Sensor system for acoustic monitoring

Abstract

A sensor system acquires an acoustic signal from an asset. The acoustic signal is monitored continuously or quasi-continuously, and a trigger signal is generated in response to an event in the acoustic signal. A digital signal processing means transitions from a sleep state to an awake state in response at least in part to the trigger signal, and performs digital signal processing of the acoustic signal. Average power consumption is at least five times lower in the sleep state than the awake state. The amplitude of the acoustic signal may be compared to a plurality of thresholds and trigger signals generated when the thresholds are reached. Respective timestamps may be obtained, indicating when the trigger signals were received. Pattern matching may be performed on a sequence of timestamps from one comparator, and the transition may be in response to a match. An ultrasonic signal may be demodulated and the demodulated signal amplitude compared with the thresholds.

Description

TECHNICAL FIELD The present disclosure relates to the field of sensor systems, particularly those designed for acquiring acoustic signals from an asset. In embodiments, system is configured to operate in a low power state, transitioning to a high-power state for digital signal processing when an event is detected in the acoustic signal. BACKGROUND Ultrasonic sensors and their applications have seen significant advancements in recent years. The growing need for remote, real-time monitoring of assets has led to the development of various sensor systems. These sensor systems, such as the one disclosed in US 10,466,209 B2, typically include components for acquiring acoustic signals from an asset and processing these signals in some meaningful way. The document US 10,466,209 B2 discloses a sensor system which utilizes a transducer for converting an analogue transmit signal to an ultrasonic transmit signal and vice versa. The transducer is housed in a unit that includes numerous other components like a processor, wireless data transmitter, transmit and receive circuitry along with an A / D converter that aids in digital conversion processes. This reported system follows a mechanism where the processor triggers the transmit / receive circuit and A / D converter repeatedly to obtain a digitized composite signal. Thereafter, the digitized composite reflected signal is processed to generate an A-scan signal which is then wirelessly transmitted as data for transmission to a discrete collection device. Although this technology presents certain advancements in ultrasonic sensor technology by incorporating elements such as wireless data transmission and digital conversion processes, it still has its limitations. For instance, it is not well suited to use cases where sensing at regular intervals does not perform satisfactorily. SUMMARY An object of the disclosure is to provide a sensor system that can monitor high-frequency ultrasonic signals from an asset on a continuous or quasi-continuous basis, notwithstanding the power constraints associated with wireless sensor systems and other low-power systems. Embodiments provide a sensor system designed for capturing and analysing acoustic signals from an asset. Embodiments comprise components for acquiring, monitoring and digitally processing such signals. In embodiments, an acquisition component is configured for continuous or quasi-continuous capture of an acoustic signal from an asset. The acoustic signal may be captured passively by a ‘listening’ transducer. In embodiments, a state transition mechanism is configured for comparing an amplitude of such acoustics signals with a predetermined threshold and generating a trigger signal when this threshold is reached. In embodiments, a digital signal processing component is designed to transition from a low-power sleep state to an awake state in response, at least partially, to a trigger signal generated due to an event in such an acoustic signal. It is noted that digital signal processing tends to consume considerably more power than signal acquisition. Example events include but are not limited to sounds associated with bearing wear or failure, rolling contact fatigue, component misalignment, gear mesh issues, cavitation, looseness of parts, leaks, pressure relief valve activation, metal fatigue, corrosion, cracking and / or crack growth, electrical arcing, or general impacts. In embodiments, the state transition mechanism can compare an amplitude of the acoustic signal with multiple different thresholds and generate respective trigger signals indicative of different thresholds being reached. This multi-threshold comparison approach allows for more nuanced control over activation of digital signal processing. In embodiments, a digital signal processing component receives these trigger signals along with respective timestamps indicating when they were received. This timestamped data provides valuable insights into sequence and timing of events within the monitored acoustic signals. Moreover, pattern matching can be performed on these timestamps to enable ‘intelligent’ activation of digital signal processing based on inferred events in the acoustic signal. In embodiments, the system includes components for demodulating ultrasonic signals upstream of comparison to thresholds. Demodulation of high-frequency signals prior to comparison enables the comparison to be performed by relatively simple circuitry. In embodiments, the system includes one or more components for conditioning acoustic signals upstream of demodulation. In embodiments, the system is further configured for periodic transitioning into awake state by its digital signal processing component with periods ranging from minutes up to hours. Such periodic activations enables regular data acquisition during prolonged sleep states thereby maintaining sufficiently consistent monitoring while still achieving substantial power savings. The skilled person will appreciate that except where mutually exclusive, a feature described in relation to any one of the aspects, examples or embodiments described herein may be applied to any other aspect, example, embodiment or feature. Further, the description of any aspect, example or feature may form part of or the entirety of an embodiment of the invention as defined by the claims. Any of the examples described herein may be an example which embodies the invention defined by the claims and thus an embodiment of the invention. BRIEF DESCRIPTION OF DRAWINGS Embodiments will be described, by way of example only, with reference to the accompanying drawing: Figure 1 is a schematic representation of a wireless sensor system according to embodiments of the present disclosure. DESCRIPTION OF EMBODIMENTS Various embodiments provide a system for continuously monitoring acoustic signals received through a medium such as a gas, liquid or a solid and identifying an event though profiling of the time and frequency domain. Example features of such systems: 1. Continuous, or quasi-continuous, monitoring of acoustic signals in the 10KHz to 500KHz band for the purpose of detecting acoustic events. 2. Very low current consumption for battery powered operation typically using a Lithium D-Cell. 3. Acoustic events are identified by amplitude profiling and frequency domain profiling of the acoustic signal. 4. Automatic adaptation to determine correct gain settings, threshold settings and frequency domain profiling settings. 