CN219551815U - Bridge support real-time monitoring system combining inspection and classical inspection - Google Patents

Abstract

The utility model discloses a real-time monitoring system of a bridge support combining inspection and classical inspection, wherein the real-time monitoring system of the bridge support combining inspection and classical inspection comprises an intelligent support unit, a bridge inspection crawling robot and a regular inspection unmanned plane; the intelligent support unit is used for long-term monitoring; the bridge detection crawling robot is used for classical detection of problems; the regular inspection unmanned aerial vehicle is used for regular inspection. According to the utility model, the appearance of the bridge support is photographed by using the unmanned aerial vehicle carried camera platform, and the appearance evaluation data is obtained through image processing analysis. Although other methods are available for shooting bridge images by using unmanned aerial vehicles to obtain surface cracks of the support, the bridge support belongs to a bridge substructure, and the problems of weak GPS signals, narrow space and the like exist, so that the flight safety of the unmanned aerial vehicle is at risk. Bridge monitoring robot that crawls pastes in bridge floor lower part and crawls, and close range wireless transmission signal is more stable, and information is more timely more accurate.

Description

Bridge support real-time monitoring system combining inspection and classical inspection

Technical Field

The utility model relates to bridge monitoring technology, in particular to a real-time monitoring system for a bridge support combining inspection and typical inspection.

Background

At present, in the bridge engineering construction process, the support belongs to an important component part of a bridge lower structure, and the safety condition of the support directly influences the structural safety and stability of the bridge. The damage and destruction of bridge supports have become one of the main diseases of active bridges in China. Typical diseases are shown as local void, shearing deformation overrun, rubber surface cracking and uneven bulging deformation, and various diseases have great influence on the stability and safety of the support and the health of the whole bridge, and must be prevented and treated. However, the proportion of the support in bridge engineering cost is small, so that the support is often not paid attention to engineering technicians and management staff, and the support is very easy to be a weak link of a bridge structure in the use process.

The regular manual detection is a common means for obtaining the health condition of the bridge support, but because of the concealment of the installation position of the bridge support, the reserved position of the support is smaller, the light is dim, and the support is difficult to accurately observe by staff, so that great errors exist compared with the actual results. For some bridges crossing rivers and bridge piers and needing to use equipment such as bridge inspection vehicles, the cost is high, so that the manual inspection method has the defects of difficult inspection, high cost, subjective damage degree judgment, incapability of early warning and the like.

At present, an intelligent support with real-time monitoring is mainly used for monitoring stress conditions of the support through arrangement of various sensors, data transmission and processing, but cannot be used for effectively monitoring apparent diseases of the support and conditions of surrounding environments of the support, such as the problems of surface crack conditions of the support, whether the support deflects, whether the support is rusted, whether supporting filler stones accumulate water, whether building left garbage accumulation exists and the like. Therefore, the bridge support monitoring system with remote real-time monitoring and early warning functions is developed by combining the unmanned aerial vehicle or the bridge detection crawling robot to carry out apparent disease detection, so that the real-time monitoring of the internal stress of the support and the effective detection of the apparent diseases are realized, the health condition and the potential risk of the support in service and the bridge are timely controlled, and the bridge support monitoring system has obvious economic value in guaranteeing the health of the bridge and prolonging the service life of the bridge.

Disclosure of Invention

Aiming at the technical problems, the utility model provides a bridge support real-time monitoring system combining inspection and typical inspection.

The technical scheme adopted by the utility model is as follows:

a bridge support real-time monitoring system combining inspection and classical inspection comprises an intelligent support unit, a bridge inspection crawling robot and a regular inspection unmanned plane;

the intelligent support unit is used for long-term monitoring;

the bridge detection crawling robot is used for classical detection of problems;

the regular inspection unmanned aerial vehicle is used for regular inspection.

Further, the intelligent support unit comprises an upper top plate, a stainless steel plate, a polytetrafluoroethylene sliding plate, a middle steel plate, a rubber block, a lower bottom basin and a fiber bragg grating strain sensor element group;

the upper top plate, the stainless steel plate, the polytetrafluoroethylene sliding plate, the middle steel plate and the rubber block are arranged in the lower bottom basin; a groove is formed in the contact part of the inner side wall of the bottom basin and the rubber block, an optical fiber grating strain sensor element group is fixed in the groove through bolts, and the sensor is connected with an external optical fiber through a wire penetrating through the bottom basin.

