CN112561257A - Bridge structure safety evaluation method and device based on big data - Google Patents
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Abstract
The invention discloses a bridge structure safety evaluation method and device based on big data, wherein the method comprises the following steps: obtaining the score of each type of measuring point, and obtaining each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point; acquiring a monitoring item score of a bridge superstructure monitored by a sensor, a monitoring item score of a bridge substructure monitored by the sensor and a monitoring item score of a bridge deck system monitored by the sensor; acquiring a safety score of the bridge based on sensor monitoring; acquiring a comprehensive score of the bridge based on monitoring and detection; the invention has the advantages that: the evaluation structure is comprehensive, data are acquired in real time, and the real-time performance is good.
Description
Technical Field
The invention relates to the technical field of bridge structure safety monitoring, in particular to a bridge structure safety evaluation method and device based on big data.
Background
The safety evaluation of the bridge structure is a core technology of a bridge structure health monitoring system and is also a research hotspot at home and abroad at present. At present, although a plurality of bridges are provided with health monitoring systems at home and abroad, the safety evaluation systems matched with the health monitoring systems are not sound. The problem with this is that the large amount of data obtained from real-time monitoring is not known how to identify and evaluate the state of the structure and the damage that may occur. A set of bridge health state safety diagnosis and evaluation method is researched and established, and identification and evaluation of bridge structure response are extremely complex processes.
In most bridge structure health monitoring systems, the initial purpose and the purpose of the design are to acquire static or dynamic response of the system through a sensor in order to know the service safety state of the structure in time, particularly the dangerous part or section of the structure, and to give early warning to the danger which is or is about to occur in time through data analysis. Therefore, the arrangement number and types of the measuring points are usually less redundant, and the comprehensive state of the bridge structure is difficult to reflect comprehensively. In addition, the health management unit of the bridge usually uses the evaluation score (BCI) of the bridge health condition in the detection report of the bridge detection unit to grasp the health condition of the bridge, and the evaluation is based on the appearance inspection of the structure. Unlike the health monitoring system, the monitoring is mainly for obtaining the internal mechanical conditions (stress strain, dynamic characteristics, rigidity, etc.) of the structure. Therefore, it is also difficult to achieve the target only by MCI (monitoring score). Furthermore, there is currently no regulation on what type and number of sensors are used to evaluate the overall safety of the bridge. In summary, in the existing bridge safety structure evaluation, the bridge health condition assessment score (BCI) or MCI (monitoring score) is considered unilaterally, and the evaluation structure is not comprehensive enough, has no convincing power, has no real-time performance, and has poor timeliness.
Chinese patent application No. CN201711287323.3 discloses an online visual bridge monitoring platform for creating and managing, which includes: the bridge monitoring and sensing module, the bridge monitoring and analyzing module and the bridge monitoring three-dimensional visual module are arranged on the bridge monitoring and analyzing module; the bridge monitoring and sensing module is used for remotely configuring a front-end acquisition sensor; the bridge monitoring and analyzing module is used for preprocessing, analyzing and early warning the monitoring data acquired by the front-end sensor and evaluating the safety state of the bridge; the bridge monitoring three-dimensional visual module is used for displaying a bridge three-dimensional model and displaying a real-time data state. Has the advantages that: the online visual bridge monitoring establishing and managing platform provided by the invention is simple in arrangement and convenient and fast to use, greatly accelerates the establishing speed of a bridge monitoring system, improves the maintenance efficiency, and has strong practicability. It provides only a general idea and does not provide a specific bridge safety state evaluation method.
Disclosure of Invention
The invention aims to solve the technical problems that the bridge safety structure evaluation method in the prior art is not comprehensive enough in evaluation structure, data are not acquired in real time, the real-time performance is poor, and the timeliness is poor.
The invention solves the technical problems through the following technical means: a bridge structure safety evaluation method based on big data comprises the following steps:
the method comprises the following steps: obtaining the score of each type of measuring point, and obtaining each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point;
step two: acquiring a monitoring item score of a bridge superstructure monitored by a sensor, a monitoring item score of a bridge substructure monitored by the sensor and a monitoring item score of a bridge deck system monitored by the sensor;
step three: acquiring a safety score of the bridge based on sensor monitoring;
step four: and acquiring a comprehensive score of the bridge based on monitoring and detection.
