A multi-parameter monitoring device for long-term measurement of existing cracks and its self-calibration method

Abstract

The present invention discloses a multi-parameter monitoring device for long-term measurement of existing cracks and a self-calibration method thereof. The mobile image sensor of the multi-parameter monitoring device for long-term measurement of existing cracks is movably arranged in a housing, and the moving path of the mobile image sensor covers a scanning area to obtain crack image information; an external sensor is arranged outside the housing, and the external sensor is specifically used to obtain environmental parameter data; an information processing unit is arranged in the housing, and the information processing unit is connected to both the mobile image sensor and the external sensor, and the information processing unit is used to process environmental parameter data and crack image information to output crack data. The present invention obtains crack image information through a mobile image sensor, and obtains environmental parameter data through an external sensor, thereby realizing the collection of multi-parameter data. The device can monitor the development of existing cracks for a long time, and can provide multi-parameter information such as stress, displacement, temperature and humidity of the structure surrounding the crack.

Description

Technical Field

[0001] The invention relates to the technical field of long-term monitoring of existing cracks in road and bridge engineering, and in particular to a multi-parameter monitoring device for long-term measurement of existing cracks and a self-calibration method thereof. Background Art

[0002] In recent years, with the vigorous development of the transportation industry, the number of roads and bridges has increased day by day. However, due to environmental and overload conditions, road and bridge facilities have deteriorated rapidly, and cracks will appear on the concrete surface. Over time, the cracks tend to expand further, ultimately affecting the bearing capacity and service life of bridges and roads. After cracks appear, by continuously monitoring the cracks, the crack growth information obtained can further understand the structural status of the bridge and provide a reliable basis and guidance for bridge maintenance and management decisions.

[0003] At present, crack detection in China is still mainly done by visual inspection, supplemented by crack observation instruments, vernier calipers and other tools, or by ultrasonic detectors to measure the crack width. The above equipment requires regular inspections by people and cannot detect crack diseases in time. In addition, there are also crack monitoring devices installed on the surface of the crack, but they can only obtain the width parameter information of the crack and cannot obtain the overall appearance of the crack. Regardless of the detection method, it is difficult to monitor the development of cracks in the same location for a long time, and it is even more difficult to obtain multi-parameter information on the structure and environmental changes around the crack. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-parameter monitoring device for long-term measurement of existing cracks and a self-calibration method thereof, aiming to solve the technical problem in the related art that it is impossible to obtain multi-parameter information on the structure and environmental changes around the cracks of highway bridge facilities.

[0005] In order to solve the above problem, according to one aspect of the present application, an embodiment of the present invention provides a multi-parameter monitoring device for long-term measurement of existing cracks, and the multi-parameter monitoring device for long-term measurement of existing cracks includes:

[0006] a housing having a scanning area opposite to a crack surface to be detected;

[0007] A mobile image sensor is movably disposed in the housing, and a moving path covers a scanning area to obtain crack image information;

[0008] An external sensor is arranged outside the housing to obtain environmental parameter data;

[0009] The information processing unit is arranged in the housing and connected to both the mobile image sensor and the external sensor, and is used for processing environmental parameter data and crack image information to output crack data.

[0010] In some embodiments, the mobile image sensor includes a driving system and a strip photosensitive device, the driving system includes a longitudinal driving mechanism and a transverse driving mechanism, the strip photosensitive device includes a pixel array area, the longitudinal driving mechanism is arranged in the housing, the transverse driving mechanism is arranged on the longitudinal driving mechanism, the strip photosensitive device is arranged on the transverse driving mechanism, the longitudinal driving mechanism is used to drive the transverse driving mechanism and the strip photosensitive device to scan longitudinally to obtain a longitudinal scanning image, the transverse driving mechanism is used to drive the strip photosensitive device to scan transversely to obtain a transverse scanning image, the information processing unit includes a connected MCU chip and an FPGA chip, the strip photosensitive device is connected to the MCU chip, the MCU chip has a built-in acquisition program, the FPGA chip is used to perform fusion processing on the transverse scanning image before sending and the longitudinal scanning image before sending, and the MCU chip is used to process the environmental parameter data obtained by the external sensor to generate crack information.

[0011] In some embodiments, the longitudinal driving mechanism includes a stepper motor, two rotating parts with parallel and spaced axes, and a synchronous belt, any one of the rotating parts is connected to the output shaft of the stepper motor, the synchronous belt is sleeved on the two rotating parts, the transverse driving mechanism is arranged on the synchronous belt, and the stepper motor is connected to the MCU chip.

[0012] In some embodiments, the lateral drive mechanism includes a loading platform, a micro stepper motor, a brushless motor, a screw and a guide rail. The brushless motor and the guide rail are arranged on a synchronous belt, the output end of the brushless motor is connected to the screw, the fixed end of the micro stepper motor is provided with a threaded sleeve, the screw is inserted in the threaded sleeve, the output end of the micro stepper motor is connected to the loading platform to control the rotation angle of the loading platform; the strip photosensitive device is arranged on the loading platform; the micro stepper motor is connected to the guide rail, and the guiding direction of the guide rail is perpendicular to the running direction of the synchronous belt, so that the micro stepper motor can move in a directional manner, and the micro stepper motor and the brushless motor are both connected to the MCU chip.

