CN117113175A - Method for identifying cable body damage in anchor zone of pulling sling based on flagelliforme optimization algorithm - Google Patents
Method for identifying cable body damage in anchor zone of pulling sling based on flagelliforme optimization algorithm Download PDFInfo
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Abstract
The application discloses a bridge pull sling anchoring area damage identification method based on a flagstone optimization algorithm, which comprises the following steps: establishing a finite element model of a pull sling simple beam; based on the established finite element model of the pull-sling simple beam, inputting the set damage state to simulate various actual damages, and calculating the relative modal strain energy of each unit, thereby positioning the pseudo damage of the structural unit and further positioning the damage position of the pull-sling anchoring area; and taking the positioned cable body of the damage pulling cable rope anchoring area as a variable to be identified in the structure, performing iterative calculation on the constructed objective function by utilizing a flagfish optimization algorithm until the objective function reaches the minimum value or iteration is finished, and finally outputting the damage degree corresponding to the damage position. The bridge pulling sling anchoring area damage identification method based on the flagfish optimization algorithm can accurately position the damage position of the fulcrum part, identify the damage degree and has good noise resistance.
Description
Technical Field
The application belongs to the field of damage identification, and particularly relates to a method for identifying damage to a cable body in a cable pulling and hanging rope anchoring area based on a flagelliforme optimization algorithm.
Background
The cable is used as the main bearing member of cable-stayed bridge, suspension bridge, etc. and is located between bridge tower and bridge deck, and its cross section is small. The service environment of the pull sling is complex, and a protection system of the pull sling is extremely easy to be influenced by the external environment to fail. If the outer sheath is broken, the steel wires or the steel strands in the cable body are directly exposed to the corrosion environment in service, and particularly, some special service environments include: the severe acid rain area, the atmospheric heavy pollution area, the ultraviolet intense area, the areas adjacent to the ocean and the like, the cable body steel wire or the steel stranded wire can bear the coupling effect of alternating load (constant load, operating load, wind load and the like) and the corrosion environment, and the corrosion is aggravated. The steel wire of the pulling sling which is corroded and fatigued is suddenly broken, so that serious safety accidents and serious social influence are caused.
The design life of the pull sling is 20 years, compared with the corrosion environment of a pure dry salt fog area or a water accumulation area, the acid environment of the pull sling anchoring area with the double damage characteristics of the water accumulation area and the salt fog area has the dry-wet alternate action, the invasion speed of corrosive ions into the cable body is definitely faster, and under the coupling action of service load, the electrochemical corrosion and stress corrosion of the cable body occur at the position, and the corrosion fatigue damage is even worse. The service life of the pull sling is determined by the service life of the cable body at the most serious part of diseases, and the dry-wet alternate corrosion environment of the lower anchoring area is definitely the most unfavorable service environment, and the service life of the pull sling is directly influenced if the cable body has the diseases.
At present, the service condition of the cable body in the anchoring area of the pull sling is not easy to be ignored due to conventional detection, and the service life of the cable body under the dry-wet alternating action of the acid environment in the anchoring area often influences the normal service limit state of the whole pull sling, so that related researches are reported at home and abroad. At present, the detection of the anchor area of the pull-sling of most bridges is limited to manual periodic detection, and the outer protective cover of the anchor area is removed by manual means to carry out naked eye observation and instrument measurement, so that the service condition of the pull-sling of a cable duct part is not detected by good detection means at present, and the detection of the diseases of the pull-sling has missed detection and misjudgment; and the detection of the pull sling is that certain danger exists in the overhead operation, and certain difficulty is brought to the inspection of the bridge pull sling. On the other hand, the detection of the manual opposite-pulling sling may be overlooked, the disease information can not be mastered and the accuracy of the detection result can not be completely ensured.
Structural damage identification is the most important link in structural health monitoring (Structural Health Monitoring, SHM). At present, the damage identification method based on the dynamic characteristics is mainly used for identifying whether the cable body in the bridge cable anchoring area has diseases or not by using the dynamic characteristics of the bridge to pull the cable as the boundary condition of the bridge structure, and if the cable body in the cable anchoring area is damaged, the rigidity of the cable body is changed, so that the rigidity change of the cable structure is affected, and the dynamic characteristics of the structure are affected.
