Wall quality detection and evaluation method and robot

Abstract

The invention provides a wall quality detection and evaluation method and a robot, and the method comprises the steps: receiving image information, determining the outer surface information of a target to-be-detected wall, and determining the movement track information and a wall model according to the outer surface information; controlling an acquisition device to acquire wall information according to the action track information; determining a corrected wall body model according to the infrared light wall body information, the infrared thermal wall body information and the wall body model, and respectively determining an ultrasonic wall body model, a microwave wall body model and a radar wall body model according to the ultrasonic wall body information, the microwave wall body information and the radar wall body information; and determining a target wall body model according to the corrected wall body model, the ultrasonic wall body model, the microwave wall body model and the radar wall body model, determining the quality of the target to-be-detected wall body through a preset method according to the target wall body model, and outputting an evaluation result. According to the invention, the problem of low accuracy of wall quality detection and evaluation caused by large measurement error and low precision of wall detection in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction engineering safety detection, and in particular to a wall quality detection and evaluation method and a robot. Background Art

[0002] Due to their years of use, the main structures of some buildings are affected by non-human destructive factors such as natural disasters, sudden changes in external forces, and interference from later human behavior and are beginning to enter the aging stage of facilities. Building structure health monitoring is becoming increasingly important. In order to ensure the normal service life and safety of buildings, quality and safety inspections of buildings are required.

[0003] At present, deformation detection of building walls mainly relies on post-construction inspections and regular inspections, and the inspection methods are mainly visual inspections and other manual measurement methods relying on tools. However, visual inspections and simple manual monitoring mainly rely on personal experience when conducting in-depth inspections of the interior of the structure, and are greatly affected by personal subjective factors. Even if the professional and technical level of the appraisers is high, they may make mistakes in judgment. To improve accuracy, it is also necessary to use other auxiliary tools for detection, such as infrared thermal imagers or ultrasonic equipment.

[0004] However, using only infrared thermal imagers or ultrasonic equipment for detection still has problems such as large measurement errors and low measurement accuracy, which in turn leads to low accuracy in wall quality detection and inability to make a correct wall quality assessment. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a wall quality detection and evaluation method and robot, aiming to solve the problem of large measurement error and low precision of wall detection in the prior art, resulting in low accuracy of wall quality detection and evaluation.

[0006] A wall quality detection and evaluation method according to an embodiment of the present invention includes:

[0007] Receiving image information from a preset image capture device, determining outer surface information of a target wall to be detected, and determining motion trajectory information and a wall model according to the outer surface information;

[0008] According to the motion trajectory information, the acquisition device is controlled to move on the surface of the target wall to be detected, so that the acquisition device collects the wall information of the target wall to be detected, and obtains the wall information transmitted by the acquisition device, wherein the wall information includes ultrasonic wall information, microwave wall information, radar wall information, infrared light wall information and infrared thermal wall information;

[0009] Determine a modified wall model according to the infrared light wall information, the infrared heat wall information and the wall model, and respectively determine an ultrasonic wall model, a microwave wall model and a radar wall model according to the ultrasonic wall information, the microwave wall information and the radar wall information;

[0010] A target wall model is determined according to the corrected wall model, the ultrasonic wall model, the microwave wall model and the radar wall model, and the quality of the target wall to be inspected is determined by a preset method according to the target wall model and an evaluation result is output.

[0011] In addition, a wall quality detection and evaluation method according to the above embodiment of the present invention may also have the following additional technical features:

[0012] Furthermore, the step of determining and correcting the wall model according to the infrared light wall information, the infrared heat wall information and the wall model includes:

[0013] Determine the material distribution information of the target wall to be detected according to the infrared light wall information;

[0014] Determine shallow defect information of the target wall to be detected according to the infrared thermal wall information;

[0015] The wall model is adjusted according to the material distribution information and the shallow defect information to obtain the corrected wall model.

