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Monitoring and diagnosis

Monitoring and diagnosis

Monitoring and diagnosis

Important components of piston compressors are subject to wear which cannot be avoided and which could lead to a shutdown of the compressor with subsequent loss of production entailing high costs as a consequence.

The manufacturer has therefore to design those components which undergo the highest wear  – such as compressor valves, piston rings and pressure packings- in such a way, that service free maintenance intervals of one to three years ( 8000 to 25000 running hours ) can be achieved.

The user has to continuously monitor the proper functioning of the compressor in order to avoid break downs and personal damage. Knowledge about the present  state of wear and its trend make it possible to plan the necessary service and shut down times of the plant in advance.

The control system of the compressor installation has to include a monitoring system which checks the interstage pressures and temperatures ( also perhaps the power input and mechanical vibrations ) and compares them within given limits. It can then, if necessary, shut down the plant.

Important compressor stations with  a high danger potential are more often fitted with an  extensive control and monitoring system. Examples follow to demonstrate the logical and technical structure of such systems.

The system works in three areas: In the explosion proof   field area sensors are fitted, which convert pressures, temperature and vibrations into electric signals. These are then converted into digital information. Via a data bus these informations are then passed on to the non explosion proof control area to the Compressor Interface Unit. The control  and monitoring system then visualises  the results of measurement and analysis and gives warnings. Via internet links clients can also visualise the results in a third remote area which can again be used  for systems configuration.

The most difficult task for the direct control system is the early warning system. A safe diagnosis of specific malfunctions is possible, if these cause characteristic changes in measurement data which can be directly related to the malfunction.

For example the wear of rider rings on horizontal cylinders can be measured by the displacement of the piston in relation to a sensor in the cylinder [Spiegel and others].

Unfortunately there do not exist enough reliable and economically useable sensors for the direct measurement of  wear and stress of moving components.

Therefore a diagnosis system is necessary, which analyses the information already obtained on interstage pressures and temperatures and a minimum of additional data (for example valve chamber temperatures, cylinder pressures , run out of the piston rod ) . From these data it then  deducts an information on the  wear condition of the compressor.

In order to solve this problem the blurred classification (fussy logic) can be used [20]. From the total of measurement data a characteristic vector is established, which is then compared with the characteristic vectors of various  stages of damage (wear conditions). For the practical use of this method the determining of characteristic vectors of all classes of damage has to be possible (learning phase).

In most cases only experts ( often via tele- monitoring at the manufacturer ) are capable of giving information on the condition of the machine, based on the changes of measurement data over time  (this includes  data on mechanical vibrations and p,V- diagrams ).  An automatic diagnosis of a fault condition is only possible  if there is a repetition of  the failure pattern [Hastings, Schrijver] .

A general solution to the diagnosis problem  presupposes the theoretical simulation of the behaviour pattern of compressor installations of any design, which can also model the effects of wear. A toolbox [Huschenbett] for the modular simulation of the gas carrying parts of compressor  installations makes a reproduction which is close to reality of the  time depending thermodynamic processes in multistage compressors possible.