Further, the bridge detection crawling robot mainly comprises a robot main body, a pitching joint, a yawing joint, a camera, a moving leg and a sucker structure;

the robot main body structure comprises a circuit board, a singlechip, a power supply and a vacuum generating device;

the camera is connected and controlled by a control circuit;

four moving legs are symmetrically arranged on the left side and the right side of the main body of the robot and are symmetrically distributed relative to the machine body, three driving servo motors are arranged on the legs of each moving leg, the driving servo motors are controlled by a singlechip, and the feet of each moving leg are provided with a vacuum chuck structure;

the thigh and the trunk of each moving leg are provided with a driving servo motor, and the rotation in a vertical plane is realized by controlling the servo motor, so that the falling and lifting functions of the leg joints are controlled;

a driving servo motor is arranged between the thigh and the shank of each movement leg and is responsible for finishing the up-and-down movement of the sole in the horizontal plane, so as to realize the forward-and-backward movement of the sole on the contact surface;

the foot of each movement leg is provided with a driving servo motor which is responsible for the adsorption and desorption work of the electromagnetic device on the contact surface, and the suction disc structure generates suction force which can bear the weight of the robot and the weight of detection equipment and other instruments carried on the robot;

two driving motors of a pitching joint and a yawing joint are added in the middle area of the trunk of the robot main body.

Further, the control system of the bridge detection crawling robot mainly comprises an upper computer man-machine interaction system and a lower computer control system;

the upper computer human-computer interaction system is responsible for completing monitoring of the bridge detection crawling robot, and real-time communication transmission with the lower computer control system is realized through the wireless communication module, so that an operator can realize remote control of the robot through wireless communication;

the lower computer control system is responsible for executing task commands sent by the upper computer, controlling the robot to complete the tasks of moving, traversing and shooting, and transmitting the internal and external environment state data of the robot acquired by the sensor in real time to the upper computer;

the lower computer control system mainly comprises a central control module, a wireless communication module, a servo motor, a motion mechanism module, an adsorption mechanism module, a sensor detection module and a power supply module;

the control system hardware circuit mainly comprises a central control module, a wireless communication module, a steering engine movement mechanism module, an adsorption mechanism module, a sensor detection module and a power supply module; the hardware function of the robot is mainly realized through a central control module to communicate with an upper computer on the ground, an instruction transmitted by the upper computer is executed, data acquired by a camera and other sensors are uploaded, and a picture set for training a neural network is increased through image processing; dividing the acquired bridge bearing disease photo into a training set and a testing set; building a convolutional neural network to obtain a neural network model with the function of automatically identifying bridge bearing diseases; and (5) whether the support is cracked or not is mastered, and the size of the crack and the degree of the crack are calculated.

Still further, the regular inspection unmanned aerial vehicle mainly comprises an unmanned aerial vehicle rotor wing, a forward distance sensing module, a camera cradle head, a high-definition photogrammetry camera, a left distance sensing module, a micro GPS positioning navigation module, a backward distance sensing module, a right distance sensing module and a top distance sensing module;

the high-definition photogrammetry camera is a high-definition camera for collecting support image data and is arranged at the top of the unmanned aerial vehicle body in a rotary cradle head mode, and multi-angle photos of the bridge support structure and the surrounding environment are shot at multiple angles;

the miniature GPS positioning navigation module is arranged at the top of the unmanned aerial vehicle body and is used for determining heading and position information of the unmanned aerial vehicle in the operation process so as to realize accurate positioning;

the forward direction sensing module, the left side distance sensing module, the backward direction distance sensing module, the right side distance sensing module and the top distance sensing module are laser ranging sensors, obstacle in different directions are detected respectively, distance information between the obstacle and the unmanned aerial vehicle is transmitted back to the power device and the flight control system for processing through the signal transmission system in real time, a real-time flight path is obtained, and the flight path of the unmanned aerial vehicle is commanded;

the unmanned aerial vehicle is provided with a signal transmission and communication module which is used for receiving the processed state data and the image data transmitted by the processor, transmitting the processed state data and the processed image data to the ground receiving station and carrying out subsequent manual inspection.

The utility model has the advantages that:

the utility model recognizes the cracking and the crack of the bridge support, utilizes the bridge detection crawling robot to adsorb the structural surface at the position of the disease, collects the disease image and the damage information inside the disease surface, and directly obtains the geometric information of the disease through the analysis of the cyclic neural network. For the problems of corrosion and garbage accumulation of the appearance of the support, the appearance of the bridge support is photographed by using an unmanned aerial vehicle-mounted camera platform, and appearance evaluation data are obtained through image processing analysis. Although other methods are available for shooting bridge images by using unmanned aerial vehicles to obtain surface cracks of the support, the bridge support belongs to a bridge substructure, and the problems of weak GPS signals, narrow space and the like exist, so that the flight safety of the unmanned aerial vehicle is at risk. Bridge monitoring robot that crawls pastes in bridge floor lower part and crawls, and close range wireless transmission signal is more stable, and information is more timely more accurate. Therefore, the periodic apparent inspection and typical inspection of key support cracks of the support, which are realized by utilizing the characteristics of the support and the key support, are more reasonable, and the state and structure detection and evaluation of the bridge support are further realized.

In addition to the objects, features and advantages described above, the present utility model has other objects, features and advantages. The present utility model will be described in further detail with reference to the drawings.

Drawings

The accompanying drawings, which are included to provide a further understanding of the utility model and are incorporated in and constitute a part of this specification, illustrate embodiments of the utility model and together with the description serve to explain the utility model.

