Abstract
Contemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous analysis of effects and interactions between many output variables. They can also be used as a tool in preparing experimental material for other advanced diagnostic tools, such as the models making use of neural networks which, when properly prepared, enable also analysing measurement results recorded during dynamic processes.
The article presents advantages of the use of the abovementioned analytical tools and a sample application of the neural model developed based on the results of examination carried out on the engine research rig.