When the structure is damaged, the dynamic characteristics of the structure can be changed, whether the structure is damaged is judged through the change of the dynamic parameter information, the dynamic parameters of the structure can reflect the local characteristics of the structure, and the performance of the whole structure can be analyzed. The recognition method based on the dynamic characteristics becomes a research hotspot in the damage recognition field more and more due to the advantages of mature calculation theory, various recognition index types and the like. In recent years, scholars have also proposed identification indexes combining structural dynamic parameters with knowledge of other disciplines theory, and the indexes are more sensitive to damage and better in robustness. However, the damage identification method based on signal processing can only judge the damage position of the structure, and the damage degree of the structure is difficult to quantitatively analyze.
Damage identification after nondestructive detection is greatly influenced by environment, detection results are often distorted, and damage identification is difficult. Therefore, a brand new method for identifying damage to the cable body in the anchor region of the pull-sling of the bridge is needed, so that the damage position of the anchor region of the pull-sling is accurately positioned, and the damage degree is identified.
Disclosure of Invention
In view of the above, the application aims to provide a method for identifying cable damage in a cable pulling and hanging rope anchoring area based on a flagelliforme optimization algorithm. The application aims to solve the problems that the existing method is poor in accuracy and difficult to quantitatively analyze the damage degree of the structure.
In order to achieve the purpose, the application provides a method for identifying damage to a rope body in a rope pulling and hanging rope anchoring area based on a flagfish optimization algorithm, which comprises the following steps:
s1, establishing an initial finite element model;
simplifying the finished pull sling into a simply supported beam taking the anchoring areas at two ends as supporting points, and establishing an initial finite element model by adopting unit relative modal strain energy indexes;
s2, dynamic testing of pre-damage structure
Carrying out structural dynamic test on the intact pull sling by using a magnetic leakage nondestructive testing technology;
s3, correcting the initial finite element model by comparing the dynamic test result of the structure before damage to obtain a reference finite element model;
s4, through damage tests of the cable body steel wire under various working conditions, presetting parameters, and establishing a finite element model for damage identification;
s5, dynamic test of damaged structure
S2, carrying out structural dynamic test on the cable body in the anchor area of the in-service pull sling by using a magnetic leakage nondestructive testing technology;
s6, establishing a damage identification objective function according to the finite element model for damage identification established in the step S4 and test data obtained after dynamic test of the cable body structure of the anchor zone of the in-service pull-sling in the step S5;
s7, damage positioning
Adding noise, calculating an FUCR index by using measured frequency and vibration mode data, and determining the damage position of the cable body in the cable-pulling anchoring area based on the FUCR index;
s8, quantifying the damage degree
And (3) taking the positioned cable body damage position of the cable anchoring area as a variable to be identified in the structure, performing iterative calculation on the damage identification objective function established in the step (S6) by utilizing a flagfish optimization algorithm until the objective function reaches a minimum value or iteration is finished, and finally outputting the damage degree corresponding to the damage position.
Further, in the step S1, an initial finite element model is established by using a MATLAB numerical analysis platform.
Further, the specific steps of the step S3 are as follows:
comparing the dynamic test result of the structure before damage, selecting correction parameters to correct the initial finite element model, and obtaining a reference finite element model if convergence; if the initial finite element model is not converged, redesigning the correction parameters, and revising the initial finite element model again until the initial finite element model is converged.
Further, in the step S7, the formula of adding noise is:
wherein:and->The mode shape is the mode shape of the ith order noiseless mode shape and the mode shape under noise pollution, and the mode shape component under the jth degree of freedom; epsilon represents the noise level; η represents a random number in normal distribution, the mean value is 0, and the variance is 1.
Further, in the step S8, when the anchoring zone cable damage is identified by adopting the flagelliforme optimization algorithm, the population size is set to 100, the maximum iteration number is set to 50, and the parameter a=4, epsilon=0.001 for controlling the attack force.
The application has the beneficial effects that:
the application discloses a method for identifying damage to a cable body in a pull-sling anchoring area based on a flagfish optimization algorithm, which takes a simple supporting beam with the pull-sling anchoring area as a fulcrum as a research object to carry out numerical simulation, and can know that the damage position and the damage degree of a fulcrum part can be accurately positioned and identified for different damage working conditions of the fulcrum of the simple supporting beam according to damage identification results; the method has high accuracy and good noise resistance, and the maximum identification error of the fulcrum damage of the simply supported beam is 1.95 percent and is within the error allowable range of 5 percent.
