CN116503369A - Deformation monitoring method of structure and image exposure parameter adjusting method - Google Patents

Abstract

The application provides a deformation monitoring method and an image exposure parameter adjusting method of a structure, wherein the method comprises the following steps: the control host generates an ith image acquisition instruction; the first image acquisition module acquires the ith image of the first structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith first structure body image; the control host calculates an average gray level change value of the imaging area of the first coordination mark on the ith first structural body image relative to the imaging area of the first coordination mark on the ith-1 th first structural body image; if the average gray level change value is smaller than or equal to the set change value threshold, the image processing module calculates a real-time pixel value of the first cooperation mark on the ith first structural body image, compares the real-time pixel value with an initial pixel value of the first cooperation mark on the initial first structural body image, and calculates a moving pixel value to determine the change amount of the pixel value, and performs deformation monitoring on the first structural body, so that the power consumption is at least reduced.

Description

Deformation monitoring method of structure and image exposure parameter adjusting method

Technical Field

The embodiment of the application relates to the technical field of object monitoring, in particular to a deformation monitoring method of a structural body.

Background

The deformation of the structure is measured by utilizing the natural texture (speckle) or the mark of the surface of the structure, so that the measurement accuracy can be improved, and a main measuring instrument is not required to be close to the structure to be measured during measurement. Meanwhile, because the measurement is performed based on natural textures (speckles) or marks on the surface of the structure body, the target point positioning with 1/200 pixel resolution can be realized, and compared with the traditional target point positioning which only takes the whole pixel as the resolution, the monitoring resolution is improved by 100 times. Therefore, the real large-view, high-precision and multi-point dynamic synchronous monitoring can be realized; and because the method of the image is adopted, the system has the advantages of simple light path, high measurement efficiency, quick frequency response, easy realization of system integration and the like. In applications, in order to suppress noise caused by ambient light and darkness changes on measurement data, when long-term deformation detection is performed on structures such as bridges, dams, slopes, tunnels, towering structures, etc., the following two solutions are generally adopted: passive light supplement and active light emission. In passive light supplementing, a high-power light supplementing lamp is arranged at the position of an image acquisition module, high-intensity light supplementing is carried out on a structure body, and environment light is fully pressed, so that the brightness of the structure body to be measured is kept unchanged no matter what day or night, and the image acquisition module acquires natural textures, speckles or marks of the structure body to be measured, so that displacement deformation of the structure is measured; in the active light supplementing process, a plurality of LED light sources are fixed on a structural body to serve as matching targets, and an image acquisition module acquires the change of the LED light sources to calculate the deformation value of the position of the structural body;

However, the above-mentioned passive light supplement and active light emission require power supply to the light supplement lamp or the LED light source to emit light so as to reduce the influence of ambient light, and the power of the light supplement cannot meet the requirements. Meanwhile, because the ambient light can change greatly in day and night, the exposure time of the image acquisition module is adjusted by the gray level of the acquired full-image of the structure body, and the matching mark on the structure body cannot be prevented from being excessively dark or excessively exposed on imaging. Whereby effective deformation monitoring of the structure is not achieved. Especially when the realization system based on solar energy is used for supplying power for structural body deformation, the power consumption is a very outstanding problem, and the power of the light filling is more difficult to meet the requirement.

Disclosure of Invention

The purpose of the present application is to provide a deformation monitoring method for a structural body, which is used for solving or alleviating the above technical problems existing in the prior art;

the embodiment of the application provides a deformation monitoring method of a structure body, a first monitoring position subarea is divided on a first structure body, a first matching identifier is assembled in the first monitoring position subarea, and the method comprises the following steps:

the control host generates an ith image acquisition instruction, wherein i is an integer greater than 1;

The first image acquisition module acquires the ith image of the first structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith first structure body image;

the control host calculates an average gray level change value of the imaging area of the first matched mark on the ith first structural body image relative to the imaging area of the first matched mark on the ith-1 th first structural body image;

if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a real-time pixel value of the first coordination mark on the ith first structure body image, compares the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure body image, and calculates a moving pixel value to determine a pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

if the average gray level change value is larger than a set change value threshold, the control host adjusts the image exposure parameters so that the first image acquisition module acquires the (i+1) th image of the first structure to form the (i+1) th image of the first structure;

The control host calculates an average gray level change value of an imaging area of the first coordination mark on the i+1th first structural body image relative to an imaging area of the first coordination mark on the i first structural body image, and if the average gray level change value is smaller than or equal to a set change value threshold value, the image processing module calculates a pixel value of the first coordination mark moving on the i+1th first structural body image; the control host compares the real-time pixel value of the first coordination mark on the (i+1) th first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image to determine the pixel value variation; the control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

optionally, the monitoring the deformation of the first structure according to the moving physical quantity includes:

calculating the deformation of the first structural body according to the moving physical quantity;

comparing the deformation with a set deformation threshold;

If the deformation is greater than or equal to the set deformation threshold, generating an alarm signal and sending the alarm signal;

optionally, the method further comprises:

continuously snapping the first structural body;

optionally, the method further comprises: detecting the light intensity of the environment where the first structural body is located based on a light intensity sensor, and if the light intensity is larger than or equal to a set light intensity threshold value, keeping the light supplementing module closed; if the light intensity is smaller than the set light intensity threshold, starting the light supplementing module to supplement light so that the adjusted image exposure parameter is smaller than or equal to the set image exposure parameter threshold, and converging the average gray level change value along the direction which can be smaller than or equal to the set change value threshold based on the adjusted image exposure parameter;

optionally, the first mating identifier includes: the device comprises a microprism type reflective substrate and a reflective mark arranged on the microprism type reflective substrate, wherein:

the microprism type reflecting substrate is used for carrying out multiple specular reflection treatment on light rays, so that the first pattern acquisition module carries out image acquisition to form a first structure body image comprising the first matching mark;

