Image acquisition system and method for concrete pressure testing machine

Abstract

The invention relates to an image acquisition system and method for a concrete pressure testing machine, and the system comprises a distance sensor array which is disposed on the pressure testing machine and is used for detecting and recording the distance change data between each sensor and a corresponding positioning point on a concrete test block in real time; the image acquisition module is mounted on the periphery of the pressure testing machine and is used for recording continuous image information in the process from test block placement to complete damage; the data synchronization and control module is used for realizing time synchronization of all equipment; the data processing and analyzing module is used for analyzing and extracting key image features and associating the image information with the distance data according to a timestamp; and the mapping and visualization module is used for automatically mapping the key image onto a concrete compressive strength curve and providing real-time data visualization. According to the invention, the concrete pressure test is more effectively supported, and the authenticity, accuracy and traceability of the test are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete compression testing machines, and particularly to an image acquisition system and method for a concrete compression testing machine. Background Art

[0002] Concrete materials are the most widely used building materials in today's world's building structures, playing an irreplaceable role in the field of civil engineering. As one of the most important indicators for evaluating the quality of concrete, the compressive strength is directly related to the safety, durability, and service life of buildings (structures). Currently, compression testing machines are most commonly used at construction sites to detect the strength of concrete. At the same time, in order to more comprehensively record the deformation and failure conditions during the compression of test blocks, operators will configure image acquisition devices beside the testing machine.

[0003] However, there are still several significant defects in the existing image acquisition methods: 1) There is a lack of an automatic association mechanism between the image information and the concrete compressive strength curve; that is, the key change points on the image and the strength curve cannot be directly corresponding, which brings inconvenience to subsequent data comparison and analysis.

[0004] 2) The complex situation at the moment of the test block rupture poses challenges to image acquisition. At the moment of rupture, the compression testing machine will vibrate briefly due to the violent destruction of the test block and be accompanied by a strong instantaneous impact. This situation not only affects the accuracy of image acquisition but may also miss the best recording opportunity due to insufficient real-time performance of image acquisition. 3) The integration degree between some image acquisition devices and the testing machine is insufficient. Most are recorded manually daily, which cannot guarantee the authenticity and uniqueness of the data, and there are problems such as low efficiency, low reliability, and low safety, further weakening the synchronization and accuracy of data acquisition.

[0005] Based on this, it is necessary to provide an image acquisition system for a concrete compression testing machine with high precision, strong real-time performance, and accurate and reliable data. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide an image acquisition system and method for a concrete compression testing machine, which effectively solves the problems of insufficient image acquisition accuracy and real-time performance, inaccurate deformation monitoring, difficult data association and analysis, and insufficient test authenticity and traceability existing in the existing concrete compression testing machine image acquisition system.

[0007] To achieve the above purpose, the technical solution adopted by the present invention is: An image acquisition system for a concrete compression testing machine, characterized in that:

[0008] It includes an array of distance sensors deployed on the compression testing machine, which is used to detect and record the distance change data between each sensor and the corresponding positioning points on the concrete test block in real time;

[0009] An image acquisition module installed around the compression testing machine, which is used to record continuous image information during the process from the placement of the test block to complete failure;

[0010] A data synchronization and control module, which is used to achieve time synchronization of all devices, and at the same time control the start, stop and exception handling of data acquisition;

[0011] A data processing and analysis module, which is used to preprocess the acquired image data, analyze and extract key image features, and associate the image information with the distance data according to the time stamp;

[0012] A mapping and visualization module, which is used to automatically map the above key images to the concrete compressive strength curve, and provide real-time data visualization, display the dynamic changes of the image and the strength curve, and present the real-time dynamic monitoring of the quality of the entire test operation process;

[0013] A data storage and management module, which is used to achieve efficient data retrieval and storage management functions;

[0014] A network and communication module, which is used for data transmission between modules.

[0015] Furthermore, the distance sensor array is arranged around the compression testing machine, and positioning points corresponding to the output points of the distance sensors are correspondingly provided on the side surfaces of each concrete test block, and it is ensured that the measurement points of the distance sensors are accurately aligned with the positioning points on the test blocks.

