A novel method of determining events in combination gas boilers: Assessing the feasibility of a passive acoustic sensor

Highlights

• Events occurring within a combination gas boiler are discernible using a single-point acoustic sensor.

• Demand type and ignition time was automatically determined, to high levels of accuracy, from noises produced by the boiler.

• Pre-mix fan motor frequency is visually disenable by analysing the acoustic profile of the boiler.

• The project has initiated a process for the development of a widely applicable set of acoustic tools for accessing energy systems.

Abstract

To assess the impact of interventions designed to reduce residential space heating demand, investigators must be armed with field-trial applicable techniques that accurately measure space heating energy use. This study assesses the feasibility of using a passive acoustic sensor to detect gas consumption events in domestic combination gas-fired boilers (C-GFBs). The investigation has shown, for the C-GFB investigated, the following events are discernible using a passive acoustic sensor: demand type (hot water or central heating); boiler ignition time; and pre-mix fan motor speed. A detection algorithm was developed to automatically identify demand type and burner ignition time with accuracies of 100% and 97% respectfully. Demand type was determined by training a naive Bayes classifier on 20 features of the acoustic profile at the start of a demand event. Burner ignition was determined by detecting low frequency (5–10 Hz) pressure pulsations produced during ignition. The acoustic signatures of the pre-mix fan and circulation-pump were identified manually. Additional work is required to detect burner duration, deal with detection in the presence of increased noise and expand the range of boilers investigated. There are considerable implications resulting from the widespread use of such techniques on improving understanding of space heating demand.

Introduction

Approximately 72% of energy consumption in the domestic environment is done so in gas-boilers for the purposes of domestic central heating (DCH) and domestic hot water (DHW) production [4]. Being such a large contributor to domestic energy consumption, gas-boilers have received significant attention from policy makers and researchers alike. In accordance to the UK Government's CO₂ target of an 80% reduction in emissions by 2050 [28], amongst other actions, policy makers have modified building regulations [11] so that boilers installed after 2006 are required to have a SEDBUK [2] efficiency of 88% or above. In addition to policy changes, many researchers look to evaluate environmental or behavioural interventions designed to reduce DCH and/or DHW consumption. To evaluate such interventions it is necessary to accurately monitor changes in disaggregated operational energy consumption, often in field trials.

Measuring energy consumed for DCH in field trials has however proven a challenge, as Hong et al. [12] note: due to the “… high cost associated with sophisticated fuel-use monitoring equipment required for different types of heating system and the complexity of its installation”. Estimates of DCH energy use have been made in a number of studies by subtracting the summer fuel load from the winter fuel load [12], [36]. These methods however require more than one years' worth of data and assume no variation occurs for non-space heating energy use between seasons. Other studies, such as Martin and Watson [22] and Love [23], used temperature sensors on flow pipes or radiators and relate temperature increases to boiler firing. These methods however miss short burner cycles and burner modulation. If methods were available that could accurately detect burner duration and modulation, space heating energy consumption estimates would be more accurate.

In addition to the above, it is well established that unnecessary cycling of boilers is undesirable [24]. Frequent on/off cycles, for example, cause boilers to operate at efficiencies “well below (their) full-load bench value” [38]. This issue has been observed in practice, for example Ren et al. [32] note “Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities.” Likewise a survey of 35 non-residential buildings revealed that “all of the installed heating capacity was oversized by a minimum of 30% …” [21]. Furthermore unnecessary cycling causes additional wear and tear on components. These problems can be due to oversizing [10], incorrect return flow temperature sensor settings, inadequate boiler modulation ranges etc. Data on cycling rates and boiler modulation could thus help identify potential issues causing efficiency losses.

Thus to accurately evaluate interventions designed to reduce demand, new field-trial applicable methods are required that can accurately measure operational burner duration for space heating purposes. Additionally such methods could be used to provide data on operational boiler cycling behaviour and help identify potential efficiency losses due to setup, design and/or sizing issues.

The aim of this study is to assess the feasibility of a single-point acoustic sensor and associated detection device that can be retrofitted to Combination Gas Fired Boilers (C-GFB) to provide data on energy consumption, demand type, boiler operation and boiler failure modes. Primary events for detection include demand type and the burner duration. Secondary events include the activity of the pre-mix fan and circulation-pump. Note, the circulation-pump circulates heating water around the closed heating system circuit (boiler, radiators etc.) and the pre-mix fan draws both natural gas and air into the burner chamber and helps to expel the exhaust gases. C-GFBs were selected for this study because, as of 2011, 60% of DCH and DHW systems in the UK were of this type. Additionally the number of C-GFBs has risen steadily since 1990, with no indication of it decreasing in popularity [4].

For this investigation, event detection will use the acoustic signal produced by the physical process of the event itself. This is to avoid making the assumption that the expected process flow of the system is being followed. For example, changes in the pre-mix fan motor speed are directly related to the period of firing, however using the pre-mix fan motor speed as a basis for detecting firing would assume the boiler is behaving as expected. Thus, the investigation bases burner identification on the acoustic signal produced by the burner and not the acoustic signal produced by any other component of the system. By doing so, events occurring outside of the expected process flow of the boiler can potentially be detected.

Alternative methods of event detection exist. One method is to monitor the boiler's Central Processing Unit (CPU). Junkers (the German brand of Bosch), for example, have developed a smartphone application which is linked via a wireless network with the CPU of some Junkers boilers [18]; however the application doesn't give detailed information on boiler events such as ignition time (only failure codes are reported back to the user). In general, accessing a boiler's CPU requires manufacturers' consent and substantial proprietary software, and if performed by research fieldwork teams, could invalidate boiler warranties. The advantage of using a non-invasive retrofitted method, such as an acoustic sensor, is that warranties are not invalidated and theoretically all boilers are accessible irrespective of age, software or hardware. Another option would be to use multiple sensors: The sensors however would need to be situated in various locations depending on the boiler. This increases both cost, complexity and the probability of sensor failure. The advantage of a single acoustic sensor is that most events of interest could, in principle, still be detected, and that the exact positioning of such an acoustic sensor would be of less importance and could sit externally to the boiler.