CN-122020436-A - Mountain foundation pit construction monitoring and optimizing method, system, equipment and medium

CN122020436ACN 122020436 ACN122020436 ACN 122020436ACN-122020436-A

Abstract

The invention discloses a mountain foundation pit construction monitoring and optimizing method, a system, equipment and a medium, which relate to the field of power transmission and transformation engineering safety construction monitoring and comprise the steps of constructing a construction behavior feature library containing characteristic relations among all mode data, acquiring multi-mode sensing data, identifying effective construction signals according to a mode filtering rule library, carrying out path correction on the effective construction signals, locking a target construction tower leg foundation pit, extracting multi-mode features according to the position of the target construction tower leg foundation pit, carrying out feature matching binding based on a mechanical feature mapping relation, acquiring the target construction signals, calculating the matching degree of the mode timing sequence features in the construction behavior feature library and the target construction signals, determining construction behavior compliance, acquiring behavior risk pre-values of construction behaviors according to a gridding risk model, responding to a grading early warning mechanism according to the behavior risk pre-values, realizing more accurate construction positioning and accurate compliance judgment, and further improving construction monitoring efficiency.

Inventors

PENG MIN
WANG XIAOBO
LI MINFENG
YANG JUN
CHEN LINGJUN
WANG XUEYAN
HE JINBO
Zeng Chengshi
YAN HAO
RUAN LINGQI

Assignees

国网浙江省电力有限公司台州市路桥区供电公司
台州宏达电力建设有限公司

Dates

Publication Date: 20260512
Application Date: 20260416

Claims (10)