The light reflection mark is used for carrying out uniform light reflection treatment on light emitted by the light supplementing module, so that the first graph acquisition module can acquire images along any direction to form a first structure image comprising the first matching mark;

optionally, the light reflection mark is a circular ring target, the circular ring target comprises a plurality of concentric circular ring black spots from inside to outside, wherein at least part of the circular ring black spots have virtual edges;

optionally, the second structure is divided into a second monitoring location sub-area, and a second matching identifier is assembled in the second monitoring location sub-area, and the method further includes:

the second image acquisition module acquires the ith image of the second structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith second structure body image;

the control host calculates an average gray level change value of the imaging area of the second matched mark on the ith second structural body image relative to the imaging area of the second matched mark on the ith 1 th second structural body image;

If the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a pixel value of the second matching mark moving on the ith second structural body image, compares the pixel value with an initial pixel value of the second matching mark on an initial second structural body image, and then calculates a moving pixel value to determine a pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the second matched mark so as to monitor a deformation value of the second structure body according to the mobile physical quantity;

if the average gray level change value is larger than a set change value threshold, the control host adjusts the image exposure parameters so that the second image acquisition module acquires the (i+1) th image of the second structure to form the (i+1) th image of the second structure;

the control host calculates the average gray level change value of the imaging area of the second coordination mark on the i+1 second structure body image relative to the imaging area of the second coordination mark on the i second structure body image, if the average gray level change value is smaller than or equal to a set change value threshold value, the image processing module calculates the real-time pixel value of the second coordination mark on the i+1 second structure body image, compares the real-time pixel value with the initial pixel value of the second coordination mark on the initial second structure body image, and calculates the moving pixel value to determine the pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the second matched mark so as to monitor the deformation of the second structure body according to the mobile physical quantity;

The embodiment of the application provides a deformation monitoring method of a structure body, wherein a first matching identifier is assembled on a first structure body, and the method comprises the following steps:

generating an ith image acquisition instruction, wherein i is an integer greater than 1, and the ith image acquisition instruction is used for controlling a first image acquisition module to acquire an ith image of the first structure body based on a set image exposure parameter so as to form an ith first structure body image;

calculating an average gray level change value of the imaging area of the first coordination mark on the ith first structure image relative to the imaging area of the first coordination mark on the ith-1 st first structure image;

if the average gray level change value is smaller than or equal to a set change value threshold, comparing the real-time pixel value of the first coordination mark on the ith first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image, and converting the determined pixel value change amount into a mobile physical quantity of the first coordination mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

if the average gray level change value is larger than a set change value threshold, adjusting the image exposure parameters to acquire the (i+1) th image of the first structure body so as to form the (i+1) th image of the first structure body;

Calculating the average gray scale change value of the imaging area of the first coordination mark on the (i+1) th first structure image relative to the imaging area of the first coordination mark on the (i) th first structure image, and if the average gray scale change value is smaller than or equal to a set change value threshold, comparing the real-time pixel value of the first coordination mark on the (i+1) th first structure image with the initial pixel value of the first coordination mark on the initial first structure image, and converting the determined pixel value change amount into a moving physical amount of the first coordination mark so as to monitor the deformation of the first structure according to the moving physical amount;

the embodiment of the application provides an image exposure parameter adjustment method, which is applied to deformation monitoring of a structural body, wherein a first matching mark is assembled on the first structural body, and the method comprises the following steps:

calculating average gray scale variation values of imaging areas of the first coordination mark on the i-1 th and i-th first structure images which are continuously acquired;

if the average gray level change value is larger than a set change value threshold, adjusting the image exposure parameters to acquire the first structure again so as to form an (i+1) th first structure image;

Calculating the average gray scale change value of the imaging area of the first coordination mark on the (i+1) th first structure image and the (i) th first structure image to determine whether to adjust the image exposure parameter, and the like until the average gray scale change value is smaller than or equal to the set change value threshold value, and monitoring the deformation of the structure based on the corresponding first structure image;

the embodiment of the application provides a deformation monitoring method of a structure body, wherein a first matching identifier is assembled on a first structure body, and the method comprises the following steps:

acquiring a corresponding real-time first structure image under the condition that the average gray change value of the imaging area of the first coordination mark determined by the image exposure parameter adjustment method is smaller than or equal to a set change value threshold value;

acquiring a real-time pixel value of the first coordination mark on the real-time first structure body image, comparing the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure body image, and then calculating a moving pixel value to determine a pixel value variation;

and converting the pixel value variation into a moving physical quantity of the first matched mark so as to monitor the deformation of the first structural body according to the moving physical quantity.

The embodiment of the application provides a deformation monitoring method of a structure body, a first monitoring position subarea is divided on a first structure body, a first matching identifier is assembled in the first monitoring position subarea, and the method comprises the following steps: the control host generates an ith image acquisition instruction, wherein i is an integer greater than 1; the first image acquisition module acquires the ith image of the first structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith first structure body image; the control host calculates an average gray level change value of the imaging area of the first matched mark on the ith first structural body image relative to the imaging area of the first matched mark on the ith-1 th first structural body image; if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a real-time pixel value of the first coordination mark on the ith first structure body image, compares the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure body image, and calculates a moving pixel value to determine a pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structure body according to the mobile physical quantity; if the average gray level change value is larger than a set change value threshold, the control host adjusts the image exposure parameters so that the first image acquisition module acquires the (i+1) th image of the first structure to form the (i+1) th image of the first structure; the control host calculates an average gray level change value of an imaging area of the first coordination mark on the i+1th first structural body image relative to an imaging area of the first coordination mark on the i first structural body image, and if the average gray level change value is smaller than or equal to a set change value threshold value, the image processing module calculates a pixel value of the first coordination mark moving on the i+1th first structural body image; the image processing module compares the real-time pixel value of the first coordination mark on the (i+1) th first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image to calculate a moving pixel value so as to determine the pixel value variation; the control host converts the pixel value variation into a mobile physical quantity of the first coordination mark, so as to monitor deformation of the first structure body according to the mobile physical quantity, thereby overcoming the problem that the coordination mark on the structure body is excessively dark or overexposed on imaging by adjusting the exposure time of the image acquisition module according to the gray level of the acquired full-image of the structure body, and simultaneously reducing the power consumption when the system for realizing deformation of the structure body based on solar energy is considered, and providing a guarantee for continuously and uninterruptedly monitoring the deformation of the structure body.