[0016] Furthermore, the step of determining the target wall model according to the corrected wall model, the ultrasonic wall model, the microwave wall model and the radar wall model comprises:

[0017] Fitting the modified wall model and the ultrasonic wall model and correcting the fitted model according to the model library to obtain a first fitting model;

[0018] Fitting the modified wall model and the microwave wall model and correcting the fitted model according to the model library to obtain a second fitting model;

[0019] Fitting the modified wall model and the radar wall model and correcting the fitted model according to the model library to obtain a third fitting model;

[0020] Perform stress simulation on the first fitting model, the second fitting model and the third fitting model to obtain stress distribution conditions corresponding to the first fitting model, the second fitting model and the third fitting model;

[0021] The first fitting model, the second fitting model and the third fitting model are corrected according to the stress distribution state, and the corrected first fitting model, the second fitting model and the third fitting model are fitted to obtain the target wall model.

[0022] Furthermore, the step of determining the quality of the target wall to be inspected by a preset method according to the target wall model and outputting an evaluation result includes:

[0023] Controlling the acquisition device to acquire the correction areas of the first fitting model, the second fitting model and the third fitting model for multiple times to obtain wall information of the correction areas;

[0024] Determine a regional verification model according to the corrected regional wall information, compare the regional verification model with the corresponding area of ​​the target wall model to determine the difference, and determine whether the difference is greater than a preset threshold;

[0025] If not, determine the quality of the target wall to be inspected according to the condition of the target wall model and output an evaluation result;

[0026] If yes, the wall is re-inspected and the target wall model is corrected, and then the quality of the target wall to be inspected is determined based on the corrected target wall model and an evaluation result is output.

[0027] Furthermore, the step of receiving image information from a preset image capture device, determining outer surface information of a target wall to be detected, and determining the motion trajectory information and the wall model according to the outer surface information includes:

[0028] Determine whether there is a historical detection digital model of the target wall to be detected in the preset database;

[0029] If not, executing the steps of receiving image information from a preset image capture device, determining outer surface information of the target wall to be detected, and determining motion trajectory information and a wall model according to the outer surface information;

[0030] If so, receive image information from a preset image capture device, determine the outer surface information of the target wall to be detected, determine the wall model based on the outer surface information and the latest historical detection digital model, and then determine the motion trajectory information based on the wall model.

[0031] Furthermore, after the step of determining the quality of the target wall to be inspected by a preset method according to the target wall model and outputting the evaluation result, the following steps are included:

[0032] The target wall model used to determine the quality of the target wall to be inspected is uploaded to the cloud database to obtain the inspection digital model, so that the cloud server determines the time node when the target wall to be inspected needs to be inspected next time according to all the inspection digital models of the target wall to be inspected in the cloud database and the upload time corresponding to the inspection digital models.

[0033] Furthermore, the step of determining the motion trajectory information according to the outer surface information includes:

[0034] Dividing the target wall to be detected into regions according to the outer surface information to obtain target regions and the number of the target regions, and determining the number of the acquisition devices required according to the number of the target regions;

[0035] The motion track information corresponding to the target area is determined according to the outer surface information corresponding to the target area, and the acquisition device corresponding to the target area is moved according to the motion track information corresponding to the target area.

[0036] Furthermore, the step of dividing the target wall to be detected into regions according to the outer surface information to obtain the target region includes:

[0037] Determine the number of gaps, the gap area, and the gap distribution area of ​​the current outer surface of the target wall to be detected according to the outer surface information;

[0038] The target wall to be detected is divided into regions according to the number of gaps, the gap area, the gap distribution area, and the collection efficiency and moving speed of the collection device, so that the collection time required by each collection device is consistent and the collection time is less than a preset time.

[0039] Furthermore, real-time external surface information transmitted by the acquisition device when it moves in the target area is obtained, and the movement trajectory information of the acquisition device is adjusted according to the real-time external surface information.

[0040] Another object of the present invention is to provide a robot, comprising:

[0041] A wall climbing module, used for receiving the motion trajectory information sent by the control center, and navigating according to the motion trajectory information to drive the robot to move on the wall;

[0042] A detection module, used for performing ultrasonic, microwave, radar, infrared light and infrared heat detection on the wall through detection equipment;

[0043] The data processing module is used to receive the detection results of the detection equipment, perform noise reduction processing on the detection results, and send the noise-reduced detection results to the control center, so that the control center determines the wall quality and evaluates it according to the detection data.