The invention is based on the bridge health monitoring system, calls real-time monitoring data at any time, carries out real-time safety scoring on the bridge health condition, reduces human interference, gives scientific scoring with timeliness and objectivity, integrates monitoring and detecting results, has more comprehensive and convincing results, and realizes daily routine evaluation of the bridge health condition and timely evaluation after major accidents occur.
Further, the types of the measuring points comprise displacement, inclination angle, stress, cable force, deflection, cracks, acceleration and fundamental frequency, wherein the measuring points of the types of the displacement, the inclination angle, the stress, the cable force and the deflection adopt an expected value variation coefficient method to calculate the values, the measuring points of the types of the cracks adopt an infinite series method to calculate the values, the measuring points of the types of the acceleration adopt a 2-norm method to calculate the values, and the measuring points of the types of the fundamental frequency adopt a deviation value method to calculate the values.
Further, the first step comprises:
using formulas
Obtaining the ith monitoring item score of the bridge superstructure, wherein D1iThe calculated value of the data of each measuring point of the same type of the upper structure of the bridge is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge substructure, D2iThe calculated value of the data of each measuring point of the same type of the bridge lower structure is represented;
using formulas
Obtaining the ith monitoring item score of the bridge deck system, D3iAnd (4) representing the calculated score of the data of each measuring point of the same type of the bridge deck system.
Further, the second step comprises:
using formulas
Acquiring a monitoring item score of the bridge superstructure monitored by the sensor, wherein l represents the type number of monitoring indexes of the bridge superstructure, and phi represents the weight factor of the monitoring indexes of the bridge superstructure;
using formulas
Acquiring the monitoring item score of the bridge substructure monitored by the sensor, wherein J represents the number of monitoring index types of the bridge substructure,
representing a monitoring index weight factor of a bridge substructure;
using formulas
And acquiring a monitoring item score of the bridge deck system monitored by the sensor, wherein K represents the type number of monitoring indexes of the bridge deck system, and delta represents the weight factor of the monitoring indexes of the bridge deck system.
Further, the third step includes:
the safety score of the bridge based on sensor monitoring is obtained by using a formula MCI (PMCI + CTCI + DMCI + zeta), wherein xi is an upper structure weight coefficient, psi is a lower structure weight coefficient, and zeta represents a bridge deck system weight coefficient.
Further, the fourth step includes:
using formulas
And acquiring a comprehensive score of the bridge based on monitoring and detection, wherein BCI represents a BCI score value, alpha represents a first weight coefficient, beta represents a second weight coefficient, and gamma represents a third weight coefficient.
The invention also provides a bridge structure safety evaluation device based on big data, which comprises:
the first acquisition module is used for acquiring the score of each type of measuring point, and acquiring each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point;
the second acquisition module is used for acquiring the monitoring item scores of the upper bridge structure monitored by the sensor, the monitoring item scores of the lower bridge structure monitored by the sensor and the monitoring item scores of the bridge deck system monitored by the sensor;
the first scoring module is used for acquiring safety scores of the bridge based on sensor monitoring;
and the second grading module is used for acquiring the comprehensive grade of the bridge based on monitoring and detection.
Further, the types of the measuring points comprise displacement, inclination angle, stress, cable force, deflection, cracks, acceleration and fundamental frequency, wherein the measuring points of the types of the displacement, the inclination angle, the stress, the cable force and the deflection adopt an expected value variation coefficient method to calculate the values, the measuring points of the types of the cracks adopt an infinite series method to calculate the values, the measuring points of the types of the acceleration adopt a 2-norm method to calculate the values, and the measuring points of the types of the fundamental frequency adopt a deviation value method to calculate the values.
Further, the first obtaining module is further configured to:
using formulas
Obtaining the ith monitoring item score of the bridge superstructure, wherein D1iThe calculated value of the data of each measuring point of the same type of the upper structure of the bridge is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge substructure, D2iThe calculated value of the data of each measuring point of the same type of the bridge lower structure is represented;
using formulas
Obtaining the ith monitoring item score of the bridge deck system, D3iAnd (4) representing the calculated score of the data of each measuring point of the same type of the bridge deck system.
