Content

1) Introduction (present challenges, history of CM, possible monitoring techniques)

- The role of condition monitoring and prognostics in a maintenance & operations framework: for machines, processes and production + maintenance strategies, RUL, terminology

- Motivating case studies: could be used throughout the course (machine/process/production) Real cases - degradation tests, possible use of test rigs

•           Importance of Condition monitoring (Measurements, Aims, Life concepts in monitoring, Failure rates)

•           Failure modes & criticality (Machine failures fault tree analysis)

•           Phases of Condition Monitoring (Fault detection/Fault diagnosis/fault prognosis)

•           Maintenance Strategies: no decision making here, focus on CM & Progn.

•           Permanent vs intermittent monitoring

•           Condition Monitoring Methods (Vibration Analysis, Oil/lubricant Analysis, Performance Analysis, Thermography, Electric Current Analysis, Ultrasonics, Acoustic Emissions, Instantaneous speed analysis)

•           Physical Quantities (vibration, current, voltage, speed)

•           Types and Benefits of Vibration Analysis (Benefits compared with other methods, International Standards and Guidelines)

•           Types and Benefits of Motor Current Signature Analysis, International Standards and Guidelines

2) Physical signatures of faults in mechatronic systems (typical faults, possible standards)

Machine faults / dynamic models for motors, gearboxes, pumps, … how does the fault occurs / generation of physical signatures

Bearings /Gears / transmissions / Motor / loads / pumps/airfans / Belts, couplings, misalignment/unbalance

3) Sensors & data acquisition (sensors, data, communication)

Sensors (Vibration Transducers, Torsional Transducers, Current Transducers, Voltage Transducers ), Characteristics of each sensor (bandwidth, ranges,..)

data types, DAQ, communication (networks) from an architectural point of view

sensor specs wrt application needs

4) Data processing (signals)

Signal class, toolchain,…

5) Diagnostics, with feature extraction and reduction

            Output is/are the features

• Vibration analysis
• Electric signal analysis
• Image based, object recognition, motion

6) Prognostics

Course material

The basic course material consists of the presentations used during the lectures. This material is complemented with compulsory reading material and optional reading materials for those students who want to deepen their insights in specific topics. Where possible, materials will be made available electronically (Toledo).