JP5145501B2 - Large building diagnostic system, large building diagnostic program, recording medium, and large building diagnostic method - Google Patents
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Description
本発明は、大型建造物の診断システム等に関し、特に、橋梁等の大型建造物の劣化および健全度を診断する大型建造物の診断システム等に関する。 The present invention relates to a diagnostic system for large buildings, and more particularly to a diagnostic system for large buildings that diagnoses deterioration and soundness of large buildings such as bridges.
社会資本、特に、橋梁、道路、港湾および教育施設等の大型建造物は、建造および整備されてから年数を経ると老朽化、陳腐化していくことは免れない。近い将来、これらの大型建造物に対する維持補修および更新等の費用は、建造等に対する全投資額の半分を超えるものと言われている。このため、上記大型建造物については、壊して新規に造る方法から既存の大型建造物に予防的な補修を行って、耐用年数の延長、すなわち長寿命化を図る方法に変更することにより、財政負担の軽減を図る必要性が高まってきている。 Social capital, especially large buildings such as bridges, roads, ports, and educational facilities, are inevitably subject to aging and becoming obsolete over the years since construction and maintenance. In the near future, it is said that the cost of maintenance and repairs for these large buildings will exceed half of the total investment in construction. For this reason, the above large-scale building is changed from a method of breaking and newly building to a method of proactively repairing an existing large-scale building and extending the useful life, that is, extending the life of the building. There is an increasing need to reduce the burden.
社会資本の中でも橋梁は大規模建造物であるだけでなく、一旦、橋梁に不具合が起こったときのインパクトは交通網の遮断に繋がるため、経済的、社会的にも非常に大きい。橋梁は、ほとんどが鉄筋コンクリート製または鉄骨製であり、その設計耐用年数は５０年〜６０年である。２０１０年頃には半数以上の橋梁が架設後４０年以上経過することになり、２０２０〜２０３０年頃には耐用年数５０年を越える橋梁が急増することとなるため、これらの橋梁を更新しなければならないと言われている。本来、コンクリートは耐久性に富んだ材料であるため、良質な材料および高度な技術を適用すれば、１０００年コンクリートの製造も不可能ではないと考えられている。その一方で、橋梁建設後２０年も経たないうちに橋梁に劣化が顕在化する等といった事例があることも事実である。これらの事例の原因は、建設当時には知られていなかった劣化現象、過去の設計技術レベルが現在の状況に対応していなかったこと等が考えられている。車の大型化、交通量の増大に伴って、過去の設計時に想定した橋梁の積載重量に対して過積載となってしまっていること、大半の橋梁で採用されている鉄筋コンクリート構造には一時期塩分を規定値以上に含む砂利が使用されていたこと、橋梁の設置場所が海岸に近い場合は潮風にさらされること等を考慮すると、橋梁の耐用年数は過去の設計値よりも短縮される可能性がある。河川に架かる橋梁の場合、橋脚部分の基礎を川底に埋設して固定することにより全体の強度を出している。しかし、河川流域の開発等により森林の保水力が減少することに伴って、河川流域に降雨後の河川流速が上がるため、橋脚基礎部分の潜掘が進みやすくなっている。このため、橋梁の強度劣化を早めているケースも生じている。以上より明らかなように、今後、維持管理し補修を要する橋梁の数は急激に増大していくものと考えられる。 Among social capital, bridges are not only large-scale buildings, but once a failure occurs in a bridge, the impact on the traffic network is interrupted, so it is very economical and social. Most of the bridges are made of reinforced concrete or steel frame and have a design life of 50 to 60 years. Around 2010, more than half of the bridges will be over 40 years old, and around 2020-2030, there will be a sudden increase in the number of bridges with a lifetime exceeding 50 years, so these bridges must be renewed. It is said. Originally, since concrete is a material with high durability, it is considered that the production of 1000-year concrete is not impossible if high-quality materials and advanced technology are applied. On the other hand, it is also true that there is a case where the deterioration of the bridge becomes apparent within 20 years after the construction of the bridge. The causes of these cases are considered to be deterioration phenomena that were not known at the time of construction, and that past design technology levels did not correspond to the current situation. As vehicles have become larger and traffic volume has increased, they have become overloaded with respect to the weight of bridges assumed at the time of past design, and the reinforced concrete structures used in most bridges are temporarily salinized. In consideration of the fact that gravel containing more than the specified value was used, and exposure to sea breezes when the bridge was installed near the coast, the useful life of the bridge could be shortened from the previous design value. There is. In the case of bridges over rivers, the overall strength is achieved by burying and fixing the foundations of the piers at the bottom of the river. However, as the water retention capacity of forests decreases due to the development of river basins, etc., the river velocities after rainfall increase in the river basins, making it easier to proceed with diving on the pier foundation. For this reason, there are cases where the strength deterioration of the bridge is accelerated. As is clear from the above, the number of bridges that require maintenance and repairs will increase rapidly in the future.
従来から実施されている、橋梁、トンネル、ダム、擁壁等道路構造物、樋門・樋管等河川構造物、港湾構造物、上下水道施設等のコンクリート構造物の維持管理および診断方法は、管理者によって異なるものの、一般には以下のような方法が採用されている（非特許文献１〜５参照）。
１．定期点検・調査（一次検査）：劣化程度の把握、劣化原因の推定
調査・検査方法を列挙すると、損傷・変状調査、構造物調査・点検、外観変状調査、健全度調査、外観目視検査、打音検査、赤外線法、Ｘ線法、非破壊検査、腐食調査、耐荷力調査、ひび割れ調査、コア採取、シュミットハンマー等がある。
２．劣化試験・評価・予測（二次検査）：劣化の経時変化の予測、要求性能と比較して評価
（１）試験・測定方法を列挙すると、静的載荷試験、耐久性試験、応力頻度測定、材料試験、圧縮強度試験、劣化試験、非破壊試験、変位測定、疲労試験等がある。
（２）評価・判定方法を列挙すると、健全度診断（ひび割れの発生原因究明と対策の検討）、耐久性評価（中性化、塩害、アルカリ骨材反応、錆・腐食）、耐荷力評価（活荷重、疲労、温度、地震）、変位・変形検討（基礎沈下・傾斜、クリープ、側方流動、振動）等がある。
（３）予測方法を列挙すると、劣化予測（コンクリート片落下の可能性）、ライフサイクルコスト予測、耐用年数予測等がある。
３．対策の判定・選定： 補修工法、補強工法
（１）補修工法を列挙すると、表面塗布、ひび割れ注入・充填、断面修復、表面被覆、電気防食等がある。
（２）補強工法を列挙すると、打ち換え、コンクリート巻立て、鋼板接着、支持点増設等がある。
The maintenance and diagnosis methods for road structures such as bridges, tunnels, dams, retaining walls, river structures such as locks and pipes, harbor structures, water supply and sewerage facilities, etc. Although it differs depending on the manager, the following methods are generally adopted (see Non-Patent Documents 1 to 5).
1. Periodic inspection / inspection (primary inspection): Understanding the degree of deterioration, estimating the cause of deterioration Enumerating inspection / inspection methods, damage / deformation inspection, structure inspection / inspection, external deformation inspection, soundness inspection, visual inspection , Hammering inspection, infrared method, X-ray method, nondestructive inspection, corrosion investigation, load bearing investigation, crack investigation, core sampling, Schmitt hammer, etc.