Further, the second obtaining module is further configured to:
using formulas
Acquiring a monitoring item score of the bridge superstructure monitored by the sensor, wherein l represents the type number of monitoring indexes of the bridge superstructure, and phi represents the weight factor of the monitoring indexes of the bridge superstructure;
using formulas
Acquiring the monitoring item score of the bridge substructure monitored by the sensor, wherein J represents the number of monitoring index types of the bridge substructure,
representing a monitoring index weight factor of a bridge substructure;
using formulas
And acquiring a monitoring item score of the bridge deck system monitored by the sensor, wherein K represents the type number of monitoring indexes of the bridge deck system, and delta represents the weight factor of the monitoring indexes of the bridge deck system.
Further, the first scoring module is further configured to:
the safety score of the bridge based on sensor monitoring is obtained by using a formula MCI (PMCI + CTCI + DMCI + zeta), wherein xi is an upper structure weight coefficient, psi is a lower structure weight coefficient, and zeta represents a bridge deck system weight coefficient.
Further, the second scoring module is further configured to:
using formulas
And acquiring a comprehensive score of the bridge based on monitoring and detection, wherein BCI represents a BCI score value, alpha represents a first weight coefficient, beta represents a second weight coefficient, and gamma represents a third weight coefficient.
The invention has the advantages that: the invention is based on the bridge health monitoring system, calls real-time monitoring data at any time, carries out real-time safety scoring on the bridge health condition, reduces human interference, gives scientific scoring with timeliness and objectivity, integrates monitoring and detecting results, has more comprehensive and convincing results, and realizes daily routine evaluation of the bridge health condition and timely evaluation after major accidents occur.
Drawings
FIG. 1 is a flowchart of a bridge structure safety evaluation method based on big data according to an embodiment of the present invention;
fig. 2 is an algorithm flowchart of a bridge structure safety evaluation method based on big data according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1 and 2, a bridge structure safety evaluation method based on big data includes:
step S1: obtaining the score of each type of measuring point, and obtaining each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point; the types of the measuring points comprise displacement, inclination angle, stress, cable force, deflection, crack, acceleration and fundamental frequency, wherein the measuring points of the types of displacement, inclination angle, stress, cable force and deflection adopt an expected value variation coefficient method to calculate the values, the measuring points of the types of crack adopt an infinite series method to calculate the values, the measuring points of the types of acceleration adopt a 2-norm method to calculate the values, and the measuring points of the types of fundamental frequency adopt a deviation value method to calculate the values. The point score calculation is described in detail below.
Due to different types and numbers of sensors, the purpose of monitoring the bridge structure is different, but the sensors of the bridge health monitoring system can be mainly classified into a structure sensing type and an environment sensing type. In the safety evaluation process of the bridge structure, the data collected by the structure sensing sensors (acceleration, strain, displacement, cable force and the like) are mainly evaluated, and the environment sensing sensors (temperature, humidity and the like) are mainly used for compensating and correcting the data collected by the structure sensing sensors, so that the method is not substituted for evaluation temporarily.
The calculation of each measuring point is divided into four types, the four types of methods are conventional processing methods in the prior art, specific principles of the methods are not described in detail, the calculation basis is roughly introduced below, and specific algorithms are selected according to the following table for calculation.
TABLE 1 measurement Point calculation method classification
| Participating in calculating measuring point Di subentry | Classification of computing methods |
| Displacement of | 1 |
| Inclination angle | 1 |
| Stress | 1 |
| Cable force | 1 |
| Deflection | 1 |
| Crack (crack) | 2 |
| Acceleration (time domain) | 3 |
| Acceleration (frequency domain) | 4 |
The calculation method 1: method of expected value coefficient of variation
Basic formula
Desired values:
standard deviation:
coefficient of variation:
note:
δ is a reference value, X ', δ' are values to be evaluated;
the calculation methods of the reference value and the value to be evaluated are consistent, but the value ranges are different, specifically see table 2, and the scoring formula is as follows:
TABLE 2 method for calculating the item values of each monitoring index
| Index (I) | Desired value deviation score | Weight value | Coefficient of variation bias | Weight value |
| Displacement of | DE | α1＝0.8 | DD | α2＝0.2 |
| Deflection | DE | α1＝0.8 | DD | α2＝0.2 |
| Inclination angle | DE | α1＝0.8 | DD | α2＝0.2 |
| Stress | DE | α1＝0.8 | DD | α2＝0.2 |
| Cable force | DE | α1＝0.8 | DD | α1＝0.2 |
TABLE 3 DE, DD bottom scoring criteria
The calculation method 2 comprises the following steps: infinite series method
The basic formula: infinite norm:
TABLE 4 Infinite norm score criterion
Note: crack width exceeding limit value of 0 min
The calculation method 3: method of 2-norm
Basic formula (2-norm):
TABLE 52 norm scoring criteria
The calculation method 4: method of deviation value
TABLE 6 fundamental frequency scoring criteria
The reference value and the expected value (or the value to be evaluated) need to be learned by a monitoring system, are corrected and adjusted after running for a period of time, and each sensor needs to be set one by one. The calculation methods 2, 3 and 4 are the same as 1, and the data of the effective sensors need to be calculated into scores and expected values.
