METHOD AND DEVICE FOR DETECTING EARTHQUAKES

Description

technical field

[0001] A method and device for earthquake detection are described. The method and device can be used, in particular, to trigger alerts and safety measures, for example, to secure a resource distribution system. Technical background

[0002] Some earthquake detection systems use vibration or acoustic pressure sensors. Such systems can be expensive and difficult to install. They can also use trained predictive models (machine learning), but these require significant computing resources, which may not be available in all applications.

[0003] It is therefore desirable to have a method for detecting earthquakes that is economical in terms of computing resources. KR 2022 0067588 discloses a method for real-time detection of seismic motion. Acceleration data are measured using seismic recorders comprising a triaxial accelerometer. The recorded data are subjected to high-pass or low-pass filtering. Then, the X and Y components of the acceleration data are determined. An earthquake is detected if the vertical acceleration data from each sensor exceeds a first predetermined reference value and the acceleration data received from each seismic recorder are correlated, and if the correlation value exceeds a third predetermined reference value. Summary

[0004] One or more embodiments relate to a method for detecting an earthquake implemented by a device comprising at least one processor and a memory containing software code, the at least one processor causing the device to implement the method when it executes the software code, the method comprising: the reception of a signal representative of measurements of a three-dimensional acceleration of the device ground as a function of time, the signal being received from an accelerometer sensor; the frequency filtering of the signal, the filtering being configured with a low cutoff frequency and a high cutoff frequency to exclude at least frequencies not corresponding to seismic wave frequencies; the determination, from the filtered signal, of data representative of directions of acceleration as a function of time; an earthquake being detected if a) the magnitude of the acceleration is greater than a first threshold and the directions of the acceleration are substantially collinear with each other during a first time interval;or b) the directions of acceleration are substantially collinear with each other during a second time interval and the directions of acceleration are substantially collinear with each other during a third time interval subsequent to the second time interval, and the directions of acceleration of the second and third intervals are substantially orthogonal.

[0005] The method uses data from a three-dimensional accelerometer. Such a sensor can be easily integrated into, or connected to, a device with relatively modest computing resources to process the sensor data. For example, such a device could be a resource meter that may need to be secured.

[0006] The invention thus makes it possible to offer a local earthquake detection device at a low cost. Local detection allows for appropriate action to trigger safety measures, even when the device is not connected to a communication network, or when that communication network is down.

[0007] According to one or more embodiment examples, the cutoff frequencies are adapted to exclude frequencies corresponding to noise from the environment of the device.

[0008] According to one or more embodiment examples, the determination of representative data of directions of acceleration as a function of time is only carried out if a magnitude of the acceleration exceeds a second threshold before the filtering of the signal and exceeds a third threshold after the filtering of the signal.

[0009] According to one or more implementation examples, the second and third thresholds are adapted to be above acceleration magnitudes corresponding to noise from the environment of the device.

[0010] According to one or more implementation examples, the method includes adapting the cutoff frequencies, respectively adapting the second threshold and the third threshold, based on historical labeled acceleration data in a device operating location.

[0011] The method involves calibrating certain thresholds to account for ambient noise and thus avoid, or at least limit, spurious triggers, such as false positives or false negatives. Advantageously, this calibration is performed using labeled historical data.

[0012] Based on one or more embodiment examples, a determination of the collinearity of acceleration directions is performed, including: the determination of a hyperplane with respect to N consecutive measurement points from the signal and the determination of a direction normal to this plane, with N>1; the iteration of the previous step on M sets of N points of a considered time interval, with M>1; the conclusion that there is substantially collinearity over the considered time interval if the angles of the N normal directions taken two by two are in two ranges including respectively 0° and 180°.

[0013] Based on one or more embodiment examples, a determination of the orthogonality of acceleration directions is performed, including: the determination of a hyperplane with respect to N consecutive measurement points from the signal and the determination of a normal direction to this plane, with N>1; the iteration of the previous step on two sets of N points of a considered time interval; the conclusion that there is substantially orthogonality if the angle between the normal directions of the two hyperplanes determined in the previous step are in two ranges including respectively 90° and 270°.

