CN-121998619-A - Digital twinning-based road and bridge intelligent maintenance supervision method

CN121998619ACN 121998619 ACN121998619 ACN 121998619ACN-121998619-A

Abstract

The invention relates to the technical field of digital twinning, in particular to an intelligent maintenance supervision method for a road bridge based on digital twinning, which comprises the steps of constructing a digital twinning model of the bridge to be analyzed, collecting monitoring data of monitoring points of the bridge to be analyzed, synchronizing the monitoring data to the digital twinning model, determining whether a division mode is adjusted to be associated division from grid division according to a structural mutation mean difference coefficient and a structural foundation difference sedimentation characterization coefficient, determining a supervision state based on a damage index and monitoring abnormality of a key area, determining maintenance or maintenance analysis for the bridge to be analyzed according to the supervision state, and determining whether to adjust supervision period duration based on fitting deviation values if maintenance is not needed. The invention can improve the maintenance decision precision.

Inventors

WANG CHUNGUANG
ZHANG BINGJIAN
WANG SHENGNAN
LIU JINGKUAN
HU RONGZHENG
ZHANG JIALI

Assignees

北京中交工程仪器研究所

Dates

Publication Date: 20260508
Application Date: 20260126

Claims (10)

1. The intelligent maintenance supervision method for the road and bridge based on digital twinning is characterized by comprising the following steps of: Constructing a digital twin model of the bridge to be analyzed; collecting monitoring data of each monitoring point of the bridge to be analyzed, and synchronizing the monitoring data to the digital twin model; Determining whether to adjust the dividing mode from grid division to association division according to the structural mutation mean difference coefficient and the structural foundation differential settlement characterization coefficient; determining a supervision state based on a damage index and monitoring abnormality degree of a key area, and determining maintenance or maintenance analysis for a bridge to be analyzed according to the supervision state, wherein the key area is determined based on an abnormality characterization value, and the damage index is determined based on a global influence coefficient; In maintenance analysis, whether to adjust a judging standard from a gradient change value to a combined standard of stress response interference degree and gradient change value is judged based on the adjacent influence coefficient, and whether to carry out maintenance is determined based on the determined judging standard; if maintenance is not needed, determining whether to adjust the supervision period duration based on the fitting deviation value.
2. The intelligent maintenance supervision method of the road and bridge based on digital twinning according to claim 1, wherein the division mode is adjusted from grid division to association division for the bridge to be analyzed, wherein the structural mutation mean difference coefficient is greater than or equal to a preset structural mutation mean difference coefficient or the structural foundation differential settlement characterization coefficient is greater than or equal to a preset structural foundation differential settlement characterization coefficient.
3. The intelligent maintenance and supervision method for roads and bridges based on digital twinning according to claim 2, wherein in the association division, the association areas are determined based on the diffusion association coefficient and the mechanical response coupling degree, and each association area is recorded as a division area.
4. The intelligent maintenance and supervision method for roads and bridges based on digital twinning according to claim 3, wherein in grid division, the grid size is determined based on monitoring abnormality; the grid size and the monitoring anomaly are in negative correlation.
5. The intelligent maintenance and supervision method for roads and bridges based on digital twinning according to claim 4, wherein the key area is a divided area with an abnormal characterization value greater than or equal to a preset abnormal characterization value.
6. The intelligent maintenance supervision method for the road and bridge based on digital twinning according to claim 1, wherein maintenance is performed on the bridge to be analyzed in a supervision state in which the damage index is greater than or equal to a preset damage index or the monitoring anomaly is greater than or equal to a preset monitoring anomaly.
7. The intelligent maintenance and supervision method for roads and bridges based on digital twinning according to claim 6, wherein maintenance analysis is performed on bridges to be analyzed whose supervision states are damage indexes smaller than a preset damage index and whose monitoring anomaly is smaller than a preset monitoring anomaly.
8. The intelligent maintenance supervision method for roads and bridges based on digital twinning according to claim 7, wherein the judgment standard is adjusted from a gradient change value to a combined standard of stress response interference degree and gradient change value aiming at the bridge to be analyzed with the proximity influence coefficient being greater than or equal to a preset proximity influence coefficient.
9. The intelligent maintenance and supervision method for roads and bridges based on digital twinning according to claim 7, wherein the confirming mode of the damage index comprises: if the global influence coefficient is larger than the preset global influence coefficient, determining a damage index based on the global influence coefficient; If the global impact coefficient is less than or equal to the predetermined global impact coefficient, then the damage index is determined based on the applied test anomaly.
10. The digital twinning-based road and bridge intelligent maintenance supervision method according to claim 8, wherein whether to reduce and adjust the supervision period duration is determined based on the fitting deviation value; Reducing and adjusting the length of a supervision period of the bridge to be analyzed, wherein the fitting deviation value is larger than a preset fitting deviation value; and the reduced value of the supervision period duration and the fitting deviation value are in positive correlation.

