Standard test method for validating the accuracy of mobile phone apps in measuring concrete crack widths

Abstract

This invention presents a standard test method and it’s standard apparatus for testing the accuracy of mobile phone apps designed to measure concrete crack widths. Said standard apparatus at least includes a simulated wall (SW), a standardized crack-width calibration plate (CWCP), a pose adjusting and fixing device (PAFD) and a spatial distance measuring assemblage (SDMA). This standard test method employs an innovative two-stage method associated with said SDMA to synchronously calculate and display the average distances ( K i, i= 1 ~ 4) from the phone’s four corner points to said SW. With continuous feedback, the phone’s spatial position can be adjusted using said PAFD until the four monitored K ivalues match the target K i. Subsequently, an app installed on the phone is used to measure crack widths on said CWCP. In the standard test method of the present invention, a standard experimental procedure was established for conducting standard test to assess the accuracy of mobile phone apps in measuring concrete crack widths.

Description

Technical Field

[0001] The present invention is a technology that uses innovative standard experimental methods and standard equipment to verify the accuracy of various mobile phone apps for measuring concrete crack width. Prior Art

[0002] Traditionally, measuring concrete crack width requires a professional to press a measuring device against the concrete surface and visually read the scale. Over the past decade or so, the cost-effectiveness of mobile phones has continued to improve. Smartphones equipped with digital cameras have recently become the norm, with significant improvements in both mobile computing power and camera performance. Consequently, smartphone apps now have the potential to transform phones into convenient tools for measuring concrete cracks, offering a new alternative to the relatively cumbersome traditional methods.

[0003] While the capabilities of mobile app software and hardware have greatly improved, many general-purpose apps used for search, entertainment, and other purposes only offer visual accuracy sufficient for the human eye. In contrast, concrete crack measurement apps must provide sufficient accuracy and precision for engineering applications. When using a mobile app to measure concrete cracks, the app first uses the phone's camera to capture a color digital image of the crack surface. Then, a digital image analysis process is applied to extract a monochrome (black and white) crack image from the crack surface. The app then determines the width of the selected crack based on this monochrome image.

[0004] Numerous studies have employed digital image processing techniques to extract characteristic and representative monochromatic crack images for detecting and / or measuring concrete surface cracks. For example, over the past two decades, Abdel-Qader et al. (2003) compared the effectiveness of four edge detection algorithms (Fast Haar Transform, Fast Fourier Transform, Sobel, and Canny) in identifying cracks in bridge deck concrete images. Hutchinson and Chen (2006) proposed a statistical procedure to find the optimal parameter sets for two of the more reliable algorithms (Canny and Fast Haar Transform) identified in Abdel-Qader et al.'s work. Yamaguchi and Hashimoto (2009, 2010) applied percolation theory to develop an image processing method for crack identification. To enable application to actual concrete structures, they developed a crack scale, which was applied to the crack surface before capturing the image. The intensity of the image within the scale was used to determine the crack width with sub-pixel accuracy. Zhu et al. (2011) slightly modified Yamaguchi and Hashimoto's percolation theory method by first identifying a crack map. They then used an image thinning algorithm and a Euclidean distance transform to identify the crack skeleton and the distance field of all crack pixels relative to the skeleton, respectively. From this, they determined the crack length, orientation, maximum width, and average width.

[0005] Many studies have also applied digital image correlation (DIC) to measure concrete crack width, such as Choi and Shah (1997), Destrebecq et al. (2010), and Dutton (2012). Lawler et al. (2001) combined two-dimensional DIC with three-dimensional X-ray microtomography to measure deformation and cracks during the rupture process of compressive concrete cubic specimens.

[0006] In the past decade, Nguyen et al. (2014) have leveraged the symmetry and linearity of concrete cracks to filter out non-crack noise. After identifying noise-free crack images, they found the crack skeleton, representing the line connecting the crack centers. Using cubic splines to connect these skeletons, they then determined the crack edges using the crack pixels perpendicular to the skeleton. Yang et al. (2015) addressed the need for experimental fine crack measurement in reinforced concrete components. By capturing images with two cameras and analyzing the tiny relative motion between the two sides of the crack, they were able to measure the size to an accuracy of 0.2 pixels. Yang et al. (2018) and Woods et al. (2018) have continued to develop new methods and damage assessment applications. Rivera et al. (2015) developed a MATLAB program called I-Crack, which uses MATLAB's built-in Prewitt edge detection and morphology routines to detect cracks and surface defects. They then use image segmentation parameters, such as the skew angle and the ratio of the major and minor axes, to separate cracks and surface defects. Finally, they use MATLAB's built-in regionprops function to calculate crack width.

[0007] In recent years, research using machine learning and deep learning methods for crack detection has surged. In an earlier study, Cha et al. (2017) used a dataset of 40,000 small images (each 256 x 256 pixels) to train convolutional neural networks (CNNs) for crack detection, achieving 98% accuracy. These trained CNNs were then used to identify 55 large images (5,888 x 3,584 pixels) of other structures using a scanning-window approach, demonstrating superior crack detection performance compared to Canny and Sobel edge detection algorithms. To address the time-consuming window scanning process and locate crack regions for subsequent crack segmentation, subsequent research has employed region-based (bounding-box) methods, such as the region proposal network in Faster R-CNN, crack candidate region methods, and YOLO-based methods. Mask R-CNN further extends Faster R-CNN by adding a branch for predicting segmentation masks. However, these machine learning and deep learning methods primarily address crack identification and segmentation, while the quantitative calculation of crack length, orientation, and width still relies on older digital image processing methods such as image thinning and distance transforms. In a study focusing on automatic crack width measurement, Carrasco et al. (2021) applied k-means clustering to determine the center point of the crack structure and classify pixels in the crack width profile into two categories: crack or substrate.

[0008] Relatively little research has been conducted in the literature on the use of mobile apps for concrete crack detection or measurement. Chen et al. (2015) developed an Android app that can capture crack images and determine the maximum crack width based on the captured images. When using this app to measure the crack surface, a spacer must be placed between the phone and the surface to keep the phone parallel to the crack surface and maintain a fixed distance of 10 cm, as the calibration factor used by the phone is based on this distance.

[0009] Kong et al. (2017) proposed a system for detecting the type and size of road cracks. The system's data acquisition module uses a smartphone to capture images of cracks and record readings from the phone's accelerometer, magnetometer, and GPS. The system's crack size estimation module then uses the captured images and sensor readings to estimate crack length and width. This system can detect road cracks ranging in width from 6 cm to 25 cm, but is not suitable for detecting finer cracks in concrete structures or components.

[0010] Through experiments on seven smartphones from four different brands, Ni et al. (2020, 2021) found that when the distance between the phone camera and the target is fixed, the size of a single pixel (η') in the captured image decreases exponentially with increasing zoom factor. Overall, their results found that η' decreases from approximately 0.37 mm to 0.03 mm as the zoom ratio increases.

[0011] Gepiga et al. (2022) proposed an automated crack detection and measurement system using smartphone-captured crack images. Their mobile app uses Google's ARCore library to measure and record the distance between the target and the camera. Gyroscope readings are used to guide the phone to align at approximately a 90° angle to the surface. The captured image and recorded distance data are then transferred to a laptop, where Musk R-CNN is used for image segmentation and the aforementioned method of Carrasco et al. (2021) is used for crack quantification.

[0012] Wang et al. (2024) developed a specialized handheld image capture device to collect crack video images and wirelessly transmit them to a smartphone. An app on the smartphone then uses the transmitted video images to detect cracks and measure their width.

[0013] In the aforementioned studies, the measured crack widths ranged from approximately 0.3mm-1.0mm (Chen et al. 2015), 0.6mm-1.2mm (Ni et al. 2020, 2021), 0.2mm-2.2mm (Gepiga et al. 2022), and 0.17mm-2.9mm (Wang et al. 2024). The minimum value (0.17mm) is still insufficient to replace traditional crack-width gauges in engineering practice. Traditional instruments, such as crack measuring magnifiers and crack-width comparator cards, can measure crack widths as fine as 0.05mm or at least 0.1mm, meeting the requirements of engineering practice and structural concrete.

[0014] Validating the accuracy and precision of crack width measurements is another issue. In the aforementioned studies, crack width values obtained using a mobile app or laptop were compared with manual measurements using a magnifying glass or other electronic instruments. However, the sample sizes of these comparisons were limited.