[0014] According to one or more embodiment examples, the method includes, in response to the detection of an earthquake, the generation of a control signal for equipment to secure a resource counted by the device.

[0015] According to one or more embodiment examples, the method includes, in response to the detection of an earthquake, the generation of an alert message to a server. According to one or more embodiment examples, an earthquake is detected in case b) only if the magnitude of the acceleration exceeds a fourth threshold, lower than the first threshold.

[0016] One or more embodiments relate to an earthquake detection device comprising a memory containing software code and the processor, the processor being adapted, when executing the code, to cause the device to implement one of the above methods.

[0017] According to one or more embodiment examples, the device includes a three-dimensional accelerometer.

[0018] One or more embodiments relate to a computer program product comprising instructions which, when executed by at least one processor, cause the execution of one of the methods described by said at least one processor.

[0019] One or more embodiments relate to a non-transient storage medium comprising instructions which, when executed by at least one processor, cause the execution of one of the methods described by said at least one processor. Brief description of the figures

[0020] Other features and advantages will become apparent as you read the detailed description that follows, for which you should refer to the attached drawings, including: there figure 1 is a schematic diagram of a system comprising a device in one or more embodiments; figure 2is a schematic diagram illustrating an XYZ coordinate system of a 200 acceleration sensor and a QLT coordinate system of seismic waves; the figure 3 is a flowchart of a method based on one or more implementation examples; figure 4 is a graph illustrating an example of a bandpass filter according to a specific implementation; the figure 5 is a flowchart of a calibration process based on an example implementation; the figure 6 is a flowchart of a vector component analysis method 600 according to a particular implementation example; the figure 7 is a non-limiting example of a method for determining collinearity and orthogonality; the figure 8includes two graphs (a) and (b) representing respectively the evolution of an angle used in the evaluation of the collinearity or orthogonality of displacements due to an earthquake as a function of time and illustrating the application of the method according to one or more examples of implementation and the magnitude of the acceleration. Detailed description

[0021] In the following description, identical, similar, or analogous elements will be designated by the same reference numbers. The block diagrams, flowcharts, and message sequence diagrams in the figures illustrate the architecture, functionality, and operation of computer systems, devices, processes, and program products according to one or more implementation examples. Each block in a block diagram or each phase in a flowchart can represent a module or a portion of software code comprising instructions for implementing one or more functions. Depending on the implementation, the order of the blocks or phases may be changed, or the corresponding functions may be implemented in parallel.The process blocks or phases can be implemented using circuits, software, or a combination of circuits and software, either centrally or in a distributed manner, for all or part of the blocks or phases. The systems, devices, processes, and methods described can be modified, supplemented, and / or deleted while remaining within the scope of this description. For example, the components of a device or system can be integrated or separated. Similarly, the described functions can be implemented using more or fewer components or phases, or with different components or through different phases. Any suitable data processing system can be used for implementation. A suitable data processing system or device might include, for example, a combination of software code and circuits, such as a processor, controller, or other circuit suitable for executing the software code.When the software code is executed, the processor or controller directs the system or device to implement all or part of the functionalities of the blocks and / or phases of the processes or methods, according to the embodiment examples. The software code can be stored in non-volatile memory or on a non-volatile storage medium (USB flash drive, memory card, or other medium) that is readable directly or through a suitable interface by the processor or controller.

[0022] This description relates to an earthquake detection device. The context of the specific embodiments is a resource meter, as well as the implementation of a safety mechanism in the event of an earthquake detection. This context is provided for illustrative purposes only and should not be interpreted as limiting the invention to this context alone. The resources being measured include, for example, fluids (gas, water, fuel, etc.) or electrical energy. More generally, earthquake detection is relevant for any meter whose resource could be lost or damaged following an earthquake.