Drawings

Some specific embodiments of the present application will be described in detail below by way of example and not by way of limitation with reference to the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts or portions. It will be appreciated by those skilled in the art that the drawings are not necessarily drawn to scale. In the accompanying drawings:

FIG. 1 is a schematic diagram of a deformation monitoring system of a structure according to an embodiment of the present disclosure;

FIG. 2 is a flow chart of a method for monitoring deformation of a structure according to an embodiment of the present disclosure;

FIG. 3 is a flow chart illustrating a method for monitoring deformation of a structure according to another embodiment of the present disclosure;

FIG. 4 is a flowchart illustrating a method for adjusting image exposure parameters according to an embodiment of the present disclosure;

fig. 5 is a schematic flow chart of a deformation monitoring method of a structure according to an embodiment of the present application;

fig. 6 is a hardware structure of the electronic device in the present embodiment.

Description of the embodiments

In order to better understand the technical solutions in the embodiments of the present application, the following descriptions will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the embodiments of the present application shall fall within the scope of protection of the embodiments of the present application;

Fig. 1 is a schematic structural diagram of a deformation monitoring system of a structural body according to an embodiment of the present application. As shown in fig. 1, the deformation monitoring system includes: the system comprises a control host 101, a first image acquisition module 102, a synchronous trigger 103, an image processing module 104, an image acquisition card 105, a wireless transmission module 106, a light supplementing module 107, an image snapshot module 108, an alarm module 109, a data storage module 110, a local server 111, a cloud server 112, a solar cell 113, a power management module 114 and a second image acquisition module 115;

in this embodiment, the control host 101, the first image acquisition module 102, the image processing module 104, the image acquisition card 105, the wireless transmission module 106, the light supplementing module 107, the image capturing module 108, and the alarm module 109, and the data storage module 110 may form a master control acquisition analysis system, where the synchronization trigger 103, the first image acquisition module 102, the image acquisition card 105, and the light supplementing module 107 form a master control image acquisition module; the first image acquisition module 102 is used for acquiring images of the first structural body so as to realize deformation monitoring of the first structural body;

the plurality of second image acquisition modules 115 form a sub-image acquisition system, and are used for acquiring images of the plurality of second structures so as to realize deformation monitoring of the plurality of second structures;

The power management module 114 is connected with the solar cell 113 and is used for performing power management;

the solar battery 113 is connected with the main control acquisition and analysis system and the second image acquisition module 115 to provide electric energy for each electric structure in the main control acquisition and analysis system so that each electric structure can work;

in the master control image acquisition module, the synchronous trigger 103 is used for synchronously triggering the first image acquisition module 102 to acquire images of the first structural body and the plurality of second image acquisition modules 115 to acquire a plurality of second structural bodies according to the image acquisition instruction. The image acquisition card 105 receives the first structure image acquired by the first image acquisition module 102 and the second structure image acquired by the second image acquisition module 115, transmits the first structure image and the second structure image to the control host 101, and then transmits the first structure image and the second structure image to the image processing module 104 to respectively calculate the average gray scale of the imaging areas of the first matching identification on the two adjacent first structure images, and further calculates the average gray scale change value of the imaging areas of the first matching identification on the two adjacent first structure images by the control host 101 so as to calculate the pixel value change amount of the imaging areas of the first matching identification on the two adjacent first structure images and monitor the deformation value of the first structure according to the pixel value change amount;

Similarly, except for the amount of change in pixel values of imaging areas on adjacent two first structure images according to the first fit identification, deformation of the first structures is monitored. If the deformation of the second structure body needs to be monitored in the field of view of the image acquisition module, the deformation of the second structure body can be monitored according to the pixel value variation of the imaging areas of the second matching marks on the two adjacent second structure body images;

the light supplementing module 107 is used for supplementing light in the process of realizing deformation monitoring;

the wireless transmission module 106 is configured to wirelessly transmit the data generated in the deformation monitoring process, the pixel value variation, and the deformation values of the first structure and the second structure to the local server 111 and the cloud server for storage; in addition, the average gray level variation value, the pixel value variation, and the deformation values of the first structure and the second structure may be stored in the data storage module 110;

the image capturing module 108 and the alarm module 109 may form an early warning capturing module, where the alarm module 109 is configured to generate first alarm information when the deformation value of the first structure body exceeds a set first deformation threshold, and start the image capturing module 108 to capture continuous images of the first structure body; and/or generating second alarm information when the deformation value of the second structure exceeds a set second deformation threshold, and starting an image snapshot module 108 to continuously take images of the second structure;

