evolution of valve diagnostics

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technology spotlight

Evolution of Valve DiagnosticsDelivering Enhanced Process Control Under Increased Scrutiny

Control valves have drawn more and more attention in recent

years, and modern diagnostic technologies and techniques

are helping them shine under this increased scrutiny.

For many years, end-users focused on infrastructure-related

assets, invested in advanced process control system equipment,

and, following the tragedy of 9/11, tightened plant security.

Meanwhile, control valves, while essential, were line items buried

in the maintenance budget.

The script is different today, however, thanks to global com-

petition and growing pressure to increase profits, boost plant

performance, and improve process reliability. The final controlelement has a direct impact on a facility’s operational excellence

– a combination of profitability, plant efficiency, quality, and safety

– putting it squarely on the radar screens of maintenance teams

and reliability and process control engineers.

This, in turn, has made valve diagnostics more important than

ever. To keep a plant’s control valves performing optimally, the

end-user must be able to monitor each

valve’s performance and have actionable

information to use in identifying which

valves require maintenance, accurately

diagnosing valve problems, and planning

maintenance activities. And they need tohave this information in hand before valve

problems impact process performance.

Diagnostic methodologies and technolo-

gies for control valves have evolved greatly

in the past 20 years with the advent of

microprocessor-based valve positioners

and the introduction of user-friendly ways

to integrate the information into the super-

visory system. This article will review the

milestones in this evolution and describe

how online valve diagnostics (OVD) can help

improve process integrity by giving opera-tions personnel the information they need to

address problems early, before they become

major issues. It also will discuss the various

types of diagnostic information that can be

provided by digital valve positioners and explain how to integrate

this information with a plant asset management solution.

Valve Diagnostics Timeline: Pre-1980Prior to the 1980s, control valves could not be monitored remote-

ly and diagnosing a problem valve involved the use of mechanical

tools and techniques that could only be mastered through exten-

sive hands-on experience.It was not uncommon to see a technician apply a finger to a

valve stem to “feel” the motion of the valve. This technique was,

certainly, more of an art than a science. Determining whether the

motion of the valve was “normal” required a unique skill set and

significant experience. And unless the valve’s motion was jerky

(sticking and slipping), this technique provided no clues as to

what might be wrong with the valve.

Veteran technicians also will recall using pencil and paper to

record pressure readings from the gauge on a valve’s actuator

and valve positions from a dial caliper. These readings would then

be used to calculate friction and spring range.

Valve Diagnostics Timeline: 1980sThe 1980s saw the introduction of computers and portable data

acquisition systems into process control facilities. These portable

systems (Figure 1) used external sensors to measure the forces

generated by a valve’s actuator and used a travel sensor to mea-

sure the valve’s motion. It was the birth of the valve signature

concept.

These portable valve diagnostic tools

were (and still are) highly effective for vali-

dating the health of a control valve before

putting it in service or for verifying a valve’s

condition post-repair. They also are stillsuccessfully used to diagnose the health of

control valves equipped with analog posi-

tioners.

These tools are not, however, user-

friendly. The diagnostic process is time-

consuming, taking at least one hour per

valve. Personnel must be specially trained

in installing the sensors. Analyzing the data

so that it becomes actionable information

involves significant number-crunching.

Personnel may be required to enter poten-

tially hazardous areas to conduct tests. Andusing these tools is more disruptive than

using newer options, as it requires that the

process be shut down or the control valve

bypassed.

Valve Diagnostics Timeline: 1990sThe 1990s were marked by the introduction of microprocessors

placed inside valve positioners – the birth of digital valve posi-

tioners (DVPs). This decade also saw a transition from proprietary

field communication protocols to open digital communication

standards such as the HART Protocol, the Foundation fieldbus,

and PROFIBUS.The new DVPs had embedded sensors to measure the pressure

Figure 1. The 1980s saw the introduction of

portable data acquisition systems that usedexternal sensors to measure the forces gener-

ated by a valve’s actuator and a travel sensor

to measure the valve’s motion.