[0023] There figure 1is a schematic diagram of a system comprising a device 100 in one or more embodiments. The device 100 is, for example, a resource meter. The device 100 receives data from a three-dimensional accelerometer 101. This sensor may also be an integral part of the device 100. The device 100 also includes a processor and non-volatile memory containing software code for implementing the earthquake detection method. Optionally, the meter may also have a control interface configured to trigger a safety action, such as closing a valve 103.

[0024] Optionally, a communication interface 102 connected to device 100 is configured to allow communication between device 100 and a third party, for example, server 104. Communication interface 102 can be a wireless interface, for example, a cellular interface, or an interface to a wired network, for example, a traditional telephone network. Device 100 is adapted to inform server 104 of the detection of an earthquake. Server 104 can then trigger an action, for example, notifying a competent authority 106, and / or inform other devices 105, similar to device 100, so that they, if necessary, can also initiate safety measures.

[0025] Optionally, device 100 is configured to transmit an earthquake alert directly to one or more other devices 105 so that they, in turn, can trigger safety measures. In one embodiment, the transmission goes through server 104; that is, an alert is sent by device 100 to server 104, which then transmits it to one or more devices 105, such as devices 105 located near device 100 and therefore also exposed to the risks of the earthquake.

[0026] The transmission of an alert by device 100 to devices 105 and / or the triggering of an action by a device 105 may be subject to a geographical proximity criterion between device 100 and the device(s) 105. Optionally, server 104 communicates with a plurality of devices 105 of the same type as device 100 and can receive earthquake alerts from several devices 100. This allows the action triggering strategy to be adapted – for example, it is possible to trigger an action only if several devices 100 have detected an earthquake.

[0027] In the context of a device 100 with a counter function, the device 100 may be required to communicate consumption data for the resource it is counting at regular intervals or on demand. This transmission is, for example, carried out daily and can be triggered by a server request. In the case of earthquake detection, the device 100 is, according to a specific embodiment, configured to force the transmission of a message, bypassing the constraints associated with transmitting counting data. Some physical principles related to an earthquake will now be described. During an earthquake, different types of seismic waves are present, defined by their propagation speed, amplitude, and polarization. The main types of waves are as follows: 'P' waves (for 'Primary') - these waves propagate quickly and are felt first; 'S' waves (for 'Secondary') - these waves usually arrive after P waves; shear waves - these waves usually arrive after the two previous waves and are the most destructive.

[0028] Table 1 presents a summary of the main types of waves generated during an earthquake. [Table 1] Waves P S Love Rayleigh Wave type Compression Shear Shear Shear Speed ​​(km / s) ~5,6 ~3,2 ~3 ~3 Damages Weak Means Students Students Polarization Horizontal Vertical Horizontal Rotational

[0029] Table 1 shows that the later the waves arrive, the more destructive they generally are. Therefore, security measures and / or alerts must be triggered as soon as possible. Early detection is thus preferable.

[0030] There figure 2This is a schematic diagram illustrating an XYZ coordinate system of an acceleration sensor 200 and a QLT coordinate system for seismic waves. An orthogonal coordinate system attached to the device has two axes, X and Y, in the plane of the surface 201 (assumed to be flat) and a Z axis vertically above this surface. The direction of propagation of the seismic waves from the source 202 to the sensor 200 is indicated by L, and the direction orthogonal to the direction of propagation and in the plane comprising this direction, L, the source 202, and the sensor 200, is indicated by Q. A T axis is perpendicular to the L and Q axes. In the illustrated example, P waves generate accelerations along the X and Z axes, while S waves generate accelerations along the X and Y axes.