5. Event processor for event profile detection. With reference to Figure 1, in a system according to an embodiment, an acoustic transducer 10 receives acoustic signals coupled via a medium and produces a signal which is fed to variable gain amplifier 11. Internal to the amplifier 11 is a programmable filter 12 for selecting one or more specific frequencies. The acoustic transducer is selected based at least in part on its bandwidth, as it should be suitable for passively detecting acoustic signals of the order of at least tens of kHz, preferably hundreds of kHz, and in some cases MHz. Similarly, the programmable filter may be configured to select frequencies of up to 500kHz, up to 1MHz, or higher. The programmable filter 12 may implement a plurality of bandpass filters, e.g. 50kHz-100kHz, 100kHz-150kHz, 150kHz-200kHz. An amplitude demodulator 13 demodulates the acoustic signal and feeds it to an array of comparators 14. It will be appreciated that the amplitude demodulator 13 separates relatively low-frequency information from high-frequency component of the signal. Various demodulation techniques would be suitable, such as envelope detector, and off-the-shelf componentry may be used. In embodiments where programmable filter 12 implements a plurality of bandpass filters, the amplitude demodulator 13 may receive and demodulate a subset of the bandpass filter outputs, for example just the output of the highest frequency bandpass filter. The respective thresholds of the comparators 14 are configurable by the processing unit 16 and are set in such a way that several discrete trigger levels are set. When a comparator (of the comparators 14) trips, it wakes up the processing unit 16 which captures a timestamp indicative of when the trip occurred. A plurality of comparators may trip in a sequence, resulting in a corresponding series of timestamps at the processing unit 16. The processing unit additionally captures respective timestamps indicative of when the trips end, enabling calculation of the time for which a given comparator output remained high. The processing unit 16 assesses the series of timestamps to validate an event in the received acoustic signal. The processing unit 16 can perform pattern matching on the timestamps from the comparators to validate events by using an algorithm like a sliding window or a dedicated pattern matching engine. The system has one or more predefined patterns that represents valid sequence(s) of comparator triggers for the event(s) being monitored. The pattem(s) may specify, for example, an order of comparator activations and the expected time intervals between them, a number of activations of a given comparator within a period of time, the time for which a comparator output was high, or the like. The processing unit 16 can maintain a sliding window of a specific size based on the expected time interval between comparator triggers. As timestamps are generated, the processing unit adds them to the window. The processing unit continually checks if the timestamps within the window match (one of) the predefined pattern(s). If the timestamps match (one of) the pattern(s) within the window, the event is considered validated. The window then slides forward to accommodate the next timestamp. If the timestamps don't match (one of) the pattern(s) within the allotted time window, the processing unit 16 can: flag the event as invalid, or reset the window and wait for a new pattern to begin. Alternatively, the processing unit 16 may implement a dedicated pattern matching engine. A simple example of an event which may be flagged as invalid is one whose duration is below a threshold. Once a valid event is identified in the received acoustic signal, the processing unit 16 causes relatively high-resolution capture of the acoustic signal in real time using an analogue to digital converter (ADC) 15. The processing unit 16 performs more advanced digital signal processing on the digital signal generated by the ADC 15, such as frequency domain analysis, to classify the type of event. In some embodiments where programmable filter 12 implements a plurality of bandpass filters, the ADC 15 may be used to analyse a set of bandpass filter outputs which is different from a subset of the bandpass filter outputs received and demodulated by the amplitude demodulator 13. For example, the ADC 15 may be used to analyse all of the bandpass filter outputs, or all except the output of the highest frequency bandpass filter, for example. Processed data, comprising inter alia final event results, are transmitted to receiving equipment via a communication module 17. There a several options for the communication module. Cellular networks provide expansive geographical coverage, making them ideal for geographically dispersed sensor deployments. They are suitable for real-time data delivery with minimal latency, but tend to carry ongoing subscription costs and potentially higher power consumption compared to other options. Low-Power Wide-Area Networks (LPWAN) technologies such as LoRaWAN, Sigfox, and NB-loT prioritize low power consumption, enabling extended sensor operation on lower power budgets, and tend to perform well in long-range transmission. Wi-Fi offers good bandwidth, making it well suited applications requiring high data rate transmission, but its range tends to be limited and it typically requires pre-existing network infrastructure for connectivity. Bluetooth Low Energy (BLE) can be suitable for battery-powered sensors with moderate data transmission requirements, offering a balance between power efficiency and moderate communication range. Satellite communication is an option for geographically remote deployments where other methods might be unavailable. For wired communication, options range from simple, low-power protocols like SPI and I2C for short-distance connections, to robust industrial solutions like RS-485 or 4-20mA for multi-sensor networks and Ethernet or CAN for high data rates and real-time needs. It will be appreciated, when reading the description above, that the types of acoustic event may vary both in amplitude and frequency content. As such, the systems have the ability of adaptation by going through a training process the results of which are used to adjusts the amplifier gain, the filter parameters and frequency domain settings accordingly. It will be appreciated that sensor systems in accordance with embodiments of the present disclosure have a far lower average power consumption in the sleep state than in the awake state, typically at least five times lower, in some cases an order of magnitude lower, in some cases two or more orders of magnitude lower. No specific method is required for determining average power consumption in a given state. By way of non-limiting example, the average power consumption of a sensor system in sleep and awake states can be determined through current measurement: a multimeter capable of measuring current in the milliamp (mA) or microamp (pA) range can be connected in series with a power supply providing the system's required voltage. The system is then configured to one of its operating modes (e.g. awake state) and then later to another of its operating modes (sleep state), with current readings logged at regular intervals for, say, several minutes in each state. Data logging software can be employed for extended measurements, for example. Subsequent analysis calculates the average current consumption for each mode, which is then converted to average power using the formula: Pavg (mW) = lavg (mA) * Vsupply (V). Other suitable methodologies will be readily apparent to the skilled person. It will be understood that the invention is not limited to the examples and embodiments above-described and various modifications and improvements can be made without departing from the concepts described herein. Except where mutually exclusive, any of the features may be employed separately or in combination with any other features and the disclosure extends to and includes all combinations and sub-combinations of one or more features described herein.

