Hydrocarbon Processing - February 2021 - 27

Special Focus

Digital Transformation
M. HASTINGS, Brüel & Kjær Vibro A/S, Nærum, Denmark

Data historian-based machine condition monitoring
Machine condition monitoring has
been playing an increasingly important
role in industrial asset healthcare for many
years. More machines are being monitored-not just the critical ones-and
more comprehensive and in-depth monitoring techniques are employed. Although
vibration analysis theory, the primary
basis of condition monitoring, has not
changed much in the last 50 yr, monitoring techniques have evolved considerably.
This is partly due to experience, monitoring system technology and data science.
Industrial Internet of Things (IIoT) technologies and strategies have been changing the information landscape drastically
in many industries, but has it also affected
machine condition monitoring?
Machine condition monitoring systems and their limitations. Condition

monitoring systems (CMSs) offer various
levels of insight into machine healthcare
but all have a common purpose: to reduce
both downtime and lifecycle costs of running and maintaining plant machinery.
This is done by detecting and diagnosing machine potential failure modes at
an early enough stage of development so
focused maintenance can be cost-effectively scheduled ahead of time without
interrupting the machine's production
capacity. The CMS does not perform process control or other enterprise functions,
so it is more or less a stand-alone system
consisting of its own sensors, signal conditioning unit, CM server and database.
Many of the systems are still based on
proprietary servers with restricted license
access, so in many cases, the user becomes
completely dependent on the CMS provider and their expertise. If the CMS
specialists are unavailable for an urgent
machine diagnostic issue, the option of
using a remote third-party analyst can be
challenging simply due to restricted CMS
access. Even if the CMS data was available

for third-party analysis, measurement configuration information regarding signal filtering and processing would be most likely
unknown, thus complicating the task of
doing a reliable diagnosis.
The disadvantages of a proprietary
CMS are not just limited to restricted
data access for analyzing a specific machine fault. It also makes it difficult to
get an overview of the general machine
healthcare awareness of a specific monitored machine or fleet of machines, especially if some of the data is monitored by
other systems. Correlating process data
and monitoring data from other CMSs
to vibration measurements is an important means for improving the reliability of
fault detection and diagnostics for all operating conditions. Although many CMSs
can import process data, this is often done
at the discretion of the CMS supplier at
the time of installation and cannot always
be easily changed when new process information is available.

Lastly, there is the question of security
and economy of scale of installing, running and maintaining a proprietary system installation within the IT infrastructure. As the user interface is different from
one system to the next, CMS training also
must be individualized.
With all the advancements of CMS
technology, is there a solution to resolve
these issues?
Data historian enhances plant and
machine healthcare. Distributed con-

trol systems (DCSs), supervisory control
and data acquisition (SCADA) and programmable logic controllers (PLCs) are
used by industry to control production to a
high level of reliability, safety and efficiency. These systems represent the pinnacle of
information and control technology. Regarding data storage, historically speaking,
a DCS typically stored data for only a week
or so, which was considered to be more
than sufficient from a control perspec-

FIG. 1. An example of a proprietary diagnostic tool offered by a monitoring system supplier.
Hydrocarbon Processing | FEBRUARY 2021 27

Hydrocarbon Processing - February 2021

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