2. Deterioration test / evaluation / prediction (secondary inspection): Prediction of deterioration over time, evaluation compared with required performance (1) List test / measurement methods, static loading test, durability test, stress frequency measurement, There are material tests, compressive strength tests, deterioration tests, nondestructive tests, displacement measurements, fatigue tests, and the like.
(2) Enumeration of evaluation / judgment methods includes soundness diagnosis (cracking cause investigation and investigation of countermeasures), durability evaluation (neutralization, salt damage, alkali aggregate reaction, rust / corrosion), load capacity evaluation ( (Live load, fatigue, temperature, earthquake), displacement / deformation studies (foundation settlement / tilt, creep, lateral flow, vibration), etc.
(3) Enumerating prediction methods includes deterioration prediction (possibility of falling concrete pieces), life cycle cost prediction, service life prediction, and the like.
3. Judgment and selection of countermeasures: Repair methods, reinforcement methods (1) List of repair methods include surface coating, crack injection / filling, cross-section repair, surface coating, and anti-corrosion.
(2) Reinforcement methods are listed, such as replacement, concrete winding, steel plate adhesion, and support point expansion.
まず、定期点検・調査の一次検査が行われ、その結果に基づき、更に詳細な二次検査を行うか否かを決める。二次検査を行う場合、劣化試験・評価・予測等を含めた破壊試験（コンクリートコアの切り出しによる断面検査等）、非破壊試験（橋脚基礎部分の洗掘の進み方の推定に用いられる衝撃振動法等）も併用される。その結果、補修、補強を施すほうが良いかどうかという判定が行われる。補修・補強を施すと判定された場合、どのような補修工法、補強工法を選定するべきかを決める。 First, the primary inspection of periodic inspections / surveys is performed, and based on the results, it is determined whether or not a more detailed secondary inspection is to be performed. When conducting secondary inspections, destructive tests (including cross-section inspection by cutting out concrete cores) including deterioration tests, evaluations, and predictions, non-destructive tests (impact vibration used to estimate the progress of scouring of pier foundations) Law). As a result, a determination is made as to whether repair or reinforcement is better. If it is determined that repair / reinforcement will be performed, determine what repair method and reinforcement method should be selected.
鉄筋コンクリート製橋梁に対する従来の維持管理、診断方法では、上述した打音検査または外観目視検査という非破壊検査、コンクリートコアの切り出しによる断面検査等という破壊検査が１〜２年に１回程度実施されていた。しかし、打音検査または外観目視検査等は官能検査であるため定性的であり且つ精度が低いという問題があった。検査は５年に１回程度の実施であったため、暴風雨等の緊急時に必要と考えられるリアルタイムな検査には対応できるものではないという問題があった。橋脚基礎部分の洗掘の進み方の推定は上述の衝撃振動法を用いるが、この方法は大掛かりな方法であるため日常的に橋梁の健全度データを収集できるものではないだけでなく、通常の振動以外の振動を必要とするものであるという問題があった。 In the conventional maintenance management and diagnosis methods for reinforced concrete bridges, destructive inspections such as non-destructive inspection such as hammering inspection or visual inspection described above, and cross-sectional inspection by cutting out concrete cores, etc. are carried out about once every two years. It was. However, the hitting sound inspection or the visual appearance inspection has a problem that it is qualitative and low in accuracy because it is a sensory inspection. Since the inspection was conducted about once every five years, there was a problem that it could not cope with a real-time inspection considered necessary in an emergency such as a storm. Although the above-mentioned shock vibration method is used to estimate the scouring progress of the pier foundation, this method is a large-scale method, so it cannot be used to collect bridge health data on a daily basis. There has been a problem that it requires vibration other than vibration.
そこで、本発明の目的は、上記問題を解決するためになされたものであり、大型建造物の維持管理、診断方法に用いることができる客観的且つ定量的な大型建造物の診断システム等を提供することにある。 Accordingly, an object of the present invention has been made to solve the above-described problems, and provides an objective and quantitative diagnostic system for a large building that can be used for maintenance and diagnosis of a large building. There is to do.
本発明の第二の目的は、大型建造物の維持管理、診断方法に用いることができる日常的且つリアルタイムで常時監視可能な大型建造物の診断システム等を提供することにある。 A second object of the present invention is to provide a diagnostic system for a large building, which can be used for maintenance and diagnosis of a large building and can be constantly monitored on a daily basis in real time.
本発明の第三の目的は、大型建造物の維持管理、診断方法に用いることができる通常の振動を用いた大型建造物の診断システム等を提供することにある。 The third object of the present invention is to provide a diagnostic system for large buildings using normal vibration that can be used for maintenance and diagnosis of large buildings.
この発明の大型構造物の診断システムは、橋梁又は橋梁の上部構造物である大型建造物の劣化及び／又は健全度を診断する大型建造物の診断システムであって、大型建造物の所定の部位に配置された複数の無線付橋梁センサと、複数の前記無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置と、前記記録装置から転送されたセンサ情報に基づき大型建造物の劣化及び／又は健全度を診断する診断装置とを備え、前記診断装置は、複数のセンサ情報から独立成分分析による独立成分の変化を検出して大型建造物全体の異常診断を行う全体異常診断手段であって、大型建造物の複数箇所の振動データを独立成分分析で信号解析を行い、該大型建造物の独立な振動成分を抽出する信号抽出手段と、前記信号抽出手段により抽出された独立な振動成分についてスペクトル解析を行うことにより、大型建造物全体の固有振動数を求める固有振動数取得手段と、予め取得された大型建造物の健全時における健全時固有振動数と前記固有振動数取得手段により取得された大型建造物全体の固有振動数との比較に基づき、大型建造物全体に異常があるかどうかを把握する異常把握手段とを備えたものと、前記全体異常診断手段による異常診断に基づき、異常箇所の特定及び劣化診断を行う異常部位把握手段であって、主桁に配置された複数の無線付橋梁センサにより測定された一定期間における加速度信号をＡＲモデル(自己回帰モデル)に基づく入出力を有するシステムとし、該無線付橋梁センサ毎に、該加速度信号を周波数毎に該システムの入力と出力との振幅比で表すＡＲモデルによる伝達関数のボード線図と予め取得した亀裂のない健全大型構造物のボード線図とを比較して、該健全大型構造物の振幅比より大きい振幅比を示す無線付橋梁センサが配置された個所に主桁の亀裂部位があると特定する亀裂部位特定手段を備えたことを特徴とする。 A diagnostic system for a large structure according to the present invention is a diagnostic system for a large building that diagnoses deterioration and / or soundness of a large building that is a bridge or a superstructure of a bridge, and is a predetermined part of the large building. A plurality of wireless bridge sensors arranged in a radio, a recording device for recording sensor information measured by the plurality of wireless bridge sensors and transmitted wirelessly by the wireless bridge sensors, and a sensor transferred from the recording device A diagnostic device for diagnosing deterioration and / or soundness of a large building based on information, wherein the diagnostic device detects a change in independent component by independent component analysis from a plurality of sensor information and detects an abnormality in the entire large building a total abnormality diagnosis means for diagnosing the vibration data at a plurality of locations of a large building performs signal analysis independent component analysis, signal extraction hand to extract independent vibration components of large-sized buildings And by performing spectrum analysis on the independent vibration component extracted by the signal extraction means, natural frequency acquisition means for obtaining the natural frequency of the entire large building, and when the large building acquired in advance is healthy. Based on a comparison between the natural frequency of soundness and the natural frequency of the entire large building acquired by the natural frequency acquisition unit, an abnormality grasping unit for grasping whether there is an abnormality in the entire large building is provided. and stuff, based on the abnormality diagnosis by the entire abnormality diagnosis means, in particular and a abnormal position detection means for performing deterioration diagnosis, a period of time measured by a plurality of radio with bridge sensor disposed on the main girder of the anomaly The acceleration signal is a system having an input / output based on an AR model (autoregressive model), and the acceleration signal is set for each frequency for each wireless bridge sensor. Compare the Bode diagram of the transfer function by the AR model expressed by the amplitude ratio of input and output with the Bode diagram of the healthy large structure without cracks obtained in advance, and the amplitude larger than the amplitude ratio of the healthy large structure It is characterized by comprising crack part specifying means for specifying that there is a crack part of the main girder at a place where the wireless bridge sensor indicating the ratio is arranged .
