Patent Description:
The invention further relates to a method for evaluating leaks in a device according to the preamble of claim <NUM>.

The present application relates to testing for and detecting leakage in hermetically sealed devices, and more specifically to evaluation of the water- and air-tightness of leakproof device modules or assemblies.

Mobile devices, such as cellular phones and tablets, are often protected from water damage and/or contamination by leakproof cases. In some instances, such cases may be integrated into the mobile device by the device manufacturer. However, damage to casing components, misapplication of sealant or adhesive, or other manufacturing irregularities can cause otherwise "waterproof" or "leakproof" outer or inner casings to fail.

For the casings of mobile devices, the cover glass, display module and frames are usually adhered together. Detection of leakage in assembled casings is important to guarantee the performance and integrity of the final product, and also for detecting and correcting errors in the manufacturing process (e.g., by determining which layer or component is creating the leak).

Efforts at leakage detection have included micro-scale mechanical structures to develop a gas "sniffing" method of detection, in which a leak is detected by detecting the presence and concentration of a particular gas. However, the gas may diffuse and/or dilute or present in small, undetectable flows, thereby impeding the precise location and character of the leak. Moreover, "sniffer" devices are generally too large for use in detecting leaks on a small scale, such as in mobile devices.

An imaging system and a method of the above kinds are disclosed in <CIT>. The imaging system comprises a point light source configured to emit a light signal and a collimation lens positioned to receive the light signal, the collimation lens configured to emit a collimated light signal. An imaging telescope is positioned to receive the collimated light signal, and a spatial filter positioned at a plane of the imaging telescope is configured to pass a filtered light signal. An image sensor is positioned at an output site of the imaging telescope such that the image sensor is positioned to receive the filtered light signal. A device under test is arranged within a chamber outside the optical path of the imaging system. A source of pressurized gas is provided and configured to pressurize an interior volume of the device under test. At an outlet of the chamber, gas leaking from the device under test is accumulated in a closed space formation member also located outside the optical path of the imaging system, but having an outlet in the optical path of the imaging system located between the collimation lens and the input side of the imaging telescope. In such a way, the imaging system is configured to detect a leak of the pressurized gas from the device under test, whereby the imaging system is configured to provide optical leak detection for the device under test.

In the scientific article of<NPL>, an optical system is disclosed having a point light source configured to emit a light signal, a collimation lens positioned to receive the light signal, the collimation lens configured to emit a collimated light signal, a nozzle for emitting test media in beam direction after the collimation lens, a decollimating lens located in beam direction after the nozzle, a rainbow filter located in beam direction after the decollimating lens and a camera system located in beam direction after the rainbow filter for acquiring a rainbow Schlieren image. With such an arrangement, the structure of complex supersonic flows requiring high-resolution, non-intrusive measurements across the field can be investigated in a small-scale environment.

<CIT> discloses a method and an apparatus for detecting leaks in hollow fibre membrane modules. Hollow fibre membrane modules comprise a housing having one or more hollow fibre bundles positioned therein with at least one end of each bundle being sealed by a cementing layer. A pressurized gas is applied to the external surfaces of the hollow fibres. The gas which is used must have a refractive index different from the refractive index of the ambient atmosphere. The atmospheric volume adjacent the sealed end of the module is optically monitored for refraction patterns caused by gas leaking through the sealed end into the volume. The optical system includes a light source and components for directing light from the source along a mixed divergent/convergent optical path including the monitored volume. Light which is passed through the monitored volume is directed to an optical display where the refraction patterns of the leaking gas will be visible. The method and apparatus permit leaks to be located without the use of liquids.

<CIT> discloses an apparatus for defective inspection of a closed container having two concave mirrors arranged opposite to each other and providing a collimated light beam, the light originating from a point light source. The container is located in an airtight chamber whereas the inside of the chamber may be rapidly sucked to a prescribed vacuum condition by a vacuum pump. Opposite the point light source a video camera is provided to take images before and after a suction for pressure reduction so to evaluate by means of a shadow-graph method whether a leak in the container under inspection is present or not.

<CIT> discloses a test unit for investigating the spontaneous combustion of a kind of a high pressure combustible gas leak and shockwaves in use by igniting leaked gas. Light originating from a point light source is collimated by a concave mirror, whereas the leaked gas is directed towards the collimated beam portion downstream of said concave mirror. By means of another concave mirror the light is directed towards a mirror within which the edge of a knife is positioned for filtering the light having traversed leaked gas whereas a high-speed camera serves for analysing the flow of the leaked gas.

