Fabricated bridge type support with monitoring function and monitoring and maintaining method thereof

Abstract

The invention relates to a fabricated bridge type support with a monitoring function and a monitoring and maintaining method thereof.The fabricated bridge type support comprises a channel steel cross beam, a channel steel vertical rod, a U-shaped adapter and a vertical rod adapter, and the channel steel cross beam and the channel steel vertical rod are connected in a transverse and longitudinal crossed mode to form a main body structure of the bridge type support; traction steel cables are connected between end points and / or connecting points of the channel steel cross beams and the channel steel vertical rods, so that the side face of the bridge type support forms an inverted trapezoid; the U-steel cross beam is provided with a plurality of U-shaped adapters, vertical rod adapters are arranged at the bottom ends of the U-steel vertical rods, the vertical rod adapters are connected with the traction steel cables through first prestress sensors, the U-shaped adapters are connected with the traction steel cables through second prestress sensors, and displacement sensors are further arranged between the U-shaped adapters and the U-steel cross beam. The device is used for monitoring the stress of the traction steel cable between the connection nodes of the channel steel cross beam and the channel steel vertical rod in real time and the displacement of the U-shaped adapter under the action of external force.

Description

Technical Field

[0001] The invention belongs to the technical field of digital buildings, and in particular relates to an assembled bridge support with a monitoring function and a monitoring and maintenance method thereof. Background Art

[0002] In today's precision engineering and automation fields, the demand for structural health monitoring is growing, and higher requirements are put forward in the field of construction, which has caused the digital transformation to attract widespread attention from technicians in the field. This is especially reflected in the maintenance of bridges, buildings and industrial equipment. As a key component in these structures, the state of the bridge bracket directly affects the safety and reliability of the overall system. The bridge bracket is a new type of prestressed component, which is mainly used in large-span structures (spacing can reach 6-10m), without roofs and floor slabs, and can greatly reduce the amount of steel and increase the aesthetics. During long-term use, the bridge bracket will be affected by factors such as temperature changes and mechanical vibrations, causing displacement or tilt, changing stress and overall state, and affecting structural performance. For the bridge bracket, prestress failure is irreversible and catastrophic to the overall structure. Therefore, it is particularly important to monitor the prestress of the bridge bracket, alarm after prestress loss, and monitor the repair and replacement of spare parts with hidden dangers. The displacement of the vertical poles during the installation of the bridge bracket (which is difficult to detect with the human eye), the insufficient prestress applied by the tension rods, and the untimely maintenance during operation, which leads to corrosion of the prestressed rods or loosening of the anchor points, will all lead to loss and failure of prestress, posing huge safety hazards. However, high-frequency maintenance and inspection will occupy the functional efficiency of the building, increase investment costs, and manual maintenance will also be missed. If there is looseness between the bridge brackets during use, all pipelines or supports must be removed for maintenance, and water and electricity must be cut off and production must be stopped, which is inefficient and costly. Summary of the invention

[0003] In view of the above problems, the present invention provides an assembled bridge support with a monitoring function and a monitoring and maintenance method thereof. In a first aspect, the assembled bridge support with a monitoring function comprises a channel steel beam, a channel steel pole, a U-shaped adapter and a pole adapter. The channel steel beam and the channel steel pole are cross-connected horizontally and vertically to form the main structure of the bridge support; a traction steel cable is connected between the end points and / or connection points of the channel steel beam and the channel steel pole, so that the side of the bridge support forms an inverted trapezoid;

[0004] The channel steel beam is provided with several U-shaped adapters, and the bottom end of the channel steel pole is provided with a pole adapter. The pole adapter is connected to the traction cable through prestressed sensor 1, and the U-shaped adapter is connected to the traction cable through prestressed sensor 2. A displacement sensor is also provided between the U-shaped adapter and the channel steel beam, which is used to monitor in real time the stress of the traction cable between each connection node of the channel steel beam and the channel steel pole and the displacement of the U-shaped adapter under the action of external force.

[0005] Optionally, the channel steel beam includes two mutually parallel main beams and a plurality of secondary beams, the main beams and the secondary beams are both arranged horizontally, and the main beam is perpendicular to the secondary beam, and a plurality of secondary beams are fixedly connected between the two main beams to improve the strength of the main beam;

[0006] The channel steel uprights are arranged vertically, and two channel steel uprights are evenly arranged along the length direction of the main beam. The channel steel uprights connected to different main beams correspond to each other in position. A number of secondary beams are also connected between the corresponding two channel steel uprights of different main beams, and the number of secondary beams are evenly arranged along the length direction of the channel steel uprights to improve the strength of the channel steel uprights.