FIG. 1 is a flow chart of real-time monitoring of a bridge bearing in combination with periodic inspection and typical inspection;

FIG. 2 is a block diagram of an intelligent support unit of the present utility model;

FIG. 3 is a block diagram of a bridge inspection crawling robot of the present utility model;

FIG. 4 is a diagram of a bridge inspection robot control system according to the present utility model;

FIG. 5 is a pin diagram of a master control CPUSTM32 control board of the bridge inspection robot control system of the present utility model;

fig. 6 is a schematic structural diagram of an unmanned aerial vehicle for periodic inspection of bridges.

Reference numerals:

21 is an upper top plate of a support, 22 is a stainless steel plate, 23 is a polytetrafluoroethylene plate, 24 is a middle rigid lining plate, 25 is a rubber bearing plate, 26 is a lower bottom basin of the support, and 27 is a fiber grating strain sensor element group; 31 is a robot main body, 32 is a pitching joint, 33 is a yawing joint, 34 is a camera, 35 is a moving leg and 36 is a sucker structure; the unmanned aerial vehicle rotor wing is 61, 62 is forward distance perception module, 63 camera cloud platform, 64 are high definition photogrammetry camera, 65 are left side distance perception module, 66 are unmanned aerial vehicle fuselage, 67 are miniature GPS location navigation module, 68 are backward distance perception module, 69 are right side distance perception module, 610 are top distance perception module.

Detailed Description

The present utility model will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present utility model more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the utility model.

Referring to fig. 1 to 6

A bridge support real-time monitoring system combining inspection and classical inspection comprises an intelligent support unit, a bridge inspection crawling robot and a regular inspection unmanned plane;

the intelligent support unit is used for long-term monitoring;

the bridge detection crawling robot is used for classical detection of problems;

the regular inspection unmanned aerial vehicle is used for regular inspection.

The intelligent support unit comprises an upper top plate 21, a stainless steel plate 22, a polytetrafluoroethylene sliding plate 23, a middle steel plate 24, a rubber block 25, a lower bottom basin 26 and a fiber grating strain sensor element group 27;

the upper top plate 21, the stainless steel plate 22, the polytetrafluoroethylene sliding plate 23, the middle steel plate 24 and the rubber block 25 are placed in the lower bottom basin 26, grooves are formed in the contact positions of the inner side wall of the bottom basin and the rubber plate, a fiber bragg grating strain sensor element group 27 is fixed in the grooves through bolts, and the sensor is connected with an external optical fiber through a wire penetrating through the bottom basin.

The bridge detection crawling robot mainly comprises a robot main body 31, a pitching joint 32, a yawing joint 33, a camera 34, a moving leg 35 and a sucker structure 36;

the robot main body 31 comprises a circuit board, a singlechip, a power supply and a vacuum generating device;

the camera 34 is controlled by a control circuit;

four moving legs 35 are symmetrically arranged on the left side and the right side of the main body 31 of the robot and are symmetrically distributed relative to the machine body, three driving servo motors are arranged on the leg parts of each moving leg 35, the driving servo motors are controlled by a singlechip, and the foot parts of each moving leg are provided with a vacuum chuck structure 36;

a driving servo motor is arranged at the thigh and trunk position of each moving leg 35, and the rotation in a vertical plane is realized by controlling the servo motor, so that the falling and lifting functions of leg joints are controlled;

a driving servo motor is arranged between the thigh and the shank of each movement leg 35 and is responsible for finishing the up-and-down movement of the sole in the horizontal plane, so as to realize the forward-and-backward movement of the sole on the contact surface;

the foot of each motion leg 35 is provided with a driving servo motor which is responsible for the adsorption and desorption work of the electromagnetic device on the contact surface, and the suction disc structure 36 generates suction force which can bear the weight of the robot and the weight of detection equipment and other instruments carried on the robot;

two driving motors of a pitch joint 32 and a yaw joint 33 are added in the middle area of the trunk of the robot main body 31.

The control system of the bridge detection crawling robot mainly comprises an upper computer man-machine interaction system and a lower computer control system;

the upper computer human-computer interaction system is responsible for completing monitoring of the bridge detection crawling robot, and real-time communication transmission with the lower computer control system is realized through the wireless communication module, so that an operator can realize remote control of the robot through wireless communication;

the lower computer control system is responsible for executing task commands sent by the upper computer, controlling the robot to complete the tasks of moving, traversing and shooting, and transmitting the internal and external environment state data of the robot acquired by the sensor in real time to the upper computer;

the lower computer control system mainly comprises a central control module, a wireless communication module, a servo motor, a motion mechanism module, an adsorption mechanism module, a sensor detection module and a power supply module;

the control system hardware circuit mainly comprises a central control module, a wireless communication module, a steering engine movement mechanism module, an adsorption mechanism module, a sensor detection module and a power supply module; the hardware function of the robot is mainly realized through a central control module to communicate with an upper computer on the ground, an instruction transmitted by the upper computer is executed, data acquired by a camera and other sensors are uploaded, and a picture set for training a neural network is increased through image processing; dividing the acquired bridge bearing disease photo into a training set and a testing set; building a convolutional neural network to obtain a neural network model with the function of automatically identifying bridge bearing diseases; and (5) whether the support is cracked or not is mastered, and the size of the crack and the degree of the crack are calculated.