In the embodiment of fig. 1, deformation monitoring of a plurality of structures comprising the first structure and the second structure is simultaneously achieved. However, in practical application, only the first structural body may be subjected to deformation monitoring, or only the second structural body may be subjected to deformation monitoring, and for this purpose, a module for implementing deformation monitoring of the first structural body may be reserved in the deformation monitoring system, or only a module for implementing deformation monitoring of the second structural body may be reserved. If the deformation monitoring is carried out on the first structural body and the second structural body, the deformation monitoring system simultaneously reserves a module for realizing the deformation monitoring of the first structural body and a module for realizing the deformation monitoring of the second structural body;

in the above embodiment, the first image capturing module 102 and the second image capturing module 115 may be, for example, industrial cameras. Further, lenses may be configured for the first image acquisition module 102 and the second image acquisition module 115 to improve the definition of image acquisition;

in the above embodiment, the control host 101 is, for example, an embedded industrial motherboard;

in addition, in the deformation monitoring system, other modules besides the control host 101, the first image acquisition module 102, and the image processing module 104 are not necessarily required according to the requirements of the application scenario, and some or all of the other modules may be omitted;

In the deformation monitoring system, data transmission is performed among modules, for example, through a communication cable;

for this reason, in the following embodiments, the deformation monitoring method of the embodiments of the present application is exemplarily described on the basis of realizing the deformation monitoring of the first structural body on the premise that only the control host 101, the first image acquisition module 102, and the image processing module 104 are necessary;

in this embodiment, the first structure and the second structure may be objects to be monitored, such as bridges, dams, slopes, tunnels, towering structures, etc.;

in the above embodiment, the specific setting manner of each structural unit may be flexibly set by a person skilled in the art according to the requirements of the application scenario, so long as deformation monitoring of the structural body can be achieved;

fig. 2 is a flow chart of a deformation monitoring method of a structure according to an embodiment of the present application. As shown in fig. 2, the method includes:

201. the control host generates an ith image acquisition instruction, wherein i is an integer greater than 1;

202. the first image acquisition module acquires the ith image of the first structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith first structure body image;

203. The control host calculates an average gray level change value of the imaging area of the first matched mark on the ith first structural body image relative to the imaging area of the first matched mark on the ith-1 th first structural body image;

204A, if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a real-time pixel value of the first matching identifier on the ith first structure image, compares the real-time pixel value with an initial pixel value of the first matching identifier on the initial first structure image, and calculates a moving pixel value to determine a pixel value change amount;

205. the control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

204B, if the average gray level change value is greater than a set change value threshold, the control host adjusts the image exposure parameter, so that the first image acquisition module performs the (i+1) th image acquisition on the first structure to form the (i+1) th first structure image;

206. the control host calculates an average gray level change value of the imaging area of the first coordination mark on the ith+1th first structural body image relative to the imaging area of the first coordination mark on the ith first structural body image;

In a specific application scenario, for example, the average gray level can be calculated with reference to the following formula (1):

formula (1)

In the above formula, W, H respectively represents the width and height of the imaging region of the first matching mark on the first structural body image, P _xy Expressed as the gray scale size at coordinates (x, y) within the imaging region;

207. if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a real-time pixel value of the first coordination mark on the ith first structure body image, compares the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure body image, and calculates a moving pixel value to determine a pixel value change amount;

for example, the moving pixel value may be calculated by if the following formula (2) and directly taken as the pixel value variation;

formula (2)

(x, y): a first coordinate identifies a center coordinate of an imaging region on the first structure image; (u, v): pixel values shifted in the X and Y directions; m: a first fit identifies a radius of an imaging region on the first structure image;

f (x, y): the first fit identifies a gray value at coordinates (x, y) in an imaging region on the i-1 th first structure image, : the first fit identifies an average gray value in an imaging region on the i-1 th first structure image; />: the first matching mark coordinates +_ in the imaging area on the ith first structure image>Gray values at; />: the first fit identifies an average gray value in an imaging region on the ith first structure image;

in this embodiment, based on the above formula (2), partial derivatives of the substitution u and v are calculated respectively, and then are set to 0, so as to obtain a formula (3), then u and v are solved by an iterative method, and the obtained (u and v) are used as pixel values moving in the X and Y directions, so that the moving pixel values can be accurately and rapidly calculated in real time;

formula (3)

208. The control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

in this embodiment, since the image exposure parameters are adjusted only according to the average gray level of the imaging area of the first matching identifier on the first structural body image, rather than adjusting the image exposure parameters according to the full image of the first structural body image, overexposure or darkness is ensured when the ambient light changes greatly, so that the first matching identifier cannot be tracked, and deformation monitoring of the first structural body cannot be realized;

Optionally, the monitoring the deformation of the first structure according to the moving physical quantity includes:

calculating the deformation of the first structural body according to the moving physical quantity;

comparing the deformation with a set deformation threshold;

if the deformation is greater than or equal to the set deformation threshold, generating an alarm signal and sending the alarm signal;

for example, the conversion of the pixel value variation into the mobile physical quantity of the first cooperation mark may be implemented with reference to the following formula:

；

wherein (u, v) are the pixel values shifted in the X and Y directions, respectively,representing the actual dimensions of two points known in the plane of the first co-ordinated logo movement, +.>Representing the difference in pixel distance between two points known in the plane of the first coordinate marker movement in the image. />Respectively are provided withMove physical quantities for the X and Y directions;

for example, calculating a deformation amount of the first structural body based on the moving physical quantity; the comparison of the deformation amount with a set deformation amount threshold value can be performed, for example, by a control host. For example, generating and transmitting an alarm signal based on an alarm module;

optionally, the method further comprises: and continuously snapping the first structural body. For example, continuous snapshot is performed based on the image snapshot module;