[0007] Optionally, both ends of the main crossbeam and the position where the channel steel uprights are connected are provided with U-shaped adapters, the U-shaped adapters include a U-shaped connector, a diagonal card and a multi-directional connector. The main crossbeam passes through the U-shaped connector, the top of the main crossbeam abuts against the middle top plate of the U-shaped connector, and the bottom abuts against the diagonal card; the wing plates on both sides of the U-shaped connector cover both sides of the main crossbeam and extend to the bottom of the diagonal card;

[0008] The bottom of the wing plate 1 of the U-shaped connecting piece is hinged to the top of the multi-directional connecting piece 1, and the bottom of the multi-directional connecting piece 1 is provided with a prestressed sensor 2.

[0009] Optionally, the pole adapter comprises a central connection piece and at least two multi-directional connection pieces; a vertical inner groove is provided at the center of the central connection piece, and the bottom end of the channel steel pole is inserted into the inner groove; both side surfaces of the central connection piece are vertical surfaces, and a plurality of through holes are provided in the areas of the two side surfaces corresponding to the inner groove, and through holes are also provided at the bottom of the channel steel pole, so as to connect the central connection piece with the channel steel pole by bolts;

[0010] Several pairs of through holes are correspondingly arranged near the edges of the two sides of the central connecting piece, and the number of the through holes is equal to the number of the multi-directional connecting piece 2; one end of the multi-directional connecting piece 2 is hinged to the central connecting piece, and the other end is connected to the prestressed sensor 1.

[0011] Further optionally, an inclination sensor is provided at the bottom of the channel steel upright to monitor the inclination angle of the channel steel upright in real time, and the inclination sensor is located above the central connecting piece.

[0012] In a second aspect, the monitoring and maintenance method of the bridge support comprises the following steps:

[0013] S1: Establishing the system state model: Using the displacement and acceleration data detected by the displacement sensor to build the state vector of the bridge support system, and then determining the state transfer equation and measurement equation of the system;

[0014] S2: Preliminary data processing: oversample the original state vector of the system to obtain a state vector with a high sampling rate, input the state vector with a high sampling rate into the Sigma-Delta modulator, generate an integrated state signal by integrating and accumulating the signal, and then remove the high-frequency components through low-pass filtering to obtain the processed signal;

[0015] S3: Input the signal processed in step S2 into the Kalman filter, and use the state transfer equation and measurement equation of the system in step S1 to perform prediction and update of the Kalman filter to obtain the final estimated state of the system state vector.

[0016] Optionally, the above-mentioned bridge support as a whole is a system. In step S1, the state vector y of the system k Including the displacement θ detected by the displacement sensor k and acceleration a k ,

[0017]

[0018] Among them, θ k is the displacement data detected by the displacement sensor, mm; a k is the acceleration data detected by the displacement sensor, mm / s 2 ; k represents the kth sampling point in the time series.

[0019] The state transition equation of the system is:

[0020] y k =A×y k-1 +ω k

[0021] in, △t is the time interval, unit is s; ω k is the process noise, that is, the noise term. The process noise obeys a zero-mean Gaussian distribution, and its covariance matrix is ​​Q, where Q is the process noise covariance matrix.

[0022] For a random vector ω k , the covariance matrix Q is defined as

[0023]

[0024] in, Yes k Expected value, specifically 0; E[·] represents the expected operation.

[0025] The measurement equation is:

[0026] Z k =H×y k +v k

[0027] Among them, Z k is the updated observation value, Z k In the measurement equation of the Kalman filter, it is used to update the state by combining the predicted system state;

[0028] H is the measurement matrix, H = [1 0]; v k is the measurement noise, which obeys the zero-mean Gaussian distribution and has a covariance matrix of R, R is the measurement noise covariance matrix, which describes the size and characteristics of the displacement sensor measurement error and is usually used to measure the measurement value Z k uncertainty.

[0029] The present invention utilizes the known y in the state transfer equation of the system k and k-1 , predict reasonable A and ω k , and then through ω k Determine Q. Similarly, using the known Z in the measurement equation k and k , we get v k , and then through v k Determine R.

[0030] Optionally, step S2 includes:

[0031] (1) Oversampling: During the data acquisition phase, the original state vector y of the system k After oversampling, the state vector y with high sampling rate is obtained k (os) , by increasing the sampling rate to reduce the impact of quantization error;

[0032] (2) Integration and quantization: After oversampling, the high sampling rate state vector y k (os) It is input into the Sigma-Delta modulator, and the integrated state vector S is generated by integrating the accumulated signal. k , the integral state transfer equation is:

[0033]

[0034] Then, the integral state is quantized to obtain the quantized integral state signal y k (q) ;

[0035] (3) Low-pass filtering: quantized signal y k (q) After passing through a low-pass filter to remove high-frequency components, the processed signal Y is obtained. k .

[0036] Further optionally, in step (1), the sampling frequency of the oversampling process is 4 times the sampling frequency of the original state vector of the system.

[0037] Further optionally, in step (2), the following equation is obtained from the integral state transfer equation:

[0038]

[0039] Among them, S k is the integral state vector; y k (os) is the state vector of high sampling rate; y k-1 (q) is the quantized integral state vector, i.e. y k (q) It is also the quantized integral state vector; k represents the kth sampling point in the time series.