[0015] There are various electronic crack width measurement instruments available on the market, generally classified into two categories. The first category is an advanced version of the traditional crack width magnifier, in which a high-resolution digital camera replaces the traditional optical lens. The second category utilizes digital image processing technology to generate crack width measurements. However, the specifications provided by the manufacturer should only reflect the electronic or mechanical performance indicators of the instrument, rather than statistically significant accuracy indicators. This is primarily due to the lack of a standard experimental procedure similar to the present invention in any conventional literature. Summary of the Invention

[0016] To address the aforementioned issues and facilitate the development of mobile phone apps capable of measuring crack widths as fine as 0.05 mm or 0.1 mm, the present invention proposes an innovative standard test method and standard apparatus to test the accuracy of all mobile phone apps in measuring concrete crack width. The standard apparatus comprises at least a simulated wall (SW), a crack-width calibration plate (CWCP), a pose adjusting and fixing device (PAFD), and a spatial distance measuring assembly (SDMA). Using the SDMA, a dedicated two-stage method is used to calculate and display the spatial position of the mobile phone relative to the simulated wall in real time. This continuous, real-time measurement, calculation, and display feedback allows the spatial position of the mobile phone to be adjusted (moved and / or rotated) using the pose adjusting and fixing device (PAFD). In a standard experimental procedure for verifying the accuracy of a mobile phone app in measuring concrete crack width, the spatial position of the phone is adjusted as described above until the desired position is reached. The app installed on the phone is then used to measure the width of a simulated crack on a crack width calibration plate embedded in a simulated wall. Based on the underlying physics, the standard experimental method and its standard equipment can accurately and cost-effectively simulate actual engineering conditions (e.g., various experimental parameters such as the phone's measurement distance, the phone's relative position to the wall, the intensity and angle of illumination on the wall, temperature, humidity, the phone's camera performance, and the app's measurement method).

[0017] In other words, the standard experimental method of the present invention can control all experimental parameters and reproduce the required experimental conditions for repeated experiments. This allows the impact of various parameters to be studied and results under the same conditions to be compared. This allows the reliability of mobile app measurement accuracy verification to be established through multiple, systematic experiments. Simple diagram description

[0018] FIG. 1 a shows an embodiment of a crack width correction plate according to the present invention embedded in a simulated wall.

[0019] FIG1b is a photograph of the actual operation of the crack width correction plate of the present invention embedded in a simulated wall.

[0020] FIG. 2 a shows an embodiment of a simulation wall according to the present invention.

[0021] FIG2 b is a first photo of the actual operation of the simulation wall of the present invention.

[0022] FIG. 3 a is a schematic diagram of the simulated wall of the present invention with the crack width correction plate removed.

[0023] FIG3 b is a second photo of the actual operation of the simulation wall of the present invention.

[0024] FIG3 c is a third photo showing the actual operation of the simulation wall of the present invention.

[0025] FIG3 d is a fourth photo showing the actual operation of the simulation wall of the present invention.

[0026] FIG. 4 a shows a first embodiment of a crack width correction plate according to the present invention.

[0027] FIG. 4 b shows a second embodiment of the crack width correction plate of the present invention.

[0028] FIG4 c is a first photo of the actual operation of the crack width correction plate of the present invention.

[0029] FIG4 d is a second photo showing the actual operation of the crack width correction plate of the present invention.

[0030] FIG4e is a first photograph of the high-precision measuring instrument for measuring simulated cracks according to the present invention.

[0031] FIG4 f is a second photo of the high-precision measuring instrument for measuring simulated cracks according to the present invention.

[0032] FIG. 5 a shows an embodiment of the posture adjustment and fixing device of the present invention.

[0033] FIG5 b is a first photo of the actual operation of the posture adjustment and fixing device of the present invention.

[0034] FIG5 c is a second photo of the actual operation of the posture adjustment and fixing device of the present invention.

[0035] FIG5 d is a third photo of the actual operation of the posture adjustment and fixing device of the present invention.

[0036] FIG6 is an embodiment of a spatial distance measurement component of the present invention.

[0037] FIG. 7 a is a schematic diagram showing the spatial distance measurement component of the present invention installed on the posture adjustment and fixing device.

[0038] FIG7 b is a first actual operation photo of the spatial distance measurement component of the present invention being installed on the posture adjustment and fixing device.

[0039] FIG. 7 c is a second actual operation photo of the spatial distance measurement component of the present invention being installed on the posture adjustment and fixing device.

[0040] FIG8 a is a schematic diagram illustrating the overall configuration of the standard equipment used in the mobile phone app standard crack width measurement experiment according to the present invention.

[0041] FIG8 b is a first actual operation photograph of the overall configuration of the standard equipment used in the mobile phone app standard crack width measurement experiment of the present invention.

[0042] FIG8 c is a second actual operation photo of the overall configuration of the standard equipment used in the mobile phone app standard crack width measurement experiment of the present invention.

[0043] FIG8 d is a third actual operation photo of the overall configuration of the standard equipment used in the mobile phone app standard crack width measurement experiment of the present invention.

[0044] FIG8e is a fourth actual operation photo of the overall configuration of the standard equipment used in the mobile phone app standard crack width measurement experiment of the present invention.

[0045] FIG. 9 a is a schematic diagram of the experimental setup for stage one of the two-stage method of the present invention.

[0046] FIG9 b is a first photograph showing the actual operation of stage 1 of the two-stage method of the present invention.

[0047] FIG9 c is a second photograph showing the actual operation of stage one of the two-stage method of the present invention.

[0048] FIG9 d is a 3D scanning point cloud photo 1 of the first stage of the two-stage method of the present invention.

[0049] FIG9 e is a second 3D scanning point cloud photo of the first stage of the two-stage method of the present invention.

[0050] FIG10 is a flow chart of stage one of the two-stage method of the present invention.

[0051] FIG. 11 a is a schematic diagram of the methodology of stage 2 of the two-stage method of the present invention.

[0052] FIG. 11 b is a first photograph showing the actual operation of the second stage of the two-stage method of the present invention.

[0053] FIG. 11 c is a second photograph showing the actual operation of the second stage of the two-stage method of the present invention.

[0054] FIG12 is a flow chart of stage 2 of the two-stage method of the present invention.

[0055] FIG. 13 a is a schematic diagram of the experimental configuration of the second stage of the verification experiment of the standard experimental process of the present invention.

[0056] FIG13 b is a first actual operation photograph of the second stage of the verification experiment of the standard experimental process of the present invention.

[0057] FIG13 c is a second actual operation photo of the second stage of the verification experiment of the standard experimental process of the present invention.

[0058] FIG13 d is a third actual operation photograph of the second stage of the verification experiment of the standard experimental process of the present invention.

[0059] FIG13e is a first 3D scanning point cloud photo of the second stage of the verification experiment of the standard experimental process of the present invention.

[0060] FIG13 f is a second 3D scanning point cloud photo of the second stage of the verification experiment of the standard experimental process of the present invention.

[0061] FIG13 g is a third 3D scanning point cloud photo of the second stage of the verification experiment of the standard experimental process of the present invention.

[0062] FIG13h is a fourth 3D scanning point cloud photo of the second stage of the verification experiment of the standard experimental process of the present invention.

[0063] FIG14 is a flow chart of the standard experimental process of the present invention.

[0064] FIG. 15 is an embodiment of a zeroing jig according to the present invention.

[0065] FIG16 is a schematic diagram of FIG15 in use.

[0066] FIG17 is a flow chart of an embodiment of a mobile phone app standard crack width measurement experiment of the standard experimental process of the present invention.

[0067] FIG18 a is a first actual operation photo of FIG17 .

[0068] FIG18 b is a second actual operation photo of FIG17 .

[0069] FIG18 c is a third actual operation photo of FIG17 .

[0070] FIG18 d is a fourth actual operation photo of FIG17 .

[0071] FIG18e is a fifth actual operation photo of FIG17.

[0072] FIG18f is a sixth actual operation photo of FIG17.

[0073] FIG18g is a seventh actual operation photo of FIG17.

[0074] FIG19 is an illustration of the simulated crack grouping and measurement point marking line positions of the crack width correction plate of FIG17.

[0075] FIG. 20 a is a first experimental data diagram of FIG. 17 .

[0076] FIG. 20 b is a second experimental data diagram of FIG. 17 .

[0077] FIG. 20 c is a third experimental data diagram of FIG. 17 .

[0078] FIG. 20 d is a fourth experimental data diagram of FIG. 17 . Implementation Method

[0079] The present invention discloses a standard experimental method for verifying the accuracy of a mobile phone app in measuring concrete crack width. The standard equipment includes at least a simulated wall 1, a crack width correction plate 2, a posture adjustment and fixing device 3, and a spatial distance measurement component 4.

[0080] As shown in Figures 1a and 1b, the crack width calibration plate 2 is embedded in the simulated wall 1 to perform the standard crack width measurement experiment using the mobile app. A wooden simulated wall is preferred for this purpose, as it is inexpensive to manufacture, lightweight and easy to move, and can realistically simulate the appearance of an actual concrete wall.