[0016] Furthermore, the image acquisition module includes a number of high-definition cameras arranged around the compression testing machine, and the image information of the entire process of the concrete test block from placement, failure to complete failure and cracking is captured and acquired through the configured high-definition cameras.

[0017] Furthermore, the data synchronization and control module integrates a central control unit and a network time protocol server. The central control unit is responsible for real-time processing and correction of various types of sensing data received, and provides a unified time reference for the entire system through the built-in NTP server to ensure that all devices operate within the same time frame.

[0018] Furthermore, the data synchronization and control module adopts a mechanism combining hardware trigger and software trigger to ensure that each sensor and camera start collecting data at the same moment; a data fusion algorithm and a delay compensation algorithm are also integrated inside the data synchronization and control module to perform time series calibration and fusion processing on multi-source data.

[0019] Furthermore, the data fusion algorithm includes using the Kalman filter recursive algorithm to process and fuse real-time data to ensure that the data has a consistent time reference during the fusion process; the delay compensation algorithm includes recording by setting timestamps. Assume that the acquisition time of data packet di is t i 采集 and the reception time is t i 接收 , then the delay δ i can be expressed as:

[0020] δ i = t i 接收 - t i 采集

[0021] When processing data, use the delay δ i to correct the timestamp:

[0022] t i 修正 = t i 采集 + δi.

[0023] Furthermore, the data processing and analysis module preprocesses the received image data and distance data, smooths the image, reduces the influence of noise, and at the same time uses image enhancement algorithms to improve the visibility of image details, identifies and marks the crack and deformation features in the image, and uses moving average or filtering algorithms to remove the noise in the distance data.

[0024] Furthermore, the data processing and analysis module uses Fourier transform to analyze the features in the frequency domain to identify the main frequency components of the signal, so as to reveal the periodic features in the signal; and through the inverse transform, it identifies the peaks and valleys in the original time-domain signal to reveal potential key events; then calculates the derivative of the distance data to identify fast-changing events.

[0025] Furthermore, the mapping and visualization module establishes a reference curve of concrete compressive strength according to the test data, determines the key failure moments identified in the analysis results, marks at the corresponding positions on the strength curve, embeds the key image thumbnails at the marked positions, uses visualization tools to draw interactive charts, and supports users to view the images at critical moments through the interactive interface.

[0026] The present invention also provides a method for image acquisition of a concrete compression testing machine, including the following steps:

[0027] Step 1: Stably install multiple high-definition cameras around the compression testing machine; on the side of each concrete test block, mark several positioning points respectively, and then place the concrete test block at the central position of the compression testing machine;

[0028] Step 2: Fix the distance sensors on the compression testing machine to ensure that the probes of each distance sensor are accurately aligned with the positioning points on the test block; use the central control unit and NTP server in the data synchronization and control module to perform time synchronization and set a unified time reference.

[0029] Step 3: Start the concrete compression test, gradually increase the pressure applied to the test block, and during the entire process of the test block changing from the normal state to complete failure, the high-definition camera captures the image information of the test block in real time. At the same time, the distance sensor measures the distance change between it and the corresponding positioning point in real time, and transmits the image information and distance change information to the data processing and analysis module.

[0030] Step 4: The data processing and analysis module stores the distance change curve in the form of a time series according to the data it receives, and preprocesses the images.

[0031] Step 5: Based on the time stamp, associate the image information and distance data, perform comparison and synchronization analysis on them, extract and mark the critical failure moments and the corresponding high-definition images, and generate preliminary structural damage judgment and feature extraction results.

[0032] Step 6: Transmit the analysis results to the mapping and visualization module, embed the key images into the concrete compressive strength curve, use visualization tools to generate interactive charts, and store them in the data storage and management module.