[0040] Further optionally, in step (3), the low-pass filtering method and parameters are determined according to the actual environment of the installation site. Bridge supports are usually used to suspend or support equipment, and the main focus is on their structural stability and whether there is long-term slow tilt or deformation. This type of monitoring requires filtering out high-frequency noise to obtain a stable signal; in bridge supports, the monitoring goal is to capture rapid vibrations, impacts and instantaneous tilt changes (such as vibrations caused by the passage of vehicles). This type of monitoring requires a higher sampling rate and lower computing delay to monitor the structural health in real time.

[0041] Optionally, step S3 specifically includes:

[0042] (4) The processed signal Y k Input Kalman filter, i.e. Z k =Y k ;

[0043] (5) Use the Kalman filter to predict the system state vector:

[0044]

[0045] in, is the predicted value of the system state vector; k represents the kth sampling point in the time series;

[0046] The prediction error covariance matrix is ​​updated as:

[0047] P k|k-1 =A×P k-1|k-1 ×A T +Q

[0048] Among them, P k|k-1 is the prediction error covariance matrix;

[0049] (6) Based on the prediction error covariance matrix and the measurement noise covariance matrix, determine the Kalman gain matrix K k :

[0050] K k =P k|k-1 ×H T ×(H×P k|k-1 ×H T +R) -1

[0051] Then, use the processed signal Y k Update system status:

[0052]

[0053] in, is the updated signal;

[0054] The updated forecast error covariance matrix is:

[0055] P k|k =(IK k ×H)×P k|k-1

[0056] Where I is the identity matrix.

[0057] Further optionally, in step (5), is the initial value, here it is assigned to Y k The initial value (Y1) of the present invention It is a preliminary estimate of the next state of the system. Through the prediction of A in step S1, a preliminary estimate can be obtained. The appropriate value of .

[0058] Further optionally, in step (6), P 1|0 , P 0|0 All are initial values, which are obtained through existing method assumptions. For example, in the large uncertainty assumption, if the initial state of the system is uncertain, P0 is usually assumed to be a large diagonal matrix, which means that all state components are highly uncertain;

[0059] Or in the smaller uncertainty assumption, if there is a good estimate of the initial state of the system (for example, the initial value is obtained by other means), P0 is assumed to be a smaller diagonal matrix.

[0060] The monitoring and maintenance method of the bridge support described in the present invention utilizes the integration and quantization of oversampling and Sigma-Delta modulation to move most of the quantization noise to the high frequency band, reduce the noise interference in the low frequency signal, and significantly improve the data quality. On this basis, the processed signal is input into the Kalman filter, and the estimation accuracy of the tilt angle is further improved by modeling the noise and system model. Due to the recursive characteristics of the Kalman filter, the entire fusion method can be implemented in an embedded system to meet the needs of real-time processing.

[0061] The present invention organically combines Sigma-Delta modulation and Kalman filtering to form an efficient method for processing bridge support monitoring data, which can not only significantly reduce the noise in the data, but also improve the accuracy and real-time performance of health status estimation, and is very suitable for application in complex industrial environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a structural schematic diagram of the bridge support of Example 1;

[0063] Figure 2 This is a schematic diagram of the decomposition of the U-shaped adapter;

[0064] Figure 3 This is a schematic diagram of the U-shaped adapter after assembly;

[0065] Figure 4 This is an exploded schematic diagram of the pole adapter;

[0066] Figure 5 This is a schematic diagram of the pole adapter after assembly.

[0067] In the accompanying drawings, 1-channel steel beam, 2-channel steel pole, 3-U-shaped adapter, 4-pole adapter, 5-traction steel cable, 6-prestressed sensor 1, 7-prestressed sensor 2, 8-displacement sensor, 9-main beam, 10-secondary beam, 11-U-shaped connector, 12-cambered card, 13-multi-directional connector 1, 14-multi-directional connector 2, 15-middle top plate, 16-wing plate 1, 17-wing plate 2, 18-wing plate 3, 19-protrusion, 20-middle bottom plate, 21-center connector, 22-inner groove, 23-middle plate, 24-tilt sensor. DETAILED DESCRIPTION

[0068] Example 1

[0069] This embodiment provides an assembled bridge support with a monitoring function, such as Figure 1-Figure 5As shown, it comprises a channel steel beam 1, a channel steel pole 2, a U-shaped adapter 3 and a pole adapter 4. The channel steel beam 1 and the channel steel pole 2 are cross-connected horizontally and vertically to form the main structure of the bridge support. A traction steel cable 5 is connected between the end points and / or connection points of the channel steel beam 1 and the channel steel pole 2, so that the side of the bridge support forms an inverted trapezoid;

[0070] The channel steel beam 1 is provided with a plurality of U-shaped adapters 3, a pole adapter 4 is provided at the bottom end of the channel steel pole 2, the pole adapter 4 is connected to the traction steel cable 5 via a prestressed sensor 1 6, the U-shaped adapter 3 is connected to the traction steel cable 5 via a prestressed sensor 2 7, and a displacement sensor 8 is also provided between the U-shaped adapter 3 and the channel steel beam 1, for real-time monitoring of the stress of the traction steel cable 5 between each connection node of the channel steel beam 1 and the channel steel pole 2 and the displacement of the U-shaped adapter 3 under the action of external force.