ここで、この発明の大型建造物の診断システムにおいて、前記大型建造物が橋梁である場合、前記所定の部位は橋梁中の各位置とすることができる。 Here, in a diagnostic system for large buildings of the present invention, when the large buildings Ru bridges der, the predetermined portion may be a respective position in the bridge.
ここで、この発明の大型建造物の診断システムにおいて、前記大型建造物が橋梁の上部構造物である場合、前記所定の部位は橋梁の桁及び／又は床版とすることができる。 Here, in a diagnostic system for large buildings of the present invention, when the large buildings Ru superstructure der bridges, the predetermined portion may be a digit and / or deck of the bridge.
ここで、この発明の大型建造物の診断システムにおいて、前記無線付橋梁センサは無線付ひずみセンサ又は加速度センサとすることができる。 Here, in the diagnostic system for a large building according to the present invention, the wireless bridge sensor may be a wireless strain sensor or an acceleration sensor.
この発明の大型構造物の診断プログラムは、橋梁又は橋梁の上部構造物である大型建造物の所定の部位に配置された複数の無線付橋梁センサと、複数の該無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置と、該記録装置から転送されたセンサ情報に基づき大型建造物の劣化及び／又は健全度を診断する診断装置とを備えた大型建造物の診断システムにおける該診断装置が診断を行うための大型建造物の診断プログラムであって、該診断装置のコンピュータを、大型建造物の所定の部位に配置された複数の無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置から転送された複数のセンサ情報から独立成分分析による独立成分の変化を検出して大型建造物全体の異常診断を行う全体異常診断手段であって、大型建造物の複数箇所の振動データを独立成分分析で信号解析を行い、該大型建造物の独立な振動成分を抽出する信号抽出手段と、前記信号抽出手段により抽出された独立な振動成分についてスペクトル解析を行うことにより、大型建造物全体の固有振動数を求める固有振動数取得手段と、予め取得された大型建造物の健全時における健全時固有振動数と前記固有振動数取得手段により取得された大型建造物全体の固有振動数との比較に基づき、大型建造物全体に異常があるかどうかを把握する異常把握手段とを備えた全体異常診断手段、前記全体異常診断手段による異常診断に基づき、異常箇所の特定及び劣化診断を行う異常部位把握手段であって、主桁に配置された複数の無線付橋梁センサにより測定された一定期間における加速度信号をＡＲモデル(自己回帰モデル)に基づく入出力を有するシステムとし、該無線付橋梁センサ毎に、該加速度信号を周波数毎に該システムの入力と出力との振幅比で表すＡＲモデルによる伝達関数のボード線図と予め取得した亀裂のない健全大型構造物のボード線図とを比較して、該健全大型構造物の振幅比より大きい振幅比を示す無線付橋梁センサが配置された個所に主桁の亀裂部位があると特定する亀裂部位特定手段として機能させるための大型建造物の診断プログラムである。 The diagnostic program for a large structure according to the present invention is measured by a plurality of wireless bridge sensors arranged at a predetermined portion of a large building that is a bridge or a superstructure of the bridge, and a plurality of the wireless bridge sensors. Large-scale equipped with a recording device for recording sensor information transmitted wirelessly by a wireless bridge sensor and a diagnostic device for diagnosing deterioration and / or soundness of a large building based on the sensor information transferred from the recording device A diagnostic program for a large building for the diagnostic apparatus in the building diagnostic system to perform a diagnosis, wherein the computer of the diagnostic apparatus is configured by a plurality of wireless bridge sensors arranged at predetermined portions of the large building. measured independent component by independent component analysis from a plurality of sensors information transferred from the recording apparatus for recording sensor information transmitted by wireless bridge sensor with wireless A total abnormality diagnosis means for performing abnormality diagnosis of the entire large building by detecting of the vibration data at a plurality of locations of a large building performs signal analysis independent component analysis, independent vibration components of large-sized buildings A signal extraction means for extracting a natural frequency, a natural frequency acquisition means for obtaining a natural frequency of the entire large building by performing spectrum analysis on the independent vibration component extracted by the signal extraction means, and a large size acquired in advance. Abnormality to determine whether there is an abnormality in the entire large building based on a comparison between the natural frequency of the healthy building and the natural frequency of the entire large building acquired by the natural frequency acquisition means overall diagnosis means and a grasping means, based on said abnormality diagnosis by whole abnormality diagnosis means, and an abnormal region detection means for performing a specific and deterioration diagnosis of the abnormal point, the main girder in place A system having an input / output based on an AR model (autoregressive model) is used as an acceleration signal measured by a plurality of wireless bridge sensors for a certain period of time, and the acceleration signal for each radio bridge sensor for each frequency. Compare the bode diagram of the transfer function based on the AR model expressed by the amplitude ratio between the input and output of the system and the board diagram of the healthy large structure without cracks obtained in advance. This is a diagnostic program for a large building for functioning as a crack part specifying means for specifying a crack part of a main girder at a place where a wireless bridge sensor having a large amplitude ratio is arranged .
ここで、この発明の大型建造物の診断プログラムムにおいて、前記大型建造物が橋梁である場合、前記所定の部位は橋梁中の各位置とすることができる。 Here, in the diagnostics beam of large buildings of the present invention, when the large buildings Ru bridges der, the predetermined portion may be a respective position in the bridge.
ここで、この発明の大型建造物の診断プログラムにおいて、前記大型建造物が橋梁の上部構造物である場合、前記所定の部位は橋梁の桁及び／又は床版とすることができる。 Here, in the diagnostics of large buildings of the present invention, when the large buildings Ru superstructure der bridges, the predetermined portion may be a digit and / or deck of the bridge.
ここで、この発明の大型建造物の診断プログラムにおいて、前記無線付橋梁センサは無線付ひずみセンサ又は加速度センサとすることができる。 Here, in the diagnostic program for a large building according to the present invention, the wireless bridge sensor may be a wireless strain sensor or an acceleration sensor.
