Engineers have licensed patented technology developed by Dr. Jeff Hay at RDI Technologies to create a vision-based system called OptiVibe that enables engineers to identify vibration issues with their equipment with a greater degree of simplicity and in a much shorter period of time.
Vibration analysis is a widely used predictive maintenance technique that enables engineers to evaluate the condition of equipment. In doing so, maintenance personnel can schedule repairs on the equipment during maintenance shutdowns to avoid failures during production runs.
One popular approach that has been deployed to visualize the vibration pattern of a machine involves the use of Operating Deflection Shape (ODS) analysis. In this process, vibration measurements are taken at a number of different locations on a machine using transducers. The data from the transducers is then analyzed by software to create a geometric stick figure model of the structure of the machine and display vibrational patterns.
However, the ODS analysis technique is not without its drawbacks. ODS requires a skilled person to configure mechanical transducers at specific locations on the machine before the data can be acquired. In many cases, the sheer number of collection points can prove problematic.
Having deployed such a system, engineers then need to set up a database to acquire the data from all the collection points and post process the data before a stick figure animation can be rendered. Although this can be achieved through software, it can take hours to complete such an analysis. Also, the data may then need to be further analyzed to determine what is happening physically between each of the points from where the data was acquired.
Vision vibrations
Now, however, engineers at Allied Reliability Group (Charleston, SC, USA;www.alliedreliability.com) have licensed patented technology developed by Dr. Jeff Hay at RDI Technologies (Knoxville, TN, USA; www.rdi-technologies.com) to create a vision-based system called OptiVibe that enables engineers to identify vibrational issues with their equipment with a greater degree of simplicity and in a much shorter period of time (Figure below).
The OptiVibe system typically captures video images of an asset in a plant using Allied Vision Technologies’ (Stadtroda, Germany;www.alliedvision.com) cameras, such as the Prosilica GE680. This camera uses a KAI-0340 CCD sensor from ON Semiconductor (Phoenix, AZ, USA; www.onsemi.com), which delivers VGA resolution at a frame rate of 205fps. Since the resolution and the frame rate of the camera determines the resolution of the displacement and the maximum frequency of the vibration that needs to be identified, cameras with higher resolution imagers and greater frame rates can be deployed if necessary. Typically, however, around 15 seconds of data are captured by the camera and transferred over a GigE interface to a PC where the images are stored prior to analysis.
Proprietary algorithms running in a National Instruments’ (Austin, TX, USA; www.ni.com) LabVIEW application on a PC take the video input and process each pixel in the set of images to detect fluctuations in pixel intensity. By using a Fourier transformation, the time-dependent intensity data is then converted into frequency-dependent intensity data. The image processing software also generates Vibragrams, color-coded representations that appear as thermograms, but which show the movement of the asset, instead of its temperature, providing an intuitive means by which the vibration of the asset can be interpreted (Figure below).