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moving the actuator and a travel sensor to track valve motion. This

made them significantly more user-friendly, because the end-user

did not need to complete any mechanical setup in order to measure

the force that moved the valve and track the valve’s actual position.In addition, the new DVPs allowed embedded test routines, in

which the positioner would modulate the valve while measuring data

from embedded sensors. This essentially eliminated the need for

portable data acquisition systems, allowing the masses to make their

own signatures. Yet skills in analyzing signatures were still necessary

and the tests were as intrusive as those completed with portable

diagnostic tools.

There also was no open standard that all valve manufacturers

used to analyze the signature results and display them to the

end-user. Each manufacturer had its own proprietary software

that required additional hardware and software if the user wanted

to remotely access the data. Equipment from various manufactur-ers could not be easily integrated, creating “islands of informa-

tion” that were frustrating and costly to use and support.

Valve Diagnostics Timeline: 2000 – TodayThe early 21st century has been marked by two significant

advances that have helped process facilities address such

emerging challenges as reduced staffing, the location of facilities

in evermore remote places, and globalization.

First is the introduction of open standards that present diag-

nostic information to the end-user in a common fashion, allowing

devices from various manufacturers to communicate with each

other and allowing end-users to “mix and match” devices fromvarious manufacturers to best meet their needs.

Second is the advent of online valve diagnostics technology

that allows sensor and other data from DVPs to be gathered,

analyzed and delivered to the end-user – all automatically and

all while the process continues running. Without disrupting the

process, valves can be tested and drifting Key Performance

Indicators (KPIs) can be identified before they begin impacting

production. And rather than raw data, the end-user receives

actionable information, eliminating the need for complex calcula-

tions and data analysis and helping the end-user more quickly

determine the appropriate course of action.

The “Flavors” of Diagnostic InformationWhile diagnostics for control valves have evolved significantly,

end-users can still be confused by the various “flavors” of diag-

nostic information that are available. Diagnostic information can

be divided into three general categories – continuous, offline

and online – based on the type of data provided and how it is

gathered.

Continuous: Continuous diagnostic information is defined as

data saved in the non-volatile memory of a digital positioner. It

can include cycle count (number of valve reversals); accumulated

travel; hours of operation closed, near closed and open, etc. It

also includes DVP alerts initiated by the positioner to notify theend-user of device performance issues or abnormal conditions,

such as low air supply or position deviation.

This data can be valuable in predicting eventual

failures or process control deficiencies, or in helping determine

whether a valve has been improperly selected for a given applica-tion.

In addition, because the values are continuously monitored

and the data is saved by the DVP, the integration to a historian

is seamless. In other words, continuous communication with the

DVP is not necessary in order to collect the data because the DVP

functions as a “field server” of control valve information.

Offline: Offline diagnostic information can only be obtained by

sending a command to the DVP using the vendor’s software to

initiate a test or to start the acquisition of specific data. The com-

mand triggers a routine inside the positioner that modulates the

valve and gathers data from the built-in sensors.

Typically, the valve must be isolated and bypassed in order toallow the test to stroke the valve back and forth. The result is

a signature that will provide insight into the mechanical condi-

tion of the valve, including how well the valve closes and how

it responds to an input signal. Essentially, the offline signature

delivers the same results that are provided by portable data

acquisition systems, but it is much easier to execute a signature

with a DVP because the necessary sensors are built into the posi-

tioner, rather than installed separately to the outside of the DVP

by the end-user.

Online Valve Diagnostics: This type of diagnostic information

is described as “online” because it is gathered while the valve

is controlling a live process. The condition of a control valve canbe assessed without disabling the positioner and interfering with

plant operations.

Data is gathered from the DVP’s built-in sensors as the DVP

modulates the valve. Once the data is gathered, fault-modeling

techniques are applied to quantify Key Performance Indicators

(KPIs), such as friction, initial and final spring settings, response

speed, positioning accuracy, and position lag. The KPIs are then

compared to the nominal values; if they are found to be outside

the desired range, fault-modeling techniques will identify the pos-

sible cause of the deviation.