1. The mountain foundation pit construction monitoring and optimizing method is characterized by comprising the following steps of: Constructing a construction behavior feature library containing characteristic relations among all mode data; acquiring multi-mode sensing data, identifying effective construction signals according to a mode filtering rule base, and locking a target construction tower leg foundation pit after carrying out path correction on the effective construction signals; Extracting multi-mode features according to the position of a foundation pit of a target construction tower leg, and performing feature matching binding based on a mechanical feature mapping relation to obtain a target construction signal; Calculating the matching degree of the construction behavior feature library and the model time sequence feature in the target construction signal, determining the compliance of the construction behavior and acquiring a behavior risk pre-value of the construction behavior according to a gridding risk model; And responding to a hierarchical early warning mechanism according to the behavior risk pre-value.
2. The mountain pit construction monitoring and optimizing method according to claim 1, wherein the constructing a construction behavior feature library containing characteristic relations among the modal data comprises: Marking the historical multi-modal time sequence data according to construction behavior labels, wherein the construction behavior labels comprise construction types, intensities and corresponding relations of corresponding modal data characteristics; After the historical multi-mode time sequence data marked by the labels are normalized, adopting a TCN network and local attention mixed architecture to extract the mode time sequence fusion characteristics and the key mode characteristic learning of the construction behavior type, and obtaining the mode time sequence characteristic vector and the construction behavior type mapping probability; Establishing a feature memory library based on the vector index library, and determining a construction behavior feature template according to the modal time sequence feature vector and the construction behavior category mapping probability so as to finish the initialization of the feature memory library; and storing the dynamically acquired modal time sequence feature vector, the corresponding construction behavior label and the time sequence metadata into the feature memory library, finishing the updating of the feature memory and taking the updated feature memory library as a construction behavior feature library.
3. The method for monitoring and optimizing mountain foundation pit construction according to claim 1, wherein the steps of obtaining multi-mode sensing data, identifying effective construction signals according to a mode filtering rule base, performing path correction on the effective construction signals, and locking a target construction tower leg foundation pit comprise the following steps: the multi-modal sensing data at least comprises sound wave signals, vibration signals, infrared data, construction machinery labels and meteorological sensing data, and each modal sensing data forms a modal sensing group based on a time sequence; Extracting a critical value of an effective construction signal and a modal interconnection rule based on a modal filtering rule base, identifying and filtering a modal sensing group of a non-monitoring area, a false heat target and an environmental interference item, and acquiring the effective construction signal by using the residual modal sensing group; And correcting the deviation of the effective construction signal, and determining a target construction tower leg foundation pit according to the corrected effective construction signal.
4. The method for monitoring and optimizing mountain foundation pit construction according to claim 3, wherein said performing deviation correction on said effective construction signal and determining a target construction leg foundation pit based on the corrected effective construction signal comprises: three-dimensional terrain parameters of the center pile and each tower leg are obtained, wherein the three-dimensional terrain parameters comprise gradient, altitude difference and surface barrier distribution, so as to determine a terrain correction factor; Determining a wind speed correction factor based on an included angle between a wind direction and a sound wave movement direction, correcting a sound wave signal by combining the terrain correction factor and a weighted average sound velocity of the sound wave, and simulating a propagation path of the sound wave from a seismic source to a sensor by adopting a ray tracing method; determining standard propagation time of each path based on the propagation path of sound waves from the source to the sensor, performing anomaly verification on time differences of actual sound waves from the source to each group of microphones of the sensor, and calculating space coordinates of a construction source target according to the effective time differences and corrected sound wave signals; And calculating the linear distances between the construction seismic source target and the centers of the foundation pits of each tower leg according to the space coordinates of the construction seismic source target, and determining the target construction tower leg foundation pit by combining the construction machinery coordinates.
5. The mountain foundation pit construction monitoring and optimizing method of claim 4, wherein calculating the straight line distance between the construction focus target and the center of each tower leg foundation pit according to the space coordinates of the construction focus target, and determining the target construction tower leg foundation pit by combining the construction machine coordinates comprises: calculating the linear distance between the space coordinates of the construction seismic source target and the center coordinates of the preset 4 tower leg foundation pits, and taking the tower leg corresponding to the minimum distance value as the primary judgment construction tower leg foundation pit; And extracting the construction machinery coordinates of the effective construction signals, calculating the distance value between the construction machinery coordinates and the primary construction tower leg foundation pit coordinates, and taking the primary construction tower leg foundation pit as a target construction tower leg foundation pit if the distance value is within a preset foundation pit range.
6. The mountain foundation pit construction monitoring and optimizing method of claim 4, wherein the steps of extracting multi-mode features according to the position of the foundation pit of the target construction tower leg, performing feature matching binding based on the mechanical feature mapping relation, and obtaining the target construction signal comprise the following steps: Extracting a construction machine label ID and construction machine coordinates according to the effective construction signals so as to screen out the construction machine labels in the monitoring area of the target construction tower leg foundation pit; extracting multi-mode perception features in the effective construction signals in the label space domain of each construction machine; Comparing the multi-mode sensing characteristics with mechanical characteristics in a mechanical characteristic mapping relation, and calculating a first characteristic matching degree, wherein the mechanical characteristic mapping relation comprises construction machinery, a construction machinery label and mechanical characteristics bound by the construction machinery; binding the multi-mode sensing features with the first feature matching degree larger than a feature matching degree threshold value with corresponding construction machine labels and construction machines to obtain target construction signals.
7. The mountain pit construction monitoring and optimizing method according to any one of claims 2 and 6, wherein the calculating the matching degree of the construction behavior feature library and the model time sequence feature in the target construction signal, determining the construction behavior compliance and obtaining the behavior risk pre-value of the construction behavior according to the gridding risk model comprises: Extracting vibration time sequence characteristics, infrared time sequence characteristics and construction machinery coordinate time sequence characteristics according to the target construction signals; Calculating second feature matching degrees of the vibration time sequence feature, the infrared time sequence feature and the construction machinery coordinate time sequence feature and each feature template in the construction behavior feature library based on Euclidean distance; determining a corresponding construction behavior category according to the second feature matching degree, and judging whether the construction behavior violates a construction specification; and determining a monitoring grid to which the current construction behavior belongs according to the construction machinery coordinates, calculating a grid risk value of the monitoring grid based on the weight of each modal time sequence characteristic, and taking the grid risk value as a behavior risk pre-value of the construction behavior.
8. A mountain pit construction monitoring optimization system, characterized by being adapted to a mountain pit construction monitoring optimization method as set forth in any one of claims 1 to 7, comprising: the memory module is used for constructing a construction behavior feature library containing characteristic relations among the modal data; The acquisition module is used for acquiring multi-mode sensing data, identifying effective construction signals according to a mode filtering rule base, and locking a target construction tower leg foundation pit after carrying out path correction on the effective construction signals; The matching module is used for extracting multi-mode characteristics according to the position of the foundation pit of the target construction tower leg, and carrying out characteristic matching binding based on the mechanical characteristic mapping relation to obtain a target construction signal; The judging module is used for calculating the matching degree of the construction behavior feature library and the model time sequence feature in the target construction signal, determining the compliance of the construction behavior and acquiring a behavior risk pre-value of the construction behavior according to the gridding risk model; And the early warning module is used for responding to the hierarchical early warning mechanism according to the behavior risk pre-value.
9. A computer device comprising a processor, a memory and a communication bus, wherein the processor, the memory, via the communication bus, is in communication with each other, the memory is for storing a computer program, and the processor, when executing the program stored on the memory, is adapted to implement the steps of a mountain pit construction monitoring optimization method according to any one of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, performs the steps of a mountain pit construction monitoring optimization method according to any one of claims 1-7.