Additional advantages, objects, and features of the application will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the application. The objects and other advantages of the application may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
FIG. 1 is a flow chart of a method for identifying cable body damage in a pull-sling anchoring area based on a flagelliforme optimization algorithm;
FIG. 2 is a schematic illustration of an initial finite element model;
FIG. 3 is a flow chart of a flagelliforme optimization algorithm.
Detailed Description
In order to make the technical scheme, advantages and objects of the present application more clear, the technical scheme of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings of the embodiment of the present application. It will be apparent that the described embodiments are some, but not all, embodiments of the application. All other embodiments, which can be obtained by a person skilled in the art without creative efforts, based on the described embodiments of the present application belong to the protection scope of the present application.
As shown in fig. 1, the application provides a method for identifying cable damage in a pull-sling anchoring area based on a flagelliforme optimization algorithm, which comprises the following steps:
s1, establishing an initial finite element model;
simplifying the finished pull sling into a simply supported beam taking the anchoring areas at two ends as supporting points, and establishing an initial finite element model by adopting unit relative modal strain energy indexes; as shown in FIG. 2, an initial finite element model is built by adopting a MATLAB numerical analysis platform, the whole model is L m, the model is divided into n beam units, the unit types used are plane beam units with 2 nodes and 6 degrees of freedom, 1# and 2# represent upper and lower anchoring areas, and 1# and 2# fulcrums are simulated by adopting fixed units.
S2, dynamic testing of pre-damage structure
Carrying out structural dynamic test on the intact pull sling by using a magnetic leakage nondestructive testing technology;
s3, correcting the initial finite element model by comparing the dynamic test result of the structure before damage to obtain a reference finite element model;
comparing the dynamic test result of the structure before damage, selecting correction parameters to correct the initial finite element model, and obtaining a reference finite element model if convergence; if the initial finite element model is not converged, redesigning correction parameters, and revising the initial finite element model again until the initial finite element model is converged;
s4, through damage tests of the cable body steel wire under various working conditions, presetting parameters, and establishing a finite element model for damage identification;
s5, dynamic test of damaged structure
Carrying out structural dynamic test on the cable body in the anchor area of the in-service pull sling by utilizing the magnetic leakage nondestructive testing technology in the step S2;
s6, establishing a damage identification objective function according to the finite element model for damage identification established in the step S4 and test data obtained after dynamic test of the cable body structure of the anchor zone of the in-service pull-sling in the step S5;
s7, damage positioning: based on a finite element model of a pull sling simple supporting beam, inputting a set damage state to simulate various actual damages, and calculating the relative modal strain energy of each unit, so that the pseudo damage of the structural unit is positioned, and the damage position of an anchor area of the pull sling is positioned;
noise is added in the positioning process, FUCR indexes are calculated by using measured frequency and vibration mode data, and then the damage position of the cable body in the cable-pulling anchoring area is determined based on the FUCR indexes;
wherein:and->Respectively is index R j Mean and standard deviation of (a).
For different types of structural damage, the damage threshold FUCR can be selected according to practical conditions. In this embodiment, the damage threshold FUCR may be selected by using a damage threshold with a 95% confidence level, that is, a unit with a FUCR greater than 1 is regarded as a pseudo-damage unit, so as to achieve the purpose of positioning the anchoring region of the pull sling.
The formula for adding noise is:
wherein:and->The mode shape is the mode shape of the ith order noiseless mode shape and the mode shape under noise pollution, and the mode shape component under the jth degree of freedom; epsilon represents the noise level; η represents a random number in normal distribution, the mean value is 0, and the variance is 1.
S8, quantifying the damage degree
And (3) taking the positioned cable body damage position of the cable anchoring area as a variable to be identified in the structure, performing iterative calculation on the damage identification objective function established in the step (S6) by utilizing a flagfish optimization algorithm until the objective function reaches a minimum value or iteration is finished, and finally outputting the damage degree corresponding to the damage position. In the embodiment, when the flagelliforme optimization algorithm is adopted to identify the cable damage of the anchoring area, the population size is set to 100, the maximum iteration number is set to 50, and the parameters A=4 and epsilon=0.001 for controlling the attack force.
