| Summary: | The paper outlines research issues relating to 2- and 3-valued logic diagnoses developed
with the diagnostic system (DIA G 2) for the equipment installed at a low-capacity solar power station.
The presentation is facilitated with an overview and technical description of the functional and
diagnostic model of the low-power solar power station. A model of the low-power solar power station
(the tested facility, a.k.a. the test object) was developed, from which a set of basic elements and a set
of diagnostic outputs were determined and developed by the number of functional elements j of j.
The work also provides a short description of the smart diagnostic system (DIA G 2) used for the tests
shown herein. (DIA G 2) is a proprietary work. The diagnostic program of (DIA G 2) operates by comparing
a set of actual diagnostic output vectors to their master vectors. The output of the comparison
are elementary divergence metrics of the diagnostic output vectors determined by a neural network.
The elementary divergence metrics include differential distance metrics which serve as the inputs
for (DIA G 2) to deduct the state (condition) of the basic elements of the tested facility.
Keywords: technical diagnostics, diagnostic inference, multiple-valued logic, artificial intelligence.
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