In 2021, we achieved the KTP certificate of excellence (find out more here) through the United Kingdom’s innovation agency, Innovate UK, which resulted in the development of our advanced self-learning condition monitoring system, called Datum Hawk as well as our latest whitepaper.
Following hot on the heels of our first whitepaper where we talked about approach to savings and vital measurements, in our second instalment, we cover the importance of Digital Twins and high sample rate torque data.
Whitepaper part 2 contents
- Interpreting Torque Data with Digital Twins: This chapter covers how ICT is obtained and the reliability of the shaft power meter which is vital in identifying, cost-effectively the onset of failures, and spotting degradation trends. This topic also includes a brief explanation of the digital twins, where and how the digital twins are utilised.
- Crankshaft Dynamics, Digital Twin & Self Adaptive Algorithm: A chapter dedicated to 2D adaptation of the self adaptive algorithm along with the explanation of how and what it utilises within the engine.
- Thermodynamics Digital Twin: This section talks about how the data collected from the thermodynamics digital twin can be used to simulate the engine performance under different conditions.
- The Bigger Picture: From providing the maximum value out of the data collecting to demonstrating the usefulness of the ICT data for engine diagnostics. This chapter explains our approach and why combining these dynamics digital twins with high sample-rate torque measurements are a key for identifying the engine’s health status.
The aim of Whitepaper is to introduce the concept and key points behind Datum Hawk and why it was created. This benefits our customers and those who wish to take advantage of a powerful, sustainable shipping tool. Check out the full whitepaper here >>