Diploma in Vibration/Acoustic Analysis and Health Index
Online postgraduate diploma of 800 hours in vibration/acoustic analysis and Health Index. 8 modules covering rotating machinery dynamics, vibro-acoustic acquisition, vibration, acoustic and ultrasound analysis, indicator fusion and learning-based health indices, with an assigned technical tutor.
Diploma in Vibration/Acoustic Analysis and Health Index — studying from Singapore
Singapore has invested heavily in artificial intelligence and data, under national plans coordinated by the Infocomm Media Development Authority and the AI Singapore programme. The sector spans industrial analytics, digital twins, simulation for engineering design and data platforms serving finance, logistics and healthcare. Engineers work across machine learning, data engineering and computational modelling. Employers range from global technology firms and banks to local research institutes and government-linked companies.
Fees for Singapore: S$2,560 (Singapore dollar), with instalments and employer sponsorship available.
Relevant bodies in Singapore
Typical roles
Questions from Singapore
Does Singapore have a recognised body for data and AI professionals, and is SEIUM recognised?
Singapore's Infocomm Media Development Authority (IMDA) and the Singapore Computer Society are key bodies in the digital and data field, and the Personal Data Protection Commission (PDPC) oversees data protection. SEIUM's qualifications are private, not state degrees, and not accredited by any national body. Acceptance is decided by employers or the relevant body, so verify this before enrolling.
Which Singapore employers hire data, AI and simulation specialists?
Demand is strong across banks, government agencies, healthcare, logistics, telecoms and tech firms. Singapore's national AI and smart nation initiatives also create roles. Employers typically assess portfolios, technical interviews and proven projects. Your final project can demonstrate applied analytics or simulation skills, though hiring decisions are the employer's.
Can I study this part-time from Singapore, and does it need a student visa?
Yes, the programmes are 100% online and taught in English, so you can study from Singapore without a student visa. Workload is substantial, with 1,900 hours for a master's, 800 for a postgraduate diploma and 300 for a specialist course. Fees can be paid in instalments, and employer sponsorship is possible, subject to your employer's approval.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Relate the dynamics of rotating machinery to its vibro-acoustic symptoms.
Acquire high-quality vibration, noise and ultrasound data.
Diagnose mechanical faults through vibration analysis.
Apply acoustic and ultrasound analysis to maintenance.
Fuse vibro-acoustic and process indicators.
Build health indices with normality models.
Integrate the health index into maintenance decision-making.
Who it's for
- Certified vibration analysts who want to add acoustics and machine learning to their toolkit.
- Condition monitoring engineers responsible for critical rotating assets.
- Maintenance data scientists building health indicators from sensor data.
- Ultrasound technicians working on lubrication and leak detection.
- Reliability engineers prioritising interventions across fleets of machines.
- Industrial acoustics engineers dealing with noise and acoustic emission.
- Engineering or science graduates looking to move into the energy sector.
What you'll work with
- ISO 20816-3 (vibration of industrial machines above 15 kW)
- ISO 13373-3 (vibration diagnostics: guidelines)
- ISO 29821:2018 (condition monitoring by ultrasound)
- ISO 18436-2 (qualification of vibration analysts)
- ISO 21940-11 (balancing of rigid rotors)
- ISO 22096:2007 (acoustic emission for condition monitoring)
- ISO 3744 (sound power from sound pressure)
- Python with librosa and SciPy
- Brüel & Kjær BK Connect
- MATLAB Predictive Maintenance Toolbox
- PyTorch
- SKF Observer
8 modules
1.1Unbalance, misalignment and looseness1.2Resonances and critical speeds1.3Bearings and their defect frequencies1.4Gears and gear mesh frequency1.5Phenomena in pumps and fans1.6Cavitation and turbulent flow1.7Sources of aerodynamic and mechanical noise1.8Structural transmission of vibrations1.9Severity criteria by machine type1.10Workshop: symptom catalogue by failure mode
2.1Accelerometers and their mounting2.2Measurement microphones and intensity probes2.3Ultrasound sensors2.4High-frequency acoustic emission2.5Measurement routes and capture points2.6Online systems versus portable routes2.7Synchronisation with a tachometer2.8Operating condition metadata2.9Measurement quality and validation2.10Lab: synchronised acquisition of vibration and noise
3.1FFT spectra and waveforms3.2Phase analysis and operating deflection shape3.3Envelope analysis for bearings3.4Order tracking3.5Waterfall diagrams3.6Operational modal analysis3.7Run-up and coast-down analysis3.8Diagnosis of unbalance and misalignment3.9Field balancing3.10Practical exercise: diagnosing misalignment in a pump
4.1Sound pressure levels and weightings4.2One-third octave band analysis4.3Psychoacoustics: loudness and roughness4.4Ultrasound for lubrication and leaks4.5Compressed air leak detection4.6Acoustic cameras and beamforming4.7Acoustic emission in cracks4.8Acoustic failure signatures4.9Sound classification with mel spectrograms4.10Case study: leak detection with ultrasound
5.1Narrowband and broadband indicators5.2Envelope and kurtosis indicators5.3Band-based acoustic indicators5.4Normalisation by operating regime5.5Fusion of vibration and acoustics5.6Fusion with process variables5.7Indicator selection by monotonicity and trend5.8Dimensionality reduction5.9Trend visualisation5.10Lab: fusion of vibro-acoustic indicators
6.1Baseline of healthy behaviour6.2Normality models with autoencoders6.3Distance to the healthy state as an index6.4Indices with Gaussian Mixture Models6.5Similarity and degradation trajectories6.6Calibration with failure events6.7Uncertainty and confidence bands6.8Indices per component and per machine6.9Comparison with expert methods6.10Practical exercise: autoencoder Health Index for a pump fleet
7.1Intervention thresholds7.2Prioritisation of work orders7.3Shutdown planning7.4Communication to operations and maintenance7.5Validation of the index after interventions7.6Feedback from workshop findings7.7Programme effectiveness indicators7.8Scaling to large fleets7.9Improving models with new failures7.10Case study: prioritising interventions on fans
8.1Asset and failure modes8.2Acquisition plan8.3Vibration analysis8.4Acoustic analysis for the vibro-acoustic index8.5Indicators and fusion8.6Health index model8.7Validation and thresholds8.8Operational proposal for the vibro-acoustic index8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
Training is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so the programme fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python with librosa and SciPy, Brüel & Kjær BK Connect, MATLAB Predictive Maintenance Toolbox, PyTorch and SKF Observer, in free, academic or evaluation versions. Exercises are based on real procedures: diagnosis of unbalance and misalignment on a test rig, detection of leaks and lubrication failures by ultrasound, and validation of health indices on pump fleets. Assessment is continuous by module, plus the final capstone project.
Standards covered: ISO 20816-3, ISO 13373-3, ISO 29821:2018, ISO 18436-2, ISO 21940-11, ISO 22096:2007, ISO 3744.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Python with librosa and SciPy, Brüel & Kjær BK Connect, MATLAB Predictive Maintenance Toolbox, PyTorch and SKF Observer, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector; no university degree is required.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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