この発明の記録媒体は、本発明のいずれかの大型建造物の診断プログラムを記録したコンピュータ読取り可能な記録媒体である。 The recording medium of the present invention is a computer-readable recording medium in which the diagnostic program for any large building of the present invention is recorded.
この発明の大型建造物の診断方法は、橋梁又は橋梁の上部構造物である大型建造物の所定の部位に配置された複数の無線付橋梁センサと、複数の該無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置と、該記録装置から転送されたセンサ情報に基づき大型建造物の劣化及び／又は健全度を診断する診断装置とを用いた大型建造物の診断方法であって、大型建造物の所定の部位に配置された複数の無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置から転送された複数のセンサ情報から独立成分分析による独立成分の変化を検出して大型建造物全体の異常診断を行う全体異常診断ステップであって、大型建造物の複数箇所の振動データを独立成分分析で信号解析を行い、該大型建造物の独立な振動成分を抽出する信号抽出ステップと、前記信号抽出ステップＳで抽出された独立な振動成分についてスペクトル解析を行うことにより、大型建造物全体の固有振動数を求める固有振動数取得ステップと、予め取得された大型建造物の健全時における健全時固有振動数と前記固有振動数取得ステップで取得された大型建造物全体の固有振動数との比較に基づき、大型建造物全体に異常があるかどうかを把握する異常把握ステップとを備えたものと、前記全体異常診断ステップによる異常診断に基づき、異常箇所の特定及び劣化診断を行う異常部位把握ステップであって、主桁に配置された複数の無線付橋梁センサにより測定された一定期間における加速度信号をＡＲモデル(自己回帰モデル)に基づく入出力を有するシステムとし、該無線付橋梁センサ毎に、該加速度信号を周波数毎に該システムの入力と出力との振幅比で表すＡＲモデルによる伝達関数のボード線図と予め取得した亀裂のない健全大型構造物のボード線図とを比較して、該健全大型構造物の振幅比より大きい振幅比を示す無線付橋梁センサが配置された個所に主桁の亀裂部位があると特定する亀裂部位特定ステップとを備えたことを特徴とする。
A diagnostic method for a large building according to the present invention includes a plurality of wireless bridge sensors arranged at a predetermined portion of a large building that is a bridge or a superstructure of a bridge, and a plurality of wireless bridge sensors that are measured by the wireless bridge sensors. A large-sized recording device that records wirelessly transmitted sensor information of a wireless bridge sensor and a diagnostic device that diagnoses deterioration and / or soundness of a large building based on the sensor information transferred from the recording device A method for diagnosing a building, which is measured by a plurality of wireless bridge sensors arranged in a predetermined part of a large building and transferred from a recording device that records the sensor information transmitted by the wireless bridge sensors. and a plurality of generally abnormality diagnosis step of detecting a change of the independent component by independent component analysis from the sensor information performs abnormality diagnosis of the entire large buildings, the vibration of the plurality of locations of a large building The signal is analyzed by independent component analysis, the signal extraction step of extracting the independent vibration component of the large building, and the spectrum analysis of the independent vibration component extracted in the signal extraction step S, The natural frequency acquisition step for obtaining the natural frequency of the entire large building, the healthy natural frequency of the large building that was acquired in advance and the natural frequency of the entire large building acquired in the natural frequency acquisition step. Based on the comparison with the vibration frequency, an abnormality grasping step for grasping whether there is an abnormality in the entire large building and an abnormality location identification and deterioration diagnosis based on the abnormality diagnosis by the overall abnormality diagnosis step a abnormalities acquisition step of performing, AR model (own acceleration signals over a period of time measured by a plurality of radio with bridge sensor disposed on the main girder A system having an input / output based on a regression model), and for each of the wireless bridge sensors, a bode diagram of a transfer function based on an AR model that represents the acceleration signal as an amplitude ratio between the input and output of the system for each frequency Compared to the obtained Bode diagram of a healthy large structure without cracks, there is a crack part of the main girder where the wireless bridge sensor with an amplitude ratio larger than the amplitude ratio of the healthy large structure is arranged And a crack site specifying step for specifying .
本発明の大型建造物の診断システム等によれば、橋梁の上部構造物の振動によって発生した信号を、上部構造物の桁や床版の複数場所の位置に設置され信号処理装置と所定の方式で接続された加速度センサまたはひずみセンサにより受信する。これらの複数のセンサ情報から独立成分分析によって独立な信号に分離し、この結果である複数の独立成分信号のスペクトル信号の周波数あるいは信号ゲインの以前の結果との違いから劣化があるかどうかにより劣化の有無を診断することができる。さらに劣化の存在が判断されれば、各信号のＡＲモデルによる伝達関数のボード線図を求め、その以前の結果からの変化から劣化箇所を特定する。この結果、大型建造物またはその構成要素の維持管理、診断方法に用いることができる客観的かつ定量的で、日常的且つリアルタイムで常時監視可能であり、大型建造物の診断システム等を提供することができるという効果がある。 According to the diagnostic system for a large building of the present invention, the signal generated by the vibration of the superstructure of the bridge is installed at a plurality of locations on the girder of the superstructure or the floor slab and a predetermined method. It is received by an acceleration sensor or a strain sensor connected at. These multiple pieces of sensor information are separated into independent signals by independent component analysis, and this results in degradation depending on whether there is degradation due to the difference in the spectrum signal frequency or signal gain from the previous results. The presence or absence of can be diagnosed. If the presence of deterioration is further determined, a Bode diagram of a transfer function based on the AR model of each signal is obtained, and a deterioration point is specified from a change from the previous result. As a result, it is possible to provide an objective, quantitative, daily and real-time monitoring system that can be used for maintenance management and diagnostic methods for large buildings or their components, and to provide a diagnostic system for large buildings. There is an effect that can be.
以下、各実施例について図面を参照して詳細に説明する。 Hereinafter, each embodiment will be described in detail with reference to the drawings.
以下の実施例１では、大型建造物として橋梁または橋梁の上部構造物を例にとり説明する。しかし、本発明の大型建造物の診断方法は橋梁または橋梁の上部構造物以外の大型建造物に対して適用可能であることは勿論である。以下では、橋梁の上部構造物の亀裂診断について説明するが、橋梁の亀裂診断についても同様である。図１は、橋梁１ｆの上部構造物の亀裂診断のために設置された橋梁データの収集システム１の概略図を示す。図１に示されるように、橋梁データの収集システム１は、無線付橋梁センサ（加速度センサあるいはひずみセンサ）１ａ、データ記憶装置（記録装置）１ｂ、およびデータ収集装置１ｃ（走行車両１ｅに搭載）および橋梁診断装置１ｄから構成される。診断のためのデータ（センサ情報）は定期的に無線付橋梁センサ１ａで計測され、その結果は無線付橋梁センサ１ａの無線（不図示）によりデータ記憶装置１ｂに格納される。その格納データは、定期的に橋梁１ｆを走行するデータ収集装置１ｃを搭載した走行車両１ｅに転送される。収集されたデータは、橋梁診断装置（診断装置）１ｄに入力され、橋梁１ｆの劣化・健全度が診断される。 In the following Example 1, a bridge or a superstructure of a bridge will be described as an example of a large building. However, it is needless to say that the diagnostic method for large buildings of the present invention can be applied to large buildings other than the bridge or the superstructure of the bridge. In the following, the crack diagnosis of the superstructure of the bridge will be described, but the same applies to the crack diagnosis of the bridge. FIG. 1 shows a schematic diagram of a bridge data collection system 1 installed for crack diagnosis of the superstructure of the bridge 1f. As shown in FIG. 1, a bridge data collection system 1 includes a wireless bridge sensor (acceleration sensor or strain sensor) 1a, a data storage device (recording device) 1b, and a data collection device 1c (mounted on a traveling vehicle 1e). And a bridge diagnosis apparatus 1d. Data (sensor information) for diagnosis is periodically measured by the wireless bridge sensor 1a, and the result is stored in the data storage device 1b by radio (not shown) of the wireless bridge sensor 1a. The stored data is transferred to a traveling vehicle 1e equipped with a data collection device 1c that travels on the bridge 1f periodically. The collected data is input to the bridge diagnostic device (diagnostic device) 1d, and the deterioration / soundness of the bridge 1f is diagnosed.