Claims

1. A sensor system comprising:- means for acquiring an acoustic signal from an asset;- means for monitoring the acoustic signal and generating a trigger signal in response to an event in the acoustic signal; and- means for performing digital signal processing of the acoustic signal when in an awake state,wherein the signal acquisition means is configured for continuous or quasi-continuous monitoring of the asset based on high frequency acoustic signals,wherein the signal processing means is configured to transition from a sleep state to the awake state in response at least in part to the trigger signal, andwherein the average power consumption of the sensor system is at least five times lower in the sleep state than in the awake state.

2. The system of claim 1 wherein the state transition means (a) comprises means for comparing an amplitude of the acoustic signal with a threshold and (b) is configured to generate the trigger signal to indicate that the threshold has been reached.

3. The system of claim 2 wherein the state transition means (a) comprises means for comparing an amplitude of the acoustic signal with a plurality of different thresholds and (b) is configured to generate respective trigger signals indicative of the different thresholds being reached.

4. The system of claim 2 wherein the signal processing means is configured to receive the trigger signal and to obtain a timestamp indicative of when it was received.

5. The system of claim 3 wherein the signal processing means is configured to receive the trigger signals and to obtain respective timestamps indicative of when they were received.

6. The system of claim 5 wherein the signal processing means is configured to perform pattern matching on the timestamps and to transition into the awake state in response to a match.

7. The system of claim 6 wherein the pattern matching is performed on a sequence of timestamps from one comparator.

8. The system of any preceding claim, further comprising means for demodulating the ultrasonic signal, wherein the comparison means is configured to compare the amplitude of the demodulated signal with the thresholds.

59. The system of claim 8, further comprising means for conditioning the ultrasonic signal upstream of the demodulation means.

10. The system of any of the foregoing claims wherein the signal processing means is10 further configured to transition into the awake state periodically, the period being of the order of minutes or hours.10

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