S. Ortmann et M. Glesner, DEVELOPMENT AND IMPLEMENTATION OF A NEURAL KNOCK DETECTOR USING CONSTRUCTIVE LEARNING-METHODS, International journal of uncertainty, fuzziness and knowledge-based systems, 6(2), 1998, pp. 127-137
The world-wide demands for reasonable fuel consumption and reduced eng
ine emissions force engine developers to improve the combustion proces
s. Automobile makers are expecting to meet these demands by increasing
the engine compression ratio. However, this improvement leads back to
the problem of engine knock and appropriate engine control. Thus, the
ability to detect engine knock with high precision will be mandatory
for car makers. We propose a detection scheme that consists of two mai
n blocks: multifeature extraction and neural classification. This pape
r gives a short overview of the concept and presents a developed const
ructive learning algorithm for the cycle-by-cycle detection task.