METHOD AND APPARATUS FOR DETERMINING THE SENSITIVITY OF AN ACOUSTIC DETECTOR DEVICE

Abstract

A method for estimating the sensitivity in an environment of a sound emission detector device capable of detecting a physical phenomenon producing a spatially limited sound emission, said detector device comprising a transducer array, said method comprising a) receiving at least one signal from at least one respective transducer of the transducer array, said array being place within said environment, b) estimating from the at least one signal received at step a) a detection threshold value of a spatially limited source sound emission parameter, c) estimating from the detection threshold value estimated at step b) a quantity representative of a magnitude of the physical phenomenon, d) displaying the quantity estimated at step c) so as to inform the user of the sensitivity of the detector.

Claims

1. A method for estimating, in an environment, the sensitivity of a sound emission detector device capable of detecting a physical phenomenon producing a spatially limited sound emission, the detector device comprising (i) a transducer array having a plurality of transducers, each transducer is arranged to measure a physical parameter related to sound, and (ii) processing means arranged to locate a possible source of sound emission from a plurality of signals measured by the plurality of transducers of the array, the method comprising: a) receiving at least one signal from at least one respective transducer of the transducer array, the array being placed within the environment, b) estimating from the at least one signal received at step a) a detector device detection threshold value of a spatially limited source sound emission parameter, c) estimating from the detector device detection threshold value estimated at step b) a quantity representative of a magnitude of the physical phenomenon, d) displaying the quantity calculated at step c) so as to inform the user of the sensitivity of the detector device within the environment.

2. The method according to claim 1, wherein steps a), b), c) and d) are performed repeatedly during the operation of the detector.

3. The method according to claim 1, wherein at step a), a plurality of signals are received, the plurality of signals resulting from a plurality of measurements obtained simultaneously by the plurality of transducers of the array, and step b) also comprises processing the plurality of received signals to detect a source that is spatially limited, the processing being performed taking into consideration the relative positions of the plurality of transducers.

4. The method according to claim 1, further comprising, prior to step a), a previous step comprising providing a spatially limited acoustic source, and step b) also comprises processing the at least one received signal to detect a sound emission resulting from the previous step, the method further comprising repeating iteratively the previous step, step a) and the processing of step b), with at the previous step various values of the provided sound emissions, to determine the smallest detectable acoustic source.

5. The method according to claim 1, further comprising, prior to step a), a previous step comprising simulating a spatially limited acoustic source by adding to at least one signal measured by the respective at least one transducer at least one respective additional signal, the at least one additional signal corresponding to the simulated source, and step b) also comprises processing the at least one received signal to detect a sound emission resulting from the previous step, the method further comprising repeating iteratively the previous step, step a) and the processing of step b), with at the previous step various values of the simulated sound emissions, to determine the smallest detectable acoustic source.

6. The method according to claim 1, wherein the method comprises, at step b), estimating a not localized acoustic parameter value from the at least one received signal, and subtracting a positive value of the acoustic parameter from the not localized value to obtain the estimated detection threshold value of a spatially limited source sound emission parameter.

7. The method according to claim 1, wherein the method further comprises processing a plurality of received signals so as to detect spatially limited acoustic sources, and in case a spatially limited acoustic source is detected, estimating a value of a parameter representative of the sound emission of the detected source, converting the value of the parameter representative of the sound emission of the detected source into a quantity representative of a magnitude of the physical phenomenon, displaying the quantity estimated at step c) so as to inform the user of the magnitude of the detected physical phenomenon.

8. The method according to claim 1, wherein the quantity estimated at step c) is a quantity of a parameter that is function of a size of a leak.

9. A computer readable medium storing computer executable code which when executed by a processor causes the processor to carry out the method of claim 1.

10. An apparatus for estimating, in an environment, the sensitivity of a sound emission detector device capable of detecting a physical phenomenon producing a spatially limited sound emission, the detector device comprising (i) a transducer array, each transducer being able to measure a physical parameter related to sound, and (ii) processing means arranged so as to be capable of locating a possible source of sound emission from signals generated by the transducer array, the apparatus comprising: receiving means adapted to receive at least one signal from at least one respective transducer of the transducer array when the array is placed within the environment, processing means arranged to estimate from the at least one signal received by the receiving means a detection threshold value of a spatially limited source sound emission parameter, and to estimate from the estimated detection threshold value a quantity representative of a magnitude of the physical phenomenon, transmitting means to transmit a signal to a display, the display signal representing the estimated quantity so as to inform the user of the sensitivity of the detector device within the environment.