[0031] Table 2 shows an earthquake intensity scale, and for each level of the scale: acceleration, velocity, felt shaking, potential damage, and the effect on certain resources. The table shows (a) that an earthquake can be felt starting at an acceleration amplitude of approximately 3 mg (2.97 mg in the table) and (b) that damage occurs starting at an acceleration amplitude of approximately 27 mg. [Table 2] Measured intensity Acceleration (9) Speed ​​(cm / s) Trembling felt Potential damages Resources I <0.000464 <0.0215 No sensation None II-III 0.000464 - 0.00297 0.135 - 1.41 Weak None IV 0.00297 - 0.00276 1.41 - 4.65 Light None V 0.0276 - 0.115 4.65 - 9.64 Moderate Very light Activation of automatic valves for domestic gas. Interruption of some water pipes. Power outages. VI 0.115 - 0.215 9.64 - 20 Strong Light Damaged water and gas lines. Interruption of gas and water supply in some areas. VII 0.215 - 0.401 20 - 41.4 Very strong Moderate As in the previous line. VIII 0.401 - 0.747 41.4 - 85.8 Severe Moderate to significant Damaged water and gas pipes. Gas supply interruption. water and electricity. IX 0.747 - 1.39 85.8 - 178 Violent Important X >1.39 >178 Extreme Very important

[0032] Depending on one or more embodiments, the aim is to detect an earthquake: i. at a time between the arrival of P waves and before the arrival of surface waves (Love and Rayleigh waves), and / or ii. at the transition from P waves to S waves.

[0033] It is proposed to implement a three-dimensional accelerometer to capture the waves caused by the earthquake. The signals from the accelerometer are then used for earthquake detection.

[0034] Regarding the first point, i, above, a check is performed on the magnitude of the acceleration. If the magnitude exceeds a threshold, then an earthquake is detected. Regarding the second point, ii, above, since P-waves and S-waves are orthogonal, the transition from P-waves to S-waves can be detected by performing a directional analysis and testing the orthogonality of the acceleration axes over time.

[0035] It should be noted that the displacements generated by P waves are collinear with each other, and that the displacements generated by S waves are collinear with each other.

[0036] It should be noted that an earthquake can be detected according to the second case without necessarily being detected first according to the first case. This can happen, for example, when the detected P-waves do not meet the detection criteria of the first case.

[0037] Furthermore, seismic waves generally have a frequency between 0 and 50 Hz. The propagation speed generally increases with frequency. In some embodiments, a low-pass frequency filter is applied to limit the bandwidth to the frequency components corresponding to seismic waves.

[0038] In some embodiments, a bandpass frequency filter is applied to limit the bandwidth to the useful components. The low and / or high cutoff frequencies of this filter are adjusted during a calibration phase described later to reduce the impact of ambient noise on earthquake detection.

[0039] Depending on the embodiment, the low-pass and band-pass filters are combined into a single filter, namely that the high frequency of this combined filter substantially filters frequencies above 50 Hz, but can be adjusted for a high cutoff frequency lower than 50 Hz.

[0040] Based on one or more implementation examples, a calibration is performed at the installation site to distinguish ambient noise from signals caused by an earthquake. Ambient noise includes, for example, noise generated by an elevator, traffic (road, rail, air), and various devices and machines. The calibration is performed, for example, based on a week of measurements to adjust the parameters used in the method, including one or more thresholds. The ambient noise is thus filtered to limit both false positives and false negatives.According to some embodiments, the adjustable parameters include at least one of: the lower cutoff frequency of the bandpass filter, the upper cutoff frequency of the bandpass filter, an SA threshold of magnitude of the initial trigger acceleration of earthquake detection based on the accelerometer signal, and an SB threshold of magnitude of the acceleration applied after filtering of the accelerometer signal.

[0041] There figure 3This is a flowchart of an earthquake detection method based on one or more non-limiting implementation examples. The accelerometer signal is received as input. It is checked in step 301 to see if the magnitude of the acceleration exceeds the initial trigger threshold SA. This trigger threshold is chosen to avoid unnecessary calculations and / or limit false positives. If the trigger threshold SA is not exceeded, then no further signal processing is undertaken—thus saving signal processing resources—and no earthquake is detected (step 302). If the initial trigger threshold SA is exceeded, then the signal from the accelerometer is subjected to low-pass frequency filtering (step 303), limiting the bandwidth to that of waves generated during an earthquake. However, implementing the SA threshold is optional, and it is entirely possible to proceed directly to signal filtering.In step 304, additional filtering is applied to the signal to eliminate or at least limit the influence of ambient noise. In step 305, the magnitude of the acceleration, after filtering, is compared to a threshold SB. If the threshold SB is not exceeded, then no earthquake is detected (step 302). If the threshold SB is exceeded, then an analysis of the directional components of the acceleration is performed in step 306. Depending on the results of this analysis, verified in step 307, either no earthquake is detected (step 302), or an earthquake is detected (step 308).

