ES2525517B2 - Method and system for measuring vibrations - Google Patents

Abstract

Method and system for measuring vibrations in an object (4, 9) comprising capturing an image by means of a camera (1), where said camera (1) has an acquisition frequency of at least twice the vibration frequency to be recorded; select a region of interest within the captured image by defining a scene (2); quantify the number of pixels that vary in the scene (2); and determining the existence of a vibration pattern by means of a Fourier transform on the scene (2), also calculating the frequency of said vibration pattern.

Description

image 1

METHOD AND SYSTEM FOR MEASURING VIBRATIONS

The object of the present invention is a non-invasive method for measuring vibrations, that is, a method where no contact is used to measure vibrations.

5 imperceptible to the human eye. This method uses a video camera, so that by processing the recorded sequence it is possible to detect movements that, apparently, do not cause a change in the image, as well as to detect its frequency of movement.

10 State of the art

The detection of movements and vibrations is a topic of interest in different scientific fields. Thus, for example, in engineering and architecture, the study of vibrations is used to diagnose the state of health of the structures and forces to which they are

15 submitted.

The measurement of vibrations is possible by acoustic methods. Thus, in certain situations the vibrations produce audible effects and with a microphone its detection is possible. However, in most cases this is not possible and it is necessary to go

20 to more sophisticated techniques.

Another technique known in the state of the art is the use of accelerometers. These systems are connected to the surface or structure under study and record the acceleration suffered by it due to dynamic forces or impacts. Despite what

25 extended of its use, it presents several drawbacks, since it is an invasive system that requires its own installation and wiring, as well as an economic cost to consider [Nassif HN, Gindy M, Davis J. Comparison of laser Doppler vibrometer with contact sensors for monitoring bridge deflection and vibration. NDT & E Int. 2005; 38 (3): 213-128].

30 On the other hand, in many cases the use of accelerometers is not indicated since, for reasons of safety, inaccessibility or integrity of the object to be measured, it is not possible to fix the system and the wiring. On these occasions, the use of non-invasive methods of distance measurement, such as Doppler interferometry, is required.

35 Doppler interferometry-based methods use interference between a reference beam and one reflected on the surface to be studied to measure the velocity of displacement. Although it is a very precise method, it requires the use of a laser beam and a very short working distance. Additionally, the cost of this method makes it prohibitive for most applications [Castellini P, Martarelli M, Tomasini EP. Lasser Doppler

image2

5 Vibrometry: Development of advanced solutions answering to technology’s needs. Mechanical systems and signal processing. 2006; 20: 1265-1285].

In recent years, motion and vibration detection techniques have appeared based on the detection of Speckle patterns [Valero, E., V. Micó, Z. Zalevsky, and J.

10 Garcia. “Depth sensing using coherence mapping.” Opt. Commun. 283 no. 16 (2010): 3122-3128].

These systems have resulted in 3D detection systems, such as Kinect® [http://en.wikipedia.org/wiki/Kinect] and audio capture methods using optical techniques (as in WO / 2007/043036, US2009 / 096783 or US 2010/226543), as well as applications in biomedicine [A. Shenhav, Z. Brodie, Y. Beiderman, J. Garcia, V. Micó, and

Z. Zalevsky “Optical Sensor for remote estimation of alcohol concentration in blood stream” Opt. Commun. 289, 15, 149-157 (2013)].

20 Despite the advantages of these systems, these methods have the disadvantage of requiring the projection of a light pattern by means of low power lasers, which limits their scope, accuracy and use.

Artificial vision techniques allow remote movement to be detected and measured without

25 need to use lasers or contact probes. In general, these methods use pattern recognition by convolution, which makes the technique very sensitive to noise and not very accurate. In addition to these inconveniences, the detection of rapid movements

o High frequencies require high speed and high resolution video systems, which significantly increases the final cost of the technique.

30 However, there are techniques to, from the detection and recognition of certain patterns in an object, determine its position with great precision, even at sub-pixel resolutions.

35 Although the image resolution is limited by the quality of the optical sensor, under certain conditions it is possible to obtain information above the spatial resolution limit. These techniques are known as sub-pixel techniques and take advantage of information about the object that is known a priori in order to increase the capabilities of the system in the detection of objects.

image3

5

The most common technique of obtaining sub-pixel resolution is to introduce a target of known geometry into the scene. By recognizing shapes and adjusting the geometry detected to the real one, it is possible to locate the object with accuracy of up to 0.02 pixels [D. Mas, J. Espinosa, A. B. Roig, B. Ferrer, J. Pérez, C. Illueca “Measurement of

10 wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques ”Applied Optics, 51, 14, 2664-2671 (2011)].

However, to apply this technique it is essential to adhere to the vibrant object a target outside the scene, which can sometimes be complicated or even unfeasible.

