Übersetzung für "Anlagenzustände" in Englisch

The visualization of the physical plant states takes place in accordance with a dynamic visualization method.

The objective was the quality-assured assessment of the plant unit conditions and a benchmark analysis among the single units.

This ensures that undefined installation statuses can be avoided.

Depending on the program selected, various sys-tem statuses are monitored.

Machine or plant statuses are typically monitored by measuring suitable parameters.

It contains test and operations programs and displays all conditions of the system.

There are system conditions that must be avoided under all circumstances.

With Elvis system status may be illustrated and the system status changed.

This provides at all times a fast summary of all relevant data and system states.

Visual display systems are also used for displaying different operating states and the loading processes.

Send critical system states, alarms and log data by e-mail

The central plant visualization displays the production data and / or system status in real-time.

Authorisations can be changed more quickly and system statuses can easily be retrieved.

This may help to adjust the maintenance intervals to the actual status of the system.

It can be used to automatically parameterise sensors, diagnose plant states and transmit measured values without loss.

Thus, for example, critical plant states can be simulated and identified beforehand using the model.

The machine terminal features 15 freely configurable keys for signalling the machine status and a piece number counter.

The variety of different machine states and process conditions often leads to errors during the metering process itself or to the misinterpretation of meter readings.

It is reminded that the Euratom safeguards system recognises the following statuses for an installation, with the corresponding definition:

With this embodiment of the invention, the operating staff is given the capability of simulating operation of the technical plant and, by manipulating the stored measured values MW, of artificially producing especially critical plant states.

In the signal processing circuit 12 one or several memory elements or ROM structural components carry out processes of identification and classification of the states of the installation downstream from the transformers 6, 7 on the basis of suitably selected parameters with a comparison being carried out with the preset or also adaptively tracking parameters, evaluation is made regarding the presence of short-circuits and a command for triggering the circuit breakers is generated.

Intelligent processes from the field of computational intelligence (CI) offer, above all, the possibility of integrating existing expert knowledge (fuzzy logic) and various plant states (state-recording machines) in a new control strategy.

With freely modifiable and combinable measurement parameters you can correctly measure a wide range of plant conditions statistically and always find new ones.

They not only provide important information about the electrical power distribution but also key measured values for assessing the system states and power quality.

As already explained in connection with the above-described embodiments of the method in accordance with the invention, the abovementioned logging of the changeover time affords an improved possibility of monitoring the installation and in this case, e.g., logging, analyzing and evaluating installation states.

For this purpose, a load or product parameter which marks the different installation states (product and/or load states) is included in step a).

As a result, there is a risk of data losses, undefined installation states and damage to workpieces and the installation, because a process or subprocess in progress is abruptly interrupted because of an uncoordinated shutdown.

This invention combines the conventionally rule-based analysis of the plant state with a special statistical data evaluation by means of SOMs, as a result of which a massive data reduction is enabled by the elimination of redundant information.

Besides the early detection of critical plant statuses, such diagnostic methods should also be suitable for carrying out servicing work on the plant only when the status requires this.