What is Diagnosis?
From a general perspective, including both the medical and technical case, diagnosis can be explained as follows. For a process there are observed variables or behaviors for which there is knowledge of what is expected or normal. The task of diagnosis is to, from the observations and the knowledge, generate a diagnosis, i.e. to decide whether there is a fault or not and also to identify the fault. Thus the basic problems in the area of diagnosis are how the procedure for generating diagnoses should look like, what variables or behaviors that are relevant to study, and how to derive the knowledge of what is expected or normal.
This text focuses on diagnosis of technical systems and the goal is to find malfunctions in for example sensors and actuators. The observations are mainly signals obtained from the sensors, but can also be observations made by a human. Examples of such human observations is for example level of noise or vibrations. The diagnosis is computed by observing inconsistencies between observed variables and what is considered normal behavior. When the diagnosis is based on an explicit model of the system, the term model based diagnosis is used.
Diagnosis of technical systems can be performed off-line or on-line. When on-line is considered, the diagnosis is usually automated so it is performed without involvement of humans. Most concepts described in this text are equally applicable to off-line and on-line diagnosis.
The Use of Diagnosis
Diagnosis systems have found their way into many applications. In the context of model based diagnosis, some important areas that have been discussed in the literature are:
- Nearly all subsystems of aircrafts, e.g. aircraft control systems, navigation systems, and engines.
- Emission control systems in automotive vehicles
- Nuclear plants
- Chemical plants
- Gas turbines
- Industrial robots
- Electrical motors
For these systems and also for technical processes in general, the main reasons to incorporate diagnosis systems are:
- Safety: In many technical systems a fault may cause serious personal damage. This is especially obvious in safety critical processes such as aircrafts and nuclear plants. For these systems, high reliability and security of the system is fundamental.
- Environment Protection: In for example emission control systems in automotive vehicles, a fault may cause increased emissions. It has been concluded that a major part of the total emissions from cars originates from vehicles with malfunctioning emission control systems. Other important examples are nuclear plants and chemical plants in which a fault may cause serious damage to the environment.
- Machine Protection: A fault can often cause damage to the machine. Therefore it is important that faults are detected as quickly as possible after they have occurred.
- Availability: For many technical systems it is critical that the systems are running continuously. This is for example the case for gas turbines in power plants and industrial robots. The reasons may be economical as well as safety. With the help of a diagnosis system, early warnings can be obtained before serious breakdown. When the fault has been detected, the system can be stopped until repair or rather be switched into a new mode. In the new mode, the performance of the system may be degraded but at least more serious breakdowns can be avoided.
- Repairability: Closely connected to availability is repairability. A good diagnosis system will quickly identify the faulty component that should be replaced. In this way, time-consuming fault localization, is reduced, which will decrease total repair time.
- Flexible Maintenance: Maintenance can be expensive since the machine/process often need to be taken out of operation. Therefore is it desirable to make sure that the machine is not taken out of operation for maintenance when there is no need for maintenance. Also, it is desirable to be able to plan maintenance stops in advance to be able to disturb the production as little as possible. A diagnosis system that detects faults early, desirably before more serious faults occur, can hopefully help both to avoid unnecessary maintenance and to indicate far in advance when a maintenance is needed.
A Short History
Manual diagnosis has been performed as long as there have existed technical systems, but automatic diagnosis started to appear first when computers became available. In the beginning of the 70's, the first research reports on model based diagnosis were published. Some of the earliest areas that were investigated were chemical plants and aerospace applications. The research on model based diagnosis has since then been intensified during both the 80's and the 90's. Today, this is still an expansive research area.
Up to now, numerous methods for doing diagnosis have been published. Unfortunately many approaches are more ad hoc than systematic and it is fair to say that few general theories exist and there is not yet a complete understanding of the relations between different methods. This is reflected in the shortage of books in the area and the fact that no general terminology has yet been agreed upon. However the importance of diagnosis is unquestioned. This can be exemplified by the computerized management systems for automotive engines, used to control the engine. For these systems more than 50% of the software can nowadays be dedicated to diagnosis. The rest is for example for control.