[0081] As shown in Figures 1a-2b, the simulated wall 1 may be provided with an angle adjustment mechanism 11 to control the tilt angle of the simulated wall 1. The angle adjustment mechanism 11 comprises a base 111, a support rod 112, and a slide 113. The base 111 is pivotally connected to the bottom of the simulated wall 1. One end of the support rod 112 is pivotally mounted behind the simulated wall 1. The slide 113 is disposed on the base 111, and the other end of the support rod 112 is disposed within the slide 113. The support rod 112 is provided with a locking element 114, which allows the support rod 112 and the slide 113 to be locked and fixed to each other after the support rod 112 is adjusted in position.

[0082] As shown in Figures 3a-3d, the simulated wall 1 is provided with a receiving groove 12, and a measuring groove 13 is provided extending from one side of the receiving groove 12. The crack width calibration plate 2 is removably embedded in the receiving groove 12. The measuring groove 13 is used to accommodate an illuminometer and is used to measure the light intensity on the surface of the crack width calibration plate 2 before conducting a crack width measurement experiment.

[0083] The crack width calibration plate 2 serves as a standard target for repeatable crack width measurements required for standard testing. As shown in Figures 4a-4d, the crack width calibration plate 2 is precision-machined with multiple simulated cracks 21 of varying widths. These simulated cracks 21 are machined using high-precision laser engraving or milling cutters. For example, laser engraving is suitable for simulated cracks with widths greater than 0.1 mm, while milling cutters are suitable for simulated cracks with widths between 0.1 mm and 0.01 mm. The engraving depth of each simulated crack can be adjusted to at least 1 mm, depending on the application. The crack width calibration plate 2 is made of metal, preferably steel. After the simulated cracks 21 are machined using precision machinery on the steel plate, the accuracy of the simulated cracks 21 can be maintained for a long period of time. Multiple markings 22 (such as the seven vertical stripes shown in Figures 4b-4d) can be spaced apart on the simulated crack 21 to facilitate multi-point measurement and comparison of each simulated crack 21. The markings 22 can be a plurality of stripes perpendicular to the simulated crack 21, or a plurality of marking symbols on the simulated crack 21, depending on the application.

[0084] In the embodiments of Figures 4c and 4d, the crack width correction plate 2 has a lateral area of 130 mm x 130 mm and a thickness of 10 mm. It includes 21 simulated cracks 21 with widths ranging from 0.05 mm to 2.00 mm, each extending up to 100 mm in length. According to design specifications, the metal crack width correction plate 2 was fabricated by a professional manufacturer. Nineteen simulated cracks with designed widths ranging from 2.0 mm to 0.10 mm were laser-engraved, and two of the thinnest simulated cracks with designed widths of 0.08 mm and 0.05 mm were engraved using a milling cutter. The engraving depth of each simulated crack 21 was 1 mm. Seven vertical stripe markings were added to the crack width correction plate 2 to indicate 14 potential crack width measurement points along each of the 21 simulated cracks 21.

[0085] In the standard experimental process used to verify the accuracy of mobile apps in measuring concrete crack widths, crack width measurements obtained from the mobile app must be compared with the corresponding "true" crack width values to determine the app's measurement error. Therefore, the plurality of simulated cracks 21 were manually measured to determine the "true" crack width values at all of the simulated cracks 21's crack width measurement points. This manual measurement involved multiple individuals using multiple high-precision measuring instruments to measure the widths of all of the simulated cracks 21 at their respective width measurement points. All manually measured width observations for each simulated crack 21 were then averaged to determine the true width value for each simulated crack 21.

[0086] As shown in Figures 4e and 4f, in one embodiment, three precision crack width measurement magnifiers (Baiyi BY-D200XS, Peak 2016-15X, and Peak 2008-100X) were used to manually measure the crack width at designated locations on each simulated crack 21 of the crack width calibration plate 2. The measurements were performed by at least three people, with each person performing at least two rounds of measurements. For each designated location on the simulated crack 21 (also used by the app for crack width measurement), at least 30 manual measurements were performed using five crack width magnifiers (one Baiyi BY-D200XS, two Peak 2016-15X, and two Peak 2008-100X). The two thinnest cracks, with design widths of 0.05 mm and 0.08 mm, were measured using only two high-precision crack width magnifiers. Each set of 30 measurements was reviewed and compared, outliers removed, and remeasured if necessary. The final true crack width value is obtained by averaging the valid measurement values at each designated width measurement location for each simulated crack 21. These true crack width values are compared with the app's measured values to determine the app's measurement error.

[0087] In the standard experimental process used to verify the accuracy of mobile phone apps in measuring concrete crack width, the spatial position of the experimental mobile phone undergoes a series of coarse and fine adjustments until the desired position is reached, and then remains unchanged. The aforementioned posture adjustment and fixation device 3 can perform coarse and fine adjustments of the mobile phone's spatial position. As shown in Figures 5a-5d, the aforementioned posture adjustment and fixation device 3 can be equipped with a pan-tilt tripod 31 and a two-axis motion mechanism 32. The two-axis motion mechanism 32 is mounted on the pan-tilt tripod 31. The pan-tilt tripod 31 can adjust the position of the mobile phone in various directions of movement or rotation (as shown in Figure 5c), and the two-axis motion mechanism 32 can adjust the position of the mobile phone in two mutually perpendicular directions (as shown in Figure 5d).

[0088] Before using the aforementioned posture adjustment and fixing device 3 for adjustment, the spatial position of the mobile phone must be identified. As shown in Figures 6-7c, the aforementioned spatial distance measurement assembly 4 is mounted above the aforementioned posture adjustment and fixing device 3. The spatial distance measurement assembly 4 comprises a fixing frame 41, which is equipped with a mobile phone clamp 42 and four fixing slots 43. The mobile phone clamp 42 is located in the center of the fixing frame 41 and secures a mobile phone 5 therein. Four high-precision laser displacement sensors (LDS) 6 are mounted on each of the four fixing slots 43.

[0089] Figures 8a-8e illustrate the overall configuration of the mobile phone app standard crack width measurement experiment of the present invention. In this overall setup, the spatial distance measurement assembly 4 is mounted on top of the posture adjustment and fixing device 3. The mobile phone 5 and four laser displacement meters 6 are aimed at the simulated wall 1 and the crack width calibration plate 2 embedded in the simulated wall 1. The measurement signals from the four laser displacement meters 6 are fed into a dynamic data logger 61, which is connected to a computer for real-time calculation and display of the results. During a mobile phone app standard crack width measurement experiment, the four laser displacement meters 6 continuously measure the spatial distances from the four laser emission points to their endpoints on the simulated wall 1. Simultaneously, the distance measurements from these laser displacement meters 6 are synchronously used to calculate and display the spatial position of the mobile phone 5 relative to the simulated wall 1. By means of this continuous spatial position measurement, calculation and display feedback, the aforementioned posture adjustment and fixing device 3 can be used to adjust (move and / or rotate) the aforementioned spatial distance measurement component 4 to adjust the relative spatial position of the mobile phone during the experiment.

[0090] In this invention, the relative position between a mobile phone and a test wall is the most important experimental parameter. Therefore, the present invention has developed a two-stage method to synchronously calculate and display the spatial position of a mobile phone relative to a test wall.

[0091] The "Phase 1" of the aforementioned two-stage method is to determine the spatial relationship between the four laser displacement meters 6 and the mobile phone 5. As shown in Figures 9a-10, the experimental configuration and process of the "Phase 1" of the aforementioned two-stage method are shown. The "Phase 1" of the aforementioned two-stage method first uses 3D scanning to determine the spatial relationship between the mobile phone 5 and the four laser displacement meters 6 in the spatial distance measurement component 4 (as shown in Figures 9a-9e). The result of this "Phase 1" is the determination of the 3D coordinates of eight spatial points (P1-P4) and (S1-S4), as well as four 3D unit vectors ( The four points P1-P4 represent the corner points of the mobile phone 5, which determine the spatial position of the mobile phone 5. The four points S1-S4 represent the laser emission points of the four laser displacement meters 6, and the four unit vectors pointing from the laser emission points (S1-S4) to their end points (on the wall of a first test wall kit 71). , which together determine the spatial position and direction of the four laser beams. As shown in Figures 9a-9e, the first test wall assembly 71 is a three-dimensional structure composed of a regular outer surface. The present invention utilizes the first test wall assembly 71 to ensure 3D scanning accuracy and reduce 3D scanning errors. Furthermore, to improve 3D scanning accuracy, the spatial distance measurement assembly 4 must be coated to form a more regular outer surface.

