Big-Time Condition Monitoring

Condition Monitoring Is More Than Walking Around the Plant With a Data Logger and a Clipboard. Done Big Time, It Can Save You Millions of Dollars

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Gurney of Concept Systems says companies should consider two underused technologies: statistical process control (SPC) and digital video recorders (DVRs). "SPC tools offer better data analysis and earlier, more accurate detection of problems," he explains. "Small variances, oftentimes operating within normal high/low limits, reveal equipment issues well before catastrophic failure."

As for DVRs, Gurney says they offer the ultimate troubleshooting device by giving personnel the ability to record processing lines when upset conditions or downtime are detected. "This way, plant personnel can go back and look at the video captured during these events and determine the root cause of the problem," he says.

As CM capabilities increase and costs come down, the challenge for many will be finding the time to install and operate these systems. Despite proven payback, plant personnel often are so burdened with day-to-day operation that they can't find the time to use proven CM tools.

Lack of skilled personnel to analyze and interpret condition monitoring data is another continuing challenge. A solution may be off-site analysis of CM data by third-party suppliers, with actionable data provided to plant personnel on an exception basis as is the case with Centro Energia's use of Emerson's off-site analysis services.

State-of-the-art CM is still not easy or inexpensive, but it's also not an insurmountable challenge, and the expense and effort are well-spent when weighed against the cost of downtime for critical assets.



Dan Hebert is Control's senior technical editor.

Condition Monitoring Tells All

Fluor designs and builds huge process facilities such as chemical plants, refineries and power plants. Romel Bhullar, senior technical fellow/director at Fluor, says, "In almost every project we do—refineries, energy, petrochemical, biochemical, pharmaceutical or power—asset condition monitoring (CM) is an integral part."

One such project at Potomac Electric Power Co. (Pepco) involved a plant supplying power to the city of Washington, D.C. "It's critical that the power generation turbines, generators and auxiliary systems have a CM system that monitors impending failures and identifies reasons to do preventive maintenance."

Putting together such a system isn't easy. "Standard commercial off-the-shelf solutions weren't flexible and functional enough to match our needs," he says. "There were mountains of challenges: technical, people, commercial, multiple company cultures and organizations," he adds. "In these days of tough economic times, all vendors are protecting their markets and providing proprietary and expensive solutions. It makes integration very difficult."

Things are improving, but problems still exist when tying together different communication protocols. "There have been significant developments in networking technologies and communications equipment, but major issues in the bottom two layers of the OSI model still need lot of work," he notes. "Management may have different objectives than the people in operations, IT and control systems—not to mention suppliers. It's a maze out there." Bhullar says the cost to install the CM system at Potomac Power "…was several million dollars."

The data being gathered is extremely important to more than just the power company. EPRI (, a power industry consortium in Palo Alto, Calif., contributed to the project, so it could see the data.

"The conditioning monitoring system provides data in real time to all the EPRI stakeholders across the U.S.," Bhullar explains. "GE is looking at their new gas turbine/generator and collecting performance parameters to improve their design. Westinghouse/Mitsubishi is collecting data on their newest gas turbines/generators. Potomac Power's operations and maintenance staff are looking at impending failures. And Fluor is collecting data for validating our methods for predicting failures."

The system works, too. "The cooling system on one of the turbine blades had failed due to plugging of the passages," he says. "The system identified the problem, and Potomac was able to replace the blade in off peak hours without any loss in power."

It works for EPRI too. The information is being used by member utilities to make decisions relating to equipment selection, design configurations, maintenance and replacement policies. The data is also being used by these same utilities to validate supplier sales claims and promises of newer technologies before making the huge required capital outlays for a comprehensive CM system.

Attacking the Problem

Systems integrator Concept Systems in Albany, Ore., has implemented many high-level asset condition monitoring (CM) solutions. Michael Gurney, co-CEO, says that a CM project takes a two-level approach: First, use control hardware already in place; next, equip assets with new instrumentation and controls.

Much of the equipment in a plant already has diagnostic capabilities. "A typical automation system will control the equipment, but stop short of pulling data off the controller or motor drives. With some simple programming, a system can collect key data such as motor start/stops, cylinder cycles, fault counts, drive current, downtime, cycle time/flow rates, valve position, pressure readings and more," says Gurney.

"Collecting and correlating this data finds problems," he explains. "For example, monitoring the flow rate at known valve positions will point to issues with the valve prior to catastrophic failure. All this information can be used to make better sense of the data and better manage that asset."

Some equipment may not have the sensors needed for CM. In this case, the asset has to be equipped with sensors and tied into the control system. "The possibilities are really endless and depend on the type of asset being monitored," points out Gurney. "Because of this, a crucial step is evaluating what assets really need to be monitored and how. The question is what assets put my processing line at greatest risk. In many cases this may not be known, and that is where data gathered from existing control hardware can help."

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