Using formulas in combination with the above
Obtaining the ith monitoring item score of the bridge superstructure, wherein D1iThe calculated value of the data of each measuring point of the same type of the upper structure of the bridge is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge substructure, D2iThe calculated value of the data of each measuring point of the same type of the bridge lower structure is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge deck system, D3iAnd the calculated value of the data of each measuring point of the same type of the bridge deck system is represented, and N represents the total number of the measuring points of the same type.
Step S2: acquiring a monitoring item score of a bridge superstructure monitored by a sensor, a monitoring item score of a bridge substructure monitored by the sensor and a monitoring item score of a bridge deck system monitored by the sensor; the specific process is as follows:
using formulas
Acquiring a monitoring item score of the bridge superstructure monitored by the sensor, wherein l represents the type number of monitoring indexes of the bridge superstructure, and phi represents the weight factor of the monitoring indexes of the bridge superstructure;
using formulas
Acquiring the monitoring item score of the bridge substructure monitored by the sensor, wherein J represents the number of monitoring index types of the bridge substructure,
representing a monitoring index weight factor of a bridge substructure;
using formulas
And acquiring a monitoring item score of the bridge deck system monitored by the sensor, wherein K represents the type number of monitoring indexes of the bridge deck system, and delta represents the weight factor of the monitoring indexes of the bridge deck system.
The weight factor phi of the monitoring index,
And δ is related to the importance of this index in structural safety.
The values of the monitoring index weight factors are shown in table 7.
TABLE 7 parts weight factor distribution Table
Note: if some monitoring index has deletion, mutation or other abnormal conditions, discarding the index; the specific method distributes the weight of the missing index to other normal index items according to the original weight proportion.
Step S3: acquiring a safety score of the bridge based on sensor monitoring; the specific process is as follows:
the safety score of the bridge based on sensor monitoring is obtained by using a formula MCI (PMCI + CTCI + DMCI + zeta), wherein xi is an upper structure weight coefficient, psi is a lower structure weight coefficient, and zeta represents a bridge deck system weight coefficient.
The values of the weight coefficients are shown in table 8.
TABLE 8 MCI weight coefficient assignment values
| Serial number | Bridge name | ξ | ψ | ζ |
| 1 | Simply supported beam bridge | 0.90 | 0.00 | 0.10 |
| 2 | Continuous beam bridge | 0.80 | 0.10 | 0.10 |
| 3 | Cable-stayed bridge | 0.84 | 0.10 | 0.06 |
| 4 | Tie rod arch | 0.64 | 0.30 | 0.06 |
Step S4: acquiring a monitoring and detection-based comprehensive score M-BCI of a bridge, and the specific process comprises the following steps:
using formulas
Acquiring comprehensive scores of the bridge based on monitoring and detection, wherein BCI represents BCI score values (BCI is a bridge condition index, is introduced from urban bridge maintenance technical standard (CJJ99-2017) and represents the intact state of the bridge structure), alpha represents a first weight coefficient, beta represents a second weight coefficient, gamma represents a third weight coefficient, and alpha, beta and gamma are constants obtained by referring to the technical standard, and the method can be used for multiple times of experiments according to actual needsTo be set up.
Through the technical scheme, the bridge structure safety evaluation method based on the big data, provided by the invention, is based on a bridge health monitoring system, real-time monitoring data is called at any time, the bridge health condition is scored in real time, the artificial interference is reduced, meanwhile, scientific scoring with timeliness and objectivity is given, the monitoring and detecting results are integrated, the results are more comprehensive and convincing, and daily routine evaluation of the bridge health condition and timely evaluation after occurrence of major accidents are realized.