15 The main problem with standard video cameras is that the temporal resolution (frames per second -fps) is usually limited to 30-50 fps, which, according to the Nyquist criteria, does not allow its use to measure frequencies above 15-25 Hz. A vibration recording system should have an acquisition capacity above

20,500 fps in order to opt for a wide range of applications (civil structures tend to vibrate below 200 Hz and the fundamental frequency of the human voice is around 250 Hz).

At this point the limitations of the electronics must be taken into account. Data flow

25 per second that a video camera can process and store depends on both the frame size (pixels) and the number of frames per second that the camera is capable of capturing. For a constant flow of data, increasing the acquisition speed implies decreasing the frame size and vice versa.

30 Thus, the higher the acquisition speed of the camera, the lower its spatial resolution will be and therefore will provide lower image quality. As a consequence of this, increasing the flow of data implies increasing the price of the device significantly, which can make the final solution unprofitable for most applications.

35

image4

Description of the invention

The present invention aims at a non-invasive vibration measurement method, which does not require external elements, such as lasers or Speckle patterns and with a cost

5 reduced. For this, the present invention is based on an analysis of the lighting changes produced by a moving object, from which it is determined whether it vibrates and, consequently, its vibration frequency.

Preferably, the method of the invention comprises:

10 capturing a succession of images of said object with a camera, where said camera has an acquisition frequency of at least twice the frequency of the vibrations to be measured;

select a region of interest within the sequence of captured images defining a scene; 15 identify a plurality of pixels whose luminance varies in the scene;

perform a multilevel thresholding of the sequence within the region of interest, said thresholding being defined according to a predetermined luminance level, so that a sequence of binary images is obtained;

add the active pixels in each image and represent the variation of the number of 20 pixels as a function of time; perform a Fourier transform on the representation obtained for each level of binary luminance; compose the Fourier transforms obtained for each level as a characterization signal of the scene; 25 obtain the vibration frequency of the object as the one that has the greatest amplitude in the characterization signal of the scene.

The method object of the invention allows the measurement of vibrations in objects of a wide frequency range by capturing and subsequent processing of a sequence of

30 video The invention allows measurements to be made from sequences with very low image quality and without the need for additional lighting systems or targets.

Thus, with respect to existing systems, the invention is applied without contact and, logically, without altering the structure or surface under study. In addition, a distance close to the object under study is not necessary, since the distance to said object is

image5

function of the video system used, allowing the study of inaccessible or insecure structures. Another technical problem that is solved, derived from the use of image analysis, compared to other systems, is that it avoids the problem of signal attenuation as a function of distance.

5

On the other hand, the invention does not require special lighting and / or specific instrumentation, which also enables its implementation in low-cost cameras.

Apart from the measurement, the invention allows direct visualization of the object and further analysis.

10 sophisticated based on algorithms that can be implemented in the camera itself.

Finally, it should be noted that, being based on images, its use is possible for both macroscopic and microscopic objects.

Throughout the description and the claims the word "comprises" and its variants are not intended to exclude other technical characteristics, additives, components or steps. For those skilled in the art, other objects, advantages and features of the invention will be derived partly from the description and partly from the practice of the invention. The

The following examples and drawings are provided by way of illustration, and are not intended to restrict the present invention. In addition, the present invention covers all possible combinations of particular and preferred embodiments indicated herein.

Brief description of the figures

A series of drawings that help to better understand the invention and that expressly relate to an embodiment of said invention that is presented as a non-limiting example thereof is described very briefly below.

30 FIG. 1 shows a schematic of the assembly required to capture a scene.

FIG. 2 shows three images where Fig. 2a shows a scene captured and adapted to the sensor grid in the camera. Fig. 2b shows the image detected by the digital sensor. Finally, in Fig.2c the image detected by

35 the digital sensor after a shift of the original image of 0.25 pixels.

image6

FIG. 3 shows four images where in Fig. 3a an object captured with four levels of gray (0-3) is shown on a uniform background. An image with values greater than 0. is shown in Fig. 3b. An image with values greater than 1 is shown in Fig. 3c.

5 and, finally, in Fig. 3d an image with values greater than 2 is shown.

FIG. 4 shows an example of a region of interest in grayscale within an image captured in a practical example for determining the vibration of a 440 Hz tuning fork.

10 FIG. 5 shows a sequence of thresholds from level 32 to 255 every 32 levels of the image of Figure 4.

FIG. 6 shows the product of the Fourier transforms obtained from the variation of pixels in each threshold sequence of Figure 5.

