Nois-IA project

Nois-IA Project – Artificial Intelligence for Underwater Noise Prediction

TSI takes a step forward in its innovation strategy with the Nois-IA project, a six-month pilot initiative that marks the beginning of our incursion into the development of solutions based on Artificial Intelligence (AI). This project, led by the R&D&I team, explores the application of intelligent algorithms for the detection and prediction of cavitation and Radiated Water Noise (URN) in different environments.

Although it is a short-term project with a limited scope, Nois-IA represents a key milestone for the company: it is the first project where we integrate artificial intelligence as the backbone of technological development to study cavitation data from campaigns already carried out, consolidating our commitment to the digital transformation of the engineering sector.

An Emerging Challenge: Cavitation and URN Prediction

Underwater noise pollution has become one of the most pressing environmental challenges in recent years. Institutions such as the European Union have acknowledged this issue due to its harmful impact on the marine environment as well as its implications for the maintenance and performance of vessels.

In this context, the Nois-IA project emerges as an innovative response, leveraging Artificial Intelligence to anticipate and mitigate phenomena such as cavitation and Underwater Radiated Noise (URN). The project aims to enhance both operational efficiency and the preservation of the underwater environment.

Real-World Validation and Technology Transfer

Nois-IA follows an experimental approach, developing a predictive model based on various AI algorithms, including neural networks. This model will be trained and validated using real data from ship measurement campaigns.

The system will be capable of: Identifying acoustic behaviour patterns. Anticipating cavitation peaks. Providing actionable insights for decision-making in areas such as structural health and vessel mobility.

A First Step Towards Quieter Seas

With the support of the Digitalisation Department of the Community of Madrid, Nois-IA lays the groundwork for a new generation of AI-powered tools for monitoring, detecting, and predicting underwater noise. Its greatest value lies in its ability to: Open new lines of research. Drive the digital transformation of acoustics, sound, and vibration engineering within the maritime sector. Strengthen the connection between engineering, technology, and sustainability. This project not only enhances the technological capabilities of TSI, but also reinforces its commitment to responsible innovation and the future of our oceans.

A unique challenge for TSI

TSI brings its extensive experience in the study of noise generated by acoustic sources, especially propeller cavitation. It leads the development of a system based on AI – Machine Learning capable of estimating and predicting the acoustic behaviour of ships using real data from past campaigns.

• The system is trained with cavitation data collected in previous campaigns, allowing to create a solid basis for the models.
• Preparation of URN models and estimation systems for the project demonstrators.
• Development of a predictive model of radiated noise to water (URN) from shipboard measurements.
• Application of AI algorithms on raw cavitation signals, saving time in processing and labelling.
• Creation of long-term reusable predictive models for future campaigns.

PROJECT BENEFICIARY

TÉCNICAS Y SERVICIOS DE INGENIERÍA S.L.