GB2608854A

GB2608854A - Acoustic heating system monitoring

Info

Publication number: GB2608854A
Application number: GB2110167.0A
Authority: GB
Inventors: Gerard Bailey Samuel; Andrew Steadman Mark
Original assignee: Skyrad Consulting Ltd
Current assignee: Skyrad Consulting Ltd
Priority date: 2021-07-15
Filing date: 2021-07-15
Publication date: 2023-01-18
Also published as: GB202110167D0

Abstract

A method for detecting a fluid leak in a heat transfer system, the method comprising monitoring acoustic emission from said system, identify signals associated with bubbles in the fluid and using the rate of emission of the signals determine if pressure within the system is within an acceptable range. The signals associated with the bubbles may be between 1 and 4 KHz for a duration between 5 and 50 milliseconds. A system or device based on the method where the expected signals are based on previous observations or predetermined information based on the type of heat source. The comparison of signals may be performed using statistical, neural network or other classifiers. The signals may be relayed to a server for the analysis or combined with other information such has temperature, flow rate, pressure, previous faults. Said signal may be used to determine energy consumption or suitable service intervals for a boil of the heat system.

Description

This invention relates to monitoring methods, systems and devices for apparatus comprising a fluid circulation system.

Knowledge of the state and condition of a mechanical system, for example a boiler for a heating system is advantageous for many reasons. Faults can be predicted or diagnosed more easily, technicians can be prepared in advance for a particular repair and have the right equipment to repair a known fault, diagnostic time can be reduced and downtime can be reduced.

In heating systems, a closed fluid circuit transfers heat between a heat source such as a boiler and a heat sink such as a radiator, but could include any other heating system for example underfloor heating, fan heaters etc. Of particular advantage is knowledge of the pressure of the fluid in such fluid circuits. Leaks in the fluid circuit can cause the pressure to drop, resulting in damage where the fluid escapes e.g. a leak in a radiator in a house, and a reduced ability to transfer heat effectively, causing a risk of dangerous overheating or explosion in a boiler that is not being cooled by sufficient water flow. To protect against this risk, most boilers will have a shut off system that cuts off the heat if the pressure drops below a certain threshold. This is a beneficial safety system. However it causes a loss of system functionality, and it is one of the most common causes of central heating system failure. Knowledge of whether a pressure loss has occurred is useful for a user who could top up the system to restore pressure or a service technician who would know to check for leaks.

Whilst some boilers communicate a pressure loss (often via a 'fault code'), being able to remotely detect and diagnose a pressure loss either prior to or at the point of shut-off would aid the customer, as they could repressurise the system before the boiler shut-off, and would also benefit a service technician as they could potentially help the customer to repressurise the system themselves, without incurring the cost of a boiler repair.

Measuring the pressure in the system can be readily achieved by a pressure sensor known in the field. However pressure sensors need to be plumbed in to the fluid circuit, requiring a service visit where a fluid system is drained down, the sensor fitted, and the system repressurised. Being able to measure the pressure non-invasively would therefore be more flexible and less costly, as a user could fit the sensor themselves if it is fitted to the outside of the circuit, and could place the sensor where convenient on the circuit or move it as necessary.

The invention here presents a method for detecting a pressure loss in a fluid circuit non-invasively using acoustic means.

In order to provide information to a service technician, a user, or a provider of for example boiler maintenance cover, it is useful to have knowledge of any system faults in the case that the boiler does not display fault codes, or the fault codes are unknown or it is inconvenient or difficult for a user to find a fault code (they may have to remove the cover on the boiler to see the display).

Connecting a vibration sensor or microphone of a type known in the field, for example a contact microphone, normal acoustic microphone, vibration sensor or accelerometer at a point where it can detect vibrations in the system can enable the monitoring of the heating systems operation. The sensor may be a microphone which is positioned where it can hear the boiler or heating system, or if it is a contact type sensor, placed in contact with a part of the system that the vibrations from the system operation from where the vibrations are detectable. This may be the boiler itself, or it may be any other part of the system e.g. pipes, pump, valves or any part of the structure on which they are in acoustic contact with.