[0033] The beneficial effects of the above technical solutions are as follows:

[0034] The concrete compression testing machine image acquisition system and method provided by the present invention install multiple high-definition cameras and distance sensors on the concrete compression testing machine, and the positions of these devices correspond to the positioning points on the concrete test block. This configuration ensures that the deformation and failure conditions of the test block during compression can be comprehensively and accurately captured. By using the distance sensor to measure the distance between the sensor and the test block positioning point in real time, it is convenient to monitor the deformation of the test block during compression. At the same time, the high-definition camera captures the whole process image information of the test block from placement, compression, failure to complete collapse. Then, using relevant algorithms, the distance change curve detected by the distance sensor can be associated with the image information captured by the camera; this association enables the identification of each key image during the failure process of the test block, and these images can be automatically mapped onto the concrete compressive strength curve, thereby marking the critical moments corresponding to the strength changes. Through this method, not only the visualization degree of the test process is improved, but also the test data is made more accurate and reliable. At the same time, due to the direct association between the key images and the strength curve, the authenticity and traceability of the test are enhanced, providing strong support for subsequent data analysis and quality control.

[0035] Through the use of a distance sensor array and a high-definition camera, the system of the present invention can accurately capture the details of the deformation and failure of concrete test blocks; through the data synchronization and control module, the time synchronization of all devices and the consistency of data are achieved, ensuring the accuracy of data acquisition; by using the delay compensation and timestamp matching algorithms, the system can effectively correct the delay in data transmission and processing, improving the real-time performance and accuracy of data processing.

[0036] Through the image acquisition and data processing and analysis module, the system can capture and analyze the failure process of concrete test blocks from multiple angles, identify the critical failure moments and characteristics, providing an accurate basis for subsequent decision-making; by adopting the dynamic time warping (DTW) and data fusion algorithms, the system can accurately correlate the image data with the distance data, ensuring the synchronous analysis of data at the same time point and improving the depth and breadth of data analysis.

[0037] The mapping and visualization module intuitively presents the analysis results. Users can view the failure feature images while observing the changes in mechanical properties, improving the interpretability and operability of experimental results. Through the data storage and management module, the system realizes efficient data retrieval and long-term preservation, and provides data backup and recovery mechanisms to ensure the security and integrity of data. The network and communication module supports remote data monitoring and control, provides API interfaces, allows external devices to access, and supports the remote upgrade and maintenance of the system, enhancing the flexibility and scalability of the system.

[0038] The system design of the present invention reduces human operation errors, improves experimental efficiency, enhances the reliability and repeatability of test results, can more effectively support the conduct of concrete pressure tests, and improves the authenticity, accuracy and traceability of tests. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the system connection of the present invention;

[0040] Figure 2 It is a flowchart of the implementation of the present invention;

[0041] Figure 3 It is a schematic diagram of the layout of the distance sensor matrix of the present invention;

[0042] Figure 4 It is a mapping diagram of the concrete strength curve and key images of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0043] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments:

[0044] Embodiment 1. This embodiment aims to provide an image acquisition system for a concrete compression testing machine, which is mainly used to acquire images of the whole process of specimen failure during the test operation of the concrete compression testing machine equipment, and automatically mark the corresponding positions on the concrete strength curve, so as to enhance the authenticity and traceability of the concrete test detection process. Aiming at the problems of insufficient image acquisition accuracy and real-time performance, inaccurate deformation monitoring, difficult data correlation and analysis, and insufficient test authenticity and traceability existing in the current image acquisition system of the concrete compression testing machine, this embodiment provides an image acquisition system for a concrete compression testing machine, which realizes the comprehensive and accurate recording and analysis of the concrete specimen failure process, and provides a more scientific and reliable basis for the evaluation of concrete strength.

[0045] As Figures 1-4 shown, the image acquisition system for a concrete compression testing machine provided in this embodiment includes a distance sensor array, an image acquisition module, a data synchronization and control module, a data processing and analysis module, a mapping and visualization module, a data storage and management module, and a network and communication module deployed on the compression testing machine.

