The VibroSense AI Chip is a cutting-edge solution designed for vibration analysis in Industrial IoT applications. It is based on the Neuromorphic Analog Signal Processor, which preprocesses raw sensor data, significantly reducing the amount of data to be stored and transmitted. This chip is particularly beneficial in predictive maintenance applications, where it helps in the early detection of potential machinery failures by analyzing vibrations generated by industrial equipment.
VibroSense excels in overcoming the traditional challenges linked to data processing for condition monitoring systems. By performing data preprocessing at the sensor level, it minimizes data volumes by a thousand times or more, making it feasible to conduct condition monitoring over narrow-bandwidth communications and at lower operational costs. This ensures industrial operations can identify issues like bearing wear or imbalance effectively, ultimately extending equipment life and improving safety.
The implementation of VibroSense's neural network architecture enables it to handle complex vibration signals with high accuracy. It supports energy-efficient designs, providing a compelling solution for industries aiming to optimize maintenance operations without increasing their OPEX. Its ease of integration with standard sensor nodes and support for energy harvesting applications further enhances its market appeal.