[0044] Another object of an embodiment of the present invention is to provide a storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the above-mentioned wall quality detection and evaluation method.

[0045] Another object of an embodiment of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned wall quality detection and evaluation method when executing the program.

[0046] The present invention obtains the outer surface information of the wall to be detected through an image capture device, and then makes a preliminary judgment on the surface condition of the wall. According to the surface condition of the wall, the wall is divided and a movement path is planned so that the acquisition device can collect data on the wall with the highest efficiency and avoid the influence of the movement of the acquisition device on the collected data and the quality of the wall. The wall model is modeled according to the outer surface information to determine the wall model. Then, different types of information collected by the acquisition device are used to correct the wall model by using the characteristics of different information, that is, using infrared light information and infrared heat information to obtain a corrected model, and the material distribution and surface crack condition of the wall model are determined. Then, according to the characteristics of microwaves, ultrasonic waves and radars, the target detection wall is modeled according to these three types of information, and according to the corrected model, the differences between the models are distinguished and determined, so as to adjust the model to obtain a digital model that is closest to the actual condition of the target detection wall in theory, that is, the target wall model, and the current quality of the wall to be detected is analyzed according to the target wall model and an evaluation result is output. Since the method collects wall information through a collection device, and obtains different types of collected information through the collection device, and converts different types of information into parameters of the same dimension for comparison and fusion, the most real and accurate information of the target wall to be detected is obtained to evaluate the quality of the target wall to be detected, thereby avoiding the errors and misjudgments of manual measurement methods, and avoiding the situation where a single type of data has large measurement errors and low measurement accuracy in wall quality detection. Therefore, the present invention solves the problem of large measurement errors and low accuracy in wall quality detection and evaluation in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flow chart of a wall quality detection and evaluation method in a first embodiment of the present invention;

[0048] Figure 2is a schematic structural diagram of an electronic device in a third embodiment of the present invention;

[0049] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0050] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0051] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0053] Embodiment 1

[0054] See also Figure 1 , which shows a wall quality detection and evaluation method in a first embodiment of the present invention, and the method specifically includes steps S01 to S04.

[0055] S01, receiving image information from a preset image capture device, determining outer surface information of a target wall to be detected, and determining motion trajectory information and a wall model according to the outer surface information;

[0056] Specifically, the target wall to be detected is divided into regions according to the outer surface information to obtain target regions and the number of target regions, and the number of the required acquisition devices is determined according to the number of target regions; the motion trajectory information corresponding to the target region is determined according to the outer surface information corresponding to the target region, and the acquisition device corresponding to the target region is moved according to the motion trajectory information corresponding to the target region. The step of dividing the target wall to be detected into regions according to the outer surface information to obtain the target region includes: determining the number of gaps, the gap area and the gap distribution area on the current outer surface of the target wall to be detected according to the outer surface information; dividing the target wall to be detected into regions according to the number of gaps, the gap area, the gap distribution area and the acquisition efficiency and moving speed of the acquisition device, so that the acquisition time required by each acquisition device is consistent and the acquisition time is less than the preset time. The real-time outer surface information transmitted by the acquisition device when it moves in the target region is obtained, and the motion trajectory information of the acquisition device is adjusted according to the real-time outer surface information.

[0057] By way of example and not limitation, in some optional embodiments, the acquisition device may use a wall-climbing robot to collect information about the wall through the equipment carried by the wall-climbing robot. Therefore, it is necessary to first use an image capture device to make a preliminary confirmation of the surface information of the wall to be detected, that is, to determine the area, shape, feature distribution, and crack distribution of the wall through image acquisition. This allows the wall to be divided into regions and the number and movement trajectory of the wall-climbing robots to be determined based on this information. This ensures efficient wall information acquisition and prevents the wall-climbing robot from causing damage to the wall due to its route, such as the wall-climbing robot driving over a crack, causing the crack to expand, or the outer wall to fall off, or the wall-climbing robot driving over a window, damaging the window, etc. In addition, it is also necessary to obtain the conditions of the nearby walls of the wall-climbing robot in real time according to the image capture device on the wall-climbing robot, so as to adjust the driving path of the wall-climbing robot. This can not only avoid the problem of the driving path of the wall-climbing robot caused by the inaccurate image information obtained before, but also adjust the driving speed or stagnation time of the wall-climbing robot according to the real-time conditions, so as to carry out careful data collection for a longer period of time for the wall parts with complex conditions.

