Predictive maintenance with vibration analysis

The problem

In factories a motor stops suddenly and the whole production line stops with it; the loss isn't the part's price but the hours of downtime. Calendar-based maintenance replaces healthy parts and misses parts about to fail. Vibration changes weeks before a fault, but it's usually only noticed when it becomes audible — too late.

How it works

1. LearningThe system records the motor's vibration fingerprint while healthy as a reference.
2. MonitoringThe accelerometer reads vibration at a high rate continuously.
3. AnalysisFrequency analysis breaks the vibration into its components, since each fault has its own frequency.
4. ComparisonA new frequency or a rise in intensity indicates a change in the motor's condition.
5. TemperatureThe motor temperature reading supports the diagnosis, since friction generates heat.
6. PredictionThe system estimates the time left before failure and issues a maintenance alert.

Project features

• Predicting a fault weeks before it happens — a direct, calculable financial value.
• Frequency analysis identifies the type of fault, not just its presence.
• It replaces calendar-based maintenance with condition-based maintenance.
• It reflects a deep understanding of signal processing, which makes the project stand out to the committee.
• It can expand to monitor several motors on a production line.

Expected challenges

These are the main obstacles to expect during the build, laid out clearly so you know them before you start.

• The sampling rate must be high, or important frequencies are lost.
• How the sensor is mounted on the motor changes the reading completely: loose mounting adds noise.
• Each motor has a different fingerprint, so no single threshold fits all motors.
• Vibration from neighboring motors interferes with the reading.
• High heat near the motor affects the electronics themselves.

The consultation gives you a solution for each one.

Expected committee questions

Prepare your answers in advance: these questions come up often in defenses of similar projects.

1. How does the system learn a healthy motor's vibration fingerprint?
2. What role does the Fast Fourier Transform (FFT) play in vibration analysis?
3. How is a bearing fault told apart from imbalance or looseness?
4. How far ahead can the system predict a fault before it happens?

Practice the defense, question by question