[0092] The "Phase 2" of the aforementioned two-stage method uses the distance measurement values of the laser displacement meter 6 to calculate the distance between the mobile phone 5 and a test wall in real time. As shown in Figures 11a-12, the experimental configuration, methodology and process of the "Phase 2" of the aforementioned two-stage method are shown. The "Phase 2" of the aforementioned two-stage method resets the posture adjustment and fixing device 3 and the spatial distance measurement component 4 to face the test wall, obtains real-time distance measurement values (d1-d4) from the four laser displacement meters 6, and the 3D coordinates (P1-P4) of the four corner points of the mobile phone determined in the previous "Phase 1", the 3D coordinates of the laser starting points of the four laser displacement meters 6 (S1-S4), and the 3D unit vector ( ), which is used to simultaneously calculate and display the four average distances Ki from the four corner points Pi (i=1-4) of the mobile phone to a test wall (as shown in Figure 12). These Ki values can then be used to adjust (move and / or rotate) the spatial distance measurement component 4 using the posture adjustment and fixing device 3, thereby adjusting the relative spatial position of the mobile phone 5 during the experiment.

[0093] Regarding the physical meaning of "Phase 2" of the aforementioned two-stage method, the spatial geometric relationship between the four corner points (P1-P4) of the phone, the laser endpoints (W1-W4) on a test wall, and the average distance (K1-K4) from the four corner points (P1-P4) of the phone to the test wall is shown in Figures 11a-11c. In fact, Ki = (Qi1 + Qi2 + Qi3 + Qi4) / 4 in "Phase 2" of the aforementioned two-stage method mathematically corresponds to the distance from the four corner points Pi of the phone to an "average spatial plane," which is the average spatial plane obtained by intersecting the four laser endpoints W1-W4 on the test wall (as shown in Figure 12). Since the typical "concrete crack surface" can only achieve the accuracy of surface painting and other decoration projects, it cannot be completely equivalent to a single mathematical spatial plane (this also explains the rationale of using a wooden simulated wall). When measuring the concrete crack surface using a mobile app, the user should perceive a psychological "perceived crack plane." Therefore, the vertical distance Ki from point Pi to the "average spatial plane" essentially simulates the vertical distance from Pi to the user's "perceived crack plane." In other words, "Phase 2" of the aforementioned two-stage method essentially simulates the "perceived crack plane" of the mobile app user using the "average spatial plane" enclosed by the four laser endpoints W1-W4. This innovative approach should be very reasonable and appropriate for simulating actual engineering usage conditions.

[0094] As previously mentioned, in "Phase 2" of the two-stage method, the real-time distance measurements (d1-d4) from the four laser displacement meters 6 are used to simultaneously calculate and display four Ki values. To be able to calculate and display Ki values in real time, the four laser displacement meters 6 must measure (d1-d4), the absolute distances from the laser emission point to the endpoint on a test wall (as shown in Figures 8a-8e and 11a-12). However, these laser displacement meters 6 are not rangefinders. Typically, high-precision laser displacement meters (such as the one used in the experiment of Figures 8a-8e and connected to the dynamic data recorder 61) are used as displacement transducers. Displacement sensors or transducers are typically used by placing the sensor at a fixed position and measuring only relative displacement relative to an initial fixed reference position. Therefore, while the four laser displacement meters 6 have a specified effective measurement range, they do not provide a precise fixed reference point. This presents a major challenge in the present invention's research, as the laser displacement meter must be mounted on a variable-position stainless steel plate fixture 41 and accurately provides the absolute spatial distance (d1-d4) from the laser's starting point to the laser's end point on a test wall.

[0095] To address this issue, the present invention has developed another method, prior to conducting standard experiments, that enables high-precision, real-time measurement of four absolute spatial distances (di) using four standard laser displacement meters 6. This method for measuring the spatial distances of the four laser displacement meters 6 employs a zero-calibration fixture 8 (ZCC) as shown in Figures 15 and 16. Then, by employing 3D scanning and 3D point cloud spatial distance measurement techniques, the spatial distance measurements of the four laser displacement meters 6 are repeatedly compared with the spatial distance measurements of the 3D scanning point cloud. This allows for fine-tuning of the spatial distances measured by the four laser displacement meters 6, establishing a fine-tuning formula, and then writing this fine-tuning formula into the real-time calculation program of the dynamic data recorder 61. In this manner, high-precision, real-time measurement of four absolute spatial distances (di) can be successfully achieved using the four standard laser displacement meters 6.

[0096] To verify the accuracy of the measured values (di) and the calculated values (Ki) (as shown in Figure 12) from the four laser displacement meters 6, a verification experiment was performed prior to executing the standard crack width measurement experiment using the mobile app, as shown in Figure 14. The verification experiment included the processes of "Phase 1" and "Phase 2" of the aforementioned two-stage method (as shown in Figures 10 and 12). The experimental configuration and process used in "Phase 1" and "Phase 2" of the verification experiment were substantially the same as those used in "Phase 1" and "Phase 2" of the two-stage method, with the following differences:

[0097] 1. Phase 2 of the aforementioned verification experiment was conducted on a second test wall assembly 72 (as shown in Figures 13a-13h), rather than on the aforementioned simulated wall 1. The use of the second test wall assembly 72 facilitated subsequent 3D scanning and improved the accuracy of 3D distance measurements derived from the 3D point cloud.

[0098] 2. In the "Phase 2" of the aforementioned verification experiment, after using four laser displacement meters 6 / dynamic data recorders 61 to measure the spatial distance (d1-d4) and the average distance (K1-K4) from the four corner points of the mobile phone to the wall of the second test wall kit 72, a 3D scanner is required to scan the entire spatial distance measurement component 4 and the second test wall kit 72 to generate a 3D point cloud of the spatial distance measurement component 4 and the second test wall kit 72 (as shown in Figures 13e-13h). Based on this 3D point cloud, the spatial distance ( ) and the distances ( ) from the four corner points of the mobile phone to the wall of the second test wall kit 72, and compared with the measured distances (d1-d4) obtained from the four laser displacement meters 6 / dynamic data recorder 61 and the average distances (K1-K4) from the four corner points of the mobile phone to the wall of the second test wall kit 72.

[0099] The inventors repeated the above verification experiments several times and the results showed that the measured distances (d1-d4) and the real-time calculated average distances (K1-K4) of the four laser displacement meters 6 were significantly different from the distances obtained by 3D scanning / 3D point cloud measurement ( ) and distance ( The error of the test results can be controlled within the range of ±1.0 mm and ±0.8 mm. Therefore, these ranges (±1.0 mm and ±0.8 mm) are adopted as the allowable standards in the standard experimental process of the present invention.

[0100] Based on the above research results, the present invention established a standard experimental procedure to conduct a standard experiment to verify the accuracy of mobile phone apps in measuring concrete crack width. As shown in Figure 14, the above standard experimental procedure includes at least the following steps:

[0101] In step (a), set the desired target average distance Ki, i.e., the target average distance between the four corner points of the mobile phone 5 and the crack width correction plate 2 on the simulated wall 1, to, for example, 15, 20, or 25 cm. Then, set up a standard device comprising the simulated wall 1, the crack width correction plate 2, the posture adjustment and fixing device 3, and the spatial distance measurement component 4.

[0102] In step (b), the four laser displacement meters 6 installed on the aforementioned spatial distance measurement component 4 are connected to a dynamic data recorder 61 and a computer, and then a zeroing fixture 8 is used to zero the distance readings of the aforementioned four laser displacement meters 6.

[0103] As shown in Figure 15 , the zeroing jig 8 comprises a base 81. A recess 82 is provided on one side of the base 81. A stop wall 83 is located near the center of the base 81. A push plate 84 is located within the recess 82, allowing it to slide perpendicularly to the stop wall 83. The push plate 84 is parallel to the stop wall 83 and equipped with a locking mechanism 85. A reference surface 86 is provided on the other side of the base 81, perpendicular to the base 81 and parallel to the stop wall 83. A fixed distance (e.g., 115 mm) is maintained between the stop wall 83 and the reference surface 86. This fixed distance is designed to achieve the 0.1 mm precision typical of CNC jig manufacturing.

[0104] As shown in Figure 16, the operator simply places all of the laser displacement meters 6 in the groove 82 of the zeroing jig 8, then presses the push plate 84 against the rear ends of all of the laser displacement meters 6 and the front end against the blocking wall 83. The push plate 84 is then locked with the locking mechanism 85, and the dynamic data recorder is operated to reset the displacement readings to zero. The measurement signals of the four laser displacement meters 6 are connected to the four channels of the dynamic data recorder 61. After the dynamic data recorder is "zeroed," the raw readings of the four channels are nearly zero. Because, as previously mentioned, the fine-grained correction formulas for the four laser displacement meters have been programmed into the real-time calculation program of the dynamic data recorder 61, the real-time calculation function of the dynamic data recorder can be used to add 115 mm to the raw readings of the four channels to obtain the absolute distance value representing the laser start point to the laser end point of the laser displacement meter at the time of zeroing.