The regular inspection unmanned aerial vehicle mainly comprises an unmanned aerial vehicle rotor 61, a forward distance sensing module 62, a camera cradle head 63, a high-definition photogrammetry camera 64, a left distance sensing module 65, a micro GPS positioning navigation module 67, a backward distance sensing module 68, a right distance sensing module 69 and a top distance sensing module 610;

the high-definition photogrammetry camera 64 is a high-definition camera for collecting support image data, is arranged at the top of the unmanned aerial vehicle body in a rotary cradle head mode, and is used for shooting multi-view photos of the bridge support structure and the surrounding environment at multiple angles;

the miniature GPS positioning navigation module 67 is arranged at the top of the unmanned aerial vehicle body and is used for determining heading and position information of the unmanned aerial vehicle in the operation process so as to realize accurate positioning;

the forward sensing module 62, the left distance sensing module 65, the backward distance sensing module 68, the right distance sensing module 69 and the top distance sensing module 610 are laser ranging sensors, respectively detect obstacles in different directions, transmit distance information between the obstacles and the unmanned aerial vehicle back to the power device and the flight control system for processing through the signal transmission system in real time, acquire a real-time flight path and command the flight path of the unmanned aerial vehicle;

the unmanned aerial vehicle is provided with a signal transmission and communication module which is used for receiving the processed state data and the image data transmitted by the processor, transmitting the processed state data and the processed image data to the ground receiving station and carrying out subsequent manual inspection.

A bridge support real-time monitoring method combining inspection and classical inspection comprises the following steps:

the intelligent support unit is an intelligent basin-type rubber support, the intelligent basin-type rubber support is used for acquiring pressure signals of the support based on an optical fiber grating sensor, when the support is subjected to vertical bearing capacity, the optical fiber grating can accurately sense pressure load change, the pressure load change is transmitted to a demodulator and displayed through output pressure wavelength signals, the demodulator is connected with a wireless router, pressure load data are transmitted to an Internet terminal in a wireless mode, terminal equipment receives the data, analyzes and processes the data, visually displays actual load of the support and compares the actual load with normal use load of the support, calculates a risk coefficient, and if the risk coefficient reaches a limit value, the risk coefficient is immediately transmitted to a bridge operation and maintenance center, the bridge operation and maintenance center is manually confirmed, and the support is subjected to next step problem classical investigation;

when the stress load of the bridge support reaches a risk limit, after the bridge operation and maintenance center confirms, starting the classical checking of the problems, and carrying out fine detection on the local details and cracks of the support by using a bridge detection crawling robot;

the bridge detection crawling robot is used for simulating that a gecko climbs over a wall to check the displacement condition of a crack of a support at the lower part of a bridge by utilizing a bionics principle, and comprises a mechanical structure platform, a vision system and a control system;

the visual system is loaded on the mechanical connecting structure platform and used for detecting appearance details of close-range cracks, void and displacement of the bridge support, and the control system is used for remotely controlling the mechanical platform and the visual system to work; the bridge detection crawling robot mainly comprises 4 legs and a machine body, wherein the 4 legs are symmetrically distributed relative to the machine body and have basically identical structural design, each leg is provided with three driving servo motors, and foot parts are provided with sucking disc sucking mechanisms to realize the wall climbing and external right-angle transitional movement of the robot;

the pitch and yaw joint drives are added in the middle area of the trunk, so that the working space of the robot when climbing on the transition surface is increased;

the hardware function of the bridge detection crawling robot is mainly realized through a central control module, communication with an upper computer on the ground is realized, instructions transmitted by the upper computer are executed, data acquired by a camera and other sensors are uploaded, and a picture set for training a neural network is increased through image processing; dividing the acquired bridge bearing disease photo into a training set and a testing set; building a convolutional neural network to obtain a neural network model with the function of automatically identifying bridge bearing diseases; whether the support is cracked or not is mastered, the crack size and the degree of the crack are calculated, and the support is required to be replaced when the limit value is reached;

unmanned aerial vehicle regularly patrols and examines: the method comprises the steps that a high-definition camera is arranged at the top of an unmanned aerial vehicle in a rotary cradle head mode, detection sensing devices such as a GPS and a range finder are installed, multi-angle rotation is carried out to shoot multi-view photos of a bridge support structure and surrounding environment, and the appearance of the lower part of a bridge and the support is comprehensively, efficiently and rapidly detected; and a signal transmission and communication module is arranged on the unmanned aerial vehicle, the processed apparent state data and image data of the support are remotely transmitted to a ground receiving station, after the receiving station receives the data and the image, relevant management personnel check and judge whether the support is rusted, the support is watered and whether building left-behind garbage is accumulated or not in a visual interpretation mode, and the workers are arranged to clean and maintain according to actual conditions.