[0013] In some embodiments, an LED supplementary light source is disposed on at least one side of the strip-shaped photosensitive device in the width direction, and the LED supplementary light source faces the crack surface to be detected and moves synchronously with the strip-shaped photosensitive device; and / or,

[0014] The MCU chip has a built-in timing circuit, which is used to start the device to collect crack information according to the set collection cycle; and / or,

[0015] An external sensor data acquisition interface connected to the MCU chip is arranged on the shell, and the external sensor is plugged into the external sensor data acquisition interface.

[0016] In some embodiments, the scanning area includes a detected area, the detected area is fixedly attached to the surface of the crack to be detected, and the scanning direction of the mobile image sensor is parallel to the extension direction of the crack; a light-shielding sponge is sealed around the scanning area, and the two sides of the light-shielding sponge are tightly attached to the housing and the surface of the crack to be detected; and / or,

[0017] The external sensor includes at least one of a strain acquisition module, a displacement acquisition module and a temperature and humidity acquisition module.

[0018] In some embodiments, the multi-parameter monitoring device for long-term measurement of existing cracks also includes an LTE communication module, the MCU chip and the FPGA chip are both connected to the LTE communication module, and the LTE communication module sends the crack information to the host computer through the Internet of Things card.

[0019] In some embodiments, the multi-parameter monitoring device for long-term measurement of existing cracks also includes a power supply, which is connected to the mobile image sensor, the external sensor, the information processing unit, and the LTE communication module.

[0020] In some embodiments, the MCU chip has a built-in self-correction algorithm, the strip photosensitive device also includes a digital image processing circuit area, the scanning area also includes a self-calibration area, and a standard part to be detected is arranged in the self-calibration area. The standard part to be detected includes a plurality of square arrays of two different colors of squares, and the two different colors of squares are alternately distributed in the self-calibration area, and squares of the same color are not adjacent to each other.

[0021] According to another aspect of the present application, an embodiment of the present invention further provides a self-calibration method for calibrating the multi-parameter monitoring device for long-term measurement of existing cracks as described above. The self-calibration method includes:

[0022] Obtain the working mode of the multi-parameter monitoring device for long-term measurement of existing cracks;

[0023] When the multi-parameter monitoring device for long-term measurement of existing cracks is switched from the monitoring working mode to the self-calibration working mode, the mobile image sensor is controlled to scan the standard part to be detected in the self-calibration area to obtain the width data of any square;

[0024] Comparing the width data with a preset standard width, calculating the deviation, and generating a correction coefficient;

[0025] The digital image processing circuit area corrects the crack image according to the correction coefficient.

[0026] In some embodiments, controlling the mobile image sensor to scan the standard part to be detected in the calibration area to obtain the width data of any square includes:

[0027] The driving system is used to control the mobile image sensor to scan the standard part to be detected in the self-calibration area for multiple times to obtain the crack widths L1 to Ln to be corrected.

[0028] In some embodiments, the width data of any square is obtained and compared with a preset standard width, and the deviation is calculated to generate a correction coefficient, including:

[0029] In the MCU chip, the crack widths to be corrected L1~Ln and the pre-stored standard width L0 are input into the self-correction algorithm calculation process, and L is compared with L0. If L and L0 are not equal, the deviation Φ between the crack width to be corrected and the standard width is calculated, and the deviation Φ is used as the correction coefficient.

[0030] In some embodiments, the deviation Φ is calculated by a method of calculating an average deviation by multiple measurements, and the calculation formula includes:

[0031] ;

[0032] Wherein, n represents the number of times the mobile image sensor detects the standard part; Indicates the specific measurement of the mobile image sensor Second-rate; Represents the mobile image sensor Measure the width of the standard part.

[0033] Compared with the prior art, the multi-parameter monitoring device for long-term measurement of existing cracks of the present invention has at least the following beneficial effects:

[0034] The embodiment of the present invention discloses a multi-parameter monitoring device for long-term measurement of existing cracks. The multi-parameter monitoring device for long-term measurement of existing cracks can be used for long-term measurement of existing cracks in road and bridge engineering. The multi-parameter monitoring device for long-term measurement of existing cracks comprises a shell, a mobile image sensor, an external sensor, an information processing unit, an LTE communication module and a power supply; the shell has a scanning area opposite to the surface of the crack to be measured; the mobile image sensor is movably arranged in the shell, and the moving path of the mobile image sensor covers the scanning area, so that the mobile image sensor can scan the scanning area, that is, scan the surface of the crack to be measured to obtain crack image information; the external sensor is arranged outside the shell, and the external sensor is specifically used to obtain environmental parameter data. The external sensor can be used to collect environmental parameter data such as stress, displacement, temperature and humidity of the crack area to be measured; the information processing unit is arranged in the shell, and the information processing unit is connected to both the mobile image sensor and the external sensor, and the information processing unit is used to process the environmental parameter data and the crack image information to output the crack data.

[0035] The present invention obtains crack image information through a mobile image sensor and obtains environmental parameter data through an external sensor to realize the collection of multi-parameter data. The device can monitor the development of existing cracks for a long time and can provide multi-parameter information such as stress, displacement, temperature and humidity of the structure around the crack.