[0042] In some embodiments, upon detection of an earthquake, safety actions triggered by the detection may include the activation of a shut-off device for the resource associated with the meter (valve, disconnect switch, etc.). In some embodiments, upon detection of an earthquake, an alert is transmitted to a distributor or supplier of the resource and / or to a competent authority.

[0043] There figure 4 is a graph illustrating an example of a bandpass filter resulting from the combination of a low-pass filter and a high-pass filter, performing the filtering at 303 and 304. The high-pass and low-pass filters can be implemented numerically based on equations 1 and 2, respectively: 1 − e − 3 f f 0 1 ∑ 0 6 a 2 × i × x 2 × i f0 is the cutoff frequency of the high-pass filter, f1 is the cutoff frequency of the low-pass filter and f is the frequency.

[0044] Table 3 gives examples of values ​​for the different parameters: [Table 3] x = f / f1 f1 = 10 f0 = 0.5 a0 = 1 a2 = 0.694 a4 = 0.241 a6 = 0.0557 a8 = 0.009664 a10 = 0.00134 a12 = 0.000155

[0045] One or more parameters are calibrated to limit the impact of ambient noise on earthquake detection. Ambient noise can include environmental noise and / or noise generated by the resource itself (e.g., noise generated by a liquid).

[0046] There figure 5 This is a flowchart of a calibration process based on an example implementation. This flowchart adjusts several parameters. It should be noted that it is entirely possible, depending on the implementation, to adjust only some of these parameters.

[0047] The 500 calibration process illustrated by the figure 5 The process receives as input a duration 501 of the calibration data interval. This duration can be fixed or adjustable. For example, it is one week, to cover a variety of events during working days and weekends. The process also receives as input initial values ​​502 of the SA and SB thresholds and cutoff frequencies f0 (low-pass) and f1 (high-pass).

[0048] Measurements 503 are then obtained over the specified duration, and earthquake detection is performed in 504 based on these measurements. False positives 505 and false negatives 506 are then manually labeled. Parameter adjustments are made based on these findings in 507. For example, if background noise falls within the filter's frequency band, the cutoff frequencies can be adjusted to exclude these noise frequencies. If the background noise has a magnitude too high relative to the thresholds, these thresholds are raised.

[0049] The analysis of the vector components of acceleration aims to characterize the presence of P-waves or the transition from P-waves to S-waves. This analysis is based on the fact that the displacements generated by a given type of wave are collinear with each other, and that the displacements between P-waves and S-waves are orthogonal. The presence of seismic waves can therefore be determined by estimating the collinearity of the motions represented by successive measurement points, where each point represents a measurement of the acceleration in three dimensions. If collinearity is confirmed over a certain period, this can indicate the presence of a wave. Furthermore, the orthogonality of the motions between two sets of collinear points can indicate the transition from P-waves to S-waves.

[0050] There figure 6 is a flowchart of a vector component analysis method 600, based on a specific implementation example. The method of figure 6 The device receives as input (in 601) an N point cloud for measurements, with N > 1. In one embodiment, N is configurable according to the desired sensitivity, computing power, and accelerometer performance. A point cloud contains a plurality of measurement points, the number of which can vary depending on the sampling frequency. For example, a sampling frequency around 100 Hz can be considered, with between 3 and 100 points per point cloud, and up to 50 points per cloud. These values ​​are given for illustrative purposes, and other values ​​can of course be considered.