Referring to fig. 2, the intelligent support unit provided by the utility model has the function of monitoring the load data condition and the health state of the bridge support.

The intelligent support monitoring system mainly comprises an intelligent support unit, a data acquisition unit, a data transmission unit and a power supply system unit. The intelligent basin-type rubber support for the bridge realizes acquisition of pressure signals of the support by using the fiber bragg grating sensor. The intelligent support unit mainly comprises a support upper top plate 21, a stainless steel plate 22, a polytetrafluoroethylene plate 23, a middle rigid lining plate 24, a rubber bearing plate 25, a support lower bottom basin 26 and a fiber grating strain sensor element group 27. Wherein, the upper top plate 21, the stainless steel plate 22, the polytetrafluoroethylene sliding plate 23, the middle steel plate 24 and the rubber block 25 of the support are arranged in the lower bottom basin 26; a groove is formed in the contact part of the inner side wall of the bottom basin and the rubber block, a fiber bragg grating strain sensor element group 27 is fixed in the groove through bolts, and the sensor is connected with an external optical fiber through a wire penetrating through the bottom basin. Adjacent intelligent support units form a fiber grating network through an optical cable, all monitoring lines are connected in series through an optical fiber to be connected with a fiber grating demodulator at the periphery of the support, the fiber grating demodulator is directly connected with a wireless router, remote transmission is realized through the wireless network and sent to terminal equipment, the fiber grating demodulator and a data transmission unit are respectively connected with a UPS (uninterrupted Power supply), and each bridge shares a fiber grating local area network.

When the support receives vertical bearing capacity, the fiber bragg grating combination module can accurately sense the stress change of the load borne by the pressing support, convert the stress change into fiber bragg grating wavelength signals, transmit the fiber bragg grating wavelength signals to the fiber bragg grating demodulator, the demodulator is directly connected with the wireless router, the support stress data monitored by the fiber bragg grating sensor is transmitted to the internet terminal through the wireless, the terminal equipment receives the data, analyzes and processes the data, visually displays the actual load of the support and compares the actual load with the normal use load of the support, meanwhile, the data acquisition technology is combined, automation of data acquisition, analysis and storage and the like is realized, alarming is carried out when abnormality occurs, and the remote monitoring of the support load is realized.

Bridge detection crawling robot

Referring to fig. 3, a mechanical structure diagram of the gecko-like bridge detection crawling robot is shown. The bridge detection crawling robot takes a singlechip as a control core, and realizes the movement of the crawling robot on the wall surface of the bridge pier. The bridge detection crawling robot mainly comprises a robot main body 31, a pitching joint 32, a yawing joint 33, a camera 34, a moving leg 35 and a sucker structure 36. The robot main body 31 comprises a circuit board, a singlechip, a power supply and a vacuum generating device, and the camera 34 is connected and controlled by a control circuit. Four moving legs 35 are symmetrically arranged on the left side and the right side of the main body 31 of the robot, are symmetrically distributed relative to the machine body, are basically completely consistent in structural design, are provided with three driving servo motors, the driving servo motors are controlled by a single chip microcomputer, and the foot parts of the moving legs are provided with vacuum chuck structures 36. A driving servo motor is arranged at the thigh and trunk position of each moving leg 35, and the rotation in a vertical plane is realized by controlling the servo motor, so that the falling and lifting functions of leg joints are controlled; a driving servo motor is arranged between the thigh and the shank of each movement leg 35 and is responsible for finishing the up-and-down movement of the sole in the horizontal plane, so as to realize the forward-and-backward movement of the sole on the contact surface; the foot of each moving leg 35 is provided with a driving servo motor which is responsible for the adsorption and desorption work of the electromagnetic device on the contact surface, and the suction disc structure 36 generates suction force which can bear the weight of the robot and the weight of detection equipment and other instruments carried on the robot. In addition, two driving motors of a pitch joint 32 and a yaw joint 33 are added in the middle area of the trunk of the robot main body 31, so that the degree of freedom of the waist joint of the robot is increased to two, the working space of the robot during climbing on a transition surface is increased, and the flexibility of the robot during movement is improved. The motion leg of the bridge detection crawling robot adopts an aluminum alloy material, other parts adopt engineering plastics, the whole weight is lighter, the firmness of the structure and the compactness of wall surface adsorption can be ensured, and falling off in the operation process is prevented.