11. A detector device for industrial equipment, comprising a transducer array and an apparatus as recited in claim 10.

12. A sound emission detector apparatus for detecting, in an environment, the magnitude of a physical phenomenon producing a spatially limited sound emission, the apparatus comprising: a transducer array having a plurality of transducers arranged to detect sound emissions within the environment and produce signals representative of the detected sound emission, a signal receiver that receives signals from at least one of the transducers of the transducer array, a processor programmed with instructions for processing the received signals so as to detect spatially limited acoustic sources and determine a value of a parameter representative of the sound emission of the spatially limited detected acoustic source and convert the value of the parameter representative of the sound emission of the detected acoustic source into a quantity representative of a magnitude of the physical phenomenon, a display for displaying at least the quantity representative of the magnitude of the physical phenomenon.

13. The apparatus of claim 12, wherein the physical phenomenon is a gas leak and the quantity representative of the magnitude of the physical phenomenon is a flow rate of the gas leak.

14. The apparatus of claim 12, wherein the physical phenomenon is an electrical discharge and the quantity representative of the magnitude of the physical phenomenon is a quantity of power.

15. The apparatus of claim 12, wherein the physical phenomenon is friction and the quantity representative of the magnitude of the physical phenomenon is a quantity of force.

16. The apparatus of claim 12, further comprising instructions for the processor to process the received signals to determine and display a detection sensitivity of the apparatus within the environment.

17. The apparatus of claim 12, further comprising instructions for the processor to process the received signals to determine and display the location of the physical phenomenon within the environment.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0147] The disclosure is explained in further detail, and by way of example, with reference to the accompanying drawings, wherein:

[0148] FIG. 1 schematically shows an example system according to an embodiment;

[0149] FIG. 2 schematically illustrates an example method according to an embodiment;

[0150] FIG. 3 schematically illustrates an example method according to another embodiment;

[0151] FIG. 4 schematically illustrates an example method according to another embodiment;

[0152] FIG. 5 schematically shows an example display possibly obtained with a method according to an embodiment.

DETAILED DESCRIPTION

[0153] The following are descriptions of illustrative embodiments that when taken in conjunction with the following drawings will demonstrate the above noted features and advantages, as well as further ones. In the following description, for purposes of explanation rather than limitation, illustrative details are set forth such as architecture, interfaces, techniques, element attributes, etc. However, it will be apparent to those of ordinary skill in the art that other embodiments that depart from these details would still be understood to be within the scope of the disclosure. Moreover, for the purpose of clarity, detailed descriptions of well known devices, circuits, tools, techniques and methods are omitted so as not to obscure the description of the present system. It should be expressly understood that the drawings are included for illustrative purposes and do not represent the scope of the present system. In the accompanying drawings, like reference numbers in different drawings may designate similar elements.

[0154] A detector device 1 as illustrated in FIG. 1 may comprise a transducer array 4 comprising a plurality of transducers 2, e.g. of MEMS microphones 2.

[0155] The MEMS microphones are spread at different locations on a two dimensional plate 5, i.e. the array 4 is planar.

[0156] In an alternative, not illustrated, embodiment, the transducer array may be 3D shaped. For example, the transducers may be on a surface of a sphere.

[0157] The MEMS microphones 2 may be arranged so as to record audio and ultrasound signals.

[0158] The detector device 1 allows non destructive test of an industrial equipment, e.g. pipes, tanks, or machinery.

[0159] The leak detection is based on a passive recording of audio and ultrasound signals at the MEMS microphones 2.

[0160] The MEMS microphones allow measuring the possible sound pressure waves generated by the flow of gas from a high pressure enclosure via a leak within a wall of this enclosure.

[0161] The microphones 4 have overlapping coverage.

[0162] The detector device 1 comprises an electronic circuit board 3 with a communication module 31 arranged to receive signals from the MEMS microphones 2 and a processor 32 in communication with the communication module 31.

[0163] The processor 32 is arranged to perform leak detection based on the signals received at the MEMS microphones 2. This processor 32 may perform a source localization algorithm, based for example on beamforming, e.g. on SRP (for steered response power), thus allowing not only to detect the presence of a leak but also to provide a localization of the detected leak.

[0164] Such algorithm is for example described in Microphone Array for Air Leakage Detection by Petr Eret and Craig Meskell published in Berlin Beamforming Conference 2012 (BeBeC 2012). In this paper, a type of beamforming algorithm, orthogonal beamforming, is used to locate air leaks. A superimposition of an optical image from a digital camera and of an acoustic image (the output of the beamforming algorithm) allows to show in real-time the potential leak locations, which correspond to the maxima of the image. Though electret microphones were used, there is nothing specific to this microphone technology and those of ordinary skill in the art would easily implement this method with MEMS microphones. Other possible types of beamforming are described in Beamforming: a versatile approach to spatial filtering by Barry D. Van Veen and Kevin M. Buckley published in IEEE ASSP magazine of April 1988, which present different types of beamformers that have optimal performance and characteristics depending of different use cases.

