Analysis of Airflow Instabilities in HVAC units

HVAC (Heat Ventilation Air Conditioning) units are devices used in various applications, such as cars, buildings, aircraft etc. They facilitate the transport and conditioning (heating, cooling, changing of humidity) of gaseous masses. Ideally, this conditioning should be performed without creation of sound or noise. However, solving airflow instabilities in HVAC is not trivial since engineering topics like fluid dynamics, acoustics, structural and rotational dynamics are involved.

The Test Setup

The data analysis example covered in this note shows how Prosig’s DATS software is used to measure signals, process data in a logical way, solve the practical issues and obtain working solutions.

Here the focus is on the joint analysis of signals from acoustics, pressure sensing and rotational quantities. For the latter, a tachometer signal, consisting of individual pulses from the ten blades of a blower inside the HVAC unit is used. It is picked up by a laser tachometer.

Therefore a counter/timer based channel is acquired.  At the same time a set of analog data acquisition channels is captured. This measures acoustic pressure information from microphones (sound pressure level, SPL) and wall pressure level sensors (WPL) mounted at various locations in the duct of the HVAC unit.

Initial Results

SPL spectrogram of airflow Instabilities in HVAC
Figure 1: Color coded amplitude-time-frequency spectrogram of SPL signal acquired during blower run-up

Figure 1 shows the SPL spectrogram in the usual fashion. The horizontal axis shows the frequency information. The vertical axis shows the elapsed time for a blower run-up. The resulting analysis data shows sound pressure amplitude as color coded information from a so called hopping FFT (Fast Fourier Transformation).

Initial observation could lead to the impression that plain vanilla order contributions can be spotted.

The Order Domain

However, a more in-depth analysis shows more. By converting data (from time domain) to synchronous domain using the DATS analysis tools non-integer shaft order contributions are revealed (Figure 2). Specifically, a strong order contribution, just below order 1.9, and broader contributions around order 2.7 and 3.6.

SPL run-up (Order domain)
Figure 2: Color coded amplitude-elapsed blower revs-order spectrogram of SPL signal acquired during blower run-up (Order domain)

With the DATS range of analysis tools it is straight forward to carry analysis into the angular (or order) domain. The phenomena may be looked at in another very powerful visualization. That is, segmented in order domain, by setting up a revolution spectrogram. This shows data as consecutive 360° rotational angle slices for the run-up.

Any attempt to perform such a visualization with time domain data alone would be futile within reasonable amount of time devoted for data analysis!

Visualising the problem

DATS provides the ability to visualise the the physical phenomenon right away. By performing appropriate band pass filtering of synchronous domain data (centered around order 1.8) and using the previously mentioned visualization sound pressure level (SPL) and wall pressure level (WPL) data are shown in Figures 3 and 4. Observe the level differences of SPL vs WPL.

Strong pressure surges propagating along the fluid path of the HVAC unit can be spotted. This is a phenomenon originating from a non-uniform movement of gaseous fluid masses by the rotating blower.

The data representation with stacked up consecutive revolutions clearly reveals that about less than two (about order 1.8) cells are forming during one blower revolution and propagation through the scroll of the blower takes place during about ten blower revolutions (this is known as “rotating stall”).

Color coded amplitude-blower angular domain
Figure 3: Color coded amplitude-blower angular domain representation SPL signal acquired during blower run-up
Airflow Instabilities in HVAC using color coded amplitude-blower angular domain representation WPL (wall pressure level)
Figure 4: Color coded amplitude-blower angular domain representation WPL (wall pressure level) signal acquired during blower run-up


DATS data analysis software is a powerful toolbox for its many diagnostic algorithms alone. In addition, the worksheet style of handling and processing data, and the possibility to concatenate analysis steps gives a professional engineer possibilities that many other programs are lacking.

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Prosig are experts in the measurement and monitoring of noise and vibration. They provide data capture and analysis systems for a wide range of applications with particular focus on noise & vibration, NVH and acoustics for the automotive, aerospace and power generation Industries. The company designs and develops its own products and its engineers have decades of experience in solving real-world noise and vibration problems for major organizations throughout the world.
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Philip Andersson
Philip Andersson
6 months ago

Did you also try to analyse the number of rotating stal cells and their change in duration and pressure gradient with regards to fan operational speed to be able to draw conclusions regarding fan operational performance?

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