<CIT> discloses an inspection method capable for optically inspecting defects of a weld miss, pin hole or the like of a vessel by utilizing the Schlieren phenomenon. A vessel to be inspected is closed up tight and positioned in a beam converged by a condenser lens of an optical system capable of observing the Schlieren phenomenon. Compressed gas of a refractive index of light or a temperature differing from them of an ambient atmosphere of the vessel is supplied into the vessel. The turbulence phenomenon of the atmosphere generated by gas leaked from the vessel is detected by a light-reception part after having passed a knife-edge blade, and the defect existence of the vessel is inspected.

What is needed is an improvement over the foregoing and providing a precise location and character of a possible leak of a device under test.

The present disclosure is directed to an imaging system and method for leakage detection using Schlieren imaging to locate and characterize a flow of pressurized gas with a refractive index different than ambient air. In particular, a schlieren imaging system includes a collimated light, a knife-edge spatial filter and a 4F telescopic imaging system to create an image of a device under test (DUT). The DUT is pressurized and monitored for leaks. When a leak is present and in the monitored plane including the DUT, contrast variation illustrates the presence, location and character of the leak. For example, a waterproof/leakproof mobile device may be evaluated for leakage between layers of modules, such as leaks in the housing of a waterproof electronics case. This detection can allow identification and characterization of the leak point via visual identification.

In one embodiment, the present disclosure provides an imaging system including a point light source configured to emit a light signal, a parabolic collimation mirror positioned to receive the light signal the parabolic collimation mirror configured to emit a collimated light signal, a parabolic collection mirror positioned to receive the collimated light signal, a spatial filter positioned at a Fourier plane of the parabolic collection mirror, the spatial filter configured to pass a filtered light signal, an image sensor positioned at an output side of the parabolic collection mirror, such that the image sensor is positioned to receive the filtered light signal, a device under test positioned at an object plane between the parabolic collimation mirror and the parabolic collection mirror, and a source of pressurized gas configured to pressurize an interior volume of the device under test, whereby the imaging system is configured to optically detect a leak of the pressurized gas from the device under test.

In aspects, the imaging system may include a gas with a refractive index different than ambient air. The device under test may be configured as a hermetically sealed device. The light signal is an incoherent light signal, such as a signal emitted by a light-emitting diode. The light may be a coherent light signal, such as a light signal is emitted by a laser.

In additional aspects, the image sensor may be an imaging device operably connected to a controller programmed to evaluate a detected image to determine the presence of a leak by assessing the presence or absence of contrast variation in the detected image. The controller may evaluate a detected image utilizing machine learning methods, such as evaluating a detected image as a machine learning regression problem. The controller may evaluate a detected image utilizing deep learning methods, such as evaluating a detected image as a deep learning classification problem. The controller may evaluate a detected image as a deep learning detector problem, such as evaluating a detected image as a deep learning segmentation problem.

In another embodiment, the present disclosure provides a method for evaluating leaks in a device, including emitting a light signal, modifying the light signal to create a collimated light signal, filtering the light signal to create a filtered light signal, sensing the filtered light signal to create a sensed image, placing a device under test in an object plane along the collimated light signal such that an image of the device under test appears in the sensed image, directing a pressurized gas into an interior volume of the device under test, evaluating contrast in the sensed image, and based on the step of evaluating contrast, determining whether the pressurized gas is leaking from the interior volume of the device under test.

In aspects, the method may include pressurized gas having a refractive index different than ambient air. The method may further include determining the magnitude and character of the leak in the device under test based on the contrast in the sensed image. The device under test may be configured to be a hermetically sealed device. The step of emitting the light signal may include emitting an incoherent light signal. The step of emitting the light signal may include emitting a coherent light signal. The step of sensing the filtered light signal to create the sensed image may include capturing the sensed image with an image sensor. The step of evaluating contrast in the sensed image may be performed by a controller operably connected to the image sensor.

According to the invention, the present disclosure provides an imaging system including a point light source configured to emit a light signal, a collimation lens positioned to receive the light signal. The collimation lens configured to emit a collimated light signal. The system also includes a 4F imaging telescope positioned to receive the collimated light signal and a spatial filter positioned at a Fourier plane of the 4F imaging telescope, the spatial filter configured to pass a filtered light signal. The system further includes an image sensor positioned at an output side of the 4F imaging telescope, such that the image sensor is positioned to receive the filtered light signal. A device under test is positioned at an object plane between the collimation lens and the 4F imaging telescope, and a source of pressurized gas is configured to pressurize an interior volume of the device under test, the imaging system configured to detect a leak of the pressurized gas from the device under test. In this way, the imaging system is configured to provide optical leak detection for the device under test.