[0036] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0038] Figure 1 An overall system schematic diagram of a multi-parameter monitoring device for long-term measurement of existing cracks provided by an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of the structure of a multi-parameter monitoring device for long-term measurement of existing cracks provided by an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of the structure of a transmission mechanism of a multi-parameter monitoring device for long-term measurement of existing cracks provided by an embodiment of the present invention;

[0041] Figure 4 A structural schematic diagram of another perspective of the transmission mechanism of the multi-parameter monitoring device for long-term measurement of existing cracks provided by an embodiment of the present invention;

[0042] Figure 5 A schematic diagram of the distribution structure of the detected area and the self-calibration area in the scanning area of ​​the multi-parameter monitoring device for long-term measurement of existing cracks provided by an embodiment of the present invention;

[0043] Figure 6 A schematic diagram of the structure of a standard part to be detected in a self-calibration area of ​​a multi-parameter monitoring device for long-term measurement of existing cracks provided by an embodiment of the present invention;

[0044] Figure 7 A flow chart of a self-calibration method for a multi-parameter monitoring device for long-term measurement of existing cracks provided in an embodiment of the present invention.

[0045] Description of reference numerals:

[0046] 1. Shell; 11. Scanning area; 111. Detected area; 112. Self-calibration area; 113. Grid; 12. External sensor data acquisition interface;

[0047] 2. Strip-shaped photosensitive device;

[0048] 31. Motor; 32. Rotating parts; 33. Synchronous belt; 34. Positioning member; 35. Limiting steel pipe; 36. Loading platform;

[0049] 4. Sunshade sponge;

[0050] 5. Fill light source. DETAILED DESCRIPTION

[0051] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention application are described in detail below in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0052] In the description of the present invention, it should be clarified that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, but are not necessarily used to describe a specific order or sequence; the terms "vertical", "lateral", "longitudinal", "front", "rear", "left", "right", "up", "down", "horizontal", etc. indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention, and do not mean that the referred device or element must have a specific direction or position, and therefore cannot be understood as a limitation on the present invention.

[0053] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] Example 1

[0055] like Figure 1-7 As shown, an embodiment of the present invention provides a multi-parameter monitoring device for long-term measurement of existing cracks, and the multi-parameter monitoring device for long-term measurement of existing cracks includes:

[0056] The housing 1 has a scanning area 11 opposite to the crack surface to be detected;

[0057] A mobile image sensor is movably disposed in the housing 1, and the moving path covers the scanning area 11 to obtain crack image information;

[0058] An external sensor is arranged outside the housing 1 to obtain environmental parameter data;

[0059] The information processing unit is disposed in the housing 1 and is connected to both the mobile image sensor and the external sensor, and is used for processing environmental parameter data and crack image information to output crack data.

[0060] Specifically, the multi-parameter monitoring device for long-term measurement of existing cracks can be used for long-term measurement of existing cracks in road and bridge engineering. The multi-parameter monitoring device for long-term measurement of existing cracks includes a housing 1, a mobile image sensor, an external sensor, an information processing unit, an LTE communication module, and a power supply; the housing 1 has a scanning area 11 opposite to the surface of the crack to be measured; the mobile image sensor is movably arranged in the housing 1, and the moving path of the mobile image sensor covers the scanning area 11, so that the mobile image sensor can scan the scanning area 11, that is, scan the surface of the crack to be measured to obtain crack image information; the external sensor is arranged outside the housing 1, and the external sensor is specifically used In order to obtain environmental parameter data, the external sensor can be used to collect environmental parameter data such as stress, displacement, temperature and humidity of the crack area to be tested; the information processing unit is arranged in the shell 1, and the information processing unit is connected to both the mobile image sensor and the external sensor. The information processing unit is used to process the environmental parameter data and crack image information to output crack data. In this embodiment, the crack image information is obtained by the mobile image sensor, and the external sensor obtains the environmental parameter data to realize the collection of multi-parameter data. The device can monitor the development of existing cracks for a long time, and can provide multi-parameter information such as stress, displacement, temperature and humidity of the structure around the crack, so as to provide more comprehensive multi-parameter monitoring data of existing cracks.

[0061] The housing 1 is a rectangular box with three fixing brackets extending outward from the bottom.

[0062] In some embodiments, the mobile image sensor includes a driving system and a strip photosensitive device 2, the driving system includes a longitudinal driving mechanism and a transverse driving mechanism, the strip photosensitive device 2 includes a pixel array area, the longitudinal driving mechanism is arranged in the housing 1, the transverse driving mechanism is arranged on the longitudinal driving mechanism, the strip photosensitive device 2 is arranged on the transverse driving mechanism, the longitudinal driving mechanism is used to drive the transverse driving mechanism and the strip photosensitive device 2 to scan longitudinally to obtain a longitudinal scanning image, the transverse driving mechanism is used to drive the strip photosensitive device 2 to scan transversely to obtain a transverse scanning image, the information processing unit includes a connected MCU chip and an FPGA chip (field programmable gate array), the strip photosensitive device 2 is connected to the MCU chip, the MCU chip has a built-in acquisition program, the FPGA chip is used to fuse the transverse scanning image before sending and the longitudinal scanning image before sending, and the MCU chip is used to process the environmental parameter data obtained by the external sensor to generate crack information.

[0063] In this embodiment, the longitudinal driving mechanism of the driving system with a built-in acquisition program in the MCU chip drives the transverse driving mechanism to drive the strip photosensitive device 2 to move, thereby realizing the longitudinal scanning and transverse scanning of the mobile image sensor, and then realizing the all-round scanning of the scanning area 11 by the mobile image sensor. The FPGA chip is used for the fusion processing of the transverse scanning image before sending and the longitudinal scanning image before sending, and the MCU chip is used for processing the environmental parameter data obtained by the external sensor to generate crack information.