The data from the sensor can then be used to analyse the pressurisation state of the system as follows.

When the pump runs, the system draws water around the circuit. Under normal operating pressures (typically 1 bar gauge or higher for a domestic heating system) the water stays in a liquid state, and the pump vibrations are detectable as a series of oscillations at the fundamental rotational frequency and its harmonics.

When the pressure is lower than the normal operating pressure -say 0.8 bar gauge or lower, bubbles start to be formed in the water as cavitation typically starts to occur around the pump blades and other sharp edges in the fluid circuit e.g. pipe bends.

The formation and subsequent popping of these bubbles creates a distinctive bubbling sound, which can be detected and measured by a suitable microphone or vibration sensor and a processing means.

Fig 1 shows an example of the spectrogram of the acoustic measurement made on a boiler with a reduced pressure of 0.8 bar. This shows the variation in the frequency components as a normalized amplitude on the vertical axis, in numbered frequency bands ranging from 1 to 4KHz, as a function of time in seconds (in the horizontal axis). A series of aligned peaks 1. show an intermittent wide band ping noise event, characteristic of a bubble in the system. The louder and more frequent the ping sounds, the larger and more numerous the bubbles in the system.

By applying a threshold to the amplitude and frequency content of these ping events, they can be counted and the rate or number of events per unit time measured.

For example a ping noise event might comprise a signal showing an increase in amplitude of 4 or more standard deviations over the background noise level, covering a frequency range of 1KHz or more, and between 1 and 4KHz, for a duration less than 50 milliseconds. While a single signal of this nature might result from a cause other than bubbles in the system, repeated signals are strongly indicative of bubbles in the system.

Fig 2. Shows the results of an empirical test where the pressure in a heating system was deliberately reduced from a 'normal' condition of 1.1 bar to a low-pressure condition of 0.8 bar. At 1.1 bar, 0.95 bar, 0.85 bar and 0.8 bar the rate of ping noise events was measured.

The rate of ping events increases noticeably between 1.1 bar and 0.8 bar. This means that an acoustic measure of ping noise events associated with bubble events can be used as an estimate of the state of pressure in the heating system, a low rate of bubble events indicating a healthy of normal pressure, and a high rate of bubble events indicating a low pressure. In practice the actual rate of pings detected will depend upon the filtering technique used to detect the pings and the threshold set. In this example a normal pressure might be < 2 events per second, and a low-pressure threshold might be > 5 events per second. However this number could very from being zero to a very high rate of up to 1000 per second, depending on the measurement used.

The relationship may not always be linear-as the pressure drops further lower numbers of high amplitude pings can be detected as the smaller numbers of larger bubbles are formed. The absolute pressures at which the bubbles are detected may also vary depending on the system being monitored, variations in flow speeds and also gravity head differences over the height of the system.

This in turn can be used as proxy estimate for the pressure in the system.

Whilst an accurate measure of pressure may not be possible, a rough estimate to within 0.1 -0.2 bar accuracy is achievable. This is sufficient, particularly if averaged over time, to detect trends in bubble characteristics indicative of a depressurisation over time, and to identify the presence of leaks. These can typically be detected at pressures that are above the pressure where a boiler is likely to shutoff (around 0.5bar). This means that the shutoff can be anticipated, giving a user opportunity to repressurise a system, or repair a leak, before the heating system fails or extensive damage is done by the leaking fluid.

The method for detecting and counting the bubbles could be one of many known in the field, for example training a machine learning algorithm to recognise the bubble sound, using matched filters, cepstrum filters, cochleagrams, or other techniques that can recognise sound signatures.

The method may also be applied to detecting bubbles in other parts of the system, for example bubbles detected at a low frequency rate in the condensate pipe of the boiler may indicate that the condensate pipe is blocked. This can be detected either by characterising the noise differently, or placing the sensor nearer the condensate pipe, or by correlating the detection with knowledge of the outdoor or indoor temperature, as blocked condensate pipes are more common when the condensate pipe freezes in low temperature.