Referring to fig. 4, a control system diagram of a gecko-like bridge detection crawling robot is shown. The control system of the gecko-like bridge detection robot mainly comprises an upper computer man-machine interaction system and a lower computer control system. The upper computer human-computer interaction system is responsible for completing monitoring of the bridge detection crawling robot, and real-time communication transmission with the lower computer control system is realized through the wireless communication module, so that an operator can realize remote control of the robot through wireless communication; the lower computer control system is responsible for executing task commands sent by the upper computer, controlling the robot to complete tasks such as moving, turning over and shooting, and transmitting the internal and external environment state data of the robot acquired by the sensor in real time to the upper computer. The lower computer control system mainly comprises a central control module (singlechip), a wireless communication module, a servo motor and a motion mechanism module, an adsorption mechanism module, a sensor detection module, a power supply module and the like. The central control module (singlechip) selects STM32F103ZET chip. The bridge detection crawling robot realizes communication with an upper computer on the ground through a central processing unit (single chip microcomputer), executes instructions transmitted by the upper computer, and uploads data acquired by the camera and other bridge sensors; the central processing unit (singlechip) controls the structure comprising 14 driving servo motors and 4 sucking discs to finish wall climbing, external right angle transitional movement and the like of the robot. The bridge detection crawling robot adopts Bluetooth positioning to solve the problem that GPS signals of a bridge substructure cannot be received. The power supply module adopts a lithium battery, performs voltage reduction treatment through an internal voltage conversion circuit, and supplies the voltage reduction treatment to corresponding circuit devices.

The STM32F103ZET pin of the central control module (singlechip) is connected with external equipment, so that the functions of communicating with the outside, controlling the outside hardware or collecting the outside hardware data can be realized. The detailed circuit pin diagram of the STM32F103ZET control board is shown in fig. 5, 11I/O ports of the STM32F103ZET are used as PWM output to control the rotation angles of 11 driving servo motors, and control signals output by 4I/O ports are used as sole adsorption force control ports to control adsorption and release of sole suction cups. The data acquisition of 4 pressure sensors and 1 infrared sensor takes up 5 ADC interfaces. The SPI serial port of the controller is externally connected with a WIFI/Bluetooth module and is responsible for communication with an upper computer to exchange data.

Unmanned aerial vehicle is patrolled and examined regularly

Referring to fig. 5, a schematic structural diagram of an unmanned aerial vehicle for periodic inspection of bridge supports is shown. The regular inspection unmanned aerial vehicle mainly comprises unmanned aerial vehicle rotor 61, forward direction distance perception module 62, camera cloud platform 63, high definition photogrammetry camera 64, left side distance perception module 65, miniature GPS location navigation module 67, backward direction distance perception module 68, right side distance perception module 69 and top distance perception module 610. The high-definition photogrammetry camera 64 is a high-definition camera for collecting support image data, is arranged at the top of the unmanned aerial vehicle body in a rotary cradle head mode, can shoot multi-view photos of bridge support structures and surrounding environments at multiple angles, effectively solves the problems of view angle deviation, dead angle, blurring and the like when visual interpretation detection is carried out from a single photo, and remarkably improves the accuracy and efficiency of bridge detection. The micro GPS positioning navigation module 67 is arranged at the top of the unmanned aerial vehicle body and used for determining information such as heading and position of the unmanned aerial vehicle in the operation process, and accurate positioning is achieved. The forward sensing module 62, the left distance sensing module 65, the backward distance sensing module 68, the right distance sensing module 69 and the top distance sensing module 610 are laser ranging sensors, detect obstacles in different directions respectively, ensure that the unmanned aerial vehicle keeps a safe distance with a bridge, and transmit distance information between the obstacles and the unmanned aerial vehicle back to a power device and a flight control system for processing through a signal transmission system in real time, so that a real-time flight path is obtained, and the flight path of the unmanned aerial vehicle is commanded. The unmanned aerial vehicle is provided with a signal transmission and communication module which is used for receiving the processed state data and the image data transmitted by the processor, transmitting the processed state data and the processed image data to the ground receiving station and carrying out subsequent manual inspection.

The utility model comprises the following steps:

intelligent support monitoring system

The intelligent support monitoring system has the function of remotely monitoring the stress load data and the health state of the bridge support, and mainly comprises an intelligent support unit, a data acquisition unit, a data transmission unit and a power supply system unit. The intelligent support unit is an intelligent basin-type rubber support, the intelligent basin-type rubber support is used for acquiring support pressure signals based on the fiber bragg grating sensor, when the support is subjected to vertical bearing capacity, the fiber bragg grating can accurately sense pressure load changes, the pressure load changes are transmitted to the demodulator and displayed through output pressure wavelength signals, the demodulator is connected with the wireless router, pressure load data are transmitted to the internet terminal in a wireless mode, terminal equipment receives data, analyzes and processes the data, visually displays actual load of the support, compares the actual load with normal use load of the support, calculates risk coefficients, and if the risk coefficients reach limit values, immediately sends the risk coefficients to a bridge operation and maintenance center, and the bridge operation and maintenance center performs manual confirmation to conduct next-step classical problem checking on the support.

When the stressed load of the bridge support reaches the risk limit in the step S10, after the stressed load is confirmed by the bridge operation and maintenance center, the classical inspection of the problem is started, and the bridge inspection crawling robot is utilized to carry out fine inspection on the local details and cracks of the support.