Optionally, in order to avoid the influence of the illumination condition of the external environment on the image acquisition, the method further includes: detecting the light intensity of the environment where the first structural body is located based on a light intensity sensor, and if the light intensity is larger than or equal to a set light intensity threshold value, keeping the light supplementing module closed; if the light intensity is smaller than the set light intensity threshold, starting the light supplementing module to supplement light so that the adjusted image exposure parameter is smaller than or equal to the set image exposure parameter threshold, and converging the average gray level change value along the direction smaller than or equal to the set change value threshold based on the adjusted image exposure parameter;

for example, when the illumination is sufficient, such as during daytime, the light intensity may be greater than or equal to a set light intensity threshold, and the light supplementing module is turned off. During the daytime, the light intensity is greater than or equal to the set light intensity threshold value, but if the light intensity is changed, the image exposure parameter (such as the exposure time and/or the exposure gain) is adjusted in the above embodiment so that the average gray scale change value converges in a direction less than or equal to the set change value threshold value, or the average gray scale change value is also referred to as being as small as possible. For example, when the light intensity is weakened, at least one of the exposure time is increased or the exposure gain is increased, and when the light intensity is strengthened, at least one of the exposure time is shortened or the exposure time is reduced, so that the increase of power consumption caused by opening the light supplementing module is avoided, and meanwhile, the tracking precision of the first matching mark when the ambient light changes can be improved;

For example, if entering an evening period, the light intensity is smaller than the set light intensity threshold, and the light intensity is regarded as failing to meet the requirement of image acquisition, the light supplementing module is turned on to supplement light, and the image exposure parameters (such as exposure time and/or exposure gain) are adjusted, so that the average gray scale variation value converges along a direction smaller than or equal to the set variation value threshold, or the average gray scale variation value is also referred as being as small as possible. The light supplementing module is used for supplementing light and adjusting the image exposure parameters, so that the situation that the image exposure parameters are smaller than or equal to the set image exposure parameter threshold value is avoided, namely the image exposure parameter threshold value of the first image acquisition module is not exceeded;

in a specific application scenario, the image exposure parameter threshold is an image exposure time threshold, and the i+1th image acquisition of the first structure body can be realized by comprehensively supplementing light and adjusting the image exposure parameter threshold so as to form an i+1th first structure body image;

if the ith first structure image is acquired, the corresponding current camera exposure time is ET, the average gray value of the imaging area where the first matching mark is located on the obtained ith first structure image is Si, the average gray value of the imaging area where the first matching mark is located on the ith-1 th first structure image is Si-1, and the change value threshold is Sc:

If the average gray level change value is less than or equal to the set change value threshold, the method includes: if it isET remains unchanged;

further, for the above step S204B, it may include the following cases:

if it isThen adjust to +.>；

If it isAnd the current ET reaches the maximum ET (i.e. exceeds the camera exposure time threshold), triggering a light supplementing module to turn on a light supplementing lamp so as to perform i+1st image acquisition on the first structure by the first image acquisition module to form an i+1st first structure image;

if it isAnd the current ET does not reach the maximum ET, then ET is adjusted to the current ET < 0 >, the maximum ET-current ET]The random numbers distributed by the positive-theta are used for carrying out the (i+1) th image acquisition on the first structure body by the first image acquisition module so as to form the (i+1) th first structure body image;

therefore, the light intensity of the environment where the first structural body is located is detected based on the light intensity sensor, and if the light intensity is larger than or equal to a set light intensity threshold value, the light supplementing module is kept to be closed; if the light intensity is smaller than the set light intensity threshold, the light supplementing module is started to supplement light so that the adjusted image exposure parameter is smaller than or equal to the set image exposure parameter threshold, and based on the adjusted image exposure parameter, the average gray level change value is converged along the direction smaller than or equal to the set change value threshold, so that overexposure or overdarkness can be avoided in day-night conversion, the average gray level of an imaging area of a first coordination mark is always kept from being excessively changed, accurate tracking and positioning of the first coordination mark are facilitated, and meanwhile, the light supplementing module is selectively started so that the light supplementing time is greatly shortened, and power consumption is greatly reduced;

Optionally, in this embodiment, the first mating identifier includes: the device comprises a microprism type reflective substrate and a reflective mark arranged on the microprism type reflective substrate, wherein: the microprism type reflecting substrate is used for carrying out multiple specular reflection treatment on light rays, so that the first pattern acquisition module carries out image acquisition to form a first structure body image comprising the first matching mark; the light reflection mark is used for carrying out uniform light reflection treatment on light emitted by the light supplementing module, so that the first graph acquisition module can acquire images along any direction to form a first structure image comprising the first matching mark. Therefore, the tracking precision of the first image acquisition module to the first matching mark on the first structure body along any direction can be ensured, and meanwhile, the light supplementing intensity of the light supplementing module can be reduced, and the power consumption caused by light supplementing is further reduced, so that the deformation monitoring of the first structure body is effectively realized;

optionally, the first image acquisition module and the light supplementing module are arranged in a same position, so that the light of the light supplementing module can be beneficial to tracking of the first matching identifier on the first structural body as much as possible;

Optionally, the reflective mark is a circular ring target, the circular ring target comprises a plurality of concentric circular ring black spots from inside to outside, wherein at least part of the circular ring black spots have virtual edges, so that a certain gray gradient is formed, textures of the first matching mark are rich, the influence of ambient light is reduced, and the tracking precision of the first matching mark is ensured. Meanwhile, the tracking device is an annular black spot, has omnidirectionality, and can avoid the influence of the rotation of the first structural body on the tracking precision;

in this embodiment, the number of the circular ring black spots is selected according to the requirement of monitoring the monitoring working condition, for example, the number of the circular ring black spots can be double-layer, triple-layer or the like;

in the above embodiment, the number of the first image capturing modules, the number of the first structures, and the number of the first matching marks are not particularly limited. The first image acquisition module, the first structure body and the first matching identifier can be in one-to-one correspondence, one-to-many correspondence or the like;

if a plurality of first matching identifications are corresponding to the same first structural body, a plurality of mobile physical quantities are calculated, and therefore, local or global deformation monitoring can be carried out on the first structural body based on the plurality of mobile physical quantities so as to monitor the health state of the first structural body;