橋梁１ｆの亀裂診断は、シミュレーションを行って得られたデータに基づいて本発明の診断方法によって行なった。図２は、本発明で提案した橋梁１ｆの上部構造物の診断方法およびプログラムの流れをフローチャートで示す。図２に示されるように、まず、亀裂が想定される橋梁１ｆの桁及び／又は床版（所定の部位）の多数の点（ここでは８点）に加速度センサ１ａを配置し、そのセンサ信号から独立成分分析（ＩＣＡ）による独立成分の変化を検出することで、橋梁１ｆ（上部構造物）全体の異常診断を行う（全体異常診断ステップ。ステップＳ２ａ）。橋梁１ｆの場合の所定の部位は橋梁１ｆ中の各位置とすればよい。それから、異常部位を把握するために、異常箇所の特定と劣化診断を行う（異常部位把握ステップ。ステップＳ２ｂ）という流れである。橋梁診断装置１ｄはパーソナルコンピュータ等のコンピュータにより実現され、上述の全体異常診断ステップ（ステップＳ２ａ）で実行される機能を有する全体異常診断手段と、上述の異常部位把握ステップ（ステップＳ２ｂ）で実行される機能を有する異常部位把握手段とを備えた橋梁診断プログラムを橋梁診断装置１ｄのコンピュータが実行することにより橋梁診断が行われる。本明細書では加速度センサは８箇所に設置したが、設置する数は８箇所に限定されるものではない。 Diagnosis of cracks in the bridge 1f was performed by the diagnosis method of the present invention based on data obtained through simulation. FIG. 2 is a flowchart showing the diagnosis method and program flow of the superstructure of the bridge 1f proposed in the present invention. As shown in FIG. 2, first, acceleration sensors 1a are arranged at a number of points (here, 8 points) of a bridge 1f and / or a floor slab (predetermined part) where a crack is assumed, and the sensor signal From this, an abnormality diagnosis of the entire bridge 1f (upper structure) is performed by detecting a change of the independent component by independent component analysis (ICA) (overall abnormality diagnosis step, step S2a). The predetermined part in the case of the bridge 1f may be each position in the bridge 1f. Then, in order to grasp the abnormal part, the abnormal part is specified and the deterioration diagnosis is performed (abnormal part grasping step, step S2b). The bridge diagnosis apparatus 1d is realized by a computer such as a personal computer, and is executed by the overall abnormality diagnosis means having a function executed in the above-described overall abnormality diagnosis step (step S2a) and the above-described abnormal part grasping step (step S2b). The bridge diagnosis is performed by the computer of the bridge diagnosis apparatus 1d executing a bridge diagnosis program including an abnormal part grasping means having a function of: In this specification, the acceleration sensors are installed at eight places, but the number of installation is not limited to eight places.
全体の異常診断とは、橋梁１ｆの上部構造物の診断を行う時、橋梁上部構造物のどこかに異常があるかを判断することである。本発明では、以下のように全体の異常診断を行った。図３は、本発明で提案した橋梁１ｆ（上部構造物）全体の異常診断方法およびプログラムの流れをフローチャートで示す。図３に示されるように、まず、橋梁１ｆの８箇所の振動データを独立成分分析（ＩＣＡ）で信号解析を行う。それによって橋梁上部構造物の独立な振動成分を求める（以上、ステップＳ３ａ）。その独立な振動成分について、スペクトル解析を行うことで、橋梁上部構造物全体の固有振動数が求められる（以上、ステップＳ３ｂ）。予め取得された健全時の橋梁データ（健全時固有振動数）とステップＳ３ｂで取得された橋梁上部構造物全体の固有振動数、すなわち亀裂の想定される橋梁１ｆの固有振動数とを比較することによって、橋梁１ｆ全体（上部建造物）に異常があるかを把握する（ステップＳ３ｃ）。上述のステップＳ３ａの機能を有する信号抽出手段と、上述のステップＳ３ｂの機能を有する固有振動数取得手段と、上述のステップＳ３ｃの機能を有する異常把握手段とを備えた橋梁診断プログラムを橋梁診断装置１ｄのコンピュータが実行することにより橋梁診断が行われる。以下に独立成分分析（ＩＣＡ）について説明する。 The overall abnormality diagnosis is to determine whether there is an abnormality in the bridge upper structure when diagnosing the upper structure of the bridge 1f. In the present invention, the entire abnormality diagnosis was performed as follows. FIG. 3 is a flowchart showing the abnormality diagnosis method and program flow of the entire bridge 1f (superstructure) proposed in the present invention. As shown in FIG. 3, first, signal analysis is performed on the vibration data of the eight locations of the bridge 1 f by independent component analysis (ICA). Thereby, an independent vibration component of the bridge superstructure is obtained (step S3a). By performing spectrum analysis on the independent vibration component, the natural frequency of the entire bridge upper structure is obtained (step S3b). Comparing the pre-acquired bridge data (health natural frequency) with the natural frequency of the entire bridge superstructure acquired at step S3b, that is, the natural frequency of the bridge 1f assumed to be cracked. Thus, it is grasped whether there is an abnormality in the entire bridge 1f (upper structure) (step S3c). A bridge diagnosis program comprising a signal extraction means having the function of step S3a, a natural frequency acquisition means having the function of step S3b, and an abnormality grasping means having the function of step S3c. Bridge diagnosis is performed by the execution of the computer 1d. The independent component analysis (ICA) will be described below.