[0071] Prestress sensor 1 6 is exactly the same as prestress sensor 2 7 .

[0072] The channel steel beam 1 includes two mutually parallel main beams 9 and a plurality of secondary beams 10. The main beams 9 and the secondary beams 10 are both arranged horizontally, and the main beam 9 is perpendicular to the secondary beams 10. A plurality of secondary beams are fixedly connected between the two main beams to improve the strength of the main beam 9.

[0073] The channel steel uprights 2 are arranged vertically, and two channel steel uprights 2 are evenly arranged along the length direction of the main cross beam 9. The channel steel uprights 2 connected to different main cross beams 9 correspond to each other in position. A plurality of secondary cross beams are also connected between the two corresponding channel steel uprights of different main cross beams, and the plurality of secondary cross beams are evenly arranged along the length direction of the channel steel uprights 2 to improve the strength of the channel steel uprights. The main cross beam can be in various forms, such as C-shaped double-piece channel steel.

[0074] As a specific implementation method, the two ends of the main crossbeam 9 are respectively connected to the structures at the two ends of the bridge support, and a channel steel upright 2 is respectively assembled and connected at 1 / 3 and 2 / 3 of the length direction of the main crossbeam 9, and a secondary crossbeam 10 is respectively fixedly welded at 1 / 3 and 2 / 3 of the length direction of the main crossbeam 9; a secondary crossbeam 10 is respectively fixedly welded at the middle and lower parts of the two corresponding channel steel uprights of different main crossbeams 9.

[0075] Both ends of the main crossbeam 9 and the position where the channel steel upright pole 2 is connected are provided with U-shaped adapters 3, the U-shaped adapter 3 includes a U-shaped connector 11, a diagonal card 12 and a multi-directional connector 13, the main crossbeam 9 passes through the U-shaped connector 11, the top of the main crossbeam 9 abuts against the middle top plate 15 of the U-shaped connector 11, and the bottom abuts against the diagonal card 12; the wing plates 16 on both sides of the U-shaped connector 11 cover both sides of the main crossbeam 9 and extend to the bottom of the diagonal card 12;

[0076] The bottom of the wing plate 16 of the U-shaped connector is hinged to the top of the multi-directional connector 13, and a prestressed sensor 2 7 is arranged at the bottom of the multi-directional connector 13.

[0077] The U-shaped connecting member 11 is integrally formed, including an intermediate top plate 15 and wing plates 16 on both sides of the intermediate top plate 15. The intermediate top plate 15 is horizontal, and the wing plates 16 are vertical. The top ends of the wing plates 16 are connected to the sides of the intermediate top plate 15, and the bottom ends thereof are vertically downward and hinged to the multi-directional connecting member 13. The spacing between the two wing plates 1 is not less than the width of the main beam 9. A plurality of through holes are opened on the intermediate top plate 15, and the wing plates 16 are connected to the top of the main beam 9 by bolts.

[0078] The inclined card 12 is parallel to the length direction of the main beam 9, and is provided with protrusions 19 at both ends. The protrusions 19 protrude outward along the width direction of the main beam 9. The two protrusions are located at the outer sides of the two ends of the two wing plates. The inner edges of the protrusions 19 can abut against the outer sides of the corresponding ends of the two wing plates, so that the position of the U-shaped connector 11 in the length direction of the main beam is fixed by the inclined card 12.

[0079] The inclined-stayed card 12 is provided with a plurality of through holes and is connected to the bottom of the main cross beam 9 by bolts.

[0080] The multi-directional connecting member 13 is U-shaped and integrally formed, including a middle bottom plate 20 and two wing plates 17 on both sides of the middle bottom plate 20, the middle bottom plate 20 is perpendicular to the two wing plates 17, the two wing plates 17 are connected to the wing plates 16 in a one-to-one correspondence, and the top of the two wing plates 17 is hinged to the bottom of the wing plates 16 through a pin shaft, so that the multi-directional connecting member 13 rotates around the wing plates 16 with the pin shaft as the rotating axis to adapt to the connection of the traction cables 5 in different directions;

[0081] The outer side surface of the middle bottom plate 20 is connected to the traction cable 5 through the prestressed sensor 2 7 .

[0082] The displacement sensor 8 is arranged on the side of the main beam 9 next to any wing plate 16, and the sensing head of the displacement sensor 8 is connected to the outer side of the wing plate 16, which is used to monitor the displacement of the U-shaped connector 11 in the length direction of the main beam 9 in real time.