Specifically, local or global deformation monitoring is performed on the first structure based on the plurality of mobile physical quantities to monitor the health state of the first structure, including: performing spectrum analysis according to the mobile physical quantity corresponding to each first coordination mark to obtain the vibration frequency of the first structure body at the first coordination mark;

if the mobile physical quantity exceeds a set mobile physical quantity threshold and the vibration frequency exceeds a set vibration frequency threshold, performing image capturing on the first structural body by using a starting image capturing module so as to monitor the deformation dynamic change of the first structural body and judge the health state of the first structural body;

for example, if the first structure is a bridge, monitoring its deformation dynamics and determining if it is due to a dynamic displacement variation of the vehicle against the bridge as a result of the vehicle traveling through the bridge; if the first structure is a reservoir dam, monitoring its deformation dynamics and determining if it is due to an accelerated change in stormwater weather displacement;

or specifically, monitoring the deformation of the first structure locally or globally based on the plurality of mobile physical quantities to monitor the health state of the first structure, including:

Judging whether a first coordination mark with the mobile physical quantity larger than a set mobile physical quantity threshold exists in the first coordination marks or not;

if the first matching mark exists, determining the moving physical quantity of other first matching marks on the same longitudinal section with the first matching mark of which the moving physical quantity is larger than a set moving physical quantity threshold value on the first structure;

determining an impact coefficient mean value according to all the moving physical quantities of the first matched marks on the same longitudinal section, and comparing the impact coefficient mean value with a set impact coefficient mean value threshold value;

if the impact coefficient mean value does not exceed the set impact coefficient mean value threshold value, comprehensively judging that the health state of the first structural body is in a good state by combining the maximum displacement value, otherwise, judging that the first structural body is in a dangerous state;

illustratively, for example, for any first fit identification, the impact coefficient value may be quickly calculated as follows:；

representing the maximum mobile physical quantity in any first matched mark on the same longitudinal section;

representing a difference between peaks of the moving physical quantity in the first cooperative identification;

the impact coefficients of all the first matched marks on the same longitudinal section are subjected to average value calculation, so that an impact coefficient average value is obtained;

As described above, in addition to the deformation monitoring of the first structural body, the deformation monitoring of the second structural body may be performed, and the first structural body and the second structural body may be the same type of monitored object or different types of monitored objects;

for this purpose, a second monitoring location sub-zone is divided on the second structure, said second monitoring location sub-zone being equipped with a second mating identification, said method further comprising:

the second image acquisition module acquires the ith image of the second structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith second structure body image;

the control host calculates an average gray level change value of the imaging area of the second matched mark on the ith second structural body image relative to the imaging area of the second matched mark on the ith-1 th second structural body image;

if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a pixel value of the second matching mark moving on the ith second structural body image, compares the pixel value with an initial pixel value of the second matching mark on an initial second structural body image, and then calculates a moving pixel value to determine a pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the second matched mark so as to monitor a deformation value of the second structure body according to the mobile physical quantity;

If the average gray level change value is larger than a set change value threshold, the control host adjusts the image exposure parameters so that the second image acquisition module acquires the (i+1) th image of the second structure to form the (i+1) th image of the second structure;

the control host calculates the average gray level change value of the imaging area of the second coordination mark on the i+1 second structure body image relative to the imaging area of the second coordination mark on the i second structure body image, if the average gray level change value is smaller than or equal to a set change value threshold value, the image processing module calculates the real-time pixel value of the second coordination mark on the i+1 second structure body image, compares the real-time pixel value with the initial pixel value of the second coordination mark on the initial second structure body image, and calculates the moving pixel value to determine the pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the second matched mark so as to monitor the deformation of the second structure body according to the mobile physical quantity;

here, the above-described calculation formulas for the deformation monitoring of the first structure are also applicable to the deformation monitoring of the second structure, and the definition for the first structure may be modified to the definition for the second structure;

Here, an exemplary scheme of deformation monitoring for the second structure is similar to an exemplary scheme of deformation monitoring for the first structure, and will not be described in detail herein;

in the above embodiment, the number of the second image capturing modules, the number of the second structures, and the number of the second matching marks are not particularly limited. The second image acquisition module, the second structure body and the second matching identifier can be in one-to-one correspondence, one-to-many correspondence or the like;

on the basis of the embodiment, another deformation monitoring method of the structural body is provided in consideration of the requirements of application scenes;

fig. 3 is a flow chart illustrating a deformation monitoring method of another structure according to an embodiment of the present application. The first structure is provided with a first mating identifier, as shown in fig. 3, and the method includes:

301. generating an ith image acquisition instruction, wherein i is an integer greater than 1, and the ith image acquisition instruction is used for controlling a first image acquisition module to acquire an ith image of the first structure body based on a set image exposure parameter so as to form an ith first structure body image;

302. calculating an average gray level change value of the imaging area of the first coordination mark on the ith first structure image relative to the imaging area of the first coordination mark on the ith-1 st first structure image;

303. If the average gray level change value is smaller than or equal to a set change value threshold, comparing the real-time pixel value of the first coordination mark on the ith first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image, and converting the determined pixel value change amount into a mobile physical quantity of the first coordination mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

304. if the average gray level change value is larger than a set change value threshold, adjusting the image exposure parameters to acquire the (i+1) th image of the first structure body so as to form the (i+1) th image of the first structure body;

