AFOM - Automatic failure and optimisation analysis by data-acquisition

In the project, methods will be developed for analysing measured value curves to detect changes in operation or failures in the system. By integrating BIM data of buildings, corresponding models will be generated to validate the heating, ventilation, and air conditioning (HVAC)-networks, which will be used for analysis.

Short Description

Status

ongoing

Starting point / motivation

Due to the progress of digitalization, the recording of measurements has become easy. In buildings, many measured values can be recorded, which provide information about the correct functioning of the technical building systems. Because of the large number of measurement channels, manual evaluation is complex and needs a high degree of expert knowledge. The possibility of data logging and the automated report generation requires further development of automated evaluation.

Contents and goals

In current systems, the evaluation of faults (FDD – Fault Detection and Diagnosis) is based on rules. By using catalogues of rules, the measured trend data are examined for faults. Based on these rules, errors and possible causes are reported to the user. Many errors and changes in the operation of systems cannot be detected by simple rules. The simplest rules are the checking of maximum and minimum values. This check is normally always done.

The aim of the project is to differentiate between dependencies of external and internal effects by analysing measured trend data using statistical methods. With these evaluations, a report for the user can be generated automatically. In order to be able to recognize dependencies, methods will be developed to describe the HVAC networks mathematically and to be able to represent the behaviour and the installations. By linking the model with the data from the building management system, the system can be checked online for operating faults.

Methods

To generate the networks, existing data from BIM (Building Information Modelling) is used or, if such methods are not available, a model is developed to describe the HVAC-networks in BIM.
In combination with statistical methods, correlations and anomalies in the regulation and control will be evaluated. Further parameters for the description of Grey-Box models can be identified through the analysis.

Based on investigations at the Living-Lab Energetikum in Pinkafeld and possible demonstration objects from the project partners, the methods will be elaborated and developed. In a final evaluation phase, the developed methods will be field-tested on a demonstration building.

Demonstration building — Living Lab Energetikum (Source: Klanatsky P., Plank H., Heschl Ch. (2019). Die "smarte" Fassade zur Optimierung des Energiebedarfs und thermischen Komforts. Internationale Konferenz, e.nova, Pinkafeld)

Expected results

Automated generation of recommendations for early detection of event-related maintenance to reduce system failures
Verification of usability of the BIM interface to extract the structure of HVAC networks from the BIM model
Methodology for mathematical modelling of interrelated influences in ventilation and hydraulic networks
Methodology for identifying processes using statistical methods of signal processing for the detection of regularities and deviations from normality
Development of data-driven models of the pipe network and the building for monitoring building and facilities
Development of an algorithm for in-situ measurement of building tightness using data of the ventilation system

Project Partners

Project management

Forschung Burgenland GmbH

Project or cooperation partners

Fachhochschule Salzburg GmbH
ZET & BZR GmbH
TBH GmbH
Technische Universität Wien

Contact Address

Forschung Burgenland GmbH
DI Johannes Schnitzer
Campus 1
A-7000 Eisenstadt
Tel: +43 (5) 7705-5438
E-mail: johannes.schnitzer@forschung-burgenland.at
Web: www.forschung-burgenland.at