[0046] Among them, the distance sensor array is used to detect the distance change data between each distance sensor and the positioning points on the detected concrete specimen, and provide accurate displacement data to reflect the specimen deformation; the image acquisition module is arranged around the compression testing machine, and is used to completely capture the overall view of the concrete specimen from all angles, and collect the image information of the whole process of the concrete specimen from being placed, damaged, and completely damaged and cracked.

[0047] Specifically, when implementing, a plurality of high-definition cameras and distance sensors are arranged around the concrete compression testing machine, and positioning points corresponding to the output points of the distance sensors are correspondingly arranged on the side surface of each concrete specimen, and it is ensured that the measurement points of the distance sensors are accurately aligned with the positioning points on the specimen.

[0048] When actually implementing, as Figure 3 shown, since grid-shaped baffles are installed around the compression testing machine to prevent safety accidents to on-site personnel during the cracking process of the concrete specimen, in the present invention, the distance sensor matrix is fixedly installed on the baffle, and the output probes of each sensor correspond to the mesh holes on the baffle, so as to be able to align with the positioning points on the concrete specimen; the high-definition cameras are correspondingly installed at the center and around the distance sensor matrix, and the probe positions of the cameras face the concrete specimen, and high-definition cameras and distance sensor matrices are installed around the compression testing machine, so as to realize the all-round angle shooting and capturing of the concrete specimen, and at the same time, through each measurement point, it is convenient for the staff to analyze and monitor the quality distribution inside the concrete specimen (in actual application, the sensor array and high-definition cameras can be reasonably optimized and arranged according to the actual situation).

[0049] In addition, since the strength test is carried out by using a concrete compression testing machine by applying continuously increasing pressure until the concrete test block breaks, during the test, the distance changes between this sensor and the positioning points on the concrete test block are measured by various distance sensors, and the surface state of the test block is comprehensively captured from different angles by a high-definition camera, that is, the high-definition camera configured captures and collects the image information of all processes of the concrete test block from the placement, damage occurrence, and complete damage and cracking. And the image information and distance data are transmitted to the data processing and analysis module through the communication module.

[0050] The above-mentioned distance sensing array and image acquisition module are both signal-connected to the data synchronization and control module through the communication module, so as to transmit the collected distance change data and image information to the data synchronization and control module, so as to achieve the time synchronization of all devices, realize the coordinated acquisition and control management of data, and ensure the consistency and accuracy of data. Specifically, the data synchronization and control module integrates a central control unit (which can be dedicated hardware or a computer) and a Network Time Protocol (NTP) server; the central control unit is responsible for real-time processing and correction of various types of sensing data received, and provides a unified time reference for the entire system through the built-in NTP server to ensure that all devices operate within the same time frame.

[0051] In addition, the data synchronization and control module adopts a mechanism combining hardware trigger and software trigger to ensure that the sensors and cameras start collecting data at the same moment. Among them, the hardware trigger is used to start the acquisition functions of all devices within an extremely short time interval, while the software trigger is used for refined timing control to adapt to the synchronization requirements under different operating conditions. The module also integrates a data fusion algorithm and a delay compensation algorithm inside, which can perform high-precision timing calibration and fusion processing on multi-source data to ensure the timeliness and consistency of data during data transmission and processing.

[0052] Furthermore, the primary task of the data fusion algorithm is to align data from different sources in time. Therefore, in order to time-correlate the image data and the distance data, in this embodiment, each image acquisition and distance measurement are attached with a timestamp during the data acquisition process to ensure that during data processing, the image and distance data at the same time point can be accurately matched. Specifically, a timestamp matching algorithm is adopted, that is, assuming that each data point d i is attached with a timestamp t i , by comparing these timestamps, the image data can be matched with the distance data within the corresponding time period, and the data can be sorted and aligned in time order.

[0053] In addition, considering that data will incur delays during transmission and processing, which is particularly important for real-time systems, in this embodiment, to compensate for these delays, the data synchronization and control module records by setting timestamps. Assume that the acquisition time of data packet di is t i 采集 and the reception time is t i 接收 , then the delay δ i can be expressed as:

[0054] δ i = t i 接收 - t i 采集

[0055] When processing data, the delay δ i is used to correct the timestamp:

[0056] t i 修正 = t i 采集 + δi

[0057] This can effectively take into account the transmission and processing delays, thereby achieving more accurate data synchronization and processing.