In aspects, the gas may have a refractive index different than ambient air. The device under test may be configured as a hermetically sealed device. The spatial filter may be a knife-edge filter. The light signal may be an incoherent light signal, such as a light signal emitted by a light-emitting diode. The light signal may be a coherent light signal, such as a light signal emitted by a laser. The image sensor may be a camera.

In other aspects, the image sensor may be an imaging device operably connected to a controller. The controller may be programmed with processing instructions to evaluate a detected image to determine the presence of a leak by assessing the presence or absence of contrast variation in the detected image.

In yet another embodiment, the present disclosure provides a method for evaluating leaks in a device, including emitting a light signal, passing the light signal through a collimation lens to create a collimated light signal, passing the collimated light signal through a 4F imaging telescope and a spatial filter positioned at a Fourier plane of the 4F imaging telescope to create a filtered light signal, sensing the filtered light signal to create a sensed image, placing a device under test in an object plane between the collimation lens and the 4F imaging telescope such that an image of the device under test appears in the sensed image, and evaluating contrast in the sensed image to determine whether the device under test has a leak.

In aspects, the method can further include evaluating contrast in the sensed image to determine the magnitude and character of the leak in the device under test. The device under test may be configured as a hermetically sealed device. The step of emitting the light signal may include emitting an incoherent light signal. The step of emitting the light signal may include emitting a coherent light signal. The step of sensing the filtered light signal to create the sensed image may include capturing the sensed image with an image sensor. The step of evaluating contrast in the sensed image may be performed by a controller operably connected to the image sensor.

The above mentioned and other features and objects of this invention, and the manner of attaining them, will become more apparent and the invention itself will be better understood by reference to the following description of embodiments of the invention taken in conjunction with the accompanying drawings (from which only the <FIG> concerns the invention), wherein:.

Corresponding reference characters indicate corresponding parts throughout the several views. Although the exemplifications set out herein illustrate embodiments of the invention, the embodiments disclosed below are not intended to be exhaustive or to be construed as limiting the scope of the invention to the precise form disclosed.

The present disclosure is directed to methods for inspecting and evaluating display modules using leak detection system <NUM>, shown in <FIG>, and other similarly arranged leak detection systems. As described in detail below, system <NUM> is a schlieren imaging system configured to generate an image of a plane in which a leak, which is a disruptive flow of gas through an otherwise uniform ambient atmosphere such as air, has a refractive index differential due to density variation arising from the composition, pressure, speed, and/or temperature of the leak flow. This refractive index differential causes the light rays projected by system <NUM> to change direction or phase. After proper spatial filtering, this difference can be observed as contrast variation which shows an optical "image" of a gas leak.

System <NUM> can be used to create an image which enables leak detection in two dimensions, showing leak position and character. Compared to conventional "sniffing" leak detection systems, the present system <NUM> and its method of use gives an evaluator precise leakage location information at the micron scale, which can in turn be used to check the seal quality of water/leak proof devices such as DUT <NUM> (<FIG>).

As further described in detail below and shown in <FIG>, system <NUM>' is an alternative imaging device which may be used interchangeably with system <NUM> to achieve the same overall result of leak detection and characterization. Descriptions herein pertaining to system <NUM> also apply to system <NUM>', except as otherwise explicitly stated.

Referring to <FIG>, leak detection system <NUM> includes a point light source <NUM> which issues a light signal <NUM> toward and through collimation lens <NUM>. The signal <NUM> from light source <NUM> may be either coherent, such as a laser light signal, or incoherent, such as an incandescent or LED light signal. In the illustrated embodiment, light source <NUM> acts as a point source of light.

Collimation lens <NUM> issues collimated light signal <NUM> to 4F imaging telescope <NUM> via object plane OP, which is the plane of examination for a device under test (DUT) such as DUT <NUM> shown in <FIG> and further described below. 4F imaging telescope <NUM> includes telescope-type lenses <NUM> and <NUM> defining Fourier plane FP, and a filter <NUM> is placed coincident with plane FP.

Filter <NUM> is knife-edge or spatial filter which selectively blocks and passes spatial frequency information from the DUT, such that any index variation caused by a leak flow at object plane OP is detected as contrast variation in image plane IP. In particular, filter <NUM> passes filtered signal <NUM> which is received at image plane IP, which is at a location on an output side of telescope <NUM> (relative to light source <NUM>). Image plane IP may include an imaging device <NUM>, such as a camera or other imaging sensor. Signal <NUM> filters out some spatial frequency information from the incoming collimated light signal <NUM>, thereby maximizing the contrast of the schlieren image received at image plane IP.