Example 2
Corresponding to embodiment 1 of the present invention, embodiment 2 of the present invention further provides a bridge structure safety evaluation device based on big data, where the device includes:
the first acquisition module is used for acquiring the score of each type of measuring point, and acquiring each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point;
the second acquisition module is used for acquiring the monitoring item scores of the upper bridge structure monitored by the sensor, the monitoring item scores of the lower bridge structure monitored by the sensor and the monitoring item scores of the bridge deck system monitored by the sensor;
the first scoring module is used for acquiring safety scores of the bridge based on sensor monitoring;
and the second grading module is used for acquiring the comprehensive grade of the bridge based on monitoring and detection.
Specifically, the types of the measuring points comprise displacement, inclination angle, stress, cable force, deflection, crack, acceleration and fundamental frequency, wherein the measuring points of the types of displacement, inclination angle, stress, cable force and deflection adopt an expected value coefficient of variation method to calculate the value, the measuring points of the types of crack adopt an infinite series method to calculate the value, the measuring points of the types of acceleration adopt a 2-norm method to calculate the value, and the measuring points of the types of fundamental frequency adopt a deviation value method to calculate the value.
Specifically, the first obtaining module is further configured to:
using formulas
Obtaining the ith monitoring item score of the bridge superstructure, wherein D1iThe calculated value of the data of each measuring point of the same type of the upper structure of the bridge is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge substructure, D2iThe calculated value of the data of each measuring point of the same type of the bridge lower structure is represented;
using formulas
Obtaining the ith monitoring item score of the bridge deck system, D3iAnd (4) representing the calculated score of the data of each measuring point of the same type of the bridge deck system.
Specifically, the second obtaining module is further configured to:
using formulas
Acquiring a monitoring item score of the bridge superstructure monitored by the sensor, wherein l represents the type number of monitoring indexes of the bridge superstructure, and phi represents the weight factor of the monitoring indexes of the bridge superstructure;
using formulas
Acquiring the monitoring item score of the bridge substructure monitored by the sensor, wherein J represents the number of monitoring index types of the bridge substructure,
representing a monitoring index weight factor of a bridge substructure;
using formulas
And acquiring a monitoring item score of the bridge deck system monitored by the sensor, wherein K represents the type number of monitoring indexes of the bridge deck system, and delta represents the weight factor of the monitoring indexes of the bridge deck system.
Specifically, the first scoring module is further configured to:
the safety score of the bridge based on sensor monitoring is obtained by using a formula MCI (PMCI + CTCI + DMCI + zeta), wherein xi is an upper structure weight coefficient, psi is a lower structure weight coefficient, and zeta represents a bridge deck system weight coefficient.
Specifically, the second scoring module is further configured to:
using formulas
And acquiring a comprehensive score of the bridge based on monitoring and detection, wherein BCI represents a BCI score value, alpha represents a first weight coefficient, beta represents a second weight coefficient, and gamma represents a third weight coefficient.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A bridge structure safety evaluation method based on big data is characterized by comprising the following steps:
the method comprises the following steps: obtaining the score of each type of measuring point, and obtaining each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point;
step two: acquiring a monitoring item score of a bridge superstructure monitored by a sensor, a monitoring item score of a bridge substructure monitored by the sensor and a monitoring item score of a bridge deck system monitored by the sensor;
step three: acquiring a safety score of the bridge based on sensor monitoring;
step four: and acquiring a comprehensive score of the bridge based on monitoring and detection.
2. The bridge structure safety evaluation method based on big data according to claim 1, characterized in that the types of the measuring points comprise displacement, inclination angle, stress, cable force, deflection, crack, acceleration and fundamental frequency, wherein the measuring points with the types of displacement, inclination angle, stress, cable force and deflection adopt an expected value coefficient of variation method to calculate the score, the measuring points with the types of crack adopt an infinite number method to calculate the score, the measuring points with the types of acceleration adopt a 2-norm method to calculate the score, and the measuring point deviation value with the types of fundamental frequency adopts a value of variation method to calculate the score.
3. The bridge structure safety evaluation method based on big data according to claim 1, wherein the first step comprises:
using formulas
Obtaining the ith monitoring item score of the bridge superstructure, wherein D1iThe calculated value of the data of each measuring point of the same type of the upper structure of the bridge is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge substructure, D2iThe calculated value of the data of each measuring point of the same type of the bridge lower structure is represented;
using formulas
Obtaining the ith monitoring item score of the bridge deck system, D3iAnd (4) representing the calculated score of the data of each measuring point of the same type of the bridge deck system.