In addition, KPIs are monitored and analyzed over time, allow-

ing plant personnel to identify trends and estimate when the valvewill require attention. Predictive maintenance can then be com-

pleted before the valve malfunctions and impacts the process.

For example, steadily decreasing friction is a sign of packing and

stem wear that could result in fluid leaking to the atmosphere,

indicating to plant personnel that the packing should be tightened

to prevent leaking and that the valve should be flagged to receive

more comprehensive maintenance in the near future.

The table in Figure 2 offers a snapshot of the various aspects

of valve performance and condition that can be tracked using

each of the diagnostic “flavors.”

Diagnostic Capabilities & LimitationsEach of the three diagnostic information “flavors” offers a differ-

By Sandro Esposito



technology spotlight

August 2011 Flow Control

ent array of information and different insight into the corrective

action that should be taken to maintain the integrity of a control

valve’s overall performance (Figure 3). For example, the accumu-

lated cycles and travel displacement data obtained via continuous

diagnostics can be used to determine when packing must be

maintained or replaced. Offline diagnostic information allows the

user to validate the valve’s response throughout its full range of

motion, as well as measure such performance characteristics as

valve friction, the spring setting, and the quality of the plug andseat contact (also known as seating profile).

Online diagnostics tools combine the capabilities of their

continuous and offline counterparts while offering additional

advantages. There is no setup involved and the DVP’s software

automatically captures the data, saving time and streamlin-

ing processes. Remote access means plant personnel are not

required to enter potentially hazardous areas. The historical datacaptured allows plant personnel to see performance trends over

time. Finally, there is the significant advantage that the tools do

not interfere with the control valve’s operation.

One key performance characteristic that cannot be tracked

with a DVP or with a portable diagnostic tool is seat leakage.

To explain why, let us begin by reviewing how tight shutoff

is achieved. When the plug makes contact with the seat, the

force generated by the actuator is delivered through the stem,

compressing the plug against the seat. This metal-to-metal con-

nection is what prevents the fluid from going through the orifice

(seat) of the valve. The surface finish of the two components

making contact is critical to shutoff. The smallest nick or scratchcan degrade the shutoff to the point that the valve does not

fulfill its ANSI (American National Standards Institute) shutoff

classification.

While DVPs can confirm that there is a firm and adequate

contact between the plug and seat, they cannot determine the

integrity of the surface finish. The only method to confirm that the

valve can achieve its shutoff classification is to run a seat leak

test, or close the valve and measure the flow going through it.

Usability of Diagnostic ToolsThe usability of diagnostic technology has improved significantly

with the emergence of such integration standards as EDDL(Electronic Device Description Language) and DTM (Device Type

Figure 3. DVPs capture valve performance data and then transfer it to an

asset management station using one of several communication protocols.

The asset management station then converts the data into actionable in-

formation that can be used by plant personnel in assessing and addressing

valve performance.

Capabilities of Various Diagnostic Tools

Key PerformanceIndicator (KPI)

OfflineDiagnostics

ContinuousDiagnostics

Online ValveDiagnostics

DVP Performance √ √ √

DVP Condition √ √

Runtime Information √

Seat Profile √

Seat Load √

Static Performance √

Packing Condition √ √

Bellows Condition √ √

Guide Friction √ √

Spring Adjustment √ √

Spring Integrity √ √

Feedback Linkage √ √

Air Leak √ √

Dynamic Performance √

Historical KPIs √

Root Cause Analysis √

Shutoff Classification

Figure 2. This diagnostics capabilities checklist summarizes the various

facets of valve performance and condition that can be monitored using

each of the three “flavors” of diagnostics technologies. All three types of

information are necessary to get a complete picture of a valve’s health.