Description

Digital twinning-based road and bridge intelligent maintenance supervision method Technical Field The invention relates to the technical field of digital twinning, in particular to an intelligent maintenance supervision method for roads and bridges based on digital twinning. Background Road and bridge is used as the core of traffic infrastructure, and long-term service of the road and bridge faces the influence of repeated actions of traffic load, temperature and humidity changes, acid rain erosion and other multi-factor coupling, so that damages such as crack expansion, steel bar corrosion, support settlement and the like are easy to occur, and the road and bridge is directly related to traffic safety and structural durability. Along with the expansion of the road network scale and the increase of the service life, the traditional maintenance supervision mode is mostly dependent on manual inspection and periodic sampling detection, and has the defects of long detection period, data discretization, disease identification delay, strong subjectivity of maintenance decision and the like, so that the maintenance efficiency and the accuracy are poor. Therefore, how to improve the intelligent level of maintenance supervision and disease early warning timeliness of roads and bridges is a technical problem to be solved urgently by the technicians in the field. Chinese patent publication No. CN108873921A discloses a bridge detection method and system based on a digital twin technology, wherein the method comprises the steps of collecting strain distribution values, vibration spectrum values and environment load spectrum values in real time through a sensor network deployed on a physical bridge, generating a structure response data set and synchronizing the structure response data set to the digital twin body, calculating damage index values and accumulated damage values based on the structure response data set, inputting the damage index values and the accumulated damage values into preset safety criteria, calculating safety margin coefficient values and failure risk level values, calculating residual life prediction values based on the safety margin coefficient values and the environment load spectrum values, synchronously correcting degradation rate values of the digital twin body, generating a priority maintenance instruction according to the failure risk level values, the residual life prediction values and the safety margin coefficient values, and feeding back maintenance effect data to the digital twin body after execution to complete updating. However, the scheme has the following problems that the analysis method cannot be dynamically adjusted according to the actual state of the bridge, the suitability of the method for the fine and dynamic maintenance supervision of the complex bridge structure is insufficient, the early characteristics of the local bridge diseases are difficult to accurately capture, and the maintenance decision precision is poor. Disclosure of Invention Therefore, the invention provides an intelligent maintenance supervision method for roads and bridges based on digital twinning, which is used for solving the problems that in the prior art, an analysis method cannot be dynamically adjusted according to the actual state of a bridge, the suitability of the maintenance supervision for the refinement and the dynamic maintenance of a complex bridge structure is insufficient, the early characteristics of local diseases of the bridge are difficult to accurately capture, and the maintenance decision precision is poor. In order to achieve the above purpose, the invention provides a digital twinning-based road and bridge intelligent maintenance supervision method, which comprises the following steps: Constructing a digital twin model of the bridge to be analyzed; collecting monitoring data of each monitoring point of the bridge to be analyzed, and synchronizing the monitoring data to the digital twin model; Determining whether to adjust the dividing mode from grid division to association division according to the structural mutation mean difference coefficient and the structural foundation differential settlement characterization coefficient; determining a supervision state based on a damage index and monitoring abnormality degree of a key area, and determining maintenance or maintenance analysis for a bridge to be analyzed according to the supervision state, wherein the key area is determined based on an abnormality characterization value, and the damage index is determined based on a global influence coefficient; In maintenance analysis, whether to adjust a judging standard from a gradient change value to a combined standard of stress response interference degree and gradient change value is judged based on the adjacent influence coefficient, and whether to carry out maintenance is determined based on the determined judging standard; if maintenance is not needed, determining whether to adjust th