[0058] In practical applications, linear interpolation can also be used to process incompletely aligned timestamps. The formula is as follows:

[0059] D(t′) = D(t1) + {[D(t2) - D(t1)] / (t2 - t)} × (t′ - t1)

[0060] where t1 and t2 are known timestamp distances from the data, and t′ is the timestamp of the image frame.

[0061] Through the above methods, it can be ensured that the data has a consistent time reference during the fusion process, thereby improving the accuracy and consistency of data fusion. Among them, the Kalman filter recursive algorithm can also be adopted in the data synchronization and control module to process and fuse real-time data. This algorithm predicts the system state and updates the prediction using new observation data, thereby improving the accuracy of the data. The specific implementation steps are as follows:

[0062] 1) State prediction: Based on the previous state x k-1 and the control input u k , predict the current state x k :

[0063]

[0064] where A is the state transition matrix and B is the control matrix.

[0065] 2) Prediction of error covariance:

[0066]

[0067] Among them, is the predicted error covariance, P k-1 is the error covariance of the previous state, A T is the transpose of the state transition matrix, and Q is the process noise covariance.

[0068] 3) Calculation of Kalman gain:

[0069]

[0070] Among them, K k is the Kalman gain, H is the observation matrix, and R is the observation noise covariance.

[0071] 4) State update:

[0072]

[0073] Among them, x k is the updated state, is the predicted state, z k is the observed value.

[0074] 5) Error covariance update:

[0075]

[0076] Among them, I is the identity matrix, and P k is the updated error covariance.

[0077] Through the above iterative process of Kalman filtering, data from multiple sensors can be effectively fused, thereby effectively improving the accuracy of the final result.

[0078] After the processing of the above data synchronization and control module ensures that the collected distance and image data correspond to each other, the synchronized data is transmitted to the data processing and analysis module through the communication module. After receiving the data from the synchronization module, the data processing and analysis module performs correlation analysis on the synchronized distance change curve and image data. Through this correlation, the system can identify the critical damage moments and characteristics, thereby providing a basis for subsequent decision-making.

[0079] This module first preprocesses the received image data and distance data, smooths the image to reduce the influence of noise, and at the same time uses image enhancement algorithms to improve the visibility of image details. It further identifies and marks the cracks and deformation features in the image, and uses moving average or filtering algorithms to remove the noise in the distance data. Curve fitting is performed on the data of the distance sensor to generate a distance change curve D(t). By analyzing the smoothed distance change curve D(t), the peaks and valleys of the curve are identified. Usually, a significant distance change occurs at the moment of rupture, and there may also be accompanied by a short-term distance instability.

[0080] Therefore, this module uses Fourier transform (FFT) to analyze the features in the frequency domain to identify the main frequency components of the signal, so as to reveal the periodic features in the signal; and through the inverse transform, the peaks and valleys in the original time-domain signal are identified to reveal potential key events. Then, the derivative of the distance data is calculated to identify rapid change events. Let d(t) be the function of the distance changing with time, and its change rate can be expressed as {dd} / {dt}. The derivative formula is:

[0081]

[0082] The difference method is used to approximately calculate the derivative, and a threshold is set to identify rapid change points (jump points), that is, to identify the critical moments when the structure may change.

[0083] Then, based on the time stamp, the image information is associated with the distance data to ensure that the data at the same time point can be analyzed synchronously. Dynamic time warping (DTW) is used to compare the distance change curve and the image frame sequence. DTW finds the optimal alignment path by calculating the minimum distance between two time series to identify the corresponding relationship in time. The formula is:

[0084] DTW(i,j)=dist(i,j)+min(DTW(i-1,j),DTW(i,j-1),DTW(i-1,j-1))

[0085] The identified rapid change events and image features are marked as critical failure moments. After identifying the critical moments, the moments of significant change are marked on the distance change curve, and the high-definition images at the corresponding time points are extracted. The qualified image set is used for screening to obtain all the key images corresponding to the rupture process. Through the extracted image information and distance change data, the failure mode, failure strength, and the real situation of the failure process of the concrete specimen are analyzed.

