Methodologies by using Time Synchronous Averaging (TSA).

• Build the Condition Indicators which will be used for Identifying the Health Condition of Rotating Critical Parts of Machines.

• Build the Neural Networks Model (Classification Learner) which will be used to train on the Condition Indicators for Predicting the Health Condition of Rotating Machines.

SCMS can be integrated with existing equipment and networks of Rotating Machines and can provide real-time data from multiple sensors for analysis, diagnosis and decision-making regarding Health Condition.

Data Acquisition (DAQ) in Smart Condition Monitoring System (SCMS) is the process of capturing and recording sensor data from mechanical equipment, such as vibration, temperature, pressure, etc. DAQ is a crucial stage in SCMS because it provides the raw data for analysis and diagnosis of the equipment condition. Engineers and technicians who design, install, operate and maintain mechanical equipment, such as pumps, compressors, gearboxes, etc. The Learner can go as Data Acquisition Developer after learning Data Acquisition (DAQ) topic.

Data Preprocessing in SCMS is the process of transforming raw sensor data into a format that can be understood and analyzed by machine learning algorithms. It is an essential step in data mining and data analysis as it improves the quality and accuracy of the data. Data analysts and data scientists who perform data mining and data analysis on sensor data to extract useful insights and patterns for condition monitoring. The Learner can go as Data Analyst, Machine Learning Engineer, Data Preprocessing Specialist.

I have designed this technology course to be easily understood by absolute beginners. My course offers hands on skills in the domains of Data Aquisition, Data Ensemble Techniques, Condition Indicators, Artificial Neural Network Model.

I Have Designed each Lecture with good number real time examples so that you can practice even after you complete the course.

At the end of each section the learner will walk away with complete detailed lecture notes of that section and a set of questions in order to measure the learner understanding of that section and finally the learner will be given with project after completion of the course which will help in getting relevant job.

What You Will Learn!

•  Rotating Machinery Measurement
•  Signal Processing Methodologies
•  Industrial Internet of Things (IIoT)
•  Supervised Data Acquisition
•  Multidimensional Data Analysys
•  MATLAB Operators and Special Characters
•  Conditional Statements
•  Loop Control Structures
•  M-File Scripts
•  M-File functions
•  2D and 3D Plots
•  Complex GUI Model Development by using Simulink
•  Fault Detection
•  Fault Identification
•  averaged time series (TSA)
• spectrogram
• Drivetrain technology
• Condition Indicators Based on Model Parameters or Dynamics
• Classification to predict categorical responses
• Prepare Model for Code Generation

Who Should Attend!

• This Course for the professionals in any Manufacturing/Process/Cement industries who want to enhance their skill set
• This Course is for Fresh Graduates from Mechanical/Mechatronics/Electrical/Electronics/Instrumentation, actively Looking for opportunities in Industry 4.0 Domain as a predictive maintenance Engineer.
• This Course is for intended learners from Mechanical/Mechatronics/Electrical/Electronics/Instrumentation Engineering background, interested in exploring Predictive Maintenance technology.
• This Course for the Faculty members from Mechanical/Mechatronics/Electrical/Electronics/Instrumentation Departments who want to start their Research work in Machine maintenance.

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