FIG. 7 shows the product of the Fourier transforms obtained from the variation of pixels in each threshold sequence for an example of a speaker vibrating at 290 Hz.

twenty

Statement of a detailed embodiment of the invention

The present invention is based on sub-pixel techniques where movement detection with high precision is possible. For a better understanding of the invention,

25 considers a specific object and it is detected that this object has moved when its detection on the camera's detection matrix passes from one pixel to another pixel. Thus, in image plane, the nominal resolution of the camera will be 1 pixel.

It is considered below that the object to be detected is smaller than a pixel. In that

30 case, the camera will not be able to solve it and the whole pixel provides an answer regardless of the specific point where the object is within that pixel. If the object below the pixel size (sub-pixel object) is found to be on one side of the useful area of the camera's optical sensor, a small displacement will be sufficient to move to another area. Thus, motion detection does not require

35 offset of a full pixel.

image7

The displaced point moves within the new pixel without the movement being detected and only when it changes again, a new movement is detected. This causes the motion detection not to be continuous, but jumps occur.

5

To avoid this problem, it must be ensured that a second point performs the detection once the first is amortized. With two points in different pixels, the first one located in the right half of the sensor and the second one in the left half, half-pixel jumps can be detected. In general, as many additional points are needed as

10 pixel fractions are wanted to be detected.

In [D. Mas, B. Ferrer, J. T. Sheridan, J. Espinosa “Resolution limits to object tracking in subpixel accuracies” Opt. Letters, 53, 23 4877-4879 (2012)] demonstrates theoretically that the detection capacity of this system is of the order of the inverse of the number of

15 total pixels in the detector, being able to reach resolutions of micro-pixels.

The invention presented is about the use of the exposed theory for the measurement of vibrations. As stated above, objects that allow sub-pixel resolution have specific properties and are not natural objects. Therefore, the use of this technique to its full potential requires the design of special targets that should adhere to the subject under study. However, the invention uses everyday objects, at the cost of losing resolution with respect to the theoretical limit, as shown in Figures 1 and

2.

More specifically, the invention comprises a first capture of an image of the object

(4) by means of a camera (1) whose acquisition frequency must be at least twice the vibration frequency to be recorded.

In the present invention, scene (2) means the image of a region of interest of a particular object (4) captured by the camera (1).

The objective (3) is variable, depending on the distance of the object (4) from the camera (1), all in order to maximize the size of the object (4) or the area of interest on the sensor the camera (1).

35

image8

Real objects (4), in general, have complex shapes, which do not fit the grid structure (5) of the digital camera sensor (usually CCD and / or CMOS). Thus, it is possible to find pixels completely occupied by the object and pixels in which the area is shared by the object and the background (6).

5

If, simplifying, we admit that the sensor will only give a white or black response, the contour pixel will be assigned to one of those values depending on whether the dominant area on the pixel belongs to the object or the background and the final image will no longer have a soft profile but trimmed (7). If the object moves slightly, even if it is an amount less than a

10 pixel, the proportion of areas in some of the contour pixels will change, which will produce a slight change in the profile (8). This small change will only affect a few pixels but it will be enough to be detected. Displacements greater than one pixel can be easily detected and are not subject to this patent.

15 Depending on the complexity of the object, a small movement will involve a change in the state of different pixels. Although simple movement is easy to detect, in a complete scene it is difficult to control which pixels have changed and which direction, so the proposed method cannot fully track the object.

20 However, if the object vibrates, there will be a change of pixels with a defined pattern, so that certain pixels will be activated and deactivated at regular intervals. Simply by counting the number of pixels that change and performing a Fourier analysis of the captured image it is possible to detect the existence of said vibration pattern and determine its frequency.

25 In any case, the objects are not pure black and white, nor have well-defined contours, but the transitions are smooth. Assuming an image in gray tones, a movement will be seen as a slight change in the luminance of some pixels due to a change in the dominant region in the detector area. Those changes are usually

30 subtle and difficult to appreciate, which makes it difficult to directly apply the method explained above. In addition, the movement of the image can be subtle and not affect the contour of the object but the shadows or the light diffused by the object, producing small alterations.

35 In any case, a movement will be translated as changes in the distribution of

image9

luminances in the object to be quantified. We can, however, transform the object into a binary object through multilevel thresholds.

In figure 3 it is considered a simple object (9). This object has been considered as only

5 has 4 levels of gray. From the object we can obtain the different thresholds by determining the pixels whose value is greater than zero (10), greater than one (11) and greater than two (12). These profiles are binary images to which the method explained above applies.

10 The idea is easily generalizable to a scene with N levels, from which N-1 binary sequences are obtained for analysis. Admitting that the object under study will move in a homogeneous way, all levels will change in a similar way, so that in general it will not be necessary to study all levels.

15 One possible limitation of the method is that any variation in the scene due to movement, shadows or change in lighting will produce a change in the different gray levels detected and, therefore, it will not be easy to discriminate which changes are due to movements and which are due to other causes.

