Monitoring Water Hammer
Monitoring differential pressure is one of the most critical functions in any heat or plumbing network.
DP is required to make water flow, but too much will damage equipment.
One of the major problems with current BMS systems is their speed - they are far too slow to spot spikes in pressure. BMS systems typically report values every 15 minutes, so trying to understand an event that may last only 0.5s is impossible. The top image on the right is from a typical BMS system, where the frequency of data logging is far too slow to catch hammer events. From this data everything looks fine, with DP controlled to targets. But the important problems are hidden - on this site something is forcing valves to let by.
On the same site we then fitted our open source controls, with resolution down to 1s, and we saw this. A 10 bar spike in DP - far in excess of equipment ratings. The actual peak is unknown as it is beyond the sensor range 0-10 bar.
In close-up the spike lasts a fraction of a second, and even at 1s resolution we are lucky to catch it.
Fast Monitoring
In response, the logging was increased to 1/10th of a second. This is too rapid for discrete values to be communicated, so instead we select to store values into a shift register of 50 values (5s) and send this out as a complete CSV file when a spike is detected.
We then waited for another event.
A day later the following email arrived.
At 1/10th of a second readings we see more detail, including the drop-off in pressure following the hammer. This confirms that we are seeing a genuine pressure spike, and also that the system is been exposed to extremely high differential pressures.
A second event, a day later...
This spike lasts for 4/10th of a second, which in terms of hammer is a long time.
With the higher resolution monitoring we are also catching more smaller spikes in DP.
We have identified the reason why valves are letting by. The next step is figuring out the cause of the spike.
Very Fast Monitoring
To understand the limits of this particular method of reading values from the DP sensor we then removed fixed times, and instead read values continuously. This provides readings every 30ms, which is just over 3 times faster still.
The results from the next hammer event are seen below. The x-axis is marked in milliseconds from the first high reading.
We achieve some 13 readings in a row (292 milliseconds) where DP is beyond the range of the sensor.
Looking at the general readings, we also see something slightly odd, not coinciding with hammer, but of interest. After 9pm we can see regular
The events appear similar, with a drop in DP followed 8 seconds later by a spike.
It is clear from this exercise that by implementing rapid DP monitoring we are able to see things that are otherwise invisible. With such clarity on DP we are able to investigate problems, and see the results of any actions taken.
Software
The flow below runs on a standard Heatweb open controller, and monitors differential pressures at 0.1s intervals. When pressure out of limits is detected, 50 consecutive readings (5 seconds worth) are emailed to engineers concerned for record and analysis, with the spike positioned in the middle of the data so we can see climb and fall in pressure.
When performing such fine detailed analysis it is important to manage data. Nobody wants 10 readings a second, every second, when things are fine - it simply overloads databases. Using the open controls software it is straightforward to attach conditions when and where to send what data. In this example we send data every minute, if it changes by more than 0.03 bar, or if pressure spikes over 3 bar you get the 5 second rapid data in an email.
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