[0165] The processor 32 may also implement an acoustic holography method, a model-based method (such as described for example in A covariance fitting approach for correlated acoustic source mapping, Yardibi and Li, 2010), or another algorithm that combines the signals issued from the microphones and spatially filter the signals, thus resulting in lower detection threshold than single microphone detectors.

[0166] The processor 32 is connected to an output port 33 in communication with a terminal 6. In a not illustrated embodiment, the terminal 6 may be remote and the communications may take place via a network such as the Internet.

[0167] The terminal 6 comprises a user interface, e.g. a screen 61 and a keyboard 62.

[0168] In case a leak is detected, the processor 32 generates an alarm messages that is transmitted to this terminal so as to report the problem.

[0169] As illustrated in FIG. 1, an acoustic image may be superimposed to an optical image. In this case a spatially limited acoustic source has been identified and localized, thus resulting in displaying a zone in red 262 and yellow 263 on the optical image representing a pipe.

[0170] The processor 32 may be programmed so as to execute at least one of the methods described in reference to FIG. 2, FIG. 3 and FIG. 4.

[0171] In particular, the processor 32 is programmed so as to estimate in real time the sensitivity of the detector device 1.

[0172] It may for example be programmed so as to execute the steps of FIG. 2.

[0173] In a first embodiment (active detection), reference sources are provided or simulated, in which latter case the corresponding input signals are added to the measured input signals. Then, for a reference source, it is determined whether it is detectable or not, and the leak flow value corresponding to the smallest detectable reference source is displayed.

[0174] More precisely, sound emitted from gas leaks may be recorded in a very quiet environment using a system identical to the device employed by the users. The recordings (or simulations thereof) are to be performed for different values of multiple parameters: pressure difference, gas type, temperature, humidity, atmospheric pressure, distance, position, etc. The actual leak rate during the sound recording may be measured too.

[0175] When the device is used (either fixed or hand-held), two acoustic images are computed in parallel: one with the direct acoustic array output and one with the addition of one of the recordings. A comparison between the two acoustic images is then performed to see whether the superimposed leak would be found in this environment. Another recording with a smaller or greater leakage rate is then selected and the same operation is repeated until the smallest leak that can be detected in this environment is found. The corresponding leakage rate is then displayed to the user.

[0176] The user may have to select the gas type or other conditions (such as pressure difference, temperature, etc.). Alternatively, additional sensors could provide this information.

[0177] In the case where a user sees a leak then, the value displayed by the algorithm is the smallest leak that would be displayed besides the currently detected leak.

[0178] With reference to FIG. 2, the method may comprise a step 201 consisting in receiving a number of synchronized acoustics signals, measured by a number of transducers of the array, e.g. 100 signals. On FIG. 2, only a single signal Sm(t) has been mentioned for the sake of simplicity, but the reader understands that there are a plurality of signals that are measured simultaneously that are received at step 201.

[0179] At step 202, an acoustic image AI_passive is obtained from this plurality of signals received at step 201, e.g. by beamforming or another method.

[0180] Then, several reference sources are tested, in a loop. For the first loop, a Boolean variable k is chosen equal to zero (step 203).

[0181] At step 204, for each transducer, a simulated signal according to a reference source is added to the signal measured by this transducer. For the first loop, the simulated signals may be computed based on a predetermined first SPL value.

[0182] Then, at step 205, an acoustic image AI_active is obtained from the signals obtained at step 204.

[0183] It is compared with an acoustic image obtained with the signals recorded with the passive listening (step 206). The comparing step actually be more sophisticated than illustrated: one may calculate a sum over the pixels of the absolute values of the differences, and compare this sum to a threshold, for example.

[0184] If a difference is detected at step 206, k is set to 1, a lower value of the SPL of the reference source is chosen (step 207), the corresponding signals are computed (step 208) and added to the measured signals (step 204). Steps 205 and 206 are then repeated until no difference is found. Then, the previous SPL value (step 209) is selected (step 210) as the estimated detection threshold value.

[0185] If no difference is detected, k is kept at zero and a higher value of the SPL of the reference source is chosen (step 211), the corresponding signals are computed (step 208) and added to the measured signals (step 204). These steps are repeated until a difference is found, in which case the algorithms allows obtaining the estimated detection threshold value (steps 209 and 210).

[0186] At step 212, a flow rate value is obtained from the estimated value Pm and from a pressure difference. For example, it is read in a look-up-table.

[0187] At step 213, a message is generated as a function of the flow rate computed at step 212, so as to display this flow rate.