As illustrated in <FIG>, in one exemplary embodiment, 4F imaging telescope <NUM> provides varying magnification depending on a combination of focal lengths of lenses <NUM>, <NUM>, such that the area of inspection at object plane OP can be altered to view more or less surface area of the DUT. Collimation lens <NUM> collects and collimates light signal <NUM> from light source <NUM>, which is incident on the DUT as back side illumination. 4F imaging system <NUM> images the DUT on image plane IP with filter <NUM>, being a knife-edge filter as described above, at Fourier plane FP, which gives contrast variation in the image when the DUT has refractive index variation due to gas leakage.

In use, a device or module to be evaluated (the DUT) for leaks gas can be placed at the object plane OP and imaged by a camera or other imaging sensor placed at the image plane IP. For example and as further described below with respect to <FIG>, the DUT may be a mobile phone or tablet having a thickness defined between its top (e.g., user-facing) and bottom layers. The DUT may be placed into object plane OP such that its thickness is in the viewing area, and leaks from the top layer, bottom layer or an intermediate layer may be detected.

Turning now to <FIG>, a photograph image shows simulation results of imaging when a gas leak is modelled by an object plane OP in a DUT with small refractive index changes, in which leak detection system <NUM> of <FIG> is used, as described above. As illustrated, spatial filtering clearly creates contrast variation in the image at the center of the image.

Turning now to <FIG>, a photograph image shows experimental results of imaging a gas flow with leak detection system <NUM>, in which light source <NUM> is a coherent laser light source generating a coherent signal <NUM> with a <NUM> wavelength. Filter <NUM> was a knife-edge spatial filter at the Fourier plane FP of the 4F imaging telescope <NUM>, as described above.

In this experiment, a tip <NUM> having a <NUM> diameter was placed at object plane OP. Tip <NUM> is the outlet end of an air dust blower conduit, with the inlet end (not shown) connected to a source of difluoroethane gas. At left is a captured image taken at image plane IP, in which the air dust blower was not activated and no difluoroethane gas was observed emanating from the tip <NUM>. At right is another captured image taken at image plane IP, in which the air dust blower was activated such that difluoroethane gas was flowing from the tip <NUM>. This flow of difluoroethane gas was clearly observed as a contrast variation CV1 in object plane OP, which was recorded at the image plane IP. From this experiment, it is shown that the location and extent of a leak of comparable magnitude from a device under test (DUT) would be similarly detectable by leak detection system <NUM>.

<FIG> shows another pair of photograph images taken at image plane IP. In this experiment, a gas flow was imaged with leak detection system <NUM>, using an incoherent light source <NUM>. In particular, light source <NUM> was a white LED emitting incoherent light signal <NUM>. Filter <NUM> was a knife-edge spatial filter at the Fourier plane FP of the 4F imaging system <NUM>, as described above.

In this experiment, a tip <NUM> having a pair of gas needles each defining a <NUM> inner diameter, and separated by approximately <NUM>, was placed at object plane OP. Tip <NUM> is the outlet end of a helium distribution conduit, with the inlet end (not shown) connected to a source of helium gas. At left is a captured image taken at image plane IP, in which the helium was not activated and no helium gas was observed emanating from the tip <NUM>. At right is another captured image taken at image plane IP, in which the helium distribution conduit was opened such that helium gas was flowing from the tip <NUM>. The resulting dual flows of helium gas were clearly observed as a contrast variation CV2 in object plant OP, which was recorded at the image plane IP. From this experiment, it is shown that the location and extent of a leak of comparable magnitude from a device under test (DUT) would be similarly detectable by leak detection system <NUM>.

Turning to <FIG>, shows one exemplary device under test (DUT) <NUM> which can be evaluated by leak detection system <NUM>. DUT <NUM> includes top module <NUM>, which may be a layer of glass for example, and bottom module <NUM>, which may be a metal or plastic casing for example. Frame <NUM> may be disposed between the top module <NUM> and the bottom module <NUM>, such that a sealed interior space (i.e., volume) is created within DUT <NUM>.

To hermetically seal the interior space, beads of sealant/adhesive 58A and 58B may be placed between frame <NUM> and top and bottom modules <NUM>, <NUM> respectively. Beads 58A and 58B may extend around the entire periphery of the abutting contact between frame <NUM> and top and bottom modules <NUM>, <NUM>, respectively, such that no air or water can flow into or out of the hermetically sealed space. However, beads 58A and/or 58B may not be uniform or continuous, such as in the case of manufacturing or automation defects. As noted above, leak detection system <NUM> can be utilized to identify, assess and characterize any leaks which may occur in DUT <NUM>.