独立成分分析（Independent Component Analysis : ＩＣＡ）とは、多変量（多次元）のデータから隠された因子や成分を見つけ出すための一手法である。大勢の人が同時に話しているときにその中から特定の人の声を抽出する方法、携帯電話などで多数の電波が歪んで混線しても、それを復元する方法、さらに脳波や脳磁波など脳の外部で観測して、脳の内部に発生している信号を分離して捉まえるなど、いろいろな使い道がある。他の手法との違いは、探すべき成分が統計的に独立であり、かつ非ガウス的であるということである。ＩＣＡの手法自体は1980 年代にJ. Herault、C. Jutten、B.Ans らによって導入された。１９８０年代を通して、ＩＣＡは世界的にあまり影響力をもたなかったが、特にフランスの研究者の間ではよく知られていた。最初に用いられたのは、ニューラルネットワークモデルに関連したものであった。１９９０年代の中頃、複数の研究グループによって紹介されたアルゴリズムは成功を収めたもので、カクテルティ効果のような問題に対して驚くほど効果があると示した。ＩＣＡは刺激的な新しいトピックとなった。ここ２０年間にＩＣＡに関する多くの論文が多くの雑誌や会議録に掲載された。 Independent component analysis (ICA) is a technique for finding hidden factors and components from multivariate (multidimensional) data. A method of extracting a specific person's voice from a large number of people who are speaking at the same time, a method of recovering even if many radio waves are distorted and mixed with a mobile phone, etc., and brain waves and magnetoencephalograms There are various uses such as observing outside the brain and segregating signals generated inside the brain. The difference from the other methods is that the components to be searched are statistically independent and non-Gaussian. The ICA method itself was introduced in the 1980s by J. Herault, C. Jutten, B. Ans and others. Throughout the 1980s, ICA was not very influential worldwide, but was well known amongst French researchers. The first one used was related to the neural network model. In the mid-1990s, algorithms introduced by several research groups were successful and showed surprisingly good effects on problems such as the cocktail tea effect. ICA has become an exciting new topic. In the last 20 years, many papers on ICA have been published in many magazines and conference proceedings.
ＩＣＡは、いくつかの独立な信号源からの信号が線形に混合されて観測されるとき、その観測された信号から元の互いに独立な信号を復元する手法であり、適用可能であるためには、信号源の信号が正規分布に従っているものではないこと、及び信号源の信号が互いに統計的独立であることが必要である。また、信号を復元する際に、復元した信号の順番、大きさは問わないとする。また、ＩＣＡの応用が可能な範囲は多くの異なる分野に及んでいて、デジタル画像、ドキュメントのデータから経済指標とか計量心理学的測定値などまで含まれる。例えば、 ICA is a technique for reconstructing original independent signals from observed signals when signals from several independent signal sources are observed as being linearly mixed and to be applicable. It is necessary that the signal of the signal source does not follow a normal distribution and that the signals of the signal source are statistically independent from each other. Further, when restoring signals, the order and magnitude of the restored signals are not limited. The range in which ICA can be applied extends to many different fields, including digital images and document data, economic indicators, and psychometric measurements. For example,
（ｉ）脳機能の可視化では、多くの場合脳中にいくつかの信号源があり、それから出る信号が混ざったものが頭外のセンサに現れる。これは基本的な暗中信号源分離モデルと同じ状況である。
（ｉｉ）計測経済学では並列的な時系列がよく出てくる。ＩＣＡによってそれらを独立な成分に分解すると、データの構造に対する洞察を得られることがある。
（ｉｉｉ）多少異なる応用として画像の特徴抽出がある。この場合、特徴量としてできるだけ独立なものを得ようとする。
(I) In visualization of brain function, in many cases, there are several signal sources in the brain, and a mixture of signals coming out of them appears in sensors outside the head. This is the same situation as the basic dark signal source separation model.
(Ii) In measurement economics, parallel time series often appear. Decomposing them into independent components by ICA may give insight into the structure of the data.
(Iii) Image feature extraction is a slightly different application. In this case, an attempt is made to obtain as independent features as possible.
ＩＣＡの目的は、複数の観測される変数を統計的に独立な変数の線形結合として表現することである。観測変数から計算される独立な変数が独立成分である。ここでは、ＩＣＡの基本概念を説明する。 The purpose of ICA is to represent multiple observed variables as a linear combination of statistically independent variables. Independent variables calculated from observed variables are independent components. Here, the basic concept of ICA will be described.
まず、原信号ｓ（ｔ）が式１で表されるベクトルで与えられるものとする。 First, it is assumed that the original signal s (t) is given by a vector represented by Equation 1.
原信号ｓ（ｔ）の各成分ｓｉ（ｔ）（ｉ＝１〜ｎ）の平均は０であり、各成分分ｓｉ（ｔ）は互いに独立であるものとする。このｎ個の原信号に対し、これらが線形和で混合された信号を式２で示される観測信号ｘ（ｔ）とする。 The average of each component s i (t) (i = 1 to n) of the original signal s (t) is 0, and each component s i (t) is independent of each other. A signal obtained by mixing these n original signals with a linear sum is taken as an observation signal x (t) expressed by Equation 2.
ここで、原信号ｓ（ｔ）と観測信号ｘ（ｔ）との関係は、混合行列Ａを用いて、式３のように表すことができる。 Here, the relationship between the original signal s (t) and the observed signal x (t) can be expressed as in Expression 3 using the mixing matrix A.
この混合行列Ａはｍ×ｎ（観測信号の次元数×独立信号の成分数）の行列である。独立成分分析において、原信号ｓ（ｔ）は観測信号ｘ（ｔ）からの線形変換により求めることができるものと考える。この復元行列をＷ、推定される原信号ｙ（ｔ）を、式５のように、 This mixing matrix A is a matrix of m × n (number of dimensions of observation signal × number of components of independent signal). In the independent component analysis, it is considered that the original signal s (t) can be obtained by linear conversion from the observed signal x (t). This restoration matrix is W, and the estimated original signal y (t) is
とすると、観測信号ｘ（ｔ）と推定される原信号ｙ（ｔ）との関係は、式６のように表される。 Then, the relationship between the observed signal x (t) and the estimated original signal y (t) is expressed as Equation 6.
式５および６より、復元行列Ｗをみつけることで、推定される原信号ｙ（ｔ）を求めることができる。従って、独立成分分析は、独立成分および混合行列に関する知識を一切利用せずに、観測信号ｘ（ｔ）から独立成分を表す原信号ｓ（ｔ）を推定する手法、あるいは、観測信号ｘ（ｔ）から復元行列Ｗを推定する手法である。 From Equations 5 and 6, the estimated original signal y (t) can be obtained by finding the restoration matrix W. Accordingly, the independent component analysis is a method for estimating the original signal s (t) representing the independent component from the observed signal x (t) without using any knowledge about the independent component and the mixing matrix, or the observed signal x (t ) To estimate the restoration matrix W.
実施例１の上部建造物の亀裂診断に使用するデータは、トラックによる亀裂シミュレーションの１０秒間のデータであり、健全橋梁と亀裂橋梁の振動の差があったＹ軸の加速度信号である。 The data used for the crack diagnosis of the superstructure in Example 1 is data for 10 seconds of the crack simulation by the track, and is an acceleration signal on the Y axis where there is a difference in vibration between the healthy bridge and the cracked bridge.
健全橋梁のシミュレーションデータに基づいて行った信号処理の結果は以下に示す。図４は、測定した８箇所の信号を示す。図５は、ＩＣＡによって抽出した７個の信号を示す。図６は、ＩＣＡによって抽出した７個の信号に基づいて、スペクトル解析を行った結果例を示す。図７は亀裂橋梁の８箇所の信号を示す。図８は、ＩＣＡによって抽出した７個の信号を示す。図９は、７個の信号に基づいてスペクトル解析結果例を示す。 The results of signal processing based on simulation data of healthy bridges are shown below. FIG. 4 shows the 8 signals measured. FIG. 5 shows seven signals extracted by ICA. FIG. 6 shows an example of a result of spectrum analysis based on seven signals extracted by ICA. FIG. 7 shows signals at eight points of the cracked bridge. FIG. 8 shows seven signals extracted by ICA. FIG. 9 shows an example of a spectrum analysis result based on seven signals.