[0188] In an alternative (not illustrated) embodiment, at step b), no SPL is directly estimated, but instead, a ordered list of reference sources is stored in a memory, the list being ordered as a monotonic function of the sources emission parameter values corresponding to said reference sources. If at step 206, the source is detected, the method may comprise testing a neighboring source of the list, that has a smaller acoustic emission. If at step 206, no source is detected and k=0, the method may comprise testing a neighboring source of the list, that has a higher acoustic emission. Step 210 consists in obtaining the name of a reference source (that actually corresponds to the smallest source that is detected among the sources of the list). At step 212, a flow rate that is associated to this name is read from a memory.

[0189] FIG. 3 relates to another embodiment of the disclosure, based on a passive listening only.

[0190] For example, an overall noise floor (due to internal and ambient noise as well as other sources) may be determined. A SPL may be derived from this overall noise floor. This determination may allow obtaining a SPL value that is actually equal or very close to the weakest spatially limited source detectable anywhere in the field of view (outside possible detected sources of course). Then the method may comprise computing from this SPL value the flow that turns out to correspond to the weakest source found, and this flow value may be displayed.

[0191] Otherwise said, this method implies approximations with regards to the methods with reference sources, such as the one described with reference to FIG. 2. The known characteristics of the acoustic camera, such as side lobe patterns, internal noise, etc., are taken into consideration for the determination of the lowest intensity a sound source can have, without being masked in the current conditions.

[0192] Sources that cause masking may include other sound sources in the environment, ambient noise, internal noise (e.g. thermal noise of the sensors) or noise caused by the transformation and processing of signals (e.g. quantization noise). From this sound intensity, and the maximum distance, a leak flow estimate can be derived, e.g. by evaluating a fitted curve/surface, or looking up values in a table stored in the device. The data for such curve fits or lookup tables can be based on experiments or a fluid dynamics model.

[0193] A possible implementation of this method would be, with regard to FIG. 3: [0194] Receive (step 301) a plurality of signals measured by a respective plurality of transducers of the array, [0195] compute an acoustic image (step 308) from the received signals and from the relative positions of the transducers, [0196] Identify (step 302) all currently detected sources (or further simplification: take maximum of current acoustic image); [0197] Compute (step 303) side lobe with largest intensity caused by any of the currently displayed sources (based on known properties of acoustic camera); [0198] Estimate (step 304) overall noise floor across acoustic image due to internal noise and ambient noise. [0199] Determine (step 305) from the two values computed at step 303 et 304 side lobe and overall noise floor) a detection threshold SPL value, e.g. select the maximum of the two values obtained at step 303 and 304 and add a constant offset; the result is considered as the minimum sound intensity that a source can have and still be detectable. [0200] For the maximum detection distance (fixed or user-defined), the given gas type, and the current frequency band, use a lookup table (not shown in FIG. 3), or an analytic function (step 306) to determine which leak flow rate corresponds to the sound intensity computed in the step above; [0201] Display this flow rate FR.sub.THR (step 307) as a sensitivity within the current environment.

[0202] Referring back to FIG. 1, the processor may be programmed so as to perform the steps of FIG. 4.

[0203] Signals are measured at the transducers at step 401, and possibly the sensitivity may be estimated and displayed (step 402), e.g. with one of the methods described with reference to FIG. 2 or 3.

[0204] In an alternative, not illustrated embodiment, the processor 32 of FIG. 1 does not estimate the sensitivity.

[0205] The signals received at step 401 are processed so as to detect a source, e.g., by beamforming, and if a source is detected (step 403) its SPL is calculated (step 404).

[0206] This calculating takes into consideration an estimated location of the source, also obtained from the measured signals, and possibly from a knowledge of the environment. So the SPL value that is calculated at step 404 is far from a recorded value, it represents the sound emission of the detected source.

[0207] At step 405, this SPL value is converted into a flow rate value, e.g. by applying a formula.

[0208] At step 406, the flow rate value of the detected leak is displayed.

[0209] Then, the device may return to step 401, such that the failure quantification is done in real time.

[0210] Referring now to FIG. 5, an acoustic image may be superimposed to an optical image.

[0211] In this case, a spatially limited acoustic source has been identified and localized, thus resulting in displaying a zone in red 162 and yellow 163 on the optical image representing a pipe.

[0212] Further, the device computes a flow rate of the detected leak and displays it, e.g. 34 liters per hours, this estimate being made for a pressure of 4 bars within the pipe.

[0213] Further, a sensitivity at a determined distance from the detector is displayed, e.g. in liters per second. In this example, the detector device has computed that its sensitivity was 20 liters per hours at 1 meter.