As depicted in <FIG>, a motive flow <NUM> of pressurized gas may be induced within the sealed interior chamber of DUT <NUM>. For example, the interior chamber may be pressurized, such as via an incoming flow of gas through a port formed in top module <NUM>, bottom module <NUM> or frame <NUM>. The interior pressure induces a flow F1 outwardly, via one or more leaks L1, L2 if leak paths are present. These leaks L1 and/or L2 may be detected using leak detection system <NUM>, as described in detail above. In particular, system <NUM> allows an evaluator to identify the location, magnitude, and character of leaks L1 and/or L2, which in turn allows the evaluator to more easily identify the root cause of leaks L1 and/or L2, such as the composition, application or location of adhesive beads 58A and/or 58B, for example.

In an exemplary embodiment, the source of pressurized gas may provide a motive flow <NUM> of a gas having a refractive index different than ambient air. For example, the motive flow <NUM> may be made up of a gas having a refractive index <NUM>, <NUM> or <NUM> larger or smaller than ambient air at A=<NUM>, <NUM> and <NUM> atm. A refractive index sufficiently larger or smaller ensures that the gas is visually distinguished from the surrounding air when imaged as described herein. Exemplary gasses having a suitably high or low refractive index include carbon dioxide, helium, and difluoroethane. Through the use of motive flow <NUM> with a refractive index different than air as described herein, signal strength may be increased at least <NUM> times, and as much as <NUM> times, as compared to a motive flow <NUM> including air alone.

Turning now to <FIG> and <FIG>, an alternative leak detection system <NUM>' is shown. Leak detection system <NUM>' operates similarly to leak detection <NUM>, and has similar structures and configuration as leak detection system <NUM> except otherwise indicated. Structures of leak detection system <NUM> have the same reference numbers as corresponding structures in leak detection system <NUM>', except with a prime added to the number as shown.

However, leak detection system <NUM>' does not include 4F imaging system <NUM>, and instead utilizes parabolic collection mirror <NUM>' and parabolic collimation mirror <NUM>'. Parabolic collection mirror <NUM>' and parabolic collimation mirror <NUM>' are larger than lenses <NUM> and <NUM>, and collimation lens <NUM>, allowing mirrors <NUM>', <NUM>' to have shorter focal length with minimized spherical aberration compared to the single element spherical lenses <NUM>, <NUM>, and <NUM> (<FIG>) with the same size. This substitution allows leak detection <NUM>' to cover a larger area of a DUT <NUM>' (which may be identical to DUT <NUM>), with larger diameter lens and a smaller overall spatial footprint. In addition, leak detection system <NUM>' utilizes a conventional high numerical aperture imaging lens <NUM>' to directly image the DUT <NUM>' in combination with having two parabolic mirrors <NUM>' and <NUM>' without satisfying the spatial requirements needed to utilize the 4F imaging system <NUM>.

For example, <FIG> shows a photograph image illustrating simulation results of imaging when a gas leak is modelled by an object plane OP' in a DUT <NUM>' with small refractive index changes. To produce the photograph of <FIG>, leak detection system <NUM>' of <FIG> and <FIG> was used as described above to examine the intentional leak created in the DUT <NUM>'. Similar to the results shown in <FIG>, spatial filtering clearly creates contrast variation in the image at the center of the image.

<FIG> illustrates an exemplary method for detecting and evaluating leaks in a device under test, such as DUT <NUM> (<FIG>). This method <NUM> may be performed by a human user of a system made in accordance with the present disclosure, or may be automated through the use of a computer or controller as further described below.

<FIG> shows a method of generating and evaluating a sensed image using a system, such as system <NUM>, in accordance with the present disclosure. Beginning with step <NUM>, a coherent or incoherent light signal is emitted, such as by applying electrical power to a light source to generate light signal <NUM>. In an exemplary embodiment, the light signal is a laser or LED signal coming from light source <NUM>. In step <NUM>, at least a portion of the light signal is passed through a collimation lens, such as lens <NUM>, to create a collimated light signal, such as signal <NUM>.

In step <NUM>, at least a portion of the collimated light signal is passed through a 4F imaging telescope, such as telescope <NUM>. As the light signal passes through telescope <NUM>, the signal is filtered by a spatial filter, such as spatial filter <NUM> described above. At this point, system <NUM> is ready to be used for evaluation of a device under test (DUT), such as DUT <NUM> shown in <FIG>.