[0064] The crack data includes parameter data such as strain, displacement, temperature and humidity, and threshold after being processed by the MCU chip, and crack image data after being processed by the FPGA.

[0065] The mobile image sensor (strip-shaped photosensitive device 2) serves as the main device for collecting crack images and transmits data to the MCU chip. The MCU chip controls the driving system to enable the mobile image sensor to perform monitoring work (vertical scanning and horizontal scanning), and transmits the image information collected by the monitoring work scanning to the FPGA chip for image fusion processing before sending. After the transmission is completed, the image information is cleared immediately to save memory space.

[0066] In some embodiments, the longitudinal driving mechanism includes a stepper motor 31, two rotating parts 32 with parallel and spaced axes, and a synchronous belt 33. Any rotating part 32 is connected to the output shaft of the stepper motor 31, and the synchronous belt 33 is sleeved on the two rotating parts 32. The transverse driving mechanism is arranged on the synchronous belt 33. The stepper motor 31 is connected to the MCU chip, and the two rotating parts 32 are rotatably connected to the housing 1. The rotating parts 32 can be gears.

[0067] In this embodiment, the information processing unit can control the forward and reverse rotation of the stepper motor 31 to realize the longitudinal scanning of the mobile image sensor. When the mobile image sensor is started in the scanning mode, the stepper motor 31 is controlled by the internal program of the MCU chip to start at a fixed time, and the forward and reverse rotation of the stepper motor 31 drives the rotating member 32 to perform corresponding forward or reverse rotation. Driven by the rotating member 32, the synchronous belt 33 and the transverse driving mechanism connected to the synchronous belt 33 begin to move with the rotation of the rotating member 32, thereby realizing the movement of the loading platform 36. Through the control of the internal program of the MCU chip, the strip-shaped photosensitive device 2 of the mobile image sensor can evenly and completely scan the entire area to be detected (scanning area 11).

[0068] According to the setting of the exposure time of the mobile image sensor, the motor speed and the frequency of the PWM wave corresponding to the complete acquisition are calculated by the program, and then the MCU chip controls the motor to generate the corresponding speed through the PWM wave, so that the image sensor can evenly and completely collect images of the entire area to be detected (scanning area 11). The above is a mature scanning process control technology, so the corresponding calculation process will not be described in detail.

[0069] The FPGA chip fuses the images scanned vertically and horizontally in the monitoring mode. The processing steps are as follows:

[0070] Pre-processing: Since the same strip-shaped photosensitive device 2 is used for longitudinal and transverse scanning of the image, the acquired image is rotated 90 degrees. The transversely scanned image is rotated 90 degrees in the opposite direction through image rotation to keep the direction consistent with the longitudinally scanned image;

[0071] Perform wavelet decomposition on the rotated horizontal and vertical images to extract high-frequency and low-frequency features in the images;

[0072] Image fusion based on wavelet decomposition takes into account that the strip photosensitive device 2 may cause incomplete crack information due to the scanning speed when scanning, and at the same time, when scanning the detected area 111, there may be pseudo-crack areas affecting the detection results due to the influence of noise, light intensity, etc. By fusing the horizontal image and the vertical image, the absolute value maximum method is used to process the high-frequency features of the crack area, and the weighted average method is used to process the low-frequency features of the non-crack background area. This not only solves the problem of incomplete crack information caused by the moving speed of the detected area 111, but also realizes the automatic removal of pseudo-crack areas to obtain accurate detection results.

[0073] In some embodiments, a positioning member 34 and a limiting steel pipe 35 are also provided on the synchronous belt 33. The positioning member 34 is located in the middle of the two rotating parts 32 and is distributed close to the rotating parts 32, which can limit the movement range of the transverse drive mechanism; the limiting steel pipe 35 is placed parallel to the synchronous belt 33 to limit the movement direction of the transverse drive mechanism.

[0074] In some embodiments, the lateral drive mechanism includes a loading platform 36, a micro stepper motor, a brushless motor, a screw and a guide rail. The brushless motor and the guide rail are arranged on the synchronous belt 33. The output end of the brushless motor is connected to the screw. The fixed end of the micro stepper motor is provided with a threaded sleeve, and the screw is inserted in the threaded sleeve. The output end of the micro stepper motor is connected to the loading platform 36 to control the rotation angle of the loading platform 36; the strip photosensitive device 2 is arranged on the loading platform 36; the micro stepper motor is connected to the guide rail, and the guiding direction of the guide rail is perpendicular to the running direction of the synchronous belt 33, so that the micro stepper motor can move in a directional manner. The micro stepper motor and the brushless motor are both connected to the MCU chip.

[0075] In this embodiment, a micro-stepping motor can be used to drive the screw to rotate, thereby driving the brushless motor on the screw to move, and then driving the strip photosensitive device 2 on the loading platform 36 connected to the brushless motor to move horizontally, so that the strip photosensitive device 2 is directed toward the scanning area 11 during assembly. Since the micro-stepping motor is connected to the guide rail, it is always ensured that the strip photosensitive device 2 is directed toward the scanning area 11.

[0076] Specifically, when the MCU chip controls the brushless motor to drive the screw to rotate at a certain speed, the screw drives the micro stepper motor to translate under the constraint of the guide rail.