The bridge detection crawling robot provided by the utility model utilizes a bionics principle to simulate the situation that a gecko climbs over a wall to shift a crack of a support at the lower part of a bridge, and consists of a mechanical structure platform, a vision system and a control system, wherein the vision system is loaded on the mechanical structure platform and is used for detecting appearance details such as close-range crack, void, shift and the like of the bridge support, and the control system is used for remotely controlling the mechanical platform and the vision system to work. The bridge detection crawling robot mainly comprises 4 legs and a machine body, wherein the 4 legs are symmetrically distributed relative to the machine body and have basically identical structural design, each leg is provided with three driving servo motors, and foot parts are provided with sucking disc sucking mechanisms to realize wall climbing, external right angle transitional movement and the like of the robot. In addition, in order to meet the requirements of wall transition, pitch and yaw joint drives are added in the middle area of the trunk, so that the working space of the robot when the robot climbs on the transition surface is increased, and the flexibility in the movement process of the robot is improved.

The control system hardware circuit mainly comprises a central control module, a wireless communication module, a steering engine movement mechanism module, an adsorption mechanism module, a sensor detection module, a power module and the like. The hardware function of the robot is mainly realized through a central control module to communicate with an upper computer on the ground, an instruction transmitted by the upper computer is executed, data acquired by a camera and other sensors are uploaded, and a picture set for training a neural network is increased through image processing; dividing the acquired bridge bearing disease photo into a training set and a testing set; and building a convolutional neural network to obtain a neural network model with the function of automatically identifying the bridge bearing diseases. And (3) whether the support is cracked or not is mastered, the size of the crack and the degree of the crack are calculated, and the support is required to be replaced when the limit value is reached.

Unmanned aerial vehicle regularly patrols and examines.

High-definition cameras are arranged at the top of the unmanned aerial vehicle in a rotary cradle head mode, detection sensing equipment such as a GPS (global positioning system) and a range finder are installed, multi-angle rotation is used for shooting multi-view photos of a bridge support structure and surrounding environment, and comprehensive, efficient and rapid detection is carried out on the appearance of the lower portion of a bridge and the support. And a signal transmission and communication module is arranged on the unmanned aerial vehicle, the processed apparent state data and image data of the support are remotely transmitted to a ground receiving station, after the receiving station receives the data and the image, relevant management personnel check and judge whether the support is rusted, the support is watered and whether construction left-behind garbage is accumulated or not in a visual interpretation mode, and the like, and arrange workers to clean and maintain according to actual conditions.

The utility model provides a real-time monitoring system for a bridge support, which combines inspection and classical inspection. Aiming at long-term monitoring of the support, the intelligent support monitoring system is built by combining the internet of things technology, the sensor technology and the data transmission and processing technology, so that the stress condition of the support can be observed in real time. When the risk coefficient of the support reaches the limit value, the problem is checked typically, the bridge detection crawling robot is used as a working platform, an optical camera is carried to carry out omnibearing photographing and detection on the problem support in a narrow space, the acquired support crack picture is subjected to image processing, and the damage level is identified through a neural network. Meanwhile, setting up periodic inspection, utilizing unmanned aerial vehicle to carry the platform of making a video recording to open automatically to inspect the bridge outward appearance, acquire support apparent and surrounding macroscopic situation fast, judge whether there are support corrosion, support filler ponding and building and leave over the rubbish and pile up scheduling problem.

The utility model utilizes the intelligent support to monitor the stress condition of the key support in real time, utilizes the bridge detection crawling robot to conduct classical detection on the problem support, utilizes the unmanned aerial vehicle to conduct inspection, and then conducts bridge support damage grade assessment according to the monitoring and detection data obtained by the intelligent support, the intelligent support and the crawling robot.

The utility model utilizes a bridge detection crawling robot to adsorb the structural surface at the position of the disease, collects the disease image and the damage information inside the disease surface, and directly obtains the geometric information of the disease through the analysis of a cyclic neural network.

For the problems of corrosion and garbage accumulation of the appearance of the support, the appearance of the bridge support is photographed by using an unmanned aerial vehicle-mounted camera platform, and appearance evaluation data are obtained through image processing analysis. Although other methods are available for shooting bridge images by using unmanned aerial vehicles to obtain surface cracks of the support, the bridge support belongs to a bridge substructure, and the problems of weak GPS signals, narrow space and the like exist, so that the flight safety of the unmanned aerial vehicle is at risk.

Bridge monitoring robot that crawls pastes in bridge floor lower part and crawls, and close range wireless transmission signal is more stable, and information is more timely more accurate. Therefore, the periodic apparent inspection and typical inspection of key support cracks of the support, which are realized by utilizing the characteristics of the support and the key support, are more reasonable, and the state and structure detection and evaluation of the bridge support are further realized.