In step <NUM>, a DUT is placed into an object plane between the collimation lens and the 4F imaging telescope, illustratively object plane OP shown in <FIG>. The DUT may be rotated, translated or otherwise reoriented to view different surfaces and areas of the DUT. In an exemplary embodiment, the DUT may be moved systematically along a series of motions to establish a "grid" or other systematic series of evaluated areas, such that the entirety of the surface of interest in the DUT are subjected to leak evaluation.

In step <NUM>, an image is generated at an image plane positioned at an output side of the 4F imaging telescope, such as image plane IP shown in <FIG>. In step <NUM>, the contrast in this sensed image may then be evaluated to determine the presence and magnitude of leaks in the DUT.

Images detected by imaging device <NUM> are evaluated by a controller. The controller may be microprocessor-based and includes a non-transitory computer readable medium which includes processing instructions stored therein that are executable by the microprocessor of controller to evaluate the detected image to evaluate the presence and/or extent of a leak L1, L2 by assessing the presence or absence of contrast variation CV1 and/or CV2 (<FIG> and <FIG>). A non-transitory computer-readable medium, or memory, may include random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (e.g., EPROM, EEPROM, or Flash memory), or any other tangible medium capable of storing information.

The image generated by the present system (such as systems <NUM> or <NUM>') may be processed by software designed to detect and evaluate contrast variation and determine the defect size and generate scores corresponding to the presence, magnitude and character of any leaks L1, L2 (<FIG>). Both conventional image processing and machine learning techniques can be used to implement this software, including using the methods described in detail below.

Exemplary images which may be generated by systems <NUM> or <NUM>' are depicted in <FIG> and <FIG>. In order to generate these images, spatial filtering may be applied to the raw image sensed by an imaging device (such as device <NUM> or <NUM>') to more clearly show the size, location and characteristics of leaks in images sensed by, e.g., the images developed by system <NUM> at step <NUM> of <FIG>. Generally speaking, optical leaks detected by system <NUM> would not be expected to present as isolated pixels in the image. The leaky regions, such as leaky region LR shown in <FIG> and <FIG>, will instead present as a cluster of pixels that connect to the DUT <NUM>. Compared to the optical noise, such as optical noise ON, the leaky region LR will have high intensity variation in the resulting background-subtracted image (<FIG>).

Further modification may be made to the image to more clearly show a leak, in view of the above two properties. In an exemplary embodiment, a spatial filtering software using the method disclosed in <FIG> can eliminate the impact of optical noise on the background-subtracted image to arrive at an optical noise filtered image, as shown in <FIG>. For instances where optical noise ON makes it difficult to detect small leaks in the DUT <NUM>, the present optical noise filtering allows for leaky region LR to be highlighted and easily discerned, as shown in <FIG>. Thus, the impact of optical noise ON is eliminated though the optical noise filtering software. Further details of noise filtering software and systems are further described herein.

As illustrated in <FIG>, a method of image modification and interpretation may be used to identify and characterize leaks. In the illustrated method, input images are first subject to background subtraction as described herein (e.g., with reference to the image of <FIG>). The resulting background subtracted image then undergoes optical noise filtering, with the optical noise filtering system optionally further including user-modifiable parameters which can be tuned and optimized to detect large leaks and/or small leaks in the DUT <NUM> as further discussed below. After the step of optical noise filtering, an image such as shown in <FIG> may be generated.

From the optical noise filtered image (e.g., of <FIG>), the method may utilize image metrics measurement for specific leaky regions or types of leaky regions, if multiple. These regions can be segmented out for separate classification. For each of the leaky regions, image metrices representing the severity of each leak can be computed. Thus, within one DUT <NUM> (<FIG>), the spots with large leaks and the spots with small leaks can be independently located and classified.

Some of the image metrices representing the optical leaks include size of the leak in terms of number of pixels, and average pixel-intensity of the leak. Furthermore, a single leaky region can be further analyzed by splitting it into two. This would allow the software to quantify the leaky regions through image metrices such as number of leaks (<FIG>), width of leaks (<FIG>), length of leaks (<FIG>), leakage travel area (<FIG>), and various gradient-based metrics.

<FIG> indicates number of leaks by placing an indicator, such as dots on the points of origination of the leak and totaling the number of indicators present in the after-analyzed image. <FIG> indicates the width of leaks by placing indicators, such as arrows, on the outer perimeter of the leakage trail and measuring the distance between indicators. <FIG> indicates length of leaks by placing indicators, such as arrows, along the entire length of the leak and measuring the length of the indicator. <FIG> indicates area of leak by drawing a line around the perimeters of the leak and calculating the area of the indicator shape.