[0077] The multi-parameter monitoring device for long-term measurement of existing cracks includes a monitoring working mode and a self-calibration working mode. In the monitoring working mode, crack monitoring is performed on the target area of ​​the measured structure. The steps of the monitoring working mode include:

[0078] The first step is vertical scanning:

[0079] Control the brushless motor in the transverse drive mechanism so that the loading platform 36 is located at the center of the screw;

[0080] Control the stepper motor in the transverse drive mechanism so that the loading platform 36 is perpendicular to the synchronous belt 33;

[0081] The strip-shaped photosensitive device 2 is controlled by a longitudinal driving mechanism to longitudinally scan the crack surface to be detected relative to the area 11;

[0082] The image information obtained by longitudinal scanning of the strip-shaped photosensitive device 2 is transmitted to the information processing unit to wait for subsequent processing;

[0083] Step 2: Horizontal scanning:

[0084] Control the longitudinal drive mechanism to move the transverse drive mechanism to the center of the synchronous belt 33;

[0085] Control the brushless motor in the transverse drive mechanism so that the loading platform 36 is located at the center of the screw;

[0086] Control the stepper motor in the transverse drive mechanism to rotate the loading platform 36 so that it is parallel to the synchronous belt 33;

[0087] The brushless motor is used to control the strip-shaped photosensitive device 2 to move to the top of the screw rod, and after it is in place, the brushless motor is used to control the horizontal scanning of the scanning area 11 relative to the crack surface to be detected;

[0088] The image information obtained by the horizontal scanning of the strip-shaped photosensitive device 2 is input to the information processing unit to wait for subsequent processing.

[0089] In some embodiments, an LED fill light source 5 is provided on at least one side of the strip-shaped photosensitive device 2 in the width direction. The LED fill light source 5 moves toward the crack surface to be measured and moves synchronously with the strip-shaped photosensitive device 2 to fill light on the crack surface to be measured, thereby ensuring the accuracy of the collected data.

[0090] In some implementations, the MCU chip has a built-in timing circuit for timing the device to start collecting crack information according to a set collection cycle.

[0091] In some embodiments, the housing 1 is provided with an external sensor data acquisition interface 12 connected to the MCU chip, and the external sensor is plugged into the external sensor data acquisition interface 12. The external sensor data acquisition interface 12 can be three types: RS485 external interface, A / D conversion external interface, and I2C communication external interface. The three types of interface circuits transmit signals with the MCU chip inside the device, and are connected to the strain sensor, displacement sensor, and temperature and humidity sensor externally through a waterproof connector.

[0092] In some embodiments, the scanning area 11 includes a detected area 111, which is fixedly attached to the surface of the crack to be detected, and the scanning direction of the mobile image sensor is parallel to the extension direction of the crack; the scanning area 11 is sealed with a shading sponge 4, and the shading sponge 4 is tightly attached to the shell 1 and the surface of the crack to be detected on both sides.

[0093] In some embodiments, the external sensor includes at least one of a strain acquisition module, a displacement acquisition module, and a temperature and humidity acquisition module. The strain acquisition module can be a strain sensor, the displacement acquisition module can be a displacement sensor, and the temperature and humidity acquisition module can be a temperature and humidity sensor, which are used to collect environmental parameter data such as stress, displacement, temperature and humidity in the crack area to be measured.

[0094] In some embodiments, the multi-parameter monitoring device for long-term measurement of existing cracks also includes an LTE communication module, the LTE communication module is arranged in the shell 1, the MCU chip and the FPGA chip are both connected to the LTE communication module, and the LTE communication module sends the crack information to the host computer through the Internet of Things card.

[0095] The crack data transmitted by the LTE communication module are parameter data such as strain, displacement, temperature and humidity, threshold, etc. processed by the MCU chip and crack image data processed by the FPGA.

[0096] After the mobile image sensor completes the longitudinal and transverse scanning, the MCU chip starts to collect information from the external sensor and stores the collected information for transmission by the LTE communication module. The LTE communication module is connected to the FPGA chip and the MCU chip respectively. The image information processed by the FPGA chip and the return information of the external sensor obtained by the MCU chip are packaged and sent to the host computer through the LTE communication module to realize the wireless transmission function.

[0097] In some embodiments, the multi-parameter monitoring device for long-term measurement of existing cracks also includes a power supply, which is connected to the mobile image sensor, the external sensor, the information processing unit and the LTE communication module; the power supply is connected to the mobile image sensor, the external sensor, the information processing unit and the LTE communication module to provide power to the mobile image sensor, the external sensor, the information processing unit and the LTE communication module. The power supply can be powered by multiple high-capacity lithium batteries, and the mobile image sensor, the external sensor, the information processing unit and the LTE communication module are powered by multiple sets of voltage stabilizing circuits. The entire monitoring device is powered by lithium batteries, and the MCU chip can use a low-power MCU chip. The overall power consumption of the equipment is low and it can monitor existing cracks in road and bridge projects for a long time.

[0098] In some embodiments, the MCU chip has a built-in self-correction algorithm, the strip photosensitive device 2 also includes a digital image processing circuit area, the scanning area 11 also includes a self-calibration area 112, and a standard part to be detected is arranged in the self-calibration area 112. The standard part to be detected includes a plurality of square arrays of two different colors of squares 113. The two different colors of squares 113 are alternately distributed in the self-calibration area 112, and the squares 113 of the same color are not adjacent to each other.