上記の結果によって、健全橋梁と亀裂橋梁の固有振動数を比較した。図１０および１１は、この比較した結果を示す。 Based on the above results, the natural frequencies of the healthy and cracked bridges were compared. Figures 10 and 11 show the results of this comparison.
図１０は、独立成分１、２、．．．、７の順に、健全橋梁と亀裂橋梁の固有振動数を示す。図１１は、図１０を固有振動数の小さい順に並び換えた結果を示す。図１１に示されるように、固有振動数の変化量は、一番変化の大きい場合は、固有振動数の変化は０．２増加しており、橋梁全体になんらかの異常があることを示している。 FIG. 10 shows independent components 1, 2,. . . , 7 shows the natural frequencies of the sound bridge and the cracked bridge. FIG. 11 shows the result of rearranging FIG. 10 in ascending order of natural frequency. As shown in FIG. 11, when the change amount of the natural frequency is the largest, the change of the natural frequency is increased by 0.2, which indicates that there is some abnormality in the entire bridge. .
異常箇所の特定と劣化診断とは、橋梁全体を見て異常があることが判明した後に、異常(亀裂)部位を特定することである。図１２は、本発明で亀裂部位を特定するために行った信号処理の流れをフローチャートで示す。図１２を簡単に説明すると、ＡＲモデル(autoregressive model：自己回帰モデル)を用いて亀裂がある主桁（２桁）の４箇所(sensor1、sensor2、sensor3、sensor4) の信号情報を解析する（ステップＳ１２ａ）。またそれに基づいてボード線図を調べ、健全橋梁と亀裂橋梁を比較する（ステップＳ１２ｂ）ことで、亀裂部位を特定する（ステップＳ１２ｃ）。上述のステップＳ１２ａの機能を有する信号情報解析手段と、上述のステップＳ１２ｂの機能を有する亀裂部位特定手段とを備え橋梁診断プログラムを橋梁診断装置１ｄのコンピュータが実行することにより橋梁診断が行われる。以下にＡＲモデルについて説明する。 Identification of an abnormal location and deterioration diagnosis are to specify an abnormal (crack) site after it is found that there is an abnormality by looking at the entire bridge. FIG. 12 is a flowchart showing the flow of signal processing performed to identify a crack site in the present invention. Briefly explaining Fig. 12, the signal information of four places (sensor1, sensor2, sensor3, sensor4) of the main girder (two digits) with cracks is analyzed using the AR model (autoregressive model) (steps) S12a). Based on this, the Bode diagram is examined, and the cracked part is specified by comparing the healthy bridge and the cracked bridge (step S12b) (step S12c). The bridge diagnosis is performed by the computer of the bridge diagnosis apparatus 1d having the signal information analysis means having the function of step S12a and the crack site specifying means having the function of step S12b described above, and executing the bridge diagnosis program. The AR model will be described below.
ある時点の出力が、過去の出力の線形結合として得られるシステムがあるとき、このシステムを表すモデルをＡＲモデルと呼ぶ。ＡＲモデルは以下の式７で表される。 When there is a system in which an output at a certain time is obtained as a linear combination of past outputs, a model representing this system is called an AR model. The AR model is expressed by Equation 7 below.
ここで、ｙ（ｎ）は離散時間の時刻ｎにおけるシステムの出力を表す。またａ（ｋ）は任意の定数で、ＡＲモデルの性質を決定するパラメータであることからＡＲパラメータとよばれる。式７の場合、過去ｐ個の出力が使われているため、これはｐ次のＡＲモデル(またはＡＲ（ｐ）モデル)とよばれる。 Here, y (n) represents the output of the system at time n in discrete time. Further, a (k) is an arbitrary constant and is called an AR parameter because it is a parameter that determines the nature of the AR model. In the case of Expression 7, since the past p outputs are used, this is called a p-order AR model (or AR (p) model).
さらに、ε（ｎ）は、システムの出力が過去の出力の線形結合で表現しきれない要素を表しており、予測誤差とよばれる。これは、実際にはシステムの出力が過去ｍ
個(ｍ＞ｐ)の出力の線形結合であるのに対し、これをモデル化するときに過去ｐ個の線形結合としたために生じる誤差である。ε（ｎ）に対しては別の見方をすることもできる。すなわち、ε（ｎ）をシステムへの入力と考え、時刻ｎにおけるシステムの出力が、過去ｐ個の出力と時刻ｎの入力ε（ｎ）の線形結合として得られるとみなすこともできる。なお、ＡＲモデルで扱う信号は確定的でも確率的でもよいが、特に、ＡＲモデルによって出力される信号が定常確率過程である場合、この出力はＡＲ過程(自己回帰過程)とよばれる。
Furthermore, ε (n) represents an element in which the output of the system cannot be expressed by a linear combination of past outputs, and is called a prediction error. This is because the actual output of the system
While this is a linear combination of (m> p) outputs, it is an error that occurs because p linear combinations in the past when modeling this. Another way of looking at ε (n) is also possible. That is, ε (n) can be considered as an input to the system, and the output of the system at time n can be regarded as being obtained as a linear combination of the past p outputs and the input ε (n) at time n. The signal handled in the AR model may be deterministic or probabilistic. In particular, when the signal output by the AR model is a stationary probability process, this output is called an AR process (autoregressive process).
異常箇所の特定と劣化診断に使用するデータも橋梁全体の異常診断と同じにトラックによる亀裂シミュレーションの１０秒間のデータであり、健全橋梁と亀裂橋梁の振動の差があったＹ軸の加速度信号である。以下に健全橋梁と亀裂橋梁のボード線図を比較した結果を示す。図１３は、桁の加速度信号測定場所と亀裂想定箇所とを示す。図１４（ａ）ないし（ｄ）は、各々センサ1から４の加速度信号を示す。 The data used to identify abnormalities and diagnose deterioration is the 10-second data of the crack simulation by the track as well as the abnormality diagnosis of the entire bridge. It is a Y-axis acceleration signal that had a difference in vibration between the sound bridge and the cracked bridge. is there. The results of comparing the board diagrams of the healthy bridge and cracked bridge are shown below. FIG. 13 shows the digit acceleration signal measurement location and the assumed crack location. 14A to 14D show acceleration signals of sensors 1 to 4, respectively.
図１５（Ａ）ないし（Ｄ）は、上記の結果を示し、青い線は健全橋梁を示し、赤い線は亀裂橋梁を示している。特許図面ではモノクロのため色判別ができないが、一例として図１５（Ａ）に赤色と青色との区別を示しておく。図１５（Ｂ）に示されるように、sensor2のボード線図のピックＰの部分は、亀裂橋梁の方が健全橋梁のより大きいことが分かった。それによって、亀裂がsensor2のところにあると考えられる。そこで、本発明で提案した信号処理の方法によって、亀裂の部位が特定できると考えられる。 FIGS. 15A to 15D show the above results. The blue line indicates a healthy bridge and the red line indicates a cracked bridge. In the patent drawing, the color cannot be distinguished because it is monochrome, but as an example, FIG. 15A shows the distinction between red and blue. As shown in FIG. 15B, it was found that the picked P portion of the Bode diagram of sensor2 is larger in the cracked bridge than in the healthy bridge. As a result, the crack is thought to be at sensor2. Therefore, it is considered that the crack site can be specified by the signal processing method proposed in the present invention.