In one exemplary embodiment, the optical noise filtered image can be divided into "grids" and the image metrices on each grid can be computed. Inferences based on the relative difference between the grid values is also contemplated for use in connection with the present system and method.

In some applications only a portion of the DUT <NUM> needs to be inspected. Using the present system, a user may define a particular Region-of-Interest (ROI) in the DUT <NUM>, as shown in <FIG>. The optical leak in that region alone can then be inspected and measured during the step of image metrics measurement, as described in detail herein.

In addition, one or more Regions-of-Non-Interest (RONI) can also be defined in the DUT <NUM> as shown in <FIG>. For example, the region closer to the DUT boundary can be expected to have higher pixel intensities due to high pressure. But these cannot be inferred as leak regions since the high pressure normally associated with a leak are also present at non-leaking boundary areas. So, the boundary area may be designated as a Region-of-Non-Interest (RONI), and the contributions from such RONI can be suppressed through imaging operations designed to exclude the RONI from the overall analysis of the DUT <NUM>.

The leak detection and optical noise filtering software can further employ a machine learning (ML) based estimation designed to determine leak location and a volumetric leak rate in Standard Cubic Centimeters per Minute (SCCM). Similarly, and as further discussed below, a deep learning (DL) regression model may be used in place of the ML model.

Turning now to <FIG> and <FIG>, the ML and DL model may be defined by the following equation: <MAT>.

In this equation, fps corresponds to the frames per second of the camera and SCCMi,j corresponds to the SCCM at the ith second and jth frame.

As shown in <FIG>, in the training phase, the background subtracted images and the corresponding ground truth cubic centimeters are provided for training. The optical noise filtering software, described herein, can also be applied on the background subtracted image prior to training. From the given input images, the features are extracted and using the ML/DL regression model, the system is trained. Turning to <FIG>, in the testing phase, from the given background subtracted image, the same features are extracted and fed to the trained ML/DL regression model. The model predicts the cubic centimeters value for each frame. The disclosed ML/DL model is trained to predict the leakage on each video frame. Then the predicted values are agglomerated to compute the corresponding SCCM value at an instant of time.

As illustrated in <FIG> and <FIG>, the optical noise filtering software can also be modeled as a classification problem. As shown in <FIG>, the training phase would include the background subtracted images and the corresponding ground truth labels, such as "no leak," "small leak" or "large leak. " A test DUT is provided with the designated leak characteristics, such as a "No Leak DUT," a "Small Leak DUT" or a "Large Leak DUT" and its ground truth label is associated with its leak characteristics. The resulting data is developed into the output DL Classification Model. Prior to training, the optical noise filtering software can also be applied on the background subtracted image as described herein.

Turning to <FIG>, in the testing phase, the trained deep learning classification model output from the method of <FIG> is used as the processing model for a background subtracted image for a DUT <NUM>. The image is uploaded to the DL Classification Model and a Predicted Label is output showing whether the DUT <NUM> is a no-leak, small-leak or large-leak device.

Alternatively, as illustrated in <FIG> and <FIG>, the optical noise filtering software can also be modeled as a detection problem. As shown in <FIG>, in the training phase, the background subtracted images and corresponding ground truth bounding boxes of known leaky regions are provided for training. Prior to training, the optical noise filtering software can also be applied to the background subtracted image as described herein. The bounding boxes represent the leaky regions known to exist in the image. The output of the training system is the DL Detection Model.

Turning to <FIG>, in the testing phase, the trained deep learning detection model output from the method of <FIG> is used as the processing model for a background subtracted image for a DUT <NUM>. The image is uploaded to the Detection Model and one or more Predicted Bounding Boxes is showing the leaky regions of the DUT <NUM>.

In another alternative, illustrated in <FIG> and <FIG>, the optical noise filtering software could be modeled as a segmentation problem. As shown in <FIG>, in the training phase, the background subtracted images and corresponding ground truth binary mask images (e.g., as shown in <FIG> and <FIG>) are provided for training. Prior to training, customized optical noise filtering can also be applied on the background subtracted image, such as the filtering shown and described in connection with the method of <FIG>. The binary mask images represent the known leaky regions in the image as white pixels and the other regions as black pixels. The output of this DL Segmentation Training is the DL Segmentation Model.

Turning to <FIG>, in the testing phase, the trained Segmentation Model output from the method of <FIG> is used as the processing model for an image from a DUT <NUM>. Predicted Leaky regions of the DUT <NUM> are output, with associated exact (i.e., binary) boundaries are obtained as the output of the DL Segmentation Model. Using this model, the leakage width, leakage length and the leakage travel area can be computed as described above with respect to <FIG>, for example.