The foregoing description of the preferred embodiments of the utility model is not intended to limit the utility model to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the utility model are intended to be included within the scope of the utility model.

Claims (1)

1. A real-time monitoring system for bridge supports combining inspection and classical inspection is characterized in that,

the intelligent support unit, the bridge detection crawling robot and the regular inspection unmanned aerial vehicle are included;

the intelligent support unit is used for long-term monitoring;

the bridge detection crawling robot is used for classical detection of problems;

the regular inspection unmanned aerial vehicle is used for regular inspection;

the intelligent support unit comprises an upper top plate (21), a stainless steel plate (22), a polytetrafluoroethylene sliding plate (23), a middle steel plate (24), a rubber block (25), a lower bottom basin (26) and a fiber bragg grating strain sensor element group (27);

the upper top plate (21), the stainless steel plate (22), the polytetrafluoroethylene sliding plate (23), the middle steel plate (24) and the rubber block (25) are arranged in the lower bottom basin (26); a groove is formed in the contact part of the inner side wall of the bottom basin and the rubber block (25), a fiber bragg grating strain sensor element group (27) is fixed in the groove through bolts, and the sensor is connected with an external optical fiber through a lead penetrating through the bottom basin;

the bridge detection crawling robot mainly comprises a robot main body (31), a pitching joint (32), a yawing joint (33), a camera (34), moving legs (35) and a sucker structure (36);

the robot main body (31) structurally comprises a circuit board, a singlechip, a power supply and a vacuum generating device;

the camera (34) is connected and controlled by a control circuit;

four moving legs (35) are symmetrically arranged on the left side and the right side of a main body (31) of the robot and are symmetrically distributed relative to the machine body, three driving servo motors are arranged on the leg parts of each moving leg (35), the driving servo motors are controlled by a single chip microcomputer, and the foot parts of each moving leg are provided with vacuum chuck structures (36);

a driving servo motor is arranged at the thigh and trunk position of each movement leg (35), and the rotation in a vertical plane is realized by controlling the servo motor, so that the falling and lifting functions of leg joints are controlled;

a driving servo motor is arranged between the thigh and the shank of each movement leg (35) and is responsible for finishing the up-and-down movement of the sole in the horizontal plane so as to realize the forward-and-backward movement of the sole on the contact surface;

the foot of each motion leg (35) is provided with a driving servo motor which is responsible for the adsorption and desorption work of the electromagnetic device on the contact surface, and the suction disc structure (36) generates suction force which can bear the weight of the robot and the weight of detection equipment and other instruments carried on the robot;

two driving motors of a pitch joint (32) and a yaw joint (33) are added in the middle area of the trunk of the robot main body (31);

the control system of the bridge detection crawling robot mainly comprises an upper computer man-machine interaction system and a lower computer control system;

the upper computer human-computer interaction system is responsible for completing monitoring of the bridge detection crawling robot, and real-time communication transmission with the lower computer control system is realized through the wireless communication module, so that an operator can realize remote control of the robot through wireless communication;

the lower computer control system is responsible for executing task commands sent by the upper computer, controlling the robot to complete the tasks of moving, traversing and shooting, and transmitting the internal and external environment state data of the robot acquired by the sensor in real time to the upper computer;

the lower computer control system mainly comprises a central control module, a wireless communication module, a servo motor, a motion mechanism module, an adsorption mechanism module, a sensor detection module and a power supply module;

the control system hardware circuit mainly comprises a central control module, a wireless communication module, a steering engine movement mechanism module, an adsorption mechanism module, a sensor detection module and a power supply module;

the regular inspection unmanned aerial vehicle mainly comprises an unmanned aerial vehicle rotor wing (61), a forward distance sensing module (62), a camera cradle head (63), a high-definition photogrammetry camera (64), a left distance sensing module (65), a miniature GPS positioning navigation module (67), a backward distance sensing module (68), a right distance sensing module (69) and a top distance sensing module (610);

the high-definition photogrammetry camera (64) is a high-definition camera for collecting support image data and is arranged at the top of the unmanned aerial vehicle body in a rotary cradle head mode, and multi-angle photos of the bridge support structure and the surrounding environment are taken at multiple angles;

the miniature GPS positioning navigation module (67) is arranged at the top of the unmanned aerial vehicle body and is used for determining heading and position information of the unmanned aerial vehicle in the operation process so as to realize accurate positioning;

the forward sensing module (62), the left distance sensing module (65), the backward distance sensing module (68), the right distance sensing module (69) and the top distance sensing module (610) are laser ranging sensors, respectively detect obstacles in different directions, transmit distance information between the obstacles and the unmanned aerial vehicle back to the power device and the flight control system for processing through the signal transmission system in real time, obtain a real-time flight path and command the flight path of the unmanned aerial vehicle;

the unmanned aerial vehicle is provided with a signal transmission and communication module which is used for receiving the processed state data and the image data transmitted by the processor, transmitting the processed state data and the processed image data to the ground receiving station and carrying out subsequent manual inspection.