Measure & Testing
| Leakage & Flow tests
| Fluid dynamics
| Electrical Measurements
| Hydraulic Measurement
| Acoustic Emissions
| SW & Simulation
Noise & Vibration
Vibration Analysis for the detection of electro-mechanical defects and their automatic identification and classification along the production line.
The technology has been applied to components (electrical motors and compressors) and home appliances such as washing machines, dishwashers and refrigerators.
Machine Vision supports test and quality control systems and presents the undeniable advantage of absolute objectivity in comparison with human operators inspection.
Completely automated systems are developed for functional and aesthetic tests, to verify presence/absence and the correct assembling of components and subassemblies.
Machine Vision systems can also be used to perform high precision measurement on devices under test avoiding any contact with them. It is suitable to check and analyse different features in various stages of the production line. The tested features are: print quality, 2D/3D measurement, correct assembly, feature detection and testing, components identification, correct positioning checking.
The infrared analysis is based on the use of a thermal camera measuring temperature without physical contact. The non contact measure is allowed by the fact that every object emits radiant energy, and the intensity of this radiation is a function of its temperature. The thermal camera simply measures the intensity of radiation and thereby its temperature. With refrigerators, the attention is focused on the outside rear part of the appliance, particularly on the inlet and outlet pipes of the condenser, where the system is able automatically detect “cold” and “hot” points and identify good and bad refrigerators. The infrared analysis can also be applied to other domestic appliances (washing machine and dishwasher) for water leakage detection.
Due to the increasing competitiveness in the mono and multi-crystalline photovoltaic market, production efficiency and cost reduction are becoming even more important.
In this context, the competences developed by Loccioni Group are able to respond to the production quality control needs in the photovoltaic manufacturing.
Using the electroluminescence effect, Loccioni’s system acquires images in the near infrared in order to identify cracks, non-active areas and poor connections between strings. The defects identification and their classification are carried out through neural networks.
Automatic robotized test stations for
| Localization systems
| Data tracking