Diagnostics cannot assess seat leakage (shutoff classification); it can only

be tested by closing the valve and measuring the flow going through it.



Manager). Prior to the introduction of such standards, the inte-

gration of field device diagnostics was complex and required

significant engineering because each vendor had proprietary,

standalone solutions. With EDDL and DTM, the diagnostics provid-ed by DVPs are easily integrated with control systems and asset

management software that support such standards. The user can,

therefore, access the digital positioner’s diagnostics with com-

mercially available software and without the need for software

engineering.

In cases in which the host system does not support EDDL or

DTM, the end-user can still integrate the information via the OPC

(OLE for Process Control) standard. OPC is a communication

protocol allowing the exchange of data between computers and

between software. It creates a “pipeline” to move data between

a computer (the server) that is connected digitally to the DVP and

the computer (the client) that uses the raw data to generate andpresent the diagnostics.

The integration of diagnostics is straightforward with control

systems that embed the HART Protocol, Foundation fieldbus, or

PROFIBUS. These systems have an architecture in which diagnos-

tic information is passed from a DVP to a user interface.

In the case of older systems that still use an analog signal,

such as 4-20mA, the DVP’s diagnostic data cannot be com-

municated through the host system’s architecture because the

system’s analog output channels are not capable of reading

the HART data. The emergence of wireless standards, such as

WirelessHART and ISA100, bridge that gap by allowing the data to

be wirelessly communicated from the DVP to a centralized dataacquisition computer.

When it comes to presenting the information to

the user, there are two primary industry standards

for doing so in a common fashion, regardless of

the DVP’s manufacturer – ISA SP75.26 and NAMUR

NE 107. ISA SP75.26 applies to offline diagnostics,

defining the terminology for valve diagnostics and

the graphical representations of valve signatures.

NAMUR NE 107 applies to continuous and online

diagnostics. It categorizes various possible asset

conditions and their severities and uses a set of col-

or-coded symbols to communicate these statuses(Figure 4). The same symbols are used for devices

made by various manufacturers, making them easily

recognized and interpreted – much like the “Check

Engine” light on a car’s dashboard.

The Next Decade –Developments to WatchControl valve diagnostics have evolved rapidly

over the past 30 years – from manual readings with gauges and

calipers to artificial intelligence that can analyze a valve’s per-

formance while the valve is in operation. Advances will come as

fast, if not more quickly, over the next decade thanks to continuedadvances in artificial intelligence and the introduction of ultra-low-

power microprocessors and sensors. These technologies and tools

will have the potential for allowing additional measurements to be

taken at the control valve, thus enabling more precise prediction

of pending performance problems and the detection of additionalvalve malfunctions, such as seat leakage.

Furthermore, wireless and cloud computing could allow

information to move seamlessly to specialized outside experts,

allowing users to tap into their knowledge and, therefore, fueling

the creation of an encyclopedia of valve symptoms, root causes

and cures.

If control valves have not yet affected a plant’s performance

and budget, it is likely only a matter of time before they do so.

Today’s diagnostics technologies can help operations personnel

prepare, help them optimize their processes, and potentially help

them trim maintenance costs. FC

Sandro Esposito is global marketing manager at GE Energy for

digital and SMART products in the company’s Masoneilan product

line. A 17-year veteran of the control valve and process automa-

tion industries, Mr. Esposito has extensive experience with control

valve diagnostics and system integration and has been granted

several patents related to digital valve positioners. He graduated

from Ahuntsic College in Montreal with a degree in instrumenta-

tion and process controls. Mr. Esposito can be reached at sandro.

[email protected] or 281 671-1683.

www.ge-energy.com

www.FlowControlNetwork.com August 2011

Figure 4. The NAMUR NE 107 standard categorizes various possible asset conditions and

their severities and uses a set of color-coded symbols to communicate these statuses. The

same symbols are used for devices made by various manufacturers, making them easily

recognized and interpreted – much like the “Check Engine” light on a car’s dashboard.

evolution of valve diagnostics

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