A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
DAMAGE PREDICTION APPARATUS, LEARNING MODEL, AND METHOD OF GENERATING LEARNING MODEL
To provide a damage prediction apparatus which predicts damage when external force is applied to a target structure without performing structure analysis every time.SOLUTION: A damage prediction apparatus comprises input means and output means. The input means accepts input including a map of degradation level distribution or soundness determination distribution in a beam structure obtained from inspection results of a target structure, a planar shape of the beam structure in the target structure, and unassumed external force applied to the target structure, as input date for prediction means utilizing a learnt model provided with teaching data to perform machine learning, the teaching data including input data and output data, the input data taking the map of degradation level distribution or soundness determination distribution in the beam structure of a pier or a bridge, the planar shape of the beam structure, and the external force applied to the beam structure, and the output data taking the information indicating damage condition of the beam structure obtained from a structure analysis result when the external force is applied to the beam structure, and the output means outputs information indicating damage condition predicted when unassumed external force is applied to the target structure.SELECTED DRAWING: Figure 1
【課題】対象となる構造物に外力が与えられたときの損傷を、その都度構造解析を行うことなく予測する。【解決手段】損傷度予測装置は、桟橋又は橋梁の梁構造における劣化度分布又は健全性判定分布のマップ、当該梁構造の平面形状、及び梁構造に与えられる外力を入力データとし、梁構造に外力が与えられたときの構造解析結果から得られる梁構造の損傷状態を示す情報を出力データとする教師データを与えて機械学習をさせた学習済モデルを用いた予測手段に対する入力データとして、対象となる構造物の点検結果から得られた梁構造における劣化度分布又は健全性判定分布のマップ、当該対象となる構造物における梁構造の平面形状、及び当該対象となる構造物に与えられる想定外力の入力を受け付ける入力手段と、学習済モデルから得られる、対象となる構造物に対し想定外力が与えられたときに予測される損傷状態を示す情報を出力する出力手段とを有する。【選択図】図１
DAMAGE PREDICTION APPARATUS, LEARNING MODEL, AND METHOD OF GENERATING LEARNING MODEL
To provide a damage prediction apparatus which predicts damage when external force is applied to a target structure without performing structure analysis every time.SOLUTION: A damage prediction apparatus comprises input means and output means. The input means accepts input including a map of degradation level distribution or soundness determination distribution in a beam structure obtained from inspection results of a target structure, a planar shape of the beam structure in the target structure, and unassumed external force applied to the target structure, as input date for prediction means utilizing a learnt model provided with teaching data to perform machine learning, the teaching data including input data and output data, the input data taking the map of degradation level distribution or soundness determination distribution in the beam structure of a pier or a bridge, the planar shape of the beam structure, and the external force applied to the beam structure, and the output data taking the information indicating damage condition of the beam structure obtained from a structure analysis result when the external force is applied to the beam structure, and the output means outputs information indicating damage condition predicted when unassumed external force is applied to the target structure.SELECTED DRAWING: Figure 1
【課題】対象となる構造物に外力が与えられたときの損傷を、その都度構造解析を行うことなく予測する。【解決手段】損傷度予測装置は、桟橋又は橋梁の梁構造における劣化度分布又は健全性判定分布のマップ、当該梁構造の平面形状、及び梁構造に与えられる外力を入力データとし、梁構造に外力が与えられたときの構造解析結果から得られる梁構造の損傷状態を示す情報を出力データとする教師データを与えて機械学習をさせた学習済モデルを用いた予測手段に対する入力データとして、対象となる構造物の点検結果から得られた梁構造における劣化度分布又は健全性判定分布のマップ、当該対象となる構造物における梁構造の平面形状、及び当該対象となる構造物に与えられる想定外力の入力を受け付ける入力手段と、学習済モデルから得られる、対象となる構造物に対し想定外力が与えられたときに予測される損傷状態を示す情報を出力する出力手段とを有する。【選択図】図１
DAMAGE PREDICTION APPARATUS, LEARNING MODEL, AND METHOD OF GENERATING LEARNING MODEL
損傷度予測装置、学習済モデル、及び学習済モデルの生成方法
BAI KE (author) / UNO KUNIHIKO (author) / KUMAGAI TAKAHIRO (author) / IWANAMI MITSUHO (author)
2021-09-24
Patent
Electronic Resource
Japanese
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