[0058] In addition, the step of receiving image information from a preset image capture device, determining the outer surface information of the target wall to be detected, and determining the motion trajectory information and the wall model according to the outer surface information includes: determining whether there is a historical detection digital model of the target wall to be detected in a preset database;

[0059] If not, executing the steps of receiving image information from a preset image capture device, determining outer surface information of the target wall to be detected, and determining motion trajectory information and a wall model according to the outer surface information;

[0060] If so, receive image information from a preset image capture device, determine the outer surface information of the target wall to be detected, determine the wall model based on the outer surface information and the latest historical detection digital model, and then determine the motion trajectory information based on the wall model.

[0061] Specifically, when conducting an evaluation, it is also possible to first confirm whether the wall has been quality inspected before and whether there are historical inspection digital models. If not, modeling and data collection are performed according to the normal process. If so, the historical inspection digital model is used as the main method, supplemented by the newly acquired surface information, to determine the wall model inspected at this time. When subsequently correcting and adjusting the ultrasonic model, microwave model, and radar model, simulation analysis can be performed based on the historical inspection digital model to determine the condition inside the theoretical wall and remove unreasonable areas or parts of each model to improve the accuracy of the model.

[0062] S02, controlling the acquisition device to move on the surface of the target wall to be detected according to the motion trajectory information, so that the acquisition device collects the wall information of the target wall to be detected, and obtains the wall information transmitted by the acquisition device, wherein the wall information includes ultrasonic wall information, microwave wall information, radar wall information, infrared light wall information and infrared thermal wall information;

[0063] Specifically, when a single type of collected data is used, errors are inevitable in obtaining information about the wall. Therefore, it is necessary to use different types of equipment to collect data from different dimensions on the wall and perform analysis to obtain accurate wall information, thereby enabling accurate assessment and analysis of the wall condition.

[0064] S03, determining a modified wall model according to the infrared light wall information, the infrared heat wall information and the wall model, and determining an ultrasonic wall model, a microwave wall model and a radar wall model according to the ultrasonic wall information, the microwave wall information and the radar wall information respectively;

[0065] Specifically, the step of determining and correcting the wall model according to the infrared light wall information, the infrared heat wall information and the wall model includes: determining the material distribution information of the target wall to be detected according to the infrared light wall information; determining the shallow defect information of the target wall to be detected according to the infrared heat wall information; adjusting the wall model according to the material distribution information and the shallow defect information to obtain the corrected wall model. The infrared light and infrared heat collection methods are difficult to obtain the conditions deep inside the wall, but the material distribution of the wall and shallow cracks and hollows are well obtained. Therefore, after determining the wall model through the external surface information, the wall model is adjusted through the infrared light and infrared heat information to facilitate the subsequent simulation analysis of the wall model.

[0066] S04, determining a target wall model according to the corrected wall model, the ultrasonic wall model, the microwave wall model and the radar wall model, and determining the quality of the target wall to be inspected by a preset method according to the target wall model and outputting an evaluation result;

[0067] Specifically, the step of determining the target wall model according to the modified wall model, the ultrasonic wall model, the microwave wall model and the radar wall model includes: fitting the modified wall model and the ultrasonic wall model, and correcting the fitted model according to a model library to obtain a first fitting model; fitting the modified wall model and the microwave wall model, and correcting the fitted model according to a model library to obtain a second fitting model; fitting the modified wall model and the radar wall model, and correcting the fitted model according to a model library to obtain a third fitting model; performing stress simulation on the first fitting model, the second fitting model and the third fitting model to obtain stress distribution conditions corresponding to the first fitting model, the second fitting model and the third fitting model; correcting the first fitting model, the second fitting model and the third fitting model according to the stress distribution state, and fitting the corrected first fitting model, the second fitting model and the third fitting model to obtain the target wall model. After the wall is modeled according to different data types, the modeled wall digital model and the corrected wall model are fitted, so that the properties of the fitted wall such as uniform material distribution are more in line with the actual situation, and then compared with the data in the model library to determine whether the shape, area and trend of each defect distribution in the fitted model match the theoretical situation, and then remove the unreasonable defect area to correct the digital model to obtain the fitted model. In addition, if the wall to be inspected has a historical inspection digital model, it can be simulated based on the historical inspection digital model to determine whether the current fitted wall condition can be achieved after the historical inspection digital model simulation, and then the preliminary fitting models are corrected to obtain multiple fitting models. Then fit multiple fitting models to obtain the target wall model.