[0105] In step (c), the four laser displacement meters 6 and the mobile phone 5 are mounted on the spatial distance measurement assembly 4. The spatial distance measurement assembly 4 is then mounted above the posture adjustment and fixing device 3. The entire assembly is then moved so that it faces a first test wall assembly 71, completing the experimental setup for "Phase 1" of the verification experiment (as shown in Figures 9a-9e).

[0106] In step (d), a 3D scanner is used to scan the experimental configuration of "Phase 1" of the verification experiment in step (c) above (as shown in FIG9c ) and obtain its 3D point cloud (as shown in FIG9d-9e ).

[0107] In step (e), CloudCompare software is used to select 12 spatial points from the 3D point cloud generated in step (d): the laser starting points S1-S4 of the laser displacement meter 6, the laser end points E1-E4 on the wall of the first test wall kit 71, and the four corner points P1-P4 of the mobile phone 5. The 3D coordinates of these 12 spatial points are then exported.

[0108] Step (f) is to calculate the spatial unit vectors of the laser starting points pointing to the end points of the four laser displacement meters 6 based on the three-dimensional coordinate values of the 12 spatial points in step (e). , and then generate parameter setting codes for use by the real-time calculation program of the dynamic data recorder 61 of the aforementioned laser displacement meter 6.

[0109] In step (g), the spatial distance measurement assembly 4, the posture adjustment and fixing device 3, the mobile phone 5, and the four laser displacement meters 6 are maintained in their relative spatial positions. The entire assembly is then moved so that it faces a second test wall assembly 72, completing the experimental setup for "Phase 2" of the verification experiment (as shown in Figures 13a-13h).

[0110] Step (h), the parameter setting code (including P1-P4, S1-S4 and ) is input into the calculation program of the aforementioned dynamic data recorder 61, and automatic continuous measurement is started, and the real-time measurement distances d1-d4 (i.e. ) and the real-time calculated average distances K1-K4 (i.e. ).

[0111] Step (i) uses the posture adjustment and fixing device 3 to adjust (move and / or rotate) the spatial distance measurement component 4 until the real-time calculated average distances K1-K4 ( K1-K4) between the four corner points of the mobile phone 5 and the wall of the second test wall kit 72 displayed by the dynamic data recorder 61 are ) approaches or matches the target average distance Ki (e.g., 15, 20, or 25 cm) of the aforementioned step (a).

[0112] In step (j), the 3D scanner is used to scan the experimental configuration of the "Phase 2" verification experiment in which the positioning adjustment in step (i) is completed, and its 3D point cloud is obtained (as shown in Figures 13e-13h).

[0113] In step (k), CloudCompare software is used to select 12 spatial points from the 3D point cloud generated in step (j): the laser starting points S1-S4 of the laser displacement meter 6, the laser end points W1-W4 on the wall of the second test wall kit 72, and the four corner points P1-P4 of the mobile phone 5. The 3D coordinates of these 12 spatial points are then exported.

[0114] Step (1) calculates the distances d1-d4 (i.e., the distances d1-d4) between the laser starting points of the four laser displacement meters 6 and the laser end points on the wall of the second test wall kit 72 based on the three-dimensional coordinates of the 12 spatial points derived in step (k). ) and the average distance K1-K4 from the four corner points of the mobile phone 5 to the wall of the second test wall kit 72 (i.e. ).

[0115] Step (m) is to measure the distance of the four laser displacement meters 6 in step (i) The 3D scanning distance measured from the starting point to the end point of the laser displacement meter 6 in the above step (1) is Compare and check whether the difference △di is within ±1.0mm; and calculate the average distance from the four corner points of the mobile phone 5 to the wall of the second test wall kit 72 in the above step (i) The average distance between the four corner points of the mobile phone 5 and the wall of the second test wall kit 72 in the 3D scan in step (1) above Compare and check whether the difference △Ki is within ±0.8mm. If both the difference △di and △Ki are within the allowable standard range, continue with the following steps (n) and (o); otherwise, return to the above step (b) and repeat.

[0116] In step (n), the spatial distance measurement assembly 4, the posture adjustment and fixing device 3, the mobile phone 5, and the four laser displacement meters 6 are maintained in their relative spatial positions and the entire assembly is moved to face the simulated wall 1 and the crack width calibration plate 2 embedded therein, completing the experimental setup for the second "Phase 2" of the standard experimental process, that is, completing the experimental setup for the "Mobile App Standard Crack Width Measurement Experiment" (as shown in Figures 8a-8e).

[0117] In step (o), the second "Phase 2" operation in the standard experimental process is performed, that is, a standard crack width measurement experiment is performed on the aforementioned spatial distance measurement component 4 using the App of the mobile phone 5 to measure the width of the simulated crack 21 on the aforementioned crack width correction plate 2.

[0118] The preceding steps (b) through (l) constitute Phase 1 and the first Phase 2 of the aforementioned standard experimental process, which are also the verification experiments of the aforementioned standard experimental process. The following steps (n) and (o) constitute Phase 2 of the aforementioned standard experimental process, which are also the standard crack width measurement experiments using a mobile app. This second Phase 2 uses a mobile app to measure the width of a simulated crack 21 on a crack width calibration plate 2 embedded in a simulated wall 1 (as shown in Figures 8a-8e).

[0119] That is, the verification experiment of the aforementioned standard experimental process includes "Phase 1" and "Phase 2" of the aforementioned two-stage method. However, the verification experiment in "Phase 2" does not use simulated wall 1, but instead uses the second test wall kit 72 shown in Figures 13a-13h. The mobile app standard crack width measurement experiment of the aforementioned standard experimental process only includes "Phase 2" of the aforementioned two-stage method, and this mobile app standard crack width measurement experiment uses simulated wall 1 shown in Figures 8a-8e.

[0120] For example, a preliminary Android app developed by the inventors utilizes Google's ARCore AR library to determine the physical distance on the crack measurement surface, thereby converting it into the physical size of each pixel in the captured crack image. Therefore, the app can independently measure the width of the simulated crack 21 without any auxiliary equipment.

[0121] The aforementioned standard crack width measurement experiment using a mobile app in the standard experimental process only includes "Phase 2" of the aforementioned two-stage method. In "Phase 2" of the standard crack width measurement experiment using a mobile app in the standard experimental process (i.e., steps (n) and (o) in Figure 14 ), the inventors used the aforementioned preliminary app on a mobile phone (Pixel 8 Pro) installed in the aforementioned spatial distance measurement assembly 4 to measure the width of a simulated crack 21 on a crack width correction plate 2 embedded in a simulated wall 1 (as shown in Figures 8a-8e ). The embodiment of Figure 17 provides a further detailed operational flow of "Phase 2" of the standard crack width measurement experiment using a mobile app in the standard experimental process (i.e., steps (n) and (o) in Figure 14 ), while Figures 18a-18g provide photographs of the actual operation of "Phase 2" of the standard crack width measurement experiment using the mobile app in the standard experimental process.

[0122] Figure 17 illustrates the detailed operation process of the second "Phase 2" of the mobile app standard crack width measurement test after successfully completing "Phase 1" and the first "Phase 2" of the verification test of the aforementioned standard experimental process (i.e., completing step (m) in Figure 14). It includes a total of 9 specific steps (steps <1> To step <9> ), are as follows:

[0123] step <1> The aforementioned spatial distance measurement assembly 4 (including the mobile phone 5 and four laser displacement meters 6 therein) that has passed the verification experiment of the aforementioned standard experimental process (i.e., step (m) in Figure 14) is kept in a relative spatial position unchanged and is moved together with the posture adjustment and fixing device 3 to face the simulated wall 1 in which the aforementioned crack width correction plate 2 is embedded (as shown in Figure 18a).

[0124] step <2> As shown in FIG18b , temporarily remove the crack width correction plate 2 from the simulated wall 1 and use a illuminometer to measure the illuminance on the surface of the original crack width correction plate on the simulated wall 1. Then, appropriately adjust the lighting device (including the position, light intensity, and light angle of the lighting device) so that the illuminometer reading is between 750 lux and 1000 lux or other set values. Then, reinsert the crack width correction plate 2 into the simulated wall 1 and open the App on the mobile phone 5 and activate the camera preview screen of the App.