305. calculating the average gray scale change value of the imaging area of the first coordination mark on the (i+1) th first structure image relative to the imaging area of the first coordination mark on the (i) th first structure image, and if the average gray scale change value is smaller than or equal to a set change value threshold, comparing the real-time pixel value of the first coordination mark on the (i+1) th first structure image with the initial pixel value of the first coordination mark on the initial first structure image, and converting the determined pixel value change amount into a moving physical amount of the first coordination mark so as to monitor the deformation of the first structure according to the moving physical amount;

In the above embodiment, the initial first structure image corresponds to an image acquired when the first structure is not deformed;

in this embodiment, the execution body of each step may refer to the embodiment of fig. 2, which is not described herein again;

on the basis of the embodiment, the embodiment of the application also provides an image exposure parameter adjusting method which is applied to deformation monitoring of the structural body. Fig. 4 is a flowchart illustrating an image exposure parameter adjustment method according to an embodiment of the present disclosure. As shown in fig. 4, the method includes:

401. calculating average gray scale variation values of imaging areas of the first coordination mark on the i-1 th and i-th first structure images which are continuously acquired;

402. if the average gray level change value is larger than a set change value threshold, adjusting the image exposure parameters to acquire the first structure again so as to form an (i+1) th first structure image;

403. calculating the average gray scale change value of the imaging area of the first coordination mark on the (i+1) th first structure image and the (i) th first structure image to determine whether to adjust the image exposure parameter, and the like until the average gray scale change value is smaller than or equal to the set change value threshold value, and monitoring the deformation of the structure based on the corresponding first structure image;

In this embodiment, an exemplary explanation of steps 401-403 may be found in the embodiment shown in FIG. 2 described above;

on the basis of the embodiment, the embodiment of the application also provides a deformation monitoring method of the structure body, wherein the first structure body is provided with the first matching mark. Fig. 5 is a flow chart of a deformation monitoring method for a structural body according to an embodiment of the present application. As shown in fig. 5, the method includes:

501. acquiring a real-time first structure image corresponding to the condition that the average gray change value of the imaging area of the first coordination mark is smaller than or equal to a set change value threshold value;

502. acquiring a real-time pixel value of the first coordination mark on the real-time first structure image, comparing the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure image, and then calculating a moving pixel value to determine a pixel value variation;

503. converting the pixel value variation into a mobile physical quantity of the first matched mark, so as to monitor deformation of the first structure body according to the mobile physical quantity;

in this embodiment, for an exemplary explanation of steps 501-503, refer to the descriptions of fig. 1-4, and are not repeated here;

Here, it should be noted that, the values of the various thresholds described in the above embodiments are specifically set according to the application scenario and the accuracy requirement of deformation monitoring;

fig. 6 is a hardware structure of the electronic device in the present embodiment. As shown in fig. 6, the hardware structure of the electronic device may include: a processor 601, a communication interface 602, a computer readable medium 603 and a communication bus 604;

wherein the processor 601, the communication interface 602, and the computer readable medium 603 communicate with each other via a communication bus 604;

alternatively, the communication interface 602 may be an interface of a communication module, such as an interface of a GSM module;

wherein the processor 601 may be specifically configured to perform all or part of the steps of any of the embodiment methods described above;

the processor 601 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like;

The computer readable medium 603 may be, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), programmable Read Only Memory (Programmable Read-Only Memory, PROM), erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.;

as another aspect, the present application also provides a computer-readable medium having stored thereon a computer program which, when executed by a processor, implements the deformation monitoring method of a structure as described in the above embodiment one;

the foregoing description is only of the preferred embodiments of the present application and is presented as a description of the principles of the technology being utilized. It will be appreciated by persons skilled in the art that the scope of the invention referred to in this application is not limited to the specific combinations of features described above, but it is intended to cover other embodiments in which any combination of features described above or equivalents thereof is possible without departing from the spirit of the invention. Such as the above-described features and technical features having similar functions (but not limited to) disclosed in the present application are replaced with each other.

Claims (10)

1. A method for monitoring deformation of a structure, wherein a first structure is divided into a first monitored location sub-area, and wherein a first mating identifier is assembled in the first monitored location sub-area, the method comprising:

the control host generates an ith image acquisition instruction, wherein i is an integer greater than 1;

the first image acquisition module acquires the ith image of the first structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith first structure body image;

the control host calculates an average gray level change value of the imaging area of the first matched mark on the ith first structural body image relative to the imaging area of the first matched mark on the ith-1 th first structural body image;

if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a real-time pixel value of the first coordination mark on the ith first structure body image, compares the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure body image, and calculates a moving pixel value to determine a pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

If the average gray level change value is larger than a set change value threshold, the control host adjusts the image exposure parameters so that the first image acquisition module acquires the (i+1) th image of the first structure to form the (i+1) th image of the first structure;

the control host calculates an average gray level change value of an imaging area of the first coordination mark on the i+1th first structural body image relative to an imaging area of the first coordination mark on the i first structural body image, and if the average gray level change value is smaller than or equal to a set change value threshold value, the image processing module calculates a pixel value of the first coordination mark moving on the i+1th first structural body image; the image processing module compares the real-time pixel value of the first coordination mark on the (i+1) th first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image, and calculates a moving pixel value so as to determine the pixel value variation; the control host converts the pixel value variation into a mobile physical quantity of the first matched mark so as to monitor deformation of the first structural body according to the mobile physical quantity.

2. The method according to claim 1, wherein the deformation monitoring of the first structure according to the moving physical quantity includes:

calculating the deformation of the first structural body according to the moving physical quantity;

comparing the deformation with a set deformation threshold;

and if the deformation is greater than or equal to the set deformation threshold, generating an alarm signal and sending the alarm signal.

3. The method according to claim 2, further comprising:

and continuously snapping the first structural body.