[0068] Further, the step of determining the quality of the target wall to be detected by a preset method according to the target wall model and outputting the evaluation result includes: controlling the acquisition device to collect the correction area of ​​the first fitting model, the second fitting model and the third fitting model for multiple times to obtain the wall information of the correction area; determining the regional verification digital model according to the wall information of the correction area, and comparing the regional verification digital model with the corresponding area of ​​the target wall model to determine the difference, and judging whether the difference is greater than a preset threshold; if not, determining the quality of the target wall to be detected according to the condition of the target wall model and outputting the evaluation result; if so, re-inspecting the wall and correcting the target wall model, and then determining the quality of the target wall to be detected according to the corrected target wall model and outputting the evaluation result. After determining the target wall model, further verification is required to judge the accuracy of the target wall model. In order to improve efficiency, the wall climbing robot can be used to collect data of the wall in the correction area for a second time, and modeling and analysis can be performed to determine the regional digital model, and then the regional digital model can be compared with the corresponding area of ​​the target wall model for difference, so as to further ensure the accuracy of the wall detection.

[0069] In addition, the step of determining the quality of the target wall to be inspected by a preset method according to the target wall model and outputting the evaluation result includes: uploading the target wall model used to determine the quality of the target wall to be inspected to the cloud database to obtain the detection digital model, so that the cloud server determines the time node of the next required inspection of the target wall to be inspected according to all the detection digital models of the target wall to be inspected in the cloud database and the upload time corresponding to the detection digital model. By storing the detection digital model of this time, a basis and benchmark can be provided for the next inspection to improve the accuracy and quality of subsequent wall inspections. In addition, the trend of wall aging and damage can be determined through multiple historical detection digital models to adjust the time node of wall inspection to further ensure the safety of the wall.

[0070] In summary, the wall quality detection and evaluation method in the above-mentioned embodiment of the present invention obtains the outer surface information of the wall to be detected through the image capture device, and then makes a preliminary judgment on the surface condition of the wall, and divides the wall according to the surface condition of the wall, and plans the action path, so that the acquisition device can collect data on the wall with the maximum efficiency, and avoids the collection device moving on the wall to affect the collected data and the quality of the wall, and models the wall according to the outer surface information to determine the wall model, and then uses the different types of information collected by the acquisition device and the characteristics of different information, that is, infrared light information and infrared heat information, to correct the wall model to obtain a corrected model, determine the material distribution and surface crack condition of the wall model, and then according to the characteristics of microwaves, ultrasound and radar, according to these three types of information, model the target detection wall, and according to the corrected model, distinguish and determine the differences between the models, so as to adjust the model to obtain a digital model that is closest to the actual condition of the target detection wall, that is, the target wall model, and analyze the current quality of the wall to be detected according to the target wall model and output the evaluation result. Since the method collects wall information through a collection device, and obtains different types of collected information through the collection device, and converts different types of information into parameters of the same dimension for comparison and fusion, the most real and accurate information of the target wall to be detected is obtained to evaluate the quality of the target wall to be detected, thereby avoiding the errors and misjudgments of manual measurement methods, and avoiding the situation where a single type of data has large measurement errors and low measurement accuracy in wall quality detection. Therefore, the present invention solves the problem of large measurement errors and low accuracy in wall quality detection and evaluation in the prior art.