[0125] step <3> The spatial distance measuring component 4 is adjusted by using the posture adjustment and fixing device 3 until the following two conditions are met: Condition 1: the average distances K1-K4 measured in real time from the four corner points of the mobile phone 5 to the simulated wall 1 displayed on the computer by the operating software of the dynamic data recorder 61 are all close to the desired target average distance (15, 20 or 25 cm) (as shown in FIG18c); Condition 2: the horizontal center line of the screen in the preview screen of the mobile phone app is aligned with the direction of the target simulated crack 21 of the crack width correction plate 2, and the vertical center line of the screen in the preview screen of the mobile phone app is aligned with the mark 22 of the measuring point position of the target simulated crack on the crack width correction plate 2 (i.e., the horizontal and vertical dotted lines shown in FIG18d and 18e).

[0126] step <4> Temporarily separate the aforementioned spatial distance measurement component 4 from the aforementioned posture adjustment and fixing device 3, move the aforementioned spatial distance measurement component 4, and allow the mobile phone to use the AR detection function of the App to detect the surfaces of the aforementioned simulated wall 1 and the crack width correction plate 2 (as shown in Figures 18f and 18g) until fluorescent spots as shown in Figures 18d or 18e appear on the mobile phone screen. After confirming that the AR detection has correctly detected the plane of the crack width correction plate, reinstall the aforementioned spatial distance measurement component 4 on the aforementioned posture adjustment and fixing device 3.

[0127] step <5> , repeat the above steps <3> , and re-satisfy the above steps <3> Two conditions.

[0128] step <6> , click the camera shutter button in the App preview screen to capture the desired image of the simulated crack 21. The phone screen will automatically switch to the crack measurement function display screen.

[0129] step <7> By operating (dragging, zooming in or out, clicking, etc.) the user interface of the crack measurement function of the App, the width of the required simulated crack 21 at the specified width measurement point is measured from the captured image.

[0130] step <8> , repeat the above steps continuously <7> , until the widths of all the required simulated cracks 21 in the captured images are measured.

[0131] step <9> , repeat steps <3> To step <8> , complete the shooting of another image of the aforementioned simulated crack and the measurement of the width of the aforementioned simulated crack 21. That is, shoot another image of the aforementioned simulated crack 21 (step <3> To step <6> ), and then continuously and repeatedly measure the width of the aforementioned simulated crack 21 at all target positions of this image.

[0132] That is, the first two steps (steps <1> and steps <2> ), the aforementioned spatial distance measurement component 4, mobile phone 5 and four laser displacement meters 6 are kept in relative spatial positions, and the entire group is moved together with the posture adjustment and fixing device 3 to face the aforementioned simulation wall 1 (as shown in FIG18a), and then the lighting conditions are checked and adjusted (as shown in FIG18b). <3> To step <8> Contains pre-targeting of the phone 5 (step <3> ), perform AR detection (step <4> ), re-aim the phone 5 (step <5> ), take a simulated crack 21 image (step <6> ), and measure the width of the simulated crack 21 in the image (step <7> and steps <8> The last step (step <9> ) is to repeat the above steps according to the needs <3> To step <8> , to take another image of the simulated crack 21 and measure the width of the simulated crack 21.

[0133] It should be noted that the measurement technology used in the preliminary app requires the above steps <4> AR (augmented-reality) detection uses the ARCore library to detect physical distance. Therefore, for apps that do not use AR detection, the above steps can be removed. <4> , and the steps <3> and steps <5> Merge into one step. That is, for crack measurement apps that do not use AR detection, the above steps can be directly removed. <4> and steps <5> .

[0134] As shown in Figure 19, in order to capture the crack image (the steps used in the preliminary software above) <3> ,step <5> and steps <6> ), the simulated cracks 21 of the crack width correction plate 2 can be divided into four groups. <3> and steps <5> During the process (as shown in FIG17 ), the vertical center line in the preview screen of the mobile phone app is aligned with the L4 edge of the crack width correction plate 2 (as shown in FIG19 ), and the horizontal center line is aligned with the center of the desired simulated crack 21. This horizontal alignment corresponds to the simulated crack 21 in the middle position of each group of simulated cracks 21 shown in FIG19 . In other words, for each of the four groups of simulated cracks 21 on the aforementioned crack width correction plate 2, the aforementioned mobile phone is aligned accordingly (step <3> and steps <5> ), and take an image of the simulated crack 21 (step <5> ). Therefore, during each complete standard experiment of this embodiment, a total of four images of the simulated cracks 21 were taken, one for each group of simulated cracks 21 (as shown in FIG19 ). For each simulated crack 21 in each captured image, the App measured its width at three locations (edges L2, L4, and L6 in FIG19 ). Therefore, each captured image contains 15 or 18 crack width values, depending on whether there are 5 simulated cracks 21 (Group (1)-(3)) or 6 cracks (Group (4)) in the crack group on the crack width calibration plate 2 (as shown in FIG19 ).

[0135] Figures 20a-20d show the experimental results of the aforementioned standard crack width measurement experiment using a Pixel 8 Pro phone and the aforementioned preliminary app in the aforementioned embodiment. As previously mentioned, the "true" crack width values wTrue corresponding to the app-measured values wApp in Figures 20a-20d were obtained through systematic and repeated manual measurements using five crack width magnifiers. Figures 20a and 20b show the experimental results of 10 standard crack width measurement experiments with an average target distance Ki of 15 cm, while Figures 20c and 20d show the experimental results of 5 standard crack width measurement experiments with an average target distance Ki of 20 cm.

[0136] The aforementioned measured value, wApp, can be divided by the "physical size per unit pixel" calculated by the app using the ARCore-AR library to obtain its corresponding pixel count. If the pixel count is too low, the error in converting the crack width to an integer number of pixels may be large. Therefore, the experimental results in Figures 20a-20d only include wApp measurements with a pixel count of 4 or more, and those with fewer than 4 pixels are discarded. This also determines the minimum crack width that the app can measure: the wApp value with a pixel count of 4. The main difference between Figures 20a and 20b and Figures 20c and 20d is likely the difference in the minimum measurable crack width. In the former (Figures 20a and 20b), the average target distance Ki between the phone 5 and the simulated wall 1 is closer (15 cm), resulting in a minimum wApp measurement of 0.33 mm. In the latter (Figures 20c and 20d), the average target distance Ki between the phone 5 and the simulated wall 1 is farther (20 cm), resulting in a minimum wApp measurement of only 0.50 mm.

[0137] The minimum target average distance Ki is approximately 15 mm, as the mobile phone camera cannot capture clear images for target average distances Ki below this value. Therefore, the experimental results (Figures 20a and 20b) show that the minimum measurable crack width of the app is 0.33 mm, which is still too large for most engineering applications. This limitation can be attributed to the low resolution of the captured images. This is because the camera preview function of the preliminary app is controlled by ARCore-AR, so its image capture is limited to the phone screen display resolution, which is generally much lower than the maximum resolution of the camera. This also results in the app's minimum measurable crack width being too large.

[0138] The above experimental results (Figures 20a-20d) can be further studied from different perspectives. For example, the △w distribution in Figures 20a-20d is more dispersed, the error range is larger, and the △w distribution is shifted to negative values. The aforementioned large △w distribution range may be due to the physical distance detected by AR (step 17 in Figure 17). <4> This is due to the limited accuracy of the software, as AR is designed solely to meet the needs of human vision, rather than the higher precision required for engineering measurements. The aforementioned negative shift in the Δw distribution (approximately half a pixel) may be related to the software's method of determining crack edges.

[0139] In summary, the present invention has developed a standard experimental method and standard equipment to test and verify the accuracy of mobile phone apps in measuring concrete crack width. The apparatus comprises a standard crack width calibration plate 2 and a simulated wall 1, as well as a dedicated spatial distance measurement component 4 and a posture adjustment and fixation device 3. In the standard experimental method used in the present invention, an innovative two-stage method associated with the aforementioned spatial distance measurement component 4 simultaneously calculates and displays the four average distances Ki from the four corner points Pi (i=1-4) of the mobile phone to the simulated wall 1. Through continuous Ki value monitoring feedback, the posture adjustment and fixation device 3 can simultaneously adjust the position of the mobile phone 5 until the monitored average distance Ki matches the target average distance Ki. Subsequently, the width of the simulated crack 21 on the crack width calibration plate 2 is measured using an app installed on the mobile phone. The present invention also establishes a standard experimental process for verifying the accuracy of mobile phone apps in measuring concrete crack width.

[0140] Regarding the cost-effectiveness of the two-stage method, the dedicated spatial distance measurement assembly 4 can be composed of a custom-designed stainless steel plate mounting frame 41, four laser displacement meters 6, and a mobile phone 5 for testing. The 3D scanning results of the "stage 1" of the two-stage method can obtain the 3D coordinates of eight spatial points (P1-P4 and S1-S4) and four 3D unit vectors ( ), which represents the spatial relationship between the mobile phone 5 and the laser beams of the four laser displacement sensors 6 in the spatial distance measurement component 4. In "Phase 2" of this two-stage method, these 3D coordinates are used together with the real-time distance measurements (d1-d4) from the laser displacement sensors 6 to simultaneously calculate and display four Ki values.