The optimization algorithm of the flagfish is shown in fig. 3, and the specific flow is as follows:
(1) Initializing population and parameters;
(2) Calculating fitness values of the flagstones and the sardines, and recording optimal fitness values and positions;
(3) Updating the position of the flagfish and the position of the sardine. If the attack force is less than 0.5, the values of alpha and beta are calculated, and the partial positions are updated. Otherwise, updating the sardine position with the new sardine position;
(4) Sardine and flagelliforme are replaced;
(5) Calculating all fitness values, and updating and recording optimal fitness values and positions;
(6) And if the iteration stopping condition is met, outputting a result, otherwise, turning to a second step to repeatedly execute.
For a cable structure considering the rigidity of the cable in the anchoring area, when the cable in the anchoring area is damaged, the mass of the cable in the anchoring area is basically unchanged, and the contribution of the cable in the anchoring area to the vibration of the cable structure only depends on the rigidity of the cable in the anchoring area. In finite element modeling, the method for processing the cable body rigidity of the anchoring area comprises the steps of enabling main diagonal elements corresponding to the freedom degree of the cable body of the anchoring area and the cable body rigidity K of the anchoring area in a unit rigidity matrix sp And (5) adding. Cable structure unit rigidity matrix K considering cable body rigidity of anchoring area under integral coordinate system e Is a constant matrix expressed by a unit length L, bending moment of inertia I and material elastic modulus E. For example, the stiffness matrix of the planar cable structural unit when the right end node considers the vertical stiffness of the cable body in the anchoring zone is:
when the cable body in the anchoring area is damaged, the rigidity of the cable body in the anchoring area is changed, so that the rigidity matrix of the unit is necessarily changed, and the relative modal strain energy of the unit is changed, thereby achieving the purpose of positioning the cable body damage in the anchoring area. Thus, a change in the stiffness matrix of the cell caused by damage to the cable body in the anchoring zone can be seen as a pseudo damage to the cell.
On the basis of the modal strain energy of the unit, the unit relative modal strain energy is improved, and the unit relative modal strain before and after structural damage is defined as:
the relative modal strain energy change rate index of the previous m-order modal participation calculation unit j is selected and used:
wherein: superscript d indicates the damage of the cable structure of the anchoring area; m is the number of modes participating in calculation; u (U) ij When the cable body in the anchoring area is not damaged, the modal strain energy of any unit j under the ith order modal shape; FU (FU) ij The relative modal strain of the unit before and after structural damage is given as the relative modal strain of the unit;when the cable body in the anchoring area is damaged, the rigidity matrix of the damaged cable body is changed, the corresponding unit is subjected to pseudo damage, and the mode strain energy of any unit j under the ith mode vibration mode is changed; k (K) j A stiffness matrix for element j; phi i Is the i-th order vibration mode vector; />Is phi i Is a transposed vector of (2); />The rigidity matrix of the unit j after the cable body in the anchoring area is damaged; />The i-th order vibration mode vector is obtained after the cable body of the anchoring area is damaged; r is R j The relative modal strain energy change rate index of the unit j is calculated for the participation of the first m-order modes.
Before structural analysis, the structural damage location has not been determined, and the damaged cell stiffness matrix and the overall stiffness matrix are unknown, so the pre-damage cell stiffness matrix and the overall stiffness matrix are used instead for approximate calculation. Therefore, the accuracy of identifying the damage is not affected, only the index value at the damage unit is larger, the result of the damage unit is more highlighted, and the accurate positioning of the damage is facilitated. Therefore, the cable body in the anchoring area can be positioned and analyzed according to the change rule of the modal strain energy before and after the pseudo damage is generated by the structural unit.
And taking the positioned cable body of the damage anchoring area as a variable to be identified in the structure, performing iterative calculation on the constructed objective function by using a flagelliforme optimization algorithm (SFO) until the objective function reaches a minimum value or the iteration is finished, and finally outputting the damage degree corresponding to the damage position.