20 As indicated, a vibrating object will produce periodic alterations in its luminance. These periodic alterations will be reflected in each binarized sequence and can be identified on the noise by a Fourier analysis. In addition, having multiple binary sequences provides redundant information that can be used to reinforce detection. The average or the product of the transformed obtained

25 at each level will reinforce the detection peaks and cancel the image noise.

Example of measurement in a tuning fork at 440 Hz

The explained method has been used to determine the vibration of a 440 Hz fingerboard.

30 The camera used has been a Casio EXFH100 recording at 1000 fps with a resolution of 224x64 pixels (width by height) located 75 cm from the fingerboard. Figure 3 shows the fretboard, that is, the object (9), on a uniform background. To illuminate, the ambient light of the laboratory is used and a 50 W halogen lamp connected to a direct current transformer to avoid oscillations of light due to alternating current (100 Hz).

35 The distance between the lamp and the fretboard is 50 cm with a lighting angle of 45º

image10

with respect to the camera-object axis.

After hitting the fretboard with a rubber hammer, the scene was filmed. The first three seconds of filming are discarded to minimize the effect of the vibration of the camera produced when the shot is pressed. A sequence of 1 second (1000 frames) has been taken for analysis.

From the sequence, the study of vibration has focused on the top of a rod. A 15 x 12 pixel rectangle has been selected to which the method has been applied

10 described.

The procedure followed once the area of interest has been established has been the following: the image has been converted to gray levels and the dynamic range of the image has been extended through a redefinition of black and white and the linear transformation of

15 luminances (figure 4). Subsequently, 8 threshold levels have been established, each 32 levels of gray, (figure 5) and the variation in the number of white pixels with respect to the first frame has been analyzed.

The variation obtained has been studied by Fourier analysis. The transformed

20 obtained for each threshold have been multiplied in order to reinforce the peaks and cancel the noise. Figure 6 shows the product of Fourier transforms with the obtained frequency peak, with an error of ± 1 Hz. It can be clearly seen that the method detects with great precision the frequency of movement of the tuning fork, providing a result of 441 Hz

25

Example of measurement on a 290 Hz speaker

Following the same method, the vibration of a speaker membrane vibrating at 290 Hz has been studied. The distance between the camera and the speaker is 75 cm. To illuminate the

A 50 W halogen lamp connected to a direct current transformer has been used. Since the loudspeaker membrane is black-matt, the luminaire was placed 50 cm in front of the object, forming an angle of 15º from the imaginary line that joins the object and the camera.

35 As before, a sequence of several seconds at 1000 fps and 224x64 pixels of resolution was taken. The first three seconds were discarded by the camera oscillation being analyzed 1000 frames. The speaker volume was set below 35 dB, so that the emitted sound was below the ambient noise.

image11

5 From the previous sequence, a region of interest of high contrast has been analyzed in order to maximize the number of levels and thus ensure optimal detection.

Following exactly the process described for the fingerboard, the Fourier transform of the number of pixels in each threshold has been obtained. The product of the eight transforms 10 obtained is shown in Figure 7, where it is appreciated that the method provides satisfactory results with an error of ± 1 Hz

The present method can be implemented in different ways, either on a personal computer, or on a processor intended for this purpose and integrated into the camera itself. In any case, the system comprises at least one camera, one or more processors, a

or more memories and one or more programs in which the program (s) are stored in the memory and configured to be executed by at least the processor (s), including the programs instructions to execute the described method.

20 Finally, the method has multiple possible uses without modification of its essential characteristics such as:

-Measurement of small vibrations in small objects. If the object is small and irregularly shaped, it is difficult to project a speckle pattern or use contact methods. -Measurement of vibrations in civil structures. It is particularly interesting for measuring inaccessible structures, or whose proximity implies danger. -Interception of mobile conversations by reading terminal vibration. 30 -Measurement of periodic variations in astronomical or satellite images, such as object tracking, pulsations, variations in brightness / reflectivity. -Make a map of vibrations of a scene through a unique sequence and zonal analysis. -Measure of vital signs (pulse and breathing) through webcam cameras. 35 -Measure of periodic variations in biological images.

image12

-

Detection of changes in low resolution images, such as resonances,

X-rays

-

Monitoring of ultra-slow periodic variations by combining the

explained technique and time-lapse photography.

5

In general, since the method is based on an image analysis, it is possible to apply it to any sequence or video stack of any source in which a periodic change is suspected. The limit frequency of detection will depend on the frequency of temporal sampling, which may be a few tenths or hundredths of Hertzio (time-lapse photography) or

10 of several hundred Hertz (high speed video).

Claims (1)

image 1