[0141] Another possible approach is to pre-design a specific spatial configuration and then manufacture a mounting bracket that matches this configuration to hold the four laser displacement meters 6. This approach can also determine the spatial relationship between the mobile phone 5 and the four laser displacement meters 6. However, this approach requires high-precision machining to manufacture the metal mounting bracket, which is costly and uneconomical. Therefore, the present invention uses standard sheet metal processing to manufacture a stainless steel mounting bracket 41 to hold the four laser displacement meters 6. It then uses currently widely used 3D scanning technology to measure the spatial relationship between the mobile phone 5 and the laser beams of the four laser displacement meters 6. This approach is significantly more economical.

[0142] Furthermore, the spatial distance measurement assembly 4 of the stainless steel plate fixing frame 41 of the present invention can also be conveniently manufactured to be suitable for maintaining the mobile phone 5 in a horizontal (transverse) orientation, so as to study the effect of the mobile phone orientation on the experimental results.

[0143] The standard crack width measurement experiments and results (shown in Figures 14, 17, and 18a-18g) performed using the preliminary app all feature four real-time average distance values, K1, K2, K3, and K4, that match the target average distance Ki. In other words, while the aforementioned embodiments all tested the phone 5 parallel to the simulated wall 1, the standard testing method of the present invention can also be expanded to accommodate situations where the phone 5 is tilted relative to the simulated wall 1. This can be achieved by setting different values of K1-K4 to produce a predetermined tilt angle.

[0144] In summary, the standard experimental method and its standard equipment developed in this invention have two main functions: (1) controlling the experimental parameters required for test conditions; and (2) reproducing the test conditions required for repeated experiments. These two functions can be used to explore the influence of various experimental parameters and allow comparison of experimental results under the same test conditions. Therefore, they can be used to perform a high number of systematic measurement experiments and establish the reliability of software accuracy verification.

[0145] Of course, the application of crack width measurement still requires verification on actual concrete cracks. However, if we draw a parallel with the recent global focus on vaccine and drug development, the "standard experimental method and standard equipment" described in this disclosure can be compared to easily repeatable animal experiments, while the measurement and verification of actual concrete cracks can be compared to human experiments. Just like human experiments in drug development, the measurement and verification of actual concrete cracks is not easily performed in a high-volume, systematic manner. Therefore, easily repeatable, standardized measurement experiments, like animal experiments, are essential.

[0146] In addition to testing and verifying the accuracy of crack width measurements using a mobile app, this standard experimental method can also standardize concrete crack width measurement and, for the first time, provide an objective, unified definition of concrete surface crack width. Traditional methods for measuring concrete crack width (such as crack width magnifiers or crack width comparison cards) rely on subjective human interpretation. Therefore, to the best of the inventor's knowledge, there is no unified, precise, objective definition of concrete crack width. Combining the mobile app's ability to perform objective crack width measurements with the standard experimental method for verifying its accuracy, as described in this invention, could help resolve this issue in the future.

[0147] The aforementioned embodiments or drawings do not limit the aspects or usage of the present invention. Any appropriate changes or modifications made by a person skilled in the art should be considered as not departing from the patent scope of the present invention.

[0148] 1: Simulation wall

[0149] 11: Angle adjustment mechanism

[0150] 111: Base

[0151] 112: support rod

[0152] 113: chute

[0153] 114: Locking element

[0154] 12: Container

[0155] 13: Measuring slot

[0156] 2: Crack width correction plate

[0157] 21: Simulate cracks

[0158] 22: Mark

[0159] 3: Posture adjustment and fixing device

[0160] 31:Pan head tripod

[0161] 32: Two-axis moving mechanism

[0162] 4: Spatial distance measurement component

[0163] 41:Fixed bracket

[0164] 42: Mobile phone holder

[0165] 43:Fixed slot

[0166] 5. Mobile Phone

[0167] 6: Laser displacement meter

[0168] 61: Dynamic Data Recorder

[0169] 71: First Test Wall Kit

[0170] 72: Second Test Wall Kit

[0171] 8: Zeroing fixture

[0172] 81: Base

[0173] 82: Groove

[0174] 83: Blocking Wall

[0175] 84: Push Plate

[0176] 85: Locking mechanism

[0177] 86: Datum

Claims

1. A standard experimental method for verifying the accuracy of mobile phone App in measuring concrete crack width, wherein the standard experimental process comprises at least the following steps: Step (a), setting a target average distance, and setting a standard device comprising a simulated wall, a crack width correction plate, a posture adjustment and fixing device, and a spatial distance measurement component; the aforementioned crack width correction plate is embedded in the aforementioned simulated wall, and the aforementioned crack width correction plate is processed by precision machinery to have a plurality of simulated cracks of different widths; a mobile phone and four laser displacement meters are fixed on the aforementioned spatial distance measurement component; the aforementioned target average distance refers to the target value of the average distance from the four corner points of the aforementioned mobile phone to the aforementioned simulated wall; Step (b), connecting the four laser displacement meters set on the aforementioned spatial distance measurement component to a dynamic data recorder and a computer, and then using a zeroing fixture to zero the distance measurement readings of the aforementioned four laser displacement meters 6; Step (c), fixing the aforementioned four laser displacement meters and the mobile phone on the aforementioned spatial distance measurement component, then installing the aforementioned spatial distance measurement component above the aforementioned posture adjustment and fixing device, and then moving the entire group and facing a first test wall kit to complete the experimental configuration of the aforementioned step (c); Step (d), using a 3D scanner to scan the experimental configuration of the aforementioned step (c) and obtain its 3D point cloud; Step (e), selecting the laser starting point of the aforementioned laser displacement meter, the laser end point on the wall of the aforementioned first test wall kit, and the four corner points of the aforementioned mobile phone from the 3D point cloud of the aforementioned step (d), and then exporting the three-dimensional coordinates of the 12 spatial points; Step (f), calculating the spatial unit vectors pointing from the laser starting point to the end point of the aforementioned four laser displacement meters according to the three-dimensional coordinate values of the 12 spatial points in the aforementioned step (e), and then generating a parameter setting code for use by the real-time calculation program of the dynamic data recorder of the aforementioned laser displacement meter; Step (g), keeping the aforementioned spatial distance measurement component, the posture adjustment and fixing device, the mobile phone and the four laser displacement meters in a relative spatial position unchanged, and then moving the entire group and facing a second test wall kit to complete the experimental configuration of the aforementioned step (g); Step (h), inputting the parameter setting code generated in the aforementioned step (f) into the calculation program of the aforementioned dynamic data recorder, and starting automatic continuous measurement, and displaying the real-time measurement distance of the aforementioned four laser displacement meters and the real-time calculated average distance from the four corner points of the aforementioned mobile phone to the wall of the aforementioned second test wall kit; Step (i), using the aforementioned posture adjustment and fixing device to adjust the aforementioned spatial distance measurement component until the real-time calculated average distance from the four corner points of the aforementioned mobile phone to the wall of the aforementioned second test wall kit displayed by the aforementioned dynamic data recorder approaches and matches the target average distance of the aforementioned step (a); Step (j), using the aforementioned 3D scanner to scan the experimental configuration adjusted and positioned in the aforementioned step (i), and obtain its 3D point cloud;Step (k), selecting 12 spatial points, including the laser starting point of the laser displacement meter, the laser end point on the wall of the second test wall kit, and the four corner points of the mobile phone, from the 3D point cloud of the step (j), and then exporting the three-dimensional coordinates of the 12 spatial points; Step (l), calculating the distance from the laser starting point of the four laser displacement meters to the laser end point on the wall of the second test wall kit, and the average distance from the four corner points of the mobile phone to the wall of the second test wall kit based on the three-dimensional coordinates of the 12 spatial points exported in the step (k); Step (m), compare the real-time measurement distance of the four laser displacement meters in the aforementioned step (i) with the 3D scanning measurement distance from the laser starting point of the four laser displacement meters in the aforementioned step (l) to the laser end point on the wall of the aforementioned second test wall kit, and check whether the difference is within the allowable standard range of mm; and compare the average distance from the four corner points of the mobile phone to the wall of the aforementioned second test wall kit in the aforementioned step (i) with the 3D scanning average distance from the four corner points of the mobile phone to the wall of the aforementioned second test wall kit in the aforementioned step (l), and check whether the difference is within the allowable standard range of mm; if both of the above differences are within the allowable standard range, continue with the following steps, otherwise return to the aforementioned step (b) and repeat; Step (n), keep the aforementioned spatial distance measurement component, posture adjustment and fixing device, mobile phone and four laser displacement meters in relative spatial position unchanged, and move the entire group to face the aforementioned simulated wall and the crack width correction plate embedded therein, to complete the experimental configuration of the aforementioned step (n); Step (o), using the aforementioned mobile phone App on the aforementioned spatial distance measurement component to perform a standard crack width measurement experiment to measure the width of the simulated crack on the aforementioned crack width calibration plate, and compare and verify the accuracy of the measurement. ; 2. The standard experimental method for verifying the accuracy of the mobile phone App in measuring the width of concrete cracks according to claim 1, wherein steps (n) and (o) of the aforementioned standard experimental process at least include the following steps: Step <1>, keeping the aforementioned spatial distance measurement component, mobile phone and four laser displacement meters that have passed the aforementioned step (m) unchanged in relative spatial position, and then moving the entire group together with the aforementioned posture adjustment and fixing device to face the simulated wall in which the aforementioned crack width correction plate has been embedded; Step <2>, temporarily removing the crack width correction plate on the aforementioned simulated wall, using a illuminance meter to measure the light illuminance on the surface of the original crack width correction plate on the aforementioned simulated wall, and then adjusting the lighting device, and then re-embedding the aforementioned crack width correction plate into the aforementioned simulated wall, and opening the aforementioned mobile phone App and starting the camera preview screen; Step <3>, by using the aforementioned posture adjustment and fixing device to adjust the aforementioned spatial distance measurement component until the following two conditions are met: Condition 1, the average distances of the real-time measurements from the four corner points of the aforementioned mobile phone to the aforementioned simulated wall displayed on the computer by the operating software of the aforementioned dynamic data recorder are all close to the aforementioned target average distance; Condition 2, a plurality of marks are set at intervals on the aforementioned simulated crack, the horizontal center line of the screen in the preview screen of the aforementioned mobile phone App is aligned with the direction of the target simulated crack of the aforementioned crack width correction plate, and the vertical center line of the screen in the preview screen of the aforementioned mobile phone App is aligned with the mark of the measuring point position of the target simulated crack on the aforementioned crack width correction plate; Step <4>, temporarily separate the aforementioned spatial distance measurement component from the aforementioned posture adjustment and fixing device, and move the aforementioned spatial distance measurement component, the aforementioned mobile phone App has an AR detection function, until the AR detection function of the aforementioned mobile phone App has correctly detected the plane of the aforementioned crack width correction plate, and then reinstall the aforementioned spatial distance measurement component to the aforementioned posture adjustment and fixing device; Step <5>, repeat the aforementioned step <3>, and re-satisfy the two conditions of the aforementioned step <3>; Step <6>, use the aforementioned mobile phone App to shoot an image of the aforementioned simulated crack, and activate the crack measurement function of the aforementioned mobile phone App; Step <7>, by operating the crack measurement function of the aforementioned mobile phone App, measure the width of the aforementioned simulated crack from the image shot in the aforementioned step <6>; Step <8>, continuously repeat the aforementioned step <7> until the widths of all the aforementioned simulated cracks in the image shot in the aforementioned step <6> are measured; Step <9>, repeat steps <3> to step <8>, shoot another image of the aforementioned simulated crack, and continuously and repeatedly measure the widths of all the aforementioned simulated cracks in the image, and then compare and verify the accuracy of the measurement.