[0051] Initially, in step 602, the magnitude of the acceleration determined for a cloud is compared to a first threshold S1. This magnitude corresponds—for example—to the median of the points in the cloud, but other ways of calculating this magnitude can be considered. The threshold S1 is—for example—located between 10 mg and 100 mg. If the threshold S1 is reached or exceeded, then an estimation of the collinearity of the motions corresponding to two successive clouds is performed on M clouds, in step 603. M is taken to be greater than or equal to 2. If the motions are collinear on the M clouds, then an earthquake is detected (step 604). This corresponds to case 'i' mentioned above—P-type waves, with a relatively high acceleration magnitude exceeding a threshold S1.

[0052] However, the detected magnitude of the P-waves may be below the S1 threshold. In this case, the P-waves go undetected. However, a test is then performed at 605 to see if the magnitude is above a threshold S2, with S2 <S1. Si c'est le cas, alors on teste en 606 pour une colinéarité, la présence d'une orthogonalité en 607, suivi d'une colinéarité en 608. Chacun de ces trois tests peut être effectué sur M nuages successifs, mais le nombre de nuages peut être différent pour chacun des trois tests.

[0053] For illustrative purposes only, S1 and S2 have respective values ​​of 20 mg and 10 mg.

[0054] In one embodiment, successive point clouds are considered over time. A hyperplane is associated with each point cloud. Each plane is associated with a direction of movement. A collinearity and / or orthogonality criterion is evaluated for the directions of successive hyperplanes.

[0055] There figure 7 is a non-limiting example of method 700 for determining collinearity and orthogonality.

[0056] The method receives as input in step 701 the three-dimensional measurement points of one of the point clouds. Outlier points can then be filtered using a method known as such to limit noisy measurements, in step 702. Filtered measurement points are thus obtained in step 703. The points are then normalized in step 704. Based on these normalized points (step 705), a collinearity score is established in step 706. This score can, for example, be based on a covariance calculation. If this score is below a collinearity threshold, then the points in the cloud are considered not collinear, and the method moves on to another point cloud. This test is performed in step 707. If the collinearity score is greater than or equal to the threshold, then the hyperplane relative to the points in the cloud is determined in step 708, for example, based on a polynomial function that determines a plane minimizing the distance between the points in the cloud and this plane.The resulting hyperplane (709) is used to determine in 710 a normal vector to this hyperplane.

[0057] A normal vector is determined per cloud. For example, for two consecutive clouds n-1 and n (referenced 712 and 713 in the figure 7 Two normal vectors A and B (references 714 and 715) are obtained. An angle Θ between the two normal vectors is determined (716). Depending on the value of Θ, the collinearity or orthogonality of the two vectors is determined. The two vectors may also be neither collinear nor orthogonal. According to the present embodiment, the two vectors are considered collinear if Θ is between -10° and +10° or between 170° and 190°, and orthogonal if Θ is between -80° and -100° or between +80° and +100°.

[0058] These thresholds can optionally be adjusted, for example to take into account accelerometer dispersion.

[0059] There figure 8 shows two example graphs illustrating the application of the method according to one or more implementation examples. The upper graph (a) of the figure 8 represents the angle Θ between successive point clouds in degrees as a function of time, while the lower graph (b) represents the magnitude of the accelerations in g represented on a logarithmic scale as a function of time. The unit of time is the 10⁻¹⁰ second. Graph (a) highlights a first part 801 of the curve, representing an angle value of less than 10 degrees over a relatively long time interval. This part corresponds to a zone of collinearity. A second part 802 of the curve, following the first part, shows a sharp peak in the angle, corresponding to orthogonality, followed by a third part 803, where the angle returns to a value around 10° for a certain time interval, corresponding to a second zone of collinearity. It should be noted that the graph of the figure 8 The curve is smoothed, and therefore the previously indicated threshold value of 80° does not appear to be reached in this graph. The first collinearity zone corresponds to P-type waves, while the second collinearity zone corresponds to S-type waves, as it is preceded by a zone indicating orthogonality between the motions between the first and second collinearity zones, respectively. Graph (b) includes a horizontal line 804 corresponding to an acceleration magnitude of 20mg. It can be seen that the first collinearity zone, corresponding to P-type waves, coincides with a significant increase in the acceleration magnitude.