In one exemplary embodiment DUT <NUM> may be a mobile phone, tablet, or other handheld display device, and system <NUM> is used to evaluate a hermetically sealed casing around the mobile phone or tablet. For example, <FIG> schematically illustrates a portion of a mobile phone. When interfacing together all of the various components, the mobile phone is configured in a convenient package suitable for handling by human hands. A tablet may be configured similarly to the phone, except with larger overall dimensions. For example, as shown in <FIG> and <FIG>, an exemplary mobile phone <NUM> includes a back cover <NUM>. A bottom shell <NUM> is interfaced with a face shell <NUM> to protect the circuit board <NUM> that is configured to provide functionality to the mobile phone <NUM>. The bottom shell <NUM> is configured to support a battery <NUM>, and is further configured to interface with the back cover <NUM>. The face shell <NUM> is configured to interface with and support a display module <NUM>. When fully assembled, the display module <NUM> includes a display layer <NUM> and cover glass/touch panel 450a. The cover glass/touch panel 450a is configured as a transparent material or transparent optical material.

Generally speaking, DUT <NUM> may be any device that is configured to be hermetically sealed, such that an understanding of the presence and character of leaks can be used to determine whether the hermetically sealed configuration has been achieved in fact with any given device sample. Devices configured to be hermetically sealed may include mobile phones and tablets, ad discussed above, as well as other devices such as smart watches and ear phones, or any other types of electrical components that require tight sealing.

The display module <NUM> includes a display layer <NUM>, such as a liquid crystal display (LCD), a circular polarizer <NUM>, and optically transparent cover glass/touch panel 450a. In some configurations, the circular polarizer <NUM> may be integrated within the display layer <NUM> as is shown by the dotted outline surrounding both the display layer <NUM> and circular polarizer <NUM>. The display layer <NUM> is configured to provide a visual interface with a corresponding user, such as by displaying images that are viewable by the user. The display layer <NUM> may include one or more additional layers, as required or desired for a particular application. Various technologies are used to build the display layer <NUM> typically configured as pixels providing colored light that are viewable by a user. These technologies include liquid-crystal displays (LCDs), light-emitting diodes (LEDs), organic light-emitting diodes (OLED), etc. The cover glass/touch panel 450a is located adjacent to the display layer <NUM> or the circular polarizer <NUM> that is associated with the display layer <NUM>. Cover glass/touch panel 450a is configured as a user interface, wherein the user may interact with the mobile phone <NUM> and/or provide input control through touching the glass or panel 450a using a stylus or one or more fingers.

Other uses of the display module <NUM> and/or transparent optical material 450a are contemplated, such as any mobile devices with display screens, television screens, computer monitors, tablet devices, integrated display screens (e.g., integrated into dash of vehicle, desk surface, panel, etc.), portable communication devices, etc..

In particular, bottom shell <NUM>, face shell <NUM>, back cover <NUM>, and/or cover glass 450a may cooperate to form a hermetically sealed interior space to contain and protect internal components, including battery <NUM>, circuit board <NUM>, polarizer <NUM> and display layer <NUM>, for example. Embodiments of the present disclosure, including leak detection system <NUM> described in detail above, are configured to detect and/or measure any leaks from this hermetically sealed interior space.

Claim 1:
An imaging system comprising:
a point light source (<NUM>) configured to emit a light signal (<NUM>);
a collimation lens (<NUM>) positioned to receive the light signal (<NUM>), the collimation lens (<NUM>) configured to emit a collimated light signal (<NUM>);
an imaging telescope (<NUM>) positioned to receive the collimated light signal (<NUM>);
a spatial filter (<NUM>) positioned at a plane of the imaging telescope (<NUM>), the spatial filter (<NUM>) configured to pass a filtered light signal (<NUM>);
an image sensor (<NUM>) positioned at an output side of the imaging telescope (<NUM>), such that the image sensor (<NUM>) is positioned to receive the filtered light signal (<NUM>);
a device under test (<NUM>); and
a source of pressurized gas configured to pressurize an interior volume of the device under test (<NUM>), the imaging system (<NUM>) configured to detect a leak of the pressurized gas from the device under test (<NUM>), whereby the imaging system (<NUM>) is configured to provide optical leak detection for the device under test (<NUM>),
characterized in
that the imaging telescope is a 4F imaging telescope (<NUM>),
that the device under test (<NUM>) is positioned at an object (OP) plane between the collimation lens (<NUM>) and the 4F imaging telescope (<NUM>), and
that the spatial filter (<NUM>) is positioned at a Fourier plane of the 4F imaging telescope (<NUM>) .