[0099] The scanning area 11 of the mobile image sensor is divided into two parts: a detected area 111 and a self-calibration area 112. The detected area 111 occupies a larger part of the scanning area 11 of the mobile image sensor, which corresponds to the crack surface to be detected; the self-calibration area 112 occupies a smaller part of the scanning area 11 of the mobile image sensor, and this part contains the standard part to be detected.

[0100] Specifically, the detected area 111 corresponds to the detection working mode of the multi-parameter monitoring device. When performing detection, the detected area 111 covers the target cracks of the road and bridge project (the crack surface to be detected), and the driving system controls the mobile image sensor to detect the crack surface to be detected to obtain relevant information of the target crack.

[0101] Specifically, the self-calibration area 112 corresponds to the self-calibration working mode of the multi-parameter monitoring device. In this mode, the device can perform a self-calibration process on the mobile image sensor to solve the problem of drift of physical characteristics and abnormal detection data caused by long-term operation of the mobile image sensor. In the above setting, when the sensor performs self-calibration, the MCU chip first controls the drive system so that the sensor detection range points to the self-calibration area 112. After positioning, the sensor starts to detect the standard parts to be detected in the self-calibration area 112 to obtain the width of the standard parts to be detected. This detection result is the measurement width to be corrected. The stored measurement width to be corrected is output to the information processing unit to start the subsequent calibration process.

[0102] In an embodiment of the present invention, the standard part to be detected is built into the self-calibration area 112 for calibrating the mobile image sensor. The standard part to be detected includes a plurality of square arrays of two different colors of square grids 113. The two different colors of square grids 113 are alternately distributed in the self-calibration area 112, and the grids 113 of the same color are not adjacent to each other. The standard part to be detected can be set to 3×2, a total of 6 black grids and white grids, three black and three white grids, and the black and white grids are alternately distributed in the self-calibration area. The grids of the same color are not adjacent to each other, so as to clearly define the boundary for the mobile image sensor to detect the grid side length data.

[0103] Specifically, the standard parameters of the black and white chessboard are: the side length of each grid is 0.3mm, and its side length data is stored in the digital image processing circuit area as standard width data, which is used to compare with the measured width to be corrected of the mobile image sensor in the subsequent self-calibration process and obtain calibration deviation and other data.

[0104] Specifically, when the self-calibration area is detected, the self-calibration area 112 is illuminated by an internal light source, and the driving system controls the mobile image sensor to detect the black and white checkerboard standard parts to be detected in the self-calibration area; during the detection, since the mobile image sensor receives different signals reflected by the black and white checkerboards, the white checkerboard represents the surface of the object to be detected, and the black checkerboard represents the cracks on the surface of the object to be detected; when the mobile image sensor measures the standard parts to be detected, the device supplements the visible light to the standard parts to be detected to ensure the visualization of the checkerboard, so that the pixel array area of ​​the sensor obtains the pixel signals of the black checkerboard and the white checkerboard respectively, and forms a pixel parameter matrix to be input into the digital image processing circuit, in which the signal strengths of the pixels measured by different checkerboards are distinguished, and the measured width of the black checkerboard representing the crack width with a stronger received signal is measured, and this is used as the measurement width data to be corrected of the mobile image sensor.

[0105] Specifically, the process of using a mobile image sensor to scan a standard part to be tested and obtain the measured width to be corrected is as follows: when the mobile image sensor scans a black checkerboard, the signal received by the reflected light in the mobile image sensor is different from the surrounding white checkerboards and the background of the structure to be tested, that is, the signal strength at the corresponding pixel points is different. By checking the image sensor pixel point array corresponding to the signal strength of the received checkerboard, the corresponding pixel points at the black and white junction and the black and white checkerboard array can be obtained. The pixel point cloud array of the obtained black checkerboard is combined according to different reflection intensities, and finally the size of the black checkerboard is obtained.

[0106] Specifically, the self-calibration process of the mobile image sensor requires the use of the self-calibration area 112 and its internal standard parts to be detected, the self-correction algorithm in the MCU chip in the drive system and the information processing unit. The self-calibration work is intended to correct the sensor detection accuracy under long-term use.

[0107] Example 2

[0108] The embodiment of the present invention further provides a self-calibration method for calibrating the multi-parameter monitoring device for long-term measurement of existing cracks in embodiment 1. The self-calibration method includes:

[0109] Obtain the working mode of the multi-parameter monitoring device for long-term measurement of existing cracks;

[0110] When the multi-parameter monitoring device for long-term measurement of existing cracks is switched from the monitoring working mode to the self-calibration working mode, the mobile image sensor is controlled to scan the standard part to be detected in the self-calibration area 112 to obtain the width data of any square 113;

[0111] The width data of any square 113 is compared with the preset standard width, and the deviation is calculated to generate a correction coefficient;

[0112] The digital image processing circuit area corrects the crack image according to the correction coefficient.

[0113] In some embodiments, controlling the mobile image sensor to scan the standard part to be detected in the calibration area 112 to obtain the width data of any square 113 includes:

[0114] The driving system is used to control the mobile image sensor to scan the standard part to be detected in the calibration area 112 for multiple times to obtain the crack widths L1 to Ln to be corrected.

[0115] In some embodiments, the width data of any square 113 is obtained and compared with a preset standard width, and the deviation is calculated to generate a correction coefficient, including:

[0116] In the MCU chip, the crack widths to be corrected L1~Ln and the pre-stored standard width L0 are input into the self-correction algorithm calculation process, and L is compared with L0. If L and L0 are not equal, the deviation Φ between the crack width to be corrected and the standard width is calculated, and the deviation Φ is used as the correction coefficient.