The same sensor and processing means could also be used to detect other faults in the system e.g. pump or fan failures using techniques described in KR101938575.

The analysis of the signal could be performed on an electronic control unit that is located near the system it is monitoring, or the data could be transmitted to a remote system for analysis. Alternatively, to reduce the amount of data that needs to be transmitted, part of the analysis could be performed locally, for example looking for salient characteristics that describe the data and only transmitting that, or only transmitting data that looks like it may be a fault for remote analysis.

A remote central system could gather data from multiple sensors and use that to build a model of the acoustic signals of different heating systems.

The information from the sensors could be combined with other information about the system, for example whether the thermostat has requested heat, the temperature of the system, the pressure of the system, flow rates in the system, input from the user or any other information.

Information about the correct running of the system or any faults detected could be transmitted back to a central service provider, or transmitted to an operator or user.

Information about the heating usage characteristics of the system such as time of use patterns, energy usage, system settings could be monitored and recorded or transmitted.

Information about the usage duration and/or power output of the boiler could be used to determine suitable service intervals. The service intervals could be based on total hours of usage, or on equivalent full flame hours, or on some other metric, where if the boiler spends longer on lower power then the service intervals can be adjusted as compared to hours usage on full power.

The indicated faults described could be indicated directly on the central heating system or sent back to a remote system for logging.

Claims

CLAIMS1. A method for fault detection in a system using fluid for heat transfer, the method comprising:- * monitoring acoustic emission from the system * from the acoustic emission identifying signals associated with bubbles in the fluid * using a rate of emission of the signals associated with bubbles in the fluid as a proxy to indicate whether pressure in the fluid is within or outside an acceptable range for the system.
2. A method as claimed in Claim 1 in which the signals associated with bubbles in the fluid comprise signals showing amplitude spikes across a frequency range of approximately 1 to 4KHz or more, for a duration or between 5 and 50 milliseconds.
3. A method as claimed in Claim 1 or Claim 2 in which the rate of emission of the signals associated with bubbles in the fluid is compared with expected values to indicate whether pressure in the fluid is within or outside an acceptable range for the system.
4. A system for identifying or pressure loss in a circulation system by the method of any preceding claim, the system being configured for monitoring the vibration or acoustic signals in the system during operation of the heat source, comparing them to expected values and identifying actual or potential pressure loss when a discrepancy between the measured and expected signal is discovered.
5. A device as in claim 4, or a method as claimed in any of claims 1 to 3, where the expected signals are based on previous observations of the same system
6. A device as in claim 4 or claim 5, or a method as claimed in any of claims 1 to 3, where the expected signals are based on generic models of a heating source behaviour
7. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the expected signals are based on knowledge of the particular type, make or model of heat source.
8. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the change in the signal over time is used to detect the behaviour or condition of the system.
9. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the comparison is performed using a statistical, neural network or other classifier.
10. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the comparison is performed based on prior knowledge of the likely noise signatures of the components of the system.
11. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the comparison is performed after transforming the signal into the frequency, quefrency or other domain.
12. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, which sends the signal, or information derived from the signal, back to a server or other monitoring system for the analysis to be performed remotely.
13. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the signal is combined with other information about the system state such as heating on or off, heat input required, temperature, flow rate, pressure, known faults, installation conditions to perform the analysis.
14. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the signal is used to determine the usage patterns of the heating system
15. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the signal is used to determine the duration that the heating system runs for.
16. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the signal is used to determine the power output, fan speed or modulation level of the boiler.
17. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the duration of use at different power levels is used to determine suitable service intervals for the boiler.
18. A device as in claim 4, or any preceding claim dependent on claim 4, or a method as claimed in any of claims 1 to 3, where the signal is used to estimate the energy consumed by the system.
19. A device or method as in any of the above claims where information from the signal is processed and used to send alerts about the condition of the heating system.