John Crane, a business of Smiths Group, has developed an industry-first validated methodology that improves the accuracy of drivetrain analysis in critical rotating equipment.

The approach enhances prediction reliability, helping operators reduce failure risk, improve system performance and minimise downtime.

Traditional modelling methods often rely on fixed assumptions that fail to reflect real-world operating conditions, particularly in complex variable-speed systems.

This can create a gap between predicted and actual performance, increasing the risk of vibration issues, reduced asset life and unplanned outages.

John Crane’s new methodology addresses this by treating drivetrain behaviour as dynamic, recognising that torsional stiffness changes depending on operating conditions and torque levels.

By combining advanced modelling techniques, static and dynamic testing, and real operational data, the system delivers a more accurate representation of drivetrain performance.

Developed over three years and validated through testing and real-world applications, the methodology enables engineers to predict critical frequencies and system behaviour with significantly greater precision.

This reduces uncertainty during commissioning and operation while improving confidence in system design.

For industries such as oil and gas, LNG and power generation, the benefits include improved reliability, fewer unexpected failures and better-informed operational decisions.

The approach is already in use with OEMs and operators, offering a practical step forward for improving performance and resilience in complex rotating equipment systems.

Steve Pennington, Global Engineering Coupling Manager at John Crane, said: “This is a significant advancement in how drivetrain behaviour is understood and predicted. For years, the industry has relied on simplified assumptions that do not fully reflect real operating conditions. By validating this methodology through testing and live applications, we are giving customers a far more accurate and reliable understanding of system behaviour.” -OGN/TradeArabia News Service