Project examples

Based on different sensors (e.g. ultrasonic sensors, gas sensors, thermal imaging cameras), energy losses are automatically detected using inspection robots and artificial intelligence. 

The Ultrasound Condition Monitoring System is an in-house development by Senzoro and an absolute world first. For the first time we have combined artificial intelligence and acoustic emissions in the ultrasonic range. The solution is used to predict damage to rolling bearings and gears.

In an interdisciplinary research project, Senzoro provides the onion layer for evaluating acoustic emissions. Components are corroded in a salt chamber in order to generate data for training an AI that detects the types of corrosion and predicts progress.

A production-critical system is monitored by means of permanent ultrasonic sensors. System failures are predicted,  The basis for the predictions is our onion layer in combination with our rolling bearing AI. The machine runtimes are evaluated in real time.

Cracks in band saws are detected on the basis of microphone data (audible audio range) in order to reduce unplanned failures. Our onion layer evaluates the data in real time 24/7.

An app was implemented that uses AI to recognize machine statuses based on the built-in sensors in iPhone's. All sensors built into the iPhone are evaluated. The solution can be used offline and is equipped with a real-time dashboard in the cloud.

In a research project, we are generating synthetic data from rolling bearings in order to enrich real AI training data. The focus is on lubrication conditions and damaged components

The time of failure of (high pressure) rotary pumps is predicted on the basis of the increasing cavitation. The core of the solution is our onion layer, which extracts the relevant information from ultrasonic sensors.