[0071] Embodiment 2

[0072] Another aspect of the present invention further provides a robot, the robot comprising: a wall climbing module, a detection module and a data processing module, wherein:

[0073] The wall climbing module is used to receive the motion trajectory information sent by the control center, and navigate according to the motion trajectory information to drive the robot to move on the wall; specifically, in actual use, an adsorption structure can be adopted to prevent the robot from falling on the wall, and the driving structure drives the wheels to move the robot on the wall. And through the navigation function, the robot is guided to move along the desired trajectory.

[0074] The detection module is used to perform ultrasonic, microwave, radar, infrared light and infrared heat detection on the wall through detection equipment; specifically, in actual use, different types of detection equipment mounted on the robot body can be used to collect information on different dimensions of the wall.

[0075] The data processing module is used to receive the detection results of the detection equipment, perform noise reduction processing on the detection results, and send the noise-reduced detection results to the control center, so that the control center determines the wall quality and evaluates it according to the detection data.

[0076] The functions or operation steps implemented when the above modules are executed are substantially the same as those in the above method embodiments, and will not be repeated here.

[0077] Embodiment 3

[0078] Another aspect of the present invention provides an electronic device, see Figure 2 , shown is a schematic diagram of an electronic device in the third embodiment of the present invention, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor, wherein the processor 10 implements the above-mentioned wall quality detection and evaluation method when executing the computer program 30.

[0079] In some embodiments, the processor 10 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 20, such as executing access restriction programs.

[0080] Among them, the memory 20 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory 20 may be an internal storage unit of an electronic device in some embodiments, such as a hard disk of the electronic device. The memory 20 may also be an external storage device of an electronic device in other embodiments, such as a plug-in hard disk equipped on the electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Further, the memory 20 may also include both an internal storage unit of the electronic device and an external storage device. The memory 20 may be used not only to store application software and various types of data of the electronic device, but also to temporarily store data that has been output or is to be output.

[0081] It should be pointed out that Figure 2 The structure shown does not constitute a limitation on the electronic device. In other embodiments, the electronic device may include fewer or more components than those shown in the figure, or combine certain components, or arrange the components differently.

[0082] The embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the wall quality detection and evaluation method as described above is implemented.

[0083] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0084] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0085] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0086] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0087] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the attached claims.

Claims

1. A wall quality detection and evaluation method, characterized in that: The method comprises: Receiving image information from a preset image capture device, determining outer surface information of a target wall to be detected, and determining motion trajectory information and a wall model according to the outer surface information; According to the motion trajectory information, the acquisition device is controlled to move on the surface of the target wall to be detected, so that the acquisition device collects the wall information of the target wall to be detected, and obtains the wall information transmitted by the acquisition device, wherein the wall information includes ultrasonic wall information, microwave wall information, radar wall information, infrared light wall information and infrared thermal wall information; Determine a modified wall model according to the infrared light wall information, the infrared heat wall information and the wall model, and respectively determine an ultrasonic wall model, a microwave wall model and a radar wall model according to the ultrasonic wall information, the microwave wall information and the radar wall information; A target wall model is determined according to the corrected wall model, the ultrasonic wall model, the microwave wall model and the radar wall model, and the quality of the target wall to be inspected is determined by a preset method according to the target wall model and an evaluation result is output.

2. The wall quality detection and evaluation method according to claim 1 is characterized in that: The step of determining and correcting the wall model according to the infrared light wall information, the infrared heat wall information and the wall model comprises: Determine the material distribution information of the target wall to be detected according to the infrared light wall information; Determine shallow defect information of the target wall to be detected according to the infrared thermal wall information; The wall model is adjusted according to the material distribution information and the shallow defect information to obtain the corrected wall model.

3. The wall quality detection and evaluation method according to claim 1 is characterized in that: The step of determining the target wall model according to the modified wall model, the ultrasonic wall model, the microwave wall model and the radar wall model comprises: Fitting the modified wall model and the ultrasonic wall model and correcting the fitted model according to the model library to obtain a first fitting model; Fitting the modified wall model and the microwave wall model and correcting the fitted model according to the model library to obtain a second fitting model; Fitting the modified wall model and the radar wall model and correcting the fitted model according to the model library to obtain a third fitting model; Perform stress simulation on the first fitting model, the second fitting model and the third fitting model to obtain stress distribution conditions corresponding to the first fitting model, the second fitting model and the third fitting model; The first fitting model, the second fitting model and the third fitting model are corrected according to the stress distribution state, and the corrected first fitting model, the second fitting model and the third fitting model are fitted to obtain the target wall model.