[0086] The data processing and analysis module conducts correlation analysis on the distance change curve of the sensor and the corresponding image data, identifies the critical damage moments and characteristics, forms a preliminary judgment of structural damage and feature extraction, generates an analysis result regarding the damage characteristics, including the damage moment and relevant image information. After ensuring that the output result is in a standardized format, the analysis result is transmitted to the mapping and visualization module.

[0087] The mapping and visualization module receives the above analysis result and maps the result into the concrete compressive strength curve to form an intuitive expression of mechanical properties, that is, embedding the identified key images into the corresponding positions of the strength curve, enabling the user to view the corresponding damage characteristic images while observing the change of mechanical properties, and providing a visual display of the mapping result on the user interface to intuitively show the relationship between the image information and the mechanical properties.

[0088] During specific implementation, a reference curve of concrete compressive strength is established based on the test data, the critical damage moments identified in the analysis result are determined, marked at the corresponding positions on the strength curve, the thumbnail of the key image is embedded at the marked positions, and an interactive chart is drawn using visualization tools, enabling the user to view the details by mouse interaction while observing the curve. The image pops up or displays a detailed view through hovering, clicking, etc., so that the user can easily switch to view the key image and the detailed damage characteristic description.

[0089] The data storage and management module integrates a database management system to store raw data, processed data, analysis results, etc., including sensor data, image data, and processing results, and realizes efficient data retrieval and management functions, including retrieval by conditions such as time, event, parameter, etc., supports long-term preservation and traceability of test data, and provides a data backup and recovery mechanism to ensure data security and integrity. The network and communication module is used to ensure stable and fast data transmission between modules; provides an API interface to allow external devices or systems to access, supports remote monitoring and control of data, accesses data through the network, designs a remote upgrade mechanism to allow the system to be updated through the network, and ensures the security of the update process at the same time, and realizes log recording and monitoring functions to facilitate system performance monitoring and fault troubleshooting. Through the organic combination of the above modules, the system can achieve precise monitoring and data visualization analysis of the whole process of concrete pressure test, and improve the authenticity and traceability of the test.

[0090] Embodiment 2: On the basis of Embodiment 1, this embodiment provides a method for collecting images of a concrete compression testing machine, applying the concrete compression testing machine image collection system described in the above embodiment, which specifically includes the following steps:

[0091] Step 1: Securely install multiple high-definition cameras on the compression testing machine to ensure that the camera can fully capture the entire view of the concrete specimen from all angles; on the side of each concrete specimen, mark several positioning points respectively, and then place the concrete specimen at the center position of the compression testing machine;

[0092] Step 2: Fix the distance sensors on the compression testing machine to ensure that the probe of each distance sensor is accurately aligned with the positioning point on the specimen; and connect the cameras and distance sensors to the data processing and analysis module for signal connection;

[0093] Step 3: Before the test starts, perform the initialization and calibration of the equipment to ensure that the measurement points of the distance sensors and cameras are precisely aligned with the positioning points on the concrete specimen; use the central control unit and NTP server in the data synchronization and control module for time synchronization to set a unified time reference;

[0094] Step 4: Start the concrete compression test, gradually increase the pressure applied to the specimen, and during the entire process from the normal state to complete failure of the specimen, the high-definition camera captures the image information of the specimen in real time, while the distance sensor measures the distance change between it and the corresponding positioning point in real time, and transmits the image information and distance change information to the data processing and analysis module; in this step, through a mechanism combining hardware triggering and software triggering, ensure that all devices start data acquisition at the same moment;

[0095] Step 5: Through the communication module, transmit the collected distance change data and images to the data synchronization and control module, and use data fusion algorithms and delay compensation algorithms to perform time series calibration and fusion processing on multi-source data, attach time stamps and perform delay compensation;