The flagelliformer (Sailed Fish Optimizer, SFO) is a heuristic swarm intelligence algorithm proposed by s.shaprava in 2019. Its inspiration is derived from a group of hunting flagella, and simulates the predation process of the flagella. Compared with 6 advanced meta-heuristic algorithms such as GWO, PSO, ALO, SBO, GSA, GA, the SFO algorithm is superior to other algorithms in terms of exploring development capability or avoiding local optimal capability and convergence speed, and has good development and utilization functions.
Under the influence of different levels of noise, the cable body rigidity of the anchoring area of the pull sling is far smaller than the integral rigidity of the structure, so that the damage of the cable body part of the anchoring area causes small change in the vibration mode of the structure, the influence of the FUCR index on the noise is small, the maximum error of the recognition result of the simple beam under the influence of the noise is 2.40%, and the maximum error is within the error allowable range of 5%, which indicates that the method has good noise resistance. The method can effectively identify the damage position and the damage degree.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted without departing from the spirit and scope of the technical solution, and the present application is intended to be covered in the scope of the present application.
Claims (5)
1. The method for identifying the cable body damage of the pull-sling anchoring area based on the flagelliforme optimization algorithm is characterized by comprising the following steps of:
s1, establishing an initial finite element model;
simplifying the finished pull sling into a simply supported beam taking the anchoring areas at two ends as supporting points, and establishing an initial finite element model of a cable body of the anchoring area of the pull sling by adopting unit relative modal strain energy indexes;
s2, dynamic testing of pre-damage structure
Carrying out structural dynamic test on the cable body in the anchoring area of the intact pull sling by using a magnetic leakage nondestructive testing technology;
s3, correcting the initial finite element model by comparing with a dynamic test result of the structure before the cable body loss of the anchoring area to obtain a reference finite element model;
s4, establishing a finite element model for identifying the damage of the cable body in the anchoring area by means of the damage test of the cable body steel wire in the anchoring area under various working conditions and presetting parameters;
s5, dynamic test of damaged structure
Carrying out structural dynamic test on the cable body in the anchor area of the in-service pull sling by utilizing the magnetic leakage nondestructive testing technology in the step S2;
s6, establishing a damage identification objective function according to the finite element model of the cable body of the anchoring area, which is established in the step S4, and test data obtained after the dynamic test of the cable body structure of the anchoring area of the in-service pull-sling in the step S5;
s7, damage positioning
Adding noise, calculating an FUCR index by using measured frequency and vibration mode data, and determining the damage position of the cable body in the cable-pulling anchoring area based on the FUCR index;
s8, quantifying the damage degree
And (3) taking the positioned cable body damage position of the cable anchoring area as a variable to be identified in the structure, performing iterative calculation on the damage identification objective function established in the step (S6) by utilizing a flagfish optimization algorithm until the objective function reaches a minimum value or iteration is finished, and finally outputting the damage degree corresponding to the damage position.
2. The method for identifying cable damage in a pull-sling anchoring zone based on the flagelliforme optimization algorithm according to claim 1, which is characterized by comprising the following steps of: in the step S1, an initial finite element model is established by adopting a MATLAB numerical analysis platform.
3. The method for identifying the cable damage in the pull-sling anchoring area based on the optimization algorithm of the flagelliforme according to claim 1, wherein the specific steps of the step S3 are as follows:
comparing the dynamic test result of the structure before damage, selecting correction parameters to correct the initial finite element model, and obtaining a reference finite element model if convergence; if the initial finite element model is not converged, redesigning the correction parameters, and revising the initial finite element model again until the initial finite element model is converged.
4. The method for identifying cable damage in a pull-sling anchoring zone based on the optimization algorithm of flagelliforme according to claim 1, wherein in the step S7, the noise adding formula is as follows:
wherein:and->The mode shape is the mode shape of the ith order noiseless mode shape and the mode shape under noise pollution, and the mode shape component under the jth degree of freedom; epsilon represents the noise level; η represents a random number in normal distribution, the mean value is 0, and the variance is 1.
5. The method for identifying rope damage in a pull-sling anchoring zone based on a flagstone optimization algorithm according to claim 1, wherein in the step S8, when the rope damage identification in the anchoring zone is performed by adopting the flagstone optimization algorithm, the population size is set to 100, the maximum iteration number is set to 50, and the parameters a=4 and epsilon=0.001 for controlling the attack force.
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