4. The bridge structure safety evaluation method based on big data according to claim 3, wherein the second step comprises:
using formulas
Acquiring a monitoring item score of the bridge superstructure monitored by the sensor, wherein l represents the type number of monitoring indexes of the bridge superstructure, and phi represents the weight factor of the monitoring indexes of the bridge superstructure;
using formulas
Acquiring the monitoring item score of the bridge substructure monitored by the sensor, wherein J represents the number of monitoring index types of the bridge substructure,
representing a monitoring index weight factor of a bridge substructure;
using formulas
And acquiring a monitoring item score of the bridge deck system monitored by the sensor, wherein K represents the type number of monitoring indexes of the bridge deck system, and delta represents the weight factor of the monitoring indexes of the bridge deck system.
5. The bridge structure safety evaluation method based on big data according to claim 4, wherein the third step comprises:
the safety score of the bridge based on sensor monitoring is obtained by using a formula MCI (PMCI + CTCI + DMCI + zeta), wherein xi is an upper structure weight coefficient, psi is a lower structure weight coefficient, and zeta represents a bridge deck system weight coefficient.
6. The bridge structure safety evaluation method based on big data according to claim 4, wherein the fourth step comprises:
using formulas
And acquiring a comprehensive score of the bridge based on monitoring and detection, wherein BCI represents a BCI score value, alpha represents a first weight coefficient, beta represents a second weight coefficient, and gamma represents a third weight coefficient.
7. A bridge structure safety evaluation device based on big data is characterized by comprising:
the first acquisition module is used for acquiring the score of each type of measuring point, and acquiring each monitoring item score of the bridge upper structure, each monitoring item score of the bridge lower structure and each monitoring item score of the bridge deck system according to the score of each type of measuring point;
the second acquisition module is used for acquiring the monitoring item scores of the upper bridge structure monitored by the sensor, the monitoring item scores of the lower bridge structure monitored by the sensor and the monitoring item scores of the bridge deck system monitored by the sensor;
the first scoring module is used for acquiring safety scores of the bridge based on sensor monitoring;
and the second grading module is used for acquiring the comprehensive grade of the bridge based on monitoring and detection.
8. The bridge structure safety evaluation device based on big data of claim 7, wherein the types of the measuring points comprise displacement, inclination angle, stress, cable force, deflection, crack, acceleration and fundamental frequency, wherein the measuring points with the types of displacement, inclination angle, stress, cable force and deflection adopt an expected value coefficient of variation method to calculate the score, the measuring points with the types of crack adopt an infinite series method to calculate the score, the measuring points with the types of acceleration adopt a 2-norm method to calculate the score, and the measuring point deviation value with the types of fundamental frequency adopts a value of variation method to calculate the score.
9. The big-data-based bridge structure safety evaluation method according to claim 7, wherein the first obtaining module is further configured to:
using formulas
Obtaining the ith monitoring item score of the bridge superstructure, wherein D1iThe calculated value of the data of each measuring point of the same type of the upper structure of the bridge is represented, and N represents the total number of the measuring points of the same type;
using formulas
Obtaining the ith monitoring item score of the bridge substructure, D2iThe calculated value of the data of each measuring point of the same type of the bridge lower structure is represented;
using formulas
Obtaining the ith monitoring item score of the bridge deck system, D3iAnd (4) representing the calculated score of the data of each measuring point of the same type of the bridge deck system.
10. The big-data-based bridge structure safety evaluation method according to claim 7, wherein the second acquisition module is further configured to:
using formulas
Acquiring a monitoring item score of the bridge superstructure monitored by the sensor, wherein l represents the type number of monitoring indexes of the bridge superstructure, and phi represents the weight factor of the monitoring indexes of the bridge superstructure;
using formulas
Acquiring the monitoring item score of the bridge substructure monitored by the sensor, wherein J represents the number of monitoring index types of the bridge substructure,
representing a monitoring index weight factor of a bridge substructure;
using formulas
And acquiring a monitoring item score of the bridge deck system monitored by the sensor, wherein K represents the type number of monitoring indexes of the bridge deck system, and delta represents the weight factor of the monitoring indexes of the bridge deck system.
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