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  1. moneo: IIoT platform
  2. Use cases

Control cabinet monitoring with moneo RTM

Condition monitoring of electrical components

In a control cabinet, electrical and electronic components are protected from dust and water as well as electromagnetic and mechanical influences that can lead to damage or failure. Waste heat produced by the components and site-related temperature fluctuations can cause overheating and increased humidity due to condensation. In order to be able to restore the ideal conditions quickly, the control cabinet is monitored.

At ifm, different types of control cabinets are used. The present case refers to two types – a control cabinet with active cooling installed indoors and a control cabinet installed outdoors (the latter contains the evaluation electronics for an employee reward system, which is installed in a bicycle shed and records the number of bicycle trips the employees take to work).

The initial situation:

In the first case, failures of the cooling aggregate were only discovered by chance or whenever a component failed and caused the system to stop.

In the second case, the components in the control cabinet are only approved for a limited temperature and humidity range. Thus, safe operation can only be guaranteed by monitoring these parameters. Temperature or relative humidity values exceeding the limits can cause damage to the system.

Aim of the project:

A central technical monitoring solution is to be implemented to ensure trouble-free operation of the components in the control cabinets. A defined group of email recipients is to be notified automatically when the temperature exceeds or falls below the set limit. In addition, the difference between the inside and outside temperature is to be determined in a comparative measurement. Since an outside temperature change also causes the inside temperature to change, which does not represent a malfunction within the set thresholds, the comparative measurement can prevent false alarms.

The aim is to avoid unplanned downtime, exploit energy saving potentials through optimised cooling, and save resources.

 

Implementation:

Due to the existing IT infrastructure, moneo was installed on a central server of ifm prover gmbh to activate the moneo RTM module.

For control cabinet monitoring, LDH292 type IO-Link multisensors from ifm (temperature + relative humidity) were installed inside and outside (for measuring the outside temperature). This makes it possible to take ambient temperature effects into account. Both sensors are connected via an IoT IO-Link master (e.g. AL1350 or AL1950). The data is retrieved by the central moneo RTM module via the IoT port of the master every second.

In addition to the temperature, the LDH292 sensor outputs the relative humidity in % as a process value, which is also monitored.
The thresholds for this application are defined according to the data sheets of the devices installed in the control cabinet. For the alarm threshold, the device with the lowest ambient temperature is taken as a basis:

  1. Control cabinet with active cooling

Temperature: 10...+50 °C
Relative air humidity: 20…60 %

  1. Outdoor control cabinet

Temperature: -10...+50 °C
Relative air humidity: 20…60 %

The result:

The correct operating environment is guaranteed and provides improved machine uptime. The components are now protected and benefit from an extended service life. Energy savings are achieved thanks to optimised cooling and heating.

Bottom line:

Continuous monitoring has helped to achieve the set targets as well as greater transparency. System information can now be viewed in detail on the dashboard. Data recording enables advanced analyses and further optimisations.

With the help of the collected data, further savings and improvements can gradually be achieved.

System structure

  1. Temperature and air humidity sensor inside the control cabinet (LDH292)
  2. Temperature and air humidity sensor outside the control cabinet (LDH292)
  3. IO-Link master (e.g. AL1350)

Dashboard

Relevant sensor information can be visualised quickly and individually via the dashboard function. Preconfigured instruments, such as a thermometer or line diagram, help to visualise current process values. Graphics in standard formats (PNG, JPEG, GIF...) can be uploaded directly to the dashboard and important parts can be labelled. Users can easily navigate between different dashboards using the navigation markers.

Indoor control cabinet:

  1. Current outside temperature in °C
  2. Calculated temperature difference in °C
  3. Current temperature inside the control cabinet in °C

Control cabinet in ifm prover’s BikeHouse

  1. Current outside temperature in °C
  2. Current status of the BikeHouse
  3. Text label
  4. Navigation object linking to other dashboards

Analysis

With this function, historical data can be analysed. For example, in both use cases, it can be evaluated how great the influence of the outside/ambient temperature is on the temperature inside the control cabinet.

  1. Temperature inside the control cabinet
  2. Outside temperature

This analysis shows the temperature curve over several days. It can be seen that the inside temperature very much depends on the outside temperature.

Settings and rules/ thresholds

This function in moneo RTM allows users to define an individual threshold for each process value. In the present use cases, a permissible range is defined for the process value. If the temperature or humidity falls below or exceeds the set thresholds, an alarm is triggered.

  1. Thresholds for humidity monitoring
  2. Thresholds for temperature monitoring

Manage ticket processing rules

If a process value is exceeded or not reached, a ticket is generated automatically. The ticket processing rules help to define further processes, e.g. the group of recipients that will receive a new ticket if another alarm is triggered. In our two use cases, the responsible people in the production or building services department are informed by email that a threshold violation has occurred.

Calculated values

Using the calculated values function, process values can be further processed and used for calculations. In both use cases, the function is used to calculate the temperature difference between the ambient temperature and the temperature inside the control cabinet.

Temperature difference [∆T]= ambient temperature [T2] - temperature inside control cabinet [T1]

  1. Ambient temperature [T2]
  2. Temperature inside control cabinet [T1]
  3. Function block: subtraction
  4. Temperature difference [∆T]