[0096] Step 6: The data processing and analysis module receives the synchronized data, performs noise removal and smoothing processing on the image data to enhance image details, performs curve fitting and smoothing processing on the distance data, identifies the peaks and valleys of the distance change, uses Fourier transform and derivative calculation to analyze the signal characteristics, and identifies key change events;

[0097] Step 7: Based on the time stamp, associate the image information and distance data, use the dynamic time warping (DTW) algorithm to perform comparison and synchronization analysis on them, extract and mark the key failure moments and corresponding high-definition images, and generate preliminary structural damage judgment and feature extraction results;

[0098] Step 8: Transmit the analysis results to the mapping and visualization module, embed the key images into the concrete compressive strength curve, and use visualization tools to generate interactive charts, and users can view the mechanical property changes and corresponding failure feature images through the interface;

[0099] Step 9: Store all the original data, processed data, and analysis results in the data storage and management module to achieve efficient retrieval and management of data, provide backup and recovery mechanisms, and ensure the security and integrity of the data.

[0100] In the present invention, by linking the image acquisition device with the testing machine, it is possible to automatically take photos during the breaking process of the test block, ensuring accurate capture of the images at the moment of the test block's failure, thereby providing a reliable basis for the authenticity and accuracy of the test data; configuring a concrete compression testing machine at the construction site to achieve automatic acquisition, analysis, and early warning of concrete strength test data and test images, ensuring the authenticity, uniqueness, and traceability of the test results.

[0101] The above-described embodiments of the present invention do not constitute a limitation to the protection scope of the present invention. The basic concept of the present invention is to install several high-definition cameras and distance sensors on the concrete compression testing machine. Corresponding positioning points corresponding to the output points of the distance sensors are provided on the side of each concrete test block, and a high-definition camera is provided on one side of each distance sensor. Thus, each distance sensor can measure the distance between this sensor and the positioning point on the concrete test block. Use the concrete compression testing machine to conduct strength tests. During this process, capture and collect image information of the entire process of the concrete test block from being placed, undergoing failure, and completely failing and cracking through the high-definition camera, and then transmit the image information to the data processing and analysis module; and during the process of the test block changing from the normal state to being completely damaged and cracked, each distance sensor can detect the change in the distance between it and the corresponding positioning point, thereby obtaining the distance change curve between each distance sensor and the corresponding positioning point on the test block. Associate the distance change curves of different positioning points with the captured image information to obtain all the key images in all directions during the process of the concrete test block undergoing failure and complete failure and cracking, and map the associated images to the concrete compressive strength curve, so that the key images are automatically marked at the corresponding positions on the concrete compressive strength curve, thereby enhancing the authenticity and traceability of the concrete test detection process. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. A concrete pressure testing machine image acquisition system, characterized in that: It includes a distance sensor array deployed on the pressure testing machine, which is used to detect and record the distance change data between each sensor and the corresponding positioning point on the concrete test block in real time; The image acquisition modules installed around the pressure testing machine are used to record continuous image information from the placement of the test block to complete destruction; Data synchronization and control module, used to achieve time synchronization of all devices, and control the opening, closing and exception handling of data collection; The data processing and analysis module is used to pre-process the collected image data, analyze and extract key image features, and associate the image information with the distance data based on the timestamp; The mapping and visualization module is used to automatically map the above key images onto the concrete compressive strength curve and provide real-time data visualization, showing the dynamic changes of the images and strength curves, and presenting real-time dynamic monitoring of the quality of the entire test operation process; Data storage and management module, used to realize efficient data retrieval and storage management functions; Network and communication module, used for data transmission between modules.

2. The image acquisition system for a concrete pressure testing machine according to claim 1, characterized in that: The distance sensor array is arranged around the pressure testing machine, and a positioning point corresponding to the output point of the distance sensor is provided on the side of each concrete test block, and it is ensured that the distance sensor measurement point is accurately aligned with the positioning point on the test block.