[0083] The U-shaped adapter 3 of the present invention can connect the inclined traction cable 5 and bear the tension. The protrusion 19 of the inclined card 12 limits the U-shaped connector 11, increasing the horizontal anti-slip ability of the U-shaped adapter; the multi-directional connector 13 is connected to the U-shaped connector 11 by a pin shaft, which can achieve multi-angle adjustment. A displacement sensor 8 is set in front of the tension side of the U-shaped adapter 3, and a prestressed sensor 2 7 is set on the multi-directional connector 13, which can monitor the horizontal displacement of the U-shaped adapter 3 and the cable tension it bears in real time.

[0084] The vertical pole adapter 4 includes a central connecting piece 21 and at least two multi-directional connecting pieces 214. A vertical inner groove 22 is provided at the center of the central connecting piece 21, and the bottom end of the channel steel vertical pole 2 is inserted into the inner groove 22. Both side surfaces of the central connecting piece 21 are vertical surfaces. A plurality of through holes are provided in the areas corresponding to the inner groove 22 on the two side surfaces. The bottom of the channel steel vertical pole 2 is also provided with through holes corresponding to the through holes, which are used to connect the central connecting piece 21 with the channel steel vertical pole 2 by bolts.

[0085] Several pairs of through holes are correspondingly arranged near the edges of the two sides of the central connecting member 21, and the number of the through holes is equal to the number of the multi-directional connecting members 14; one end of the multi-directional connecting member 14 is hinged to the central connecting member 21, and the other end is connected to the prestressed sensor 6.

[0086] The multidirectional connecting member 2 14 has the same structure as the multidirectional connecting member 1 13, that is, the multidirectional connecting member 2 14 is U-shaped and integrally formed, including a middle plate 23 and wing plates 3 18 on both sides of the middle plate 23, the middle plate 23 is perpendicular to the wing plates 3 18, the wing plates 3 18 are correspondingly connected to the side surfaces of the central connecting member 21, and one end of the wing plates 3 18 is hinged to the central connecting member 21 through a pin shaft, so that the multidirectional connecting member 2 14 rotates around the central connecting member 21 with the pin shaft as the rotating shaft to adapt to the connection of the traction cables 5 in different directions;

[0087] The outer side surface of the middle plate 23 is connected to the traction cable 5 through a prestressed sensor 6.

[0088] According to the number and direction of the traction cables 5 to be connected at the bottom of the channel steel upright 2, the number of the multi-directional connectors 14 and the position of the connecting center connector 21 are reasonably set.

[0089] The bottom of the channel steel upright 2 is provided with an inclination sensor 24 for real-time monitoring of the inclination angle of the channel steel upright 2. The inclination sensor 24 is located above the central connecting member 21. The inclination sensor 24 monitors the overall overturning or twisting of the bridge support to ensure that the entire construction system has no relative rotation.

[0090] As a specific implementation method, the U-shaped adapters 3 at both ends of the main beam 9 are connected to the pole adapters 4 at the bottom of the adjacent channel steel poles 2 of the same main beam 9 through the traction steel cables 5; the pole adapters 4 at the bottom of the two channel steel poles 2 of the same main beam 9 are connected to each other through the traction steel cables 5; the U-shaped adapter near the place where the channel steel pole 2 is connected to the main beam is connected to the pole adapter at the bottom of another channel steel pole of the same main beam through the traction steel cables, so that a cross-shaped traction steel cable 5 is formed under the main beam; through the connection of the above-mentioned traction steel cables 5, the side of the bridge bracket forms an isosceles trapezoid with a larger upper part and a smaller lower part.

[0091] The pole adapter 4 is connected to the channel steel pole 2 through the inner groove 22 and bolts, which is stable and reliable. The multi-directional connector 2 14 is connected to the central connector 21 by a pin shaft, which can achieve multi-angle adjustment; the shape of the side of the central connector 21 can be circular or polygonal, so that multiple connection points can be set to connect the multi-directional connector 2 14, and connection points can be reserved for subsequent maintenance and replacement of steel cables, and the installation position can be flexibly adjusted according to actual conditions. The multi-directional connector 2 14 is provided with a prestressed sensor 1 6, and the channel steel pole 2 is provided with an inclination sensor 24, which can monitor the steel cable tension in each direction of the pole adapter 4 and the inclination angle after tension in real time.

[0092] The present invention performs comprehensive data analysis and processing through the relative position between the main crossbeam 9 and each node of the channel steel upright 2, prestress data, and the angle change of the channel steel upright 2. The displacement sensor 8, prestress sensor 1 6, and prestress sensor 2 7 are all connected to the external monitoring and processing device, and the monitoring data of each sensor is displayed one by one on the three-dimensional model of the monitoring and processing device, and alarms, drawings, and spare parts types and other information are issued in time. During the use of the bridge bracket, when the U-shaped adapter 3 and the main crossbeam 9 have relative displacement and exceed the preset threshold of the displacement sensor 8, the monitoring and processing device will alarm, and multiple displacement change intervals can be set to correspond to different levels of alarms, and the positioning information of the alarming sensor will be displayed synchronously, so that maintenance personnel can arrive and repair at the first time.

