Diagnose sensor faults based on mathematical models? When there is a problem, the first time is to diagnose it, to see what is wrong, so that it is easy to deal with, from different angles, we use more than one method when diagnosing the problem, if this is classified, it can be divided into two kinds, one is based on the method of analyzing the mathematical model, and the other is the method that does not rely on the mathematical model. Today let's talk about one of them, according to the method of analyzing mathematical models. Let's get to know each other together.
According to the different ways in which the residuals occur, the methods according to the analytical mathematical model can be further divided into: parameter estimation method, condition estimation method and equivalent space method.
The diagnosis method according to the model is the earliest diagnosis method developed and the most widely used diagnosis method.
The advantage is that the model mechanism is clear, the structure is simple, easy to complete, easy to analyze, and can be diagnosed in real time. It has an important position in the field of problem diagnosis, and will still be the primary research direction of sensor problem diagnosis methods in the future development.
The disadvantages are that the amount of accounting is large, the system is messy, there are modeling errors, and the adaptability of the model is poor. Poor reliability, easy to present false alarms, false negatives and other phenomena, robustness of external disturbances, and insensitivity to noise and interference of the system.
At present, the research results of this diagnosis method are still mainly focused on linear systems, which is of great significance for in-depth study of the general problem diagnosis technology of nonlinear systems, and the robustness problem also has high research value.
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