Page 34 - The Mechatronics Handbook

FIGURE 2.6 Scheme for a model-based fault detection.
Supervision and Fault Detection

With an increasing number of automatic functions (autonomy), including electronic components, sen-
sors and actuators, increasing complexity, and increasing demands on reliability and safety, an integrated
supervision with fault diagnosis becomes more and more important. This is a significant natural feature
of an intelligent mechatronic system. Figure 2.6 shows a process influenced by faults. These faults indicate
unpermitted deviations from normal states and can be generated either externally or internally. External
faults can be caused by the power supply, contamination, or collision, internal faults by wear, missing
lubrication, or actuator or sensor faults. The classical way for fault detection is the limit value checking
of some few measurable variables. However, incipient and intermittant faults can not usually be detected,
and an in-depth fault diagnosis is not possible by this simple approach. Model-based fault detection and
diagnosis methods were developed in recent years, allowing for early detection of small faults with normally
measured signals, also in closed loops [21]. Based on measured input signals, U(t), and output signals,
Y(t), and process models, features are generated by parameter estimation, state and output observers,
and parity equations, as seen in Fig. 2.6.
These residuals are then compared with the residuals for normal behavior and with change detection
methods analytical symptoms are obtained. Then, a fault diagnosis is performed via methods of classi-
fication or reasoning. For further details see [22,23].
A considerable advantage is if the same process model can be used for both the (adaptive) controller
design and the fault detection. In general, continuous time models are preferred if fault detection is based
on parameter estimation or parity equations. For fault detection with state estimation or parity equations,
discrete-time models can be used.
Advanced supervision and fault diagnosis is a basis for improving reliability and safety, state dependent
maintenance, triggering of redundancies, and reconfiguration.

Intelligent Systems (Basic Tasks)
The information processing within mechatronic systems may range between simple control functions
and intelligent control. Various definitions of intelligent control systems do exist, see [24–30]. An intel-
ligent control system may be organized as an online expert system, according to Fig. 2.5, and comprises
• multi-control functions (executive functions),
• a knowledge base,
• inference mechanisms, and
• communication interfaces.

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