[0117] In some embodiments, the deviation Φ is calculated by a method of calculating an average deviation by multiple measurements, and the calculation formula includes:

[0118] ;

[0119] Wherein, n represents the number of times the mobile image sensor detects the standard part, which is usually ten times or more; Indicates the specific measurement of the mobile image sensor Second-rate; Represents the mobile image sensor Measure the width of the standard part.

[0120] Specifically, the self-calibration process steps of the multi-parameter monitoring device for long-term measurement of existing cracks include:

[0121] The driving system is used to control the mobile image sensor to scan the standard part to be detected in the calibration area 112 for multiple times to obtain the crack widths L1 to Ln to be corrected;

[0122] The crack width to be corrected is output to the MCU chip of the information processing unit through the mobile image sensor data transmission interface;

[0123] In the MCU chip, the crack widths to be corrected L1~Ln and the pre-stored standard width L0 are input into the self-correction algorithm calculation process together, and L is compared with L0 to determine whether they are equal. If L and L0 are equal, the self-correction algorithm calculation is terminated. If they are not equal, the deviation Φ between the crack width to be corrected and the standard width is calculated and sent to the output port of the MCU chip of the information processing unit as the output of the self-correction algorithm.

[0124] The deviation Φ calculated in the information processing unit is output to the mobile image sensor and sent to the digital image processing circuit area inside the sensor. The deviation Φ is used as a correction coefficient to calibrate the crack image detection threshold to obtain a new calibrated crack image detection threshold. The new calibrated crack image detection threshold is the sum of the correction coefficient Φ and the original calibrated crack image detection threshold. In this way, the self-calibration process of the mobile image sensor is completed.

[0125] Specifically, when the digital image processing circuit area inside the mobile image sensor is working, the detected pixel data of the pixel array area is converted into crack width data to be output, and compared with the preset crack image detection threshold, the crack width detection result of the target area is obtained and output through the sensor data transmission interface.

[0126] Specifically, the crack image detection threshold is pre-set. Under the long-term measurement conditions of existing cracks in the road and bridge engineering to which the present invention is applied, the initial setting value of the threshold is 0.01 mm. When measuring cracks in the target area, in the image processing circuit area, the target crack pixels obtained by the pixel array are compared with the crack image detection threshold. If the obtained crack pixel result is less than the set threshold, the target is not used as crack width data, and is not output or subsequently processed to avoid crack detection anomalies caused by slight unevenness or fine impurities on the surface of the structure to be measured; when performing self-calibration, the mobile image sensor is self-calibrated. At this time, if the sensor needs to be calibrated after calculation by the information processing unit, the deviation Φ between the crack width to be corrected and the standard width is transmitted to the digital image processing circuit area inside the sensor, and the deviation Φ is used as a correction coefficient for the processing circuit to correct the crack image detection threshold and the output result to complete the self-calibration of the linear graphic sensor.

[0127] In summary, the present invention uses a mobile image sensor and a bidirectional scanning method to quickly obtain images of cracks. This non-contact monitoring method not only improves the efficiency and accuracy of monitoring, but also greatly extends the service life of the equipment.

[0128] The present invention adopts the self-calibration algorithm of the existing multi-parameter monitoring device for long-term crack measurement, and realizes the calibration of the detection threshold of the crack image by calling the self-calibration working mode by software, thereby improving the detection accuracy of the mobile image sensor and solving the problem of aging of the mobile image sensor under long-term monitoring conditions.

[0129] The present invention adopts an image fusion algorithm. Through the image fusion algorithm stored in the FPGA chip, the crack features of the images of the horizontal scan and the vertical scan are fused, thereby eliminating the loss or deformation of the crack features caused by uneven speed in one-way scanning and improving the accuracy of the crack image.

[0130] The present invention adopts a variety of sensors to obtain data information, and coordinates the operation of strain sensors, displacement sensors, and temperature and humidity sensors, which can conveniently realize the collection of multi-parameter data such as deformation of existing crack structures, crack width, ambient temperature and humidity of road and bridge projects.