[0093] During the operation and maintenance of bridge supports, the biggest impact is the loss of prestress, which leads to overall structural failure and collapse; the second is the difficulty in replacing the parts of the bridge supports. That is, when replacing parts, the steel cables, beams, and poles need to be temporarily fixed to prevent the prestress from failing during the replacement process and causing overall collapse. Traditional temporary fixing methods generally use more mechanical equipment and support systems, which are costly.

[0094] The vertical pole adapter 4 of the present invention has multiple connection points and a multi-directional connector 14, and the assembly form is flexible and easy to assemble and disassemble. When replacing, it is only necessary to install new identical parts on the original basis. Each sensor reads data in real time to assist in replacing parts to meet the original design requirements. After that, the replaced components can be disassembled to achieve in-situ replacement, thereby completing the maintenance work in the lowest cost, most effective and fastest way.

[0095] The side surface of the central connecting member of this embodiment is circular, and the central connecting member connects three multi-directional connecting members 2.

[0096] Example 2

[0097] This embodiment provides a monitoring and maintenance method for the assembled bridge support of Embodiment 1, comprising the following steps:

[0098] S1: Establishing the system state model: Using the displacement and acceleration data detected by the displacement sensor to build the state vector of the bridge support system, and then determining the state transfer equation and measurement equation of the system;

[0099] S2: Preliminary data processing: oversample the original state vector of the system to obtain a state vector with a high sampling rate, input the state vector with a high sampling rate into the Sigma-Delta modulator, generate an integrated state signal by integrating and accumulating the signal, and then remove the high-frequency components through low-pass filtering to obtain the processed signal;

[0100] S3: Input the signal processed in step S2 into the Kalman filter, and use the state transfer equation and measurement equation of the system in step S1 to perform prediction and update of the Kalman filter to obtain the final estimated state of the system state vector.

[0101] The bridge support of Example 1 is a system as a whole. In step S1, the state vector y of the system k Including the displacement θ detected by the displacement sensor k and acceleration a k ,

[0102]

[0103] Among them, θ k is the displacement data detected by the displacement sensor, mm; a k is the acceleration data detected by the displacement sensor, mm / s 2 ; k represents the kth sampling point in the time series.

[0104] The state transition equation of the system is:

[0105] y k =A×y k-1 +ω k

[0106] in, △t is the time interval, unit is s; ω k is the process noise, that is, the noise term. The process noise obeys a zero-mean Gaussian distribution, and its covariance matrix is ​​Q, where Q is the process noise covariance matrix.

[0107] For a random vector ω k , the covariance matrix Q is defined as

[0108]

[0109] in, Yes k Expected value, specifically 0; E[·] represents the expected operation.

[0110] The measurement equation is:

[0111] Z k =H×y k +v k

[0112] Among them, Z k is the updated observation value, Z k In the measurement equation of the Kalman filter, it is used to update the state by combining the predicted system state;

[0113] H is the measurement matrix, H = [1 0]; v k is the measurement noise, which obeys the zero-mean Gaussian distribution and has a covariance matrix of R, where R is the measurement noise covariance matrix".

[0114] Step S2 includes:

[0115] (1) Oversampling: Use displacement sensors to collect data. During the data collection phase, the original state vector y of the system k After oversampling, the state vector y with high sampling rate is obtained k (os) ;

[0116] (2) Integration and quantization: After oversampling, the high sampling rate state vector y k (os) It is input into the Sigma-Delta modulator, and the integrated state vector S is generated by integrating the accumulated signal. k , the integral state transfer equation is:

[0117]

[0118] Then, the integral state is quantized to obtain the quantized integral state signal y k (q) ;

[0119] (3) Low-pass filtering: quantized signal y k (q) After passing through a low-pass filter to remove high-frequency components, the processed signal Y is obtained. k .

[0120] In step (1), displacement sensors are used to collect data, and each sensor is connected to the software platform to read the initial value of each node sensor. After the data is read, it is assigned to each node corresponding to the three-dimensional model of the bridge support in the software platform. At the same time, the three-dimensional model of the bridge support in the software platform has the location information in the project, for example, a certain layer, a certain area, a certain span, and a certain number, which is consistent with the project site number; the construction drawings of the bridge support, the names and quantities of spare parts are embedded in the software platform;

[0121] The sampling frequency of the oversampling process is 4 times the sampling frequency of the original state vector. The sampling frequency of the original state vector is 50Hz, and the sampling frequency of the oversampling process is 200Hz. While ensuring the signal details, it also meets the needs of general support and hanger monitoring.

[0122] In step (2), the following equation is obtained from the integral state transfer equation:

[0123]

[0124] Among them, S k is the integral state vector; y k (os) is the state vector of high sampling rate; y k-1 (q) is the quantized state vector, i.e., y k (q) It is also the quantized state vector; k represents the kth sampling point in the time series.

[0125] In step (3), the low-pass filtering method and parameters are determined according to the actual environment of the installation site.