Description

Mountain foundation pit construction monitoring and optimizing method, system, equipment and medium Technical Field The application relates to the field of safety construction monitoring of power transmission and transformation engineering, in particular to a mountain foundation pit construction monitoring and optimizing method, a system, equipment and a medium. Background In the construction of power transmission and transformation engineering lines, an electric iron tower is used as an important node for electric energy transmission of a power transmission network, and a plurality of tower bases are distributed on high-difficulty terrains such as mountainous areas. The concealment of mountain construction causes the supervision degree of difficulty great, and the scene safety management of operating personnel is restricted, and the manual inspection is limited by human cost and coverage, and the mountain topography is difficult to high-efficient all construction areas of going over by the inspection personnel, has led to forming safety management "vacuum zone". The video monitoring and the vibration acoustic wave detection are monitoring technologies commonly used in engineering sites, however, are affected by topography and topography, have monitoring blind areas, cannot accurately distinguish operation types in foundation pits, cannot completely cover construction conditions such as construction modes and the like lower than vibration acoustic wave detection standard conditions or non-vibration type, are interfered by environmental conditions, cannot accurately position sound sources and construction modes due to vibration detection deviation, and therefore overall construction supervision and operation and maintenance efficiency are affected. The patent CN120538580A discloses a method and a system for remotely monitoring intelligent sensing situation, vibration and azimuth, which are used for identifying and acquiring a dynamic construction behavior mode, constructing a space-time dependent topological graph of the dynamic construction behavior mode by monitoring a tracing situation and an azimuth tracking community, deducing state potential energy of the space-time dependent topological graph according to the evolution of vibration sensing signals and horizontal sensing data to determine a global construction sensing situation of a target monitoring area, evaluating a phase space evolution track of the global construction sensing situation through an evaluation phase space of a space evolution evaluation criterion to obtain a stable node situation, and analyzing whether a divergence degree of the stable node situation interferes with buried facilities or not by introducing a Lyapunov function to control remote monitoring equipment to send monitoring early warning signals. However, the scheme only compensates the vibration sound source error caused by the equipment posture deviation by correcting the equipment posture, and the complex mountain construction environment is not compensated by multi-mode sensing and terrain adaptation, so that the scheme still has vibration signal error, and has poor adaptability. Disclosure of Invention The application aims to solve the problems that the perceived dimension is single and the terrain adaptation compensation is lacking and the construction behavior compliance cannot be accurately identified when the existing construction monitoring technology is used for coping with complex mountain scenes, and provides a mountain foundation pit construction monitoring optimization method, system, equipment and medium, wherein the construction behavior compliance is accurately identified and the risk level is predicted through multi-mode perceived data and path correction, so that more comprehensive perceived, accurate construction positioning and accurate compliance judgment are realized. In order to achieve the above purpose, the technical scheme adopted by the embodiment of the application is as follows: in a first aspect, an embodiment of the present application provides a mountain pit construction monitoring optimization method, where the method includes: The method comprises the steps of constructing a construction behavior feature library containing characteristic relations among all mode data, obtaining multi-mode sensing data, identifying effective construction signals according to a mode filtering rule library, carrying out path correction on the effective construction signals, locking target construction tower leg foundation pits, extracting multi-mode features according to the positions of the target construction tower leg foundation pits, carrying out feature matching binding based on mechanical feature mapping relations, obtaining target construction signals, calculating matching degree of the construction behavior feature library and model time sequence features in the target construction signals, determining construction behavior compliance, obtaining behavi