4. A method according to any one of claims 1-3, further comprising: detecting the light intensity of the environment where the first structural body is located based on a light intensity sensor, and if the light intensity is larger than or equal to a set light intensity threshold value, keeping the light supplementing module closed; and if the light intensity is smaller than the set light intensity threshold, starting the light supplementing module to supplement light so that the adjusted image exposure parameter is smaller than or equal to the set image exposure parameter threshold, and converging the average gray level change value along the direction smaller than or equal to the set change value threshold based on the adjusted image exposure parameter.

5. The method of claim 4, wherein the first mating identification comprises: the device comprises a microprism type reflective substrate and a reflective mark arranged on the microprism type reflective substrate, wherein:

the microprism type reflecting substrate is used for carrying out multiple specular reflection treatment on light rays, so that the first pattern acquisition module carries out image acquisition to form a first structure body image comprising the first matching mark;

the light reflection mark is used for carrying out uniform light reflection treatment on light emitted by the light supplementing module, so that the first graph acquisition module can acquire images along any direction to form a first structure image comprising the first matching mark.

6. The method of claim 5, wherein the retroreflective marker is a torus target comprising a plurality of torus black spots from inside to outside and concentric, wherein at least a portion of the torus black spots have a darkened edge.

7. The method of claim 6, wherein a second structure is divided into a second monitored location sub-area, the second monitored location sub-area being populated with a second mating identifier, the method further comprising:

The second image acquisition module acquires the ith image of the second structure body based on the set image exposure parameters under the triggering of the ith image acquisition instruction so as to form an ith second structure body image;

the control host calculates an average gray level change value of the imaging area of the second matched mark on the ith second structural body image relative to the imaging area of the second matched mark on the ith-1 th second structural body image;

if the average gray level change value is smaller than or equal to a set change value threshold, the image processing module calculates a pixel value of the second matching mark moving on the ith second structural body image, compares the pixel value with an initial pixel value of the second matching mark on an initial second structural body image, and then calculates a moving pixel value to determine a pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the second matched mark so as to monitor a deformation value of the second structure body according to the mobile physical quantity;

if the average gray level change value is larger than a set change value threshold, the control host adjusts the image exposure parameters so that the second image acquisition module acquires the (i+1) th image of the second structure to form the (i+1) th image of the second structure;

The control host calculates the average gray level change value of the imaging area of the second coordination mark on the i+1 second structure body image relative to the imaging area of the second coordination mark on the i second structure body image, if the average gray level change value is smaller than or equal to a set change value threshold value, the image processing module calculates the real-time pixel value of the second coordination mark on the i+1 second structure body image, compares the real-time pixel value with the initial pixel value of the second coordination mark on the initial second structure body image, and calculates the moving pixel value to determine the pixel value change amount; the control host converts the pixel value variation into a mobile physical quantity of the second matched mark so as to monitor the deformation of the second structure body according to the mobile physical quantity.

8. A method of monitoring deformation of a structure, wherein a first structure is provided with a first mating identifier, the method comprising:

generating an ith image acquisition instruction, wherein i is an integer greater than 1, and the ith image acquisition instruction is used for controlling a first image acquisition module to acquire an ith image of the first structure body based on a set image exposure parameter so as to form an ith first structure body image;

Calculating an average gray level change value of the imaging area of the first coordination mark on the ith first structure image relative to the imaging area of the first coordination mark on the ith-1 st first structure image;

if the average gray level change value is smaller than or equal to a set change value threshold, comparing the real-time pixel value of the first coordination mark on the ith first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image, and converting the determined pixel value change amount into a mobile physical quantity of the first coordination mark so as to monitor deformation of the first structure body according to the mobile physical quantity;

if the average gray level change value is larger than a set change value threshold, adjusting the image exposure parameters to acquire the (i+1) th image of the first structure body so as to form the (i+1) th image of the first structure body;

calculating the average gray scale change value of the imaging area of the first coordination mark on the i+1 first structure body image relative to the imaging area of the first coordination mark on the i first structure body image, and if the average gray scale change value is smaller than or equal to a set change value threshold value, converting the pixel value change quantity determined by comparing the real-time pixel value of the first coordination mark on the i+1 first structure body image with the initial pixel value of the first coordination mark on the initial first structure body image into the moving physical quantity of the first coordination mark so as to monitor the deformation of the first structure body according to the moving physical quantity.

9. An image exposure parameter adjustment method applied to deformation monitoring of a structure body is characterized in that a first structure body is provided with a first matching mark, and the method comprises the following steps:

calculating average gray scale variation values of imaging areas of the first coordination mark on the i-1 th and i-th first structure images which are continuously acquired;

if the average gray level change value is larger than a set change value threshold, adjusting the image exposure parameters to acquire the first structure again so as to form an (i+1) th first structure image;

calculating the average gray scale change value of the imaging area of the first coordination mark on the (i+1) th first structure image and the (i) th first structure image to determine whether to adjust the image exposure parameter, and the like until the average gray scale change value is smaller than or equal to the set change value threshold value, and monitoring the deformation of the structure based on the corresponding first structure image.

10. A method of monitoring deformation of a structure, wherein a first structure is provided with a first mating identifier, the method comprising:

acquiring a real-time first structure image corresponding to the condition that the average gray change value of the imaging area of the first coordination mark determined by the method according to claim 9 is smaller than or equal to a set change value threshold value;

Acquiring a real-time pixel value of the first coordination mark on the real-time first structure image, comparing the real-time pixel value with an initial pixel value of the first coordination mark on an initial first structure image, and then calculating a moving pixel value to determine a pixel value variation;

and converting the pixel value variation into a moving physical quantity of the first matched mark so as to monitor the deformation of the first structural body according to the moving physical quantity.