Man, Technology and Organisation



PEANO is a signal validation toolbox developed at Halden in the years 1995-98. It is based on neuro-fuzzy techniques and is able to track in real-time the expected behaviour of a complex process both in steady state and transient conditions. PEANO implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process has to be performed. The possibilistic approach (rather than probabilistic) allows a "don't know" classification that results in a fast detection of unforeseen plant conditions or outliers.

Hoffmann, Mario

Department Head


The operation of each industrial plant is based on the readings of a set of sensors. Their reliable operation is essential as the output of sensors provides the only objective information of the process. The task of the signal validation is to confirm whether the sensors are functioning properly. Faulted or miscalibrated instrumentation channels lead to the following problems:

  • Erroneous identification and diagnosis of abnormal events, which results in possible human errors by the operators in the control room
  • When these sensors are connected to control and automation systems, the process could become uncontrollable and unstable, resulting in emergency shutdown of the entire process.
  • Sensors out of calibrations can reduce the plant performance and efficiency.

It must be pointed out that these three points might have safety implications in some cases, but they have always negative economical consequences, due to forced shutdowns in the first two scenarios and to efficiency losses in the third.
Signal validation must be robust to handle multiple sensor faults as well. This requirement is important especially in case of common cause failures in instrumentation channels (for example, common sensing lines in pressure transmitters), which would result in a completely wrong understanding about the plant state