Claims

1. Method for detecting an earthquake implemented by a device (100) comprising at least one processor and a memory including software code, the at least one processor causing the device to implement the method when it executes the software code, the method comprising: - receiving a signal representative of measurements of a three-dimensional acceleration of the device over time, the signal being received from an accelerometer sensor; - frequency filtering of the signal (303, 304), the filtering being configured with a low cut-off frequency (f1) and a high cut-off frequency (f0) to exclude at least frequencies not corresponding to seismic wave frequencies; - determining (306, 600), from the filtered signal, data representative of directions of the acceleration over time; - an earthquake being detected (604) if a) the magnitude of the acceleration is greater (603) than a first threshold (S1) and the directions of the acceleration are substantially collinear with one another during a first time interval; or b) the directions of the acceleration are substantially collinear with one another during a second time interval (606) and the directions of the acceleration are substantially collinear with one another during a third time interval (608) subsequent to the second time interval, and the directions of the acceleration of the second interval and the third interval are substantially orthogonal (607).

2. Method according to claim 1, wherein the cut-off frequencies are adapted (507) to exclude frequencies corresponding to noise from the device environment.

3. Method according to either claim 1 or claim 2, wherein determining data representative of directions of the acceleration over time is performed only if a magnitude of the acceleration exceeds a second threshold (SA) before filtering the signal (301) and exceeds a third threshold (SB) after filtering the signal (305).

4. Method according to claim 3, wherein the second and third thresholds are adapted (507) to be above acceleration magnitudes corresponding to noise from the device environment.

5. Method according to claim 3 or claim 4, respectively, comprising adapting the cut-off frequencies, respectively adapting the second threshold and the third threshold, on the basis of historical labeled data of the acceleration at a device operating location.

6. Method according to any of claims 1 to 5, wherein a determination of the collinearity of directions of the acceleration is carried out, comprising: - determining a hyperplane (709) with respect to N consecutive measurement points from the signal and determining a direction normal to this plane, where N>1; - iterating the previous step on M sets of N points of a given time interval, where M>1; - concluding (717) that there is substantial collinearity over the given time interval if the angles of the N normal directions taken in pairs are within two ranges comprising 0° and 180°, respectively.

7. Method according to any of claims 1 to 6, wherein a determination of the orthogonality of directions of the acceleration is carried out, comprising: - determining a hyperplane (709) with respect to N consecutive measurement points from the signal and determining a direction normal to this plane, where N>1; - iterating the previous step on two sets of N points of a given time interval; - concluding (717) that there is substantial orthogonality if the angle between the normal directions of the two hyperplanes determined in the previous step are within two ranges comprising 90° and 270°, respectively.

8. Method according to any of claims 1 to 7, comprising, in response to the detection of an earthquake, generating a control signal for equipment securing a resource metered by the device.

9. Method according to any of claims 1 to 8, comprising, in response to the detection of an earthquake, generating an alert message to a server.

10. Method according to any of claims 1 to 9, wherein an earthquake is detected in case b) only if the magnitude of the acceleration exceeds a fourth threshold (S2), lower than the first threshold.

11. Earthquake detection device (100) comprising a memory including software code and a processor, the processor being adapted, when it executes the code, to cause the device to implement the method according to any of claims 1 to 9.

12. Device according to claim 11, comprising the three-dimensional accelerometer (101).

13. Computer program product comprising instructions which, when executed by at least one processor, cause the method according to any of claims 1 to 10 to be executed by said at least one processor.

14. Non-transitory storage medium comprising instructions which, when executed by the at least one processor, cause the method according to any of claims 1 to 10 to be executed by said at least one processor.