3. The image acquisition system for concrete pressure testing machine according to claim 1, characterized in that: The image acquisition module includes a plurality of high-definition cameras arranged around the pressure testing machine, and the configured high-definition cameras are used to capture and collect image information of the entire process of the concrete test block from placement, damage, and complete damage and cracking.

4. The image acquisition system for concrete pressure testing machine according to claim 1, characterized in that: The data synchronization and control module integrates a central control unit and a network time protocol server. The central control unit is responsible for real-time processing and correction of various sensor data received, and provides a unified time reference for the entire system through a built-in NTP server to ensure that all devices operate within the same time frame.

5. The image acquisition system for concrete pressure testing machine according to claim 4 is characterized in that: The data synchronization and control module adopts a mechanism that combines hardware triggering and software triggering to ensure that each sensor and camera starts collecting data at the same time; the data synchronization and control module also integrates a data fusion algorithm and a delay compensation algorithm to perform timing calibration and fusion processing on multi-source data.

6. The image acquisition system for concrete pressure testing machine according to claim 5, characterized in that: The data fusion algorithm includes using a Kalman filter recursive algorithm to process and fuse real-time data to ensure that the data has a consistent time reference during the fusion process; The delay compensation algorithm includes recording by setting a timestamp, assuming that the collection time of the data packet di is t i 采集 and the receiving time is t i 接收 , then the delay δ i It can be expressed as: δ i =t i 接收 -t i 采集 When processing data, use a delay of δ i Correct the timestamp: t i 修正 =t i 采集 +δi。 7. The image acquisition system for concrete pressure testing machine according to claim 1, characterized in that: The data processing and analysis module pre-processes the received image data and distance data, smoothes the image, reduces the influence of noise, and uses an image enhancement algorithm to improve the visibility of image details, and identifies and marks cracks and deformation features in the image, and uses a moving average or filtering algorithm to remove noise in the distance data.

8. The image acquisition system for a concrete pressure testing machine according to claim 8, characterized in that: The data processing and analysis module uses Fourier transform to analyze the features in the frequency domain, thereby identifying the main frequency components of the signal to reveal the periodic features in the signal; and identifies the peaks and troughs in the original time domain signal through inverse transform to reveal potential key events; and then calculates the derivative of the distance data to identify rapidly changing events.

9. The image acquisition system for concrete pressure testing machine according to claim 1, characterized in that: The mapping and visualization module establishes a baseline curve of concrete compressive strength based on test data, determines the critical failure moment identified in the analysis results, marks the corresponding position of the strength curve, embeds the key image thumbnail at the marked position, draws an interactive chart using a visualization tool, and supports users in viewing the key moment images through an interactive interface.

10. A method for collecting images of a concrete pressure testing machine, using the image collection system of the concrete pressure testing machine according to claims 1 to 9, characterized in that: The following steps are involved: Step 1: Install multiple high-definition cameras securely around the pressure testing machine; mark several positioning points on the side of each concrete test block, and then place the concrete test block in the center of the pressure testing machine; Step 2: Fix the distance sensor on the pressure testing machine to ensure that the probe of each distance sensor is accurately aligned with the positioning point on the test block; use the central control unit and NTP server in the data synchronization and control module to synchronize the time and set a unified time base; Step 3: Start the concrete pressure test, gradually increase the pressure applied to the test block, and in the whole process from the normal state to the complete destruction of the test block, the high-definition camera captures the image information of the test block in real time, and the distance sensor measures the distance change between it and the corresponding positioning point in real time, and transmits the image information and distance change information to the data processing and analysis module; Step 4: The data processing and analysis module stores the received data into a distance change curve in the form of a time series and pre-processes the image; Step 5: Associate image information and distance data based on timestamps, compare and synchronously analyze them, extract and mark key damage moments and corresponding high-definition images, and generate preliminary structural damage judgment and feature extraction results; Step 6: The analysis results are transferred to the mapping and visualization module, the key images are embedded in the concrete compressive strength curve, interactive charts are generated using visualization tools, and stored in the data storage and management module.

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