[0126] Optionally, step S3 specifically includes:

[0127] (4) The processed signal Y k Input Kalman filter, i.e. Z k =Y k ;

[0128] (5) Use the Kalman filter to predict the system state vector:

[0129]

[0130] in, is the predicted value of the system state vector;

[0131] The prediction error covariance matrix is ​​updated as:

[0132] P k|k-1 =A×P k-1|k-1 ×A T +Q

[0133] Among them, P k|k-1 is the prediction error covariance matrix, and ω can be obtained through the state transfer equation of the system. k , and then by ω k Get Q, substitute Q into the above formula as a known quantity;

[0134] (6) Based on the prediction error covariance matrix and the measurement noise covariance matrix, determine the Kalman gain matrix K k :

[0135] K k =P k|k-1 ×H T ×(H×P k|k-1 ×H T +R) -1

[0136] Then, use the processed signal Y k Update system status:

[0137]

[0138] in, is the updated signal;

[0139] The updated forecast error covariance matrix is:

[0140] P k|k =(IK k ×H)×P k|k-1

[0141] Where I is the identity matrix.

[0142] Further optionally, in step (5), is the initial value, here it is assigned to Y k The initial value (Y1) of the present invention It is a preliminary estimate of the next state of the system. Through the prediction of A in step S1, a preliminary estimate can be obtained. The appropriate value of .

[0143] Further optionally, in step (6), P 1|0 , P 0|0 is the initial value, which is obtained by the existing method assumption. For example, in the large uncertainty assumption, if the initial state of the system is uncertain, P0 is usually assumed to be a large diagonal matrix, which means that all state components are highly uncertain;

[0144] Or in the smaller uncertainty assumption, if there is a good estimate of the initial state of the system (for example, the initial value is obtained by other means), P0 is assumed to be a smaller diagonal matrix.

[0145] Based on the data obtained by the above method, subsequent real-time monitoring is carried out. When the data deviation exceeds 5% during the monitoring process, the software platform will issue an early warning and prompt the specific location information of the early warning, so that maintenance personnel can arrive at it as soon as possible.

[0146] After arriving at the site, if there is damage to the rods or structures, a maintenance process will be carried out; if only the bolts or pipelines need to be adjusted instead of the rods or structures, after the adjustment is completed, each sensor will be initialized, the data will be re-read, and the above monitoring will continue.

[0147] Maintenance process:

[0148] 1. The software platform calls out the construction drawings and material list of the cross-bridge bracket, finds the corresponding products and quantities in the material list according to the on-site damage situation, and transports them to the replacement point.

[0149] 2. Combined with the present invention Figure 4 The center connecting piece 21 (rectangular 4 bolt holes, hexagonal 6 bolt holes, circular can customize the required number of bolt holes), during normal installation, only the upper right, lower right and lower left 3 bolt holes of the center connecting piece need to be used; when the prestressed component needs to be replaced, only the same rod needs to be installed on the original basis, and the installation positions are upper right, middle right and middle left.

[0150] 3. When replacing prestressed components, first replace the inner cross traction cables, and then install various sensors as an auxiliary. At this time, the prestressed sensor installed at the end of the traction cable reads the data in real time. When the data reaches within ±5% of the previous normal data, the installation is completed. Then replace the inclined cables of the side spans and the horizontal cables of the middle span in turn. After the replacement of the prestressed components of the overall structure is completed, remove the original components to realize the in-situ replacement function.

[0151] 4. After the overall component replacement is completed, the sensor data in various locations are re-read, the software platform is updated, and normal monitoring is carried out based on the new data.

Claims

1. The assembled bridge bracket with monitoring function is characterized by: It includes a channel steel beam, a channel steel pole, a U-shaped adapter and a pole adapter. The channel steel beam and the channel steel pole are cross-connected horizontally and vertically to form the main structure of the bridge support. A traction steel cable is connected between the end points and / or connection points of the channel steel beam and the channel steel pole, so that the side of the bridge support forms an inverted trapezoid. The channel steel beam is provided with several U-shaped adapters, and the bottom end of the channel steel pole is provided with a pole adapter. The pole adapter is connected to the traction cable through prestressed sensor 1, and the U-shaped adapter is connected to the traction cable through prestressed sensor 2. A displacement sensor is also provided between the U-shaped adapter and the channel steel beam, which is used to monitor in real time the stress of the traction cable between each connection node of the channel steel beam and the channel steel pole and the displacement of the U-shaped adapter under the action of external force.

2. The assembled bridge support with monitoring function according to claim 1 is characterized in that: The channel steel beam includes two mutually parallel main beams and a plurality of secondary beams, the main beams and the secondary beams are both arranged horizontally, and the main beam is perpendicular to the secondary beam, and a plurality of secondary beams are fixedly connected between the two main beams to improve the strength of the main beam; The channel steel uprights are arranged vertically, and two channel steel uprights are evenly arranged along the length direction of the main beam. The channel steel uprights connected to different main beams correspond to each other in position. A number of secondary beams are also connected between the corresponding two channel steel uprights of different main beams, and the number of secondary beams are evenly arranged along the length direction of the channel steel uprights to improve the strength of the channel steel uprights.

