March 2009

Special Report: Instruments and Networks

Soft sensor modeling using artificial neural networks

Here are guidelines for proper construction

Nandakumar, V., Mangalore Refinery & Petrochemicals Ltd.

With increased competition and rising feedstock cost, pressures are increasing for refinery managers to extract maximum value out of processes. In operations, the online quality monitoring is an important part of process control. Typically, analyzers are provided for this application. However, as parameters increase in complexity from density, moisture content, octane number, sulfur content, etc., the cost and maintenance efforts on analyzers increase exponentially. Moreover, the inherent rigidity in hardwired analyzers makes their extended usage difficult, if not impossible, so soft sensors play a vital role. Soft sensors have the advantages of easy maintainability, low cost and extensibi

Log in to view this article.

Not Yet A Subscriber? Here are Your Options.

1) Start a FREE TRIAL SUBSCRIPTION and gain access to all articles in the current issue of Hydrocarbon Processing magazine.

2) SUBSCRIBE to Hydrocarbon Processing magazine in print or digital format and gain ACCESS to the current issue as well as to 3 articles from the HP archives per month. $409 for an annual subscription*.

3) Start a FULL ACCESS PLAN SUBSCRIPTION and regain ACCESS to this article, the current issue, all past issues in the HP Archive, the HP Process Handbooks, HP Market Data, and more. $1,995 for an annual subscription.  For information about group rates or multi-year terms, contact email Peter Ramsay or call +44 20 3409 2240*.

*Access will be granted the next business day.

Related Articles

From the Archive



{{ error }}
{{ comment.comment.Name }} • {{ comment.timeAgo }}
{{ comment.comment.Text }}