[0131] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0132] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A multi-parameter monitoring device for long-term measurement of existing cracks, characterized in that: The multi-parameter monitoring device for long-term measurement of existing cracks includes: A housing (1) having a scanning area (11) opposite to a crack surface to be detected; A mobile image sensor, movably disposed in the housing (1), with a moving path covering the scanning area (11) to obtain crack image information; An external sensor is arranged outside the housing (1) to obtain environmental parameter data; An information processing unit, disposed in the housing (1) and connected to both the mobile image sensor and the external sensor, for processing the environmental parameter data and the crack image information to output crack data; The mobile image sensor comprises a driving system and a strip-shaped photosensitive device (2), the driving system comprising a longitudinal driving mechanism and a transverse driving mechanism, the strip-shaped photosensitive device (2) comprising a pixel array area, the longitudinal driving mechanism being arranged in the housing (1), the transverse driving mechanism being arranged on the longitudinal driving mechanism, the strip-shaped photosensitive device (2) being arranged on the transverse driving mechanism, the longitudinal driving mechanism being used to drive the transverse driving mechanism and the strip-shaped photosensitive device (2) to scan longitudinally to obtain a longitudinal scanning image, the transverse driving mechanism being used to drive the strip-shaped photosensitive device (2) to scan transversely to obtain a transverse scanning image, the information processing unit comprising a connected MCU chip and an FPGA chip, the strip-shaped photosensitive device (2) being connected to the MCU chip, the MCU chip having a built-in acquisition program, the FPGA chip being used to fuse the transverse scanning image before sending and the longitudinal scanning image before sending, and the MCU chip being used to process environmental parameter data obtained by an external sensor to generate crack information; The longitudinal drive mechanism comprises a stepping motor (31), two rotating members (32) whose axes are parallel and spaced apart, and a synchronous belt (33), any one of the rotating members (32) is connected to an output shaft of the stepping motor (31), the synchronous belt (33) is sleeved on the two rotating members (32), the transverse drive mechanism is arranged on the synchronous belt (33), and the stepping motor (31) is connected to the MCU chip; The lateral drive mechanism comprises a loading platform (36), a micro-stepping motor, a brushless motor, a screw and a guide rail, wherein the brushless motor and the guide rail are arranged on the synchronous belt (33), the output end of the brushless motor is connected to the screw, the fixed end of the micro-stepping motor is provided with a threaded sleeve, the screw is inserted into the threaded sleeve, the output end of the micro-stepping motor is connected to the loading platform (36) to control the rotation angle of the loading platform (36); the strip-shaped photosensitive device (2) is arranged on the loading platform (36); the micro-stepping motor is connected to the guide rail, the guiding direction of the guide rail is perpendicular to the running direction of the synchronous belt (33), so that the micro-stepping motor moves in a directional manner, and the micro-stepping motor and the brushless motor are both connected to the MCU chip; The scanning area (11) comprises a detected area (111), the detected area (111) is fixedly attached to the surface of the crack to be detected, and the scanning direction of the mobile image sensor is parallel to the extension direction of the crack; a light shielding sponge (4) is sealed around the scanning area (11), and the two sides of the light shielding sponge (4) are tightly attached to the housing (1) and the surface of the crack to be detected; and / or, The external sensor includes at least one of a strain acquisition module, a displacement acquisition module, and a temperature and humidity acquisition module; The multi-parameter monitoring device for long-term measurement of existing cracks also includes an LTE communication module, the MCU chip and the FPGA chip are both connected to the LTE communication module, and the LTE communication module sends crack information to a host computer through an Internet of Things card; The multi-parameter monitoring device for long-term measurement of existing cracks also includes a power supply, which is connected to the mobile image sensor, the external sensor, the information processing unit and the LTE communication module; The MCU chip has a built-in self-calibration algorithm, the strip-shaped photosensitive device (2) further includes a digital image processing circuit area, the scanning area (11) further includes a self-calibration area (112), a standard part to be detected is arranged in the self-calibration area (112), the standard part to be detected includes a plurality of square grids (113) of two different colors in a square array, the square grids (113) of the two different colors are alternately distributed in the self-calibration area (112), and the square grids (113) of the same color are not adjacent to each other; The self-calibration method of the multi-parameter monitoring device for long-term measurement of existing cracks includes: Obtaining the working mode of the multi-parameter monitoring device for long-term measurement of existing cracks; When the multi-parameter monitoring device for long-term measurement of existing cracks is switched from a monitoring working mode to a self-calibration working mode, the mobile image sensor is controlled to scan the standard part to be detected in the self-calibration area (112) to obtain width data of any square (113); Comparing the width data with a preset standard width, calculating the deviation, and generating a correction coefficient; The digital image processing circuit area corrects the crack image according to the correction coefficient; The step of controlling the mobile image sensor to scan the standard part to be detected in the calibration area (112) to obtain width data of any square (113) comprises: Using a driving system to control a mobile image sensor to scan the standard part to be inspected in the calibration area (112) multiple times to obtain crack widths L1 to Ln to be corrected; The width data of any square (113) is compared with the preset standard width, and the deviation is calculated to generate a correction factor, including: In the MCU chip, the crack widths to be corrected L1-Ln and the pre-stored standard width L0 are input into the self-correction algorithm calculation process, L is compared with L0, and if L and L0 are not equal, the deviation Φ between the crack width to be corrected and the standard width is calculated, and the deviation Φ is used as the correction coefficient; The deviation Φ is calculated by multiple measurements to calculate the average deviation, and the calculation formula includes: ； Where n represents the number of times the standard part is tested; Indicates the specific measurement of the mobile image sensor Second-rate; Represents the mobile image sensor The width of the standard part measured for the first time; The crack image detection threshold is pre-set. Under the long-term measurement conditions of existing cracks in road and bridge projects, the initial setting value of the threshold is 0.01mm. When measuring cracks in the target area, in the image processing circuit area, the target crack pixels obtained by the pixel array are compared with the crack image detection threshold. If the obtained crack pixel result is less than the set threshold, the target is not used as crack width data, and no output or subsequent processing is performed.

2. The multi-parameter monitoring device for long-term measurement of existing cracks according to claim 1 is characterized in that: An LED supplementary light source (5) is provided on at least one side of the strip-shaped light sensing device (2) in the width direction, and the LED supplementary light source (5) is directed toward the crack surface to be detected and moves synchronously with the strip-shaped light sensing device (2); and / or, The MCU chip has a built-in timing circuit for timing the device to collect crack information according to a set collection cycle; and / or, An external sensor data acquisition interface (12) connected to the MCU chip is provided on the housing (1), and the external sensor is plugged into the external sensor data acquisition interface (12).

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