3. The assembled bridge support with monitoring function according to claim 2 is characterized in that: Both ends of the main crossbeam and the position where the channel steel uprights are connected are provided with U-shaped adapters, the U-shaped adapters include a U-shaped connector, a diagonal card and a multi-directional connector. The main crossbeam passes through the U-shaped connector, the top of the main crossbeam abuts against the middle top plate of the U-shaped connector, and the bottom abuts against the diagonal card; the wing plates on both sides of the U-shaped connector cover both sides of the main crossbeam and extend to the bottom of the diagonal card; The bottom of the wing plate 1 of the U-shaped connecting piece is hinged to the top of the multi-directional connecting piece 1, and the bottom of the multi-directional connecting piece 1 is provided with a prestressed sensor 2.

4. The assembled bridge support with monitoring function according to claim 3 is characterized in that: The pole adapter comprises a central connecting piece and at least two multi-directional connecting pieces. A vertical inner groove is provided at the center of the central connecting piece, and the bottom end of the channel steel pole is inserted into the inner groove. Both sides of the central connecting piece are vertical surfaces. A plurality of through holes are provided in the areas corresponding to the inner grooves of the two sides. Through holes are also provided at the bottom of the channel steel pole, which are used to connect the central connecting piece with the channel steel pole by bolts. Several pairs of through holes are correspondingly arranged near the edges of the two sides of the central connecting piece, and the number of the through holes is equal to the number of the multi-directional connecting piece 2; one end of the multi-directional connecting piece 2 is hinged to the central connecting piece, and the other end is connected to the prestressed sensor 1.

5. The assembled bridge support with monitoring function according to claim 4 is characterized in that: An inclination sensor is arranged at the bottom of the channel steel upright pole for real-time monitoring of the inclination angle of the channel steel upright pole, and the inclination sensor is located above the central connecting piece.

6. The monitoring and maintenance method of the assembled bridge support according to claim 5 is characterized in that: The following steps are involved: S1: Establishing the system state model: Using the displacement and acceleration data detected by the displacement sensor to build the state vector of the bridge support system, and then determining the state transfer equation and measurement equation of the system; S2: Preliminary data processing: oversample the original state vector of the system to obtain a state vector with a high sampling rate, input the state vector with a high sampling rate into the Sigma-Delta modulator, generate an integrated state signal by integrating and accumulating the signal, and then remove the high-frequency components through low-pass filtering to obtain the processed signal; S3: Input the signal processed in step S2 into the Kalman filter, and use the state transfer equation and measurement equation of the system in step S1 to perform prediction and update of the Kalman filter to obtain the final estimated state of the system state vector.

7. The monitoring and maintenance method according to claim 6, characterized in that: The above-mentioned bridge support as a whole is a system. In step S1, the state vector y of the system is k Including the displacement θ detected by the displacement sensor k and acceleration a k , Among them, θ k is the displacement data detected by the displacement sensor; a k is the acceleration data detected by the displacement sensor; k represents the kth sampling point in the time series; The state transition equation of the system is: y k =A×y k-1 +oh k in, △t is the time interval; ω k is the process noise; The measurement equation is: With k =H×y k +v k Among them, Z k is the measured value; H is the measurement matrix, H = [1 0]; v k To measure noise.

8. The monitoring and maintenance method according to claim 6, characterized in that: Step S2 includes: (1) Oversampling: During the data acquisition phase, the original state vector y of the system k After oversampling, the state vector y with high sampling rate is obtained k (os) ; (2) Integration and quantization: After oversampling, the high sampling rate state vector y k (os) It is input into the Sigma-Delta modulator, and the integrated state vector S is generated by integrating the accumulated signal. k , the integral state transfer equation is: Then, the integral state is quantized to obtain the quantized integral state signal y k (q) ; (3) Low-pass filtering: quantized signal y k (q) After passing through a low-pass filter to remove high-frequency components, the processed signal Y is obtained. k .

9. The monitoring and maintenance method according to claim 6, characterized in that: Step S3 is specifically as follows: (4) The processed signal Y k Input Kalman filter, i.e. Z k =Y k ; (5) Use the Kalman filter to predict the system state vector: in, is the predicted value of the system state vector; The prediction error covariance matrix is ​​updated as: P k|k-1 =A×P k-1|k-1 ×A T +Q Among them, P k|k-1 is the prediction error covariance matrix; (6) Based on the prediction error covariance matrix and the measurement noise covariance matrix, determine the Kalman gain matrix K k : K k =P k|k-1 ×H T ×(H×P k|k-1 ×H T +R) -1 Then, use the processed signal Y k Update system status: in, is the updated signal; The updated forecast error covariance matrix is: P k|k =(I-K k ×H)×P k|k-1 Where I is the identity matrix.

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