3. The standard experimental method for verifying the accuracy of the mobile phone App in measuring the width of concrete cracks according to claim 1, wherein steps (n) and (o) of the aforementioned standard experimental process at least include the following steps: Step <1>, keeping the aforementioned spatial distance measurement component, mobile phone and four laser displacement meters that have passed the aforementioned step (m) unchanged in relative spatial position, and then moving the entire group together with the aforementioned posture adjustment and fixing device to face the simulated wall in which the aforementioned crack width correction plate has been embedded; Step <2>, temporarily removing the crack width correction plate on the aforementioned simulated wall, using an illuminance meter to measure the light illuminance on the surface of the original crack width correction plate on the aforementioned simulated wall, and then adjusting the lighting device, and then re-embedding the aforementioned crack width correction plate into the aforementioned simulated wall, and opening the aforementioned mobile phone App and starting the camera preview screen; Step <3>, by using the aforementioned posture adjustment and fixing device to adjust the aforementioned spatial distance measurement component until the following two conditions are met: Condition 1, the average distances of the real-time measurement from the four corner points of the aforementioned mobile phone to the aforementioned simulated wall displayed on the computer by the operating software of the aforementioned dynamic data recorder are all close to the aforementioned target average distance; Condition 2, a plurality of marks are set at intervals on the aforementioned simulated crack, the horizontal center line of the screen in the preview screen of the aforementioned mobile phone App is aligned with the direction of the target simulated crack of the aforementioned crack width correction plate, and the vertical center line of the screen in the preview screen of the aforementioned mobile phone App is aligned with the mark of the measuring point position of the target simulated crack on the aforementioned crack width correction plate; Step <4>, using the aforementioned mobile phone App to capture an image of the aforementioned simulated crack, and activating the crack measurement function of the aforementioned mobile phone App; Step <5>, by operating the crack measurement function of the aforementioned mobile phone App, measure the width of the aforementioned simulated crack from the image captured in the aforementioned step <4>; Step <6>, continuously repeating the aforementioned step <5> until the widths of all the aforementioned simulated cracks in the image taken in the aforementioned step <4> are measured; Step <7>, repeating steps <3> to <6>, taking another image of the aforementioned simulated cracks, and continuously and repeatedly measuring the widths of all the aforementioned simulated cracks in the image, and then comparing and verifying the accuracy of the measurement.

4. The standard experimental method for verifying the accuracy of mobile phone apps in measuring concrete crack width according to claim 1, wherein the simulated wall is a wooden simulated wall, and the crack width correction plate is a crack width correction steel plate.

5. According to the standard experimental method for verifying the accuracy of mobile phone apps in measuring concrete crack width as described in claim 4, the aforementioned simulated wall is provided with an angle adjustment mechanism to control the inclination angle of the aforementioned simulated wall; the aforementioned angle adjustment mechanism is provided with a base, a support rod and a slide groove, the aforementioned base is pivotally connected to the bottom of the aforementioned simulated wall, one end of the aforementioned support rod is pivotally arranged behind the aforementioned simulated wall, the aforementioned slide groove is arranged on the aforementioned base, and the other end of the aforementioned support rod is arranged in the aforementioned slide groove, and the support rod is provided with a locking element, so that the aforementioned support rod can be locked and fixed to each other with the aforementioned slide groove through the locking element after the aforementioned support rod is adjusted and positioned.

6. According to the standard experimental method for verifying the accuracy of mobile phone apps in measuring concrete crack width as described in claim 1, the aforementioned simulated wall is provided with a receiving groove, and a measuring groove is extended on one side of the receiving groove, the aforementioned crack width correction plate is embedded in the aforementioned receiving groove, and the aforementioned measuring groove is used to place an illuminance meter to accurately measure the light intensity at the position of the aforementioned crack width correction plate.

7. According to the standard experimental method for verifying the accuracy of mobile phone apps in measuring concrete crack width as described in claim 1, all the aforementioned crack width measurement points of the simulated cracks are manually measured in advance to determine the actual crack width values at all the aforementioned crack width measurement points of the simulated cracks.

8. The standard experimental method for verifying the accuracy of mobile phone apps in measuring concrete crack width according to claim 1, wherein the posture adjustment and fixing device is provided with a pan-tilt tripod and a two-axis moving mechanism, and the two-axis moving mechanism is provided on the pan-tilt tripod.

9. According to the standard experimental method for verifying the accuracy of mobile phone App in measuring concrete crack width as described in claim 1, the aforementioned spatial distance measurement component is provided with a fixing frame, on which a mobile phone clamp and four fixing slots are provided, the aforementioned mobile phone clamp is located in the middle position of the aforementioned fixing frame and fixes the aforementioned mobile phone; the aforementioned four laser displacement meters are respectively fixed on the aforementioned four fixing slots.

10. The standard experimental method for verifying the accuracy of mobile phone apps in measuring concrete crack width according to claim 1, wherein the zeroing fixture is provided with a base, a groove is provided on one side of the base, a blocking wall is provided on one side of the groove near the middle of the base, a push plate is provided in the groove that can slide in the vertical direction of the blocking wall, the push plate and the blocking wall are parallel to each other, and the push plate is provided with a locking mechanism; a reference plane perpendicular to the base is provided on the other side of the base, the reference plane and the blocking wall are parallel to each other, and there is a fixed distance between the blocking wall and the reference plane.