4. The wall quality detection and evaluation method according to claim 3 is characterized in that: The step of determining the quality of the target wall to be inspected by a preset method according to the target wall model and outputting the evaluation result comprises: Controlling the acquisition device to acquire the correction areas of the first fitting model, the second fitting model and the third fitting model for multiple times to obtain wall information of the correction areas; Determine a regional verification model according to the corrected regional wall information, compare the regional verification model with the corresponding area of ​​the target wall model to determine the difference, and determine whether the difference is greater than a preset threshold; If not, determining the quality of the target wall to be inspected according to the condition of the target wall model and outputting an evaluation result; If yes, the wall is re-inspected and the target wall model is corrected, and then the quality of the target wall to be inspected is determined based on the corrected target wall model and an evaluation result is output.

5. The wall quality detection and evaluation method according to claim 1 is characterized in that: The step of receiving image information from a preset image capture device, determining the outer surface information of the target wall to be detected, and determining the motion trajectory information and the wall model according to the outer surface information includes: Determine whether there is a historical detection digital model of the target wall to be detected in the preset database; If not, executing the steps of receiving image information from a preset image capture device, determining outer surface information of the target wall to be detected, and determining motion trajectory information and a wall model according to the outer surface information; If so, receive image information from a preset image capture device, determine the outer surface information of the target wall to be detected, determine the wall model based on the outer surface information and the latest historical detection digital model, and then determine the motion trajectory information based on the wall model.

6. The wall quality detection and evaluation method according to claim 2 is characterized in that: After the step of determining the quality of the target wall to be inspected by a preset method according to the target wall model and outputting the evaluation result, the following steps are included: The target wall model used to determine the quality of the target wall to be inspected is uploaded to the cloud database to obtain the inspection digital model, so that the cloud server determines the time node when the target wall to be inspected needs to be inspected next time according to all the inspection digital models of the target wall to be inspected in the cloud database and the upload time corresponding to the inspection digital models.

7. The wall quality detection and evaluation method according to claim 2 is characterized in that: The step of determining the motion trajectory information according to the outer surface information comprises: Dividing the target wall to be detected into regions according to the outer surface information to obtain target regions and the number of the target regions, and determining the number of the acquisition devices required according to the number of the target regions; The motion track information corresponding to the target area is determined according to the outer surface information corresponding to the target area, and the acquisition device corresponding to the target area is moved according to the motion track information corresponding to the target area.

8. The wall quality detection and evaluation method according to claim 7 is characterized in that: The step of dividing the target wall to be detected into regions according to the outer surface information to obtain the target region comprises: Determine the number of gaps, the gap area, and the gap distribution area of ​​the current outer surface of the target wall to be detected according to the outer surface information; The target wall to be detected is divided into regions according to the number of gaps, the gap area, the gap distribution area, and the collection efficiency and moving speed of the collection device, so that the collection time required by each collection device is consistent and the collection time is less than a preset time.

9. The wall quality detection and evaluation method according to claim 7, characterized in that: The real-time external surface information transmitted by the acquisition device when it moves in the target area is acquired, and the movement track information of the acquisition device is adjusted according to the real-time external surface information.

10. A robot, characterized in that: Used to implement the wall quality detection and evaluation method according to any one of claims 1 to 9, the robot comprises: A wall climbing module, used for receiving the motion trajectory information sent by the control center, and navigating according to the motion trajectory information to drive the robot to move on the wall; A detection module, used for performing ultrasonic, microwave, radar, infrared light and infrared heat detection on the wall through detection equipment; The data processing module is used to receive the detection results of the detection equipment, perform noise reduction processing on the detection results, and send the noise-reduced detection results to the control center, so that the control center determines the wall quality and evaluates it according to the detection data.

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