Conjecture is a system
identification software solution which allows you to create best-fit
models of your industrial process data (such as from SCADA) using machine
learning techniques, to
better understand, diagnose, and control your industrial systems.
System identification is the method of using mathematical
models to characterise dynamic systems from measured data. Dynamic systems have
measurements of inputs and outputs to the system that change with time.
Conjecture can be used in any
industry which requires automated feedback loop control of processes, including
oil and gas, minerals, and manufacturing.
The Conjecture System
Identification software solution was developed by Robert A.
Anderson, an electrical and process control engineer from Perth, Western
Australia. In 2011, Robert
began exploring the mathematics of system identification in process control. He
realised that the models and methods commonly taught at university for system
identification were difficult to implement in everyday engineering
work. Furthermore, currently available system identification programs did not
accommodate important process dynamics such as delays and output shifts. This
resulted in models that were a poor representation of real-world
industrial systems.
Over several years of independent work, Robert
identified the machine learning techniques that could be used to model
industrial plant dynamics straight from the data, incorporating both delays
and output shifts. He then set about creating a simple software program to
apply these techniques that would be intuitive to fellow engineers, finally
completing the first prototype of Conjecture in 2017.
Simplicity
Most system identification
programs are based on the theoretical models commonly taught in engineering
study, such as z-domains and Laplace transforms, which are difficult to use in
daily engineering
work. In contrast, Conjecture helps the user to
specify a simple model for their data based on time series equations – X’s and
Y’s with time delays and an output shift. It then runs all the calculations
in the background, producing easy-to-understand results that translate directly
to the real-world system.
Goodness of Fit
Conjecture is
the only system identification
program readily available on the market that allows users to model both delay
and output shift in their systems. This produces models that are a much better
reflection of these systems. All these dynamics can
be modelled and understood easily in the Conjecture interface.
By
adding an output shift with the click of a button, Conjecture
modelling allows the user to estimate
the output level corresponding to a zero input. This capability is essential to
producing a useful model, but is not easily accessible from some other system
identification programs.
Furthermore, Conjecture allows
users to estimate the delay in their system. Delay is the time lag between a
change in input and the corresponding change in output. Industrial systems with
delay are difficult to control effectively since traditional control
algorithms cannot compensate for this time lag. By estimating delay, Conjecture gives
engineers the information they need for smoother, more stable control.
Conjecture
has
a graphing function that allows users to view their input data, output data,
and model on the same plot, to easily assess how well the fitted model reflects
their real-world data. This assessment is crucial to choosing
a useful model.
Through intuitive best-fit modelling of your plant data,
Conjecture can benefit your plant operations through
improvements in:
Diagnosis
By modelling your plant’s
typical
operation using Conjecture, you can more easily
identify periods of atypical operation where the data produced by your plant
deviates from the model. Problems such as valve passing or blocked pipes
could be spotted early on, before they cause significant interruption to your
operation.
Understanding
A Conjecture
model provides greater understanding of the
dynamics of your plant. You can use this information to train operators and
engineers, and even to experiment with the operation of your plant in the
digital world – where experimentation is safer and cheaper.
Control
Most
process engineers would say that their biggest challenge in controlling an
industrial system is accounting for time delay. Model-fitting with Conjecture
allows you to quantify the delay in your
system, giving you the tools to control your system more stably. The Conjecture
user training videos include a demonstration on how to do
this.
No – with just a few quick training videos, users can adeptly
load and model their data in Conjecture. The
simplicity of Conjecture is what sets it apart from
other system
identification software.
No. Conjecture uses different mathematical techniques compared
to traditional system identification programs – techniques that are easier to
grasp and more intuitive than the z-domains and Laplace transforms usually
taught
in engineering study. Also, most of this mathematics runs in the background,
behind our simple, easy-to-use interface. Most users can adeptly load and model
their data in Conjecture after a short
training session.
Conjecture has been designed to work
on systems with a single output and one or more inputs. You can try modelling you data using
our online portal. Feel free to contact us if you
have further questions about whether Conjecture will
work for your system.
We have just released our online version of Conjecture here. This will soon have facilities enabling you to log-in and subscribe. If you have any questions or need any assistance using the portal, please contact us.
At present, the Conjecture System
Identification solution stands alone as the flagship product of
Conjecture Data Solutions. It is the result of years of development and
represents an approach to data
that we believe is the future of the engineering industry. Hence, we are
focusing our efforts on establishing Conjecture as
the process control analysis software of choice in Western Australian
engineering. In the coming years, we will be looking to develop other software
products in response to the needs of the engineering community.