Solving Control Valve Vibration Challenges - Emerson Automation Experts

Solving Control Valve Vibration Challenges

The production areas of many process manufacturing facilities can sometimes seem deafening. Some of this noise may be attributed to excessive vibration surround equipment such as control valves, piping and instrumentation.

Flow Control: Analyzing Vibration in and Around Control ValvesEmerson’s Adin Mann and Shawn Anderson have written a great Flow Control article, Analyzing Vibration in and Around Control Valves to look at the causes and remedies for excessive vibration. Many times, fixes are attempted:

…by measuring vibration, moving equipment, stiffening the valve structure, rewelding broken pipes, changing the piping system and other remedies — only to find problems still exist.

The challenge is to determine the root cause instead of addressing the symptoms. Around a control valve, vibration can be generated by:

…pump cavitation, flow pulsation, flow-induced excitations, vortex shedding, rapid valve closure, vapor pocket collapse, pump startup and shutdown, slug flow, water hammer and many other hard-to-diagnose conditions.

They describe two types of vibration:

Acoustically induced vibration (AIV) generates excessive levels of high-frequency acoustic energy that can cause fatigue failure of welded downstream connectors. This is often seen in liquid natural gas emergency blowdown systems, but is also found in other process piping systems. The noise levels generated by the valve and other piping elements are high enough to cause damaging vibration to the piping system.

Flow-induced vibration (FIV) generates high levels of kinetic energy that can cause piping vibration, loosen piping supports and cause fatigue failure at piping branches…

Typical rotating machinery vibration sensors do not measure vibration at these higher frequencies. The sensors need to be able to measure 3-5Khz or higher. These are installed:

…to measure the vibration in and around the valve and assess its severity in various locations; second, to assess changes and reductions in vibration after corrective measures are taken.

They used industrial wireless sensors to provide:

…complete vibration data including overall levels, energy bands, high resolution spectra and waveforms.

This data can be sent to cloud-based analytics applications for remote experts via connected services to analyze and make recommendations to plant personnel.

They describe how the placement of these sensors—upstream, on the control valve, and downstream—can help uncover the root cause. Conditions can range from the proximity of piping bends to the wrong valve trim for the application. An advantage of continuous monitoring over periodic manual monitoring is the trends over time:

…to reveal patterns leading to failure, allowing corrective action to be taken beforehand.

This vibration data can also be correlated with surrounding process data to uncover process changes which may be causing or contributing to the vibration issues.

Read the article for specific examples of the types of problems these sensors can uncover through analysis. There is also a great one-hour video from the fall 2017 Emerson Exchange conference, Control Valve Vibration Problems – Monitoring, Predicting, & Avoiding Them with Shawn, Adin and a customer where this vibration monitoring and analysis were performed to identify and solve a tough vibration challenge.

You can connect and interact with other valve experts in the Valves group in the Emerson Exchange 365 community.


  1. Jonas Berge says:

    This is another great example of how additional sensors and analytics software solves problems in plants. You can’t use use existing process sensors and expect to find “correlations” by analyze the history over the past few years. The reason for this is simple; by the time a problem gets so bad it impacts the process reading, the problem has already gone too far and the equipment is about to fail anyway. You can attempt all kinds of data science, but unless you measure directly the early indication of trouble is not visible. You can’t be predictive using only process sensors and analytics sensors. To solve problems you have to put in sensors that directly measure the symptoms; be it vibration or acoustics or whatever. Once that’s done, the analytics becomes pretty straight forward because you are already measuring the problem, in this case vibration. And of course it has to be done in real-time on live streaming data. Learn how other plants do it from this essay:

  2. Ajinkya Sakhare says:

    Good to know. Really helpful article.
    Please visit-

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