以上より、本発明の大型建造物の診断方法によれば、橋梁１ｆの桁の複数個所で計測した加速度信号を独立成分分析によって独立な信号に分離し、この結果である複数の独立成分信号のスペクトル信号の周波数あるいは信号ゲインの以前の結果との違いから劣化があることを診断する全体診断と、各信号のＡＲモデルによる伝達関数のボード線図の以前の結果からの変化から劣化箇所を特定することができる。 As described above, according to the diagnostic method for a large building of the present invention, acceleration signals measured at a plurality of places of the bridge 1f are separated into independent signals by independent component analysis, and a plurality of independent component signals as a result of this are separated. Overall diagnosis for diagnosing the deterioration from the difference in the spectrum signal frequency or signal gain from the previous result, and identifying the deterioration point from the change from the previous result of the bode diagram of the transfer function by the AR model of each signal can do.
図１６は、上述した橋梁診断を実現するための本発明のコンピュータ・プログラム（大型建造物に診断プログラム）を実行する橋梁診断装置１ｄのコンピュータの内部回路３０を示すブロック図である。図１６に示されるように、ＣＰＵ３１、ＲＯＭ３２、ＲＡＭ３３、画像制御部３６、コントローラ３７、入力制御部３９および外部インタフェース（Ｉ／Ｆ）部４１はバス４２に接続されている。図１６において、上述の本発明のコンピュータ・プログラムは、ＲＯＭ３２、ディスク３８ａ、ＣＤ−ＲＯＭあるいはＤＶＤ３８ｎ等の記録媒体（脱着可能な記録媒体を含む）に記録されている。ディスク３８ａには上述したセンサ情報等が記録されている。本発明のコンピュータ・プログラムは、ＲＯＭ３２からバス４２を介し、またはディスク３８ａ、ＣＤ−ＲＯＭまたはＤＶＤ３８ｎ等の記録媒体からコントローラ３７を経由してバス４２を介しＲＡＭ３３へロードされる。入力制御部３９はマウス、キーボード等の入力操作部４０と接続され入力制御等を行う。画像メモリであるＶＲＡＭ３５は表示装置３４の少なくとも一画面分のデータ容量に相当する容量を有しており、画像制御部３６はＶＲＡＭ３５のデータを画像データへ変換して表示装置３４へ送出する機能を有している。外部Ｉ／Ｆ部４１は、センサ１４ａ等と通信する際の入出力インタフェース機能を有する。 FIG. 16 is a block diagram showing an internal circuit 30 of the computer of the bridge diagnosis apparatus 1d that executes the computer program of the present invention (diagnosis program for a large building) for realizing the above-described bridge diagnosis. As shown in FIG. 16, the CPU 31, ROM 32, RAM 33, image control unit 36, controller 37, input control unit 39 and external interface (I / F) unit 41 are connected to a bus 42. In FIG. 16, the above-described computer program of the present invention is recorded on a recording medium (including a removable recording medium) such as a ROM 32, a disk 38a, a CD-ROM, or a DVD 38n. The above-described sensor information and the like are recorded on the disk 38a. The computer program of the present invention is loaded into the RAM 33 from the ROM 32 via the bus 42 or from a recording medium such as a disk 38a, CD-ROM or DVD 38n via the controller 37 via the bus 42. The input control unit 39 is connected to an input operation unit 40 such as a mouse and a keyboard to perform input control and the like. The VRAM 35 that is an image memory has a capacity corresponding to the data capacity of at least one screen of the display device 34, and the image control unit 36 has a function of converting the data in the VRAM 35 into image data and sending it to the display device 34. Have. The external I / F unit 41 has an input / output interface function when communicating with the sensor 14a and the like.
上述のようにＣＰＵ３１が本発明のコンピュータ・プログラムを実行することにより、本発明の目的を達成することができる。当該コンピュータ・プログラムは上述のようにＣＤ−ＲＯＭまたはＤＶＤ３８ｎ等の記録媒体の形態でコンピュータＣＰＵ３１に供給することができ、当該コンピュータ・プログラムを記録したＣＤ−ＲＯＭまたはＤＶＤ３８ｎ等の記録媒体も同様に本発明を構成することになる。当該コンピュータ・プログラムを記録した記録媒体としては上述された記録媒体の他に、例えばメモリ・カード、メモリ・スティック、光ディスク、ＦＤ等を用いることができる。 As described above, the CPU 31 executes the computer program of the present invention to achieve the object of the present invention. The computer program can be supplied to the computer CPU 31 in the form of a recording medium such as a CD-ROM or DVD 38n as described above, and a recording medium such as a CD-ROM or DVD 38n on which the computer program is recorded is also recorded in this manner. It constitutes the invention. As a recording medium on which the computer program is recorded, for example, a memory card, a memory stick, an optical disk, an FD, or the like can be used in addition to the recording medium described above.
本発明の活用例として、大型構造物、例えば橋梁、ビル、トンネル、ダム、擁壁等道路構造物、桶門・桶管等河川構造物、港湾構造物、上下水道施設等自体およびこれらの構成要素への適用が挙げられる。 Examples of the use of the present invention include large structures such as bridges, buildings, tunnels, dams, road structures such as retaining walls, river structures such as locks and pipes, harbor structures, water and sewage facilities themselves, and configurations thereof. Application to elements.
１ａ 無線付き橋梁センサ、 １ｂ データ記憶装置、 １ｃ データ収集装置、 １ｄ 橋梁診断装置、 １ｅ 走行車両、 １ｆ 橋梁、 ３０ 内部回路、 ３１ ＣＰＵ、 ３２ ＲＯＭ、 ３３ ＲＡＭ、 ３４ 表示装置、 ３５ ＶＲＡＭ、 ３６ 画像制御部、 ３７ コントローラ、 ３８ａ ディスク、 ３８ｎ ＣＤ−ＲＯＭ、ＤＶＤ、 ３９ 入力制御部、 ４０ 入力操作部、 ４１ 外部Ｉ／Ｆ部、 ４２ バス。 1a Bridge sensor with radio, 1b data storage device, 1c data collection device, 1d bridge diagnostic device, 1e traveling vehicle, 1f bridge, 30 internal circuit, 31 CPU, 32 ROM, 33 RAM, 34 display device, 35 VRAM, 36 image Control unit, 37 controller, 38a disk, 38n CD-ROM, DVD, 39 input control unit, 40 input operation unit, 41 external I / F unit, 42 bus.
Claims (10)
大型建造物の所定の部位に配置された複数の無線付橋梁センサと、
複数の前記無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置と、
前記記録装置から転送されたセンサ情報に基づき大型建造物の劣化及び／又は健全度を診断する診断装置とを備え、
前記診断装置は、
複数のセンサ情報から独立成分分析による独立成分の変化を検出して大型建造物全体の異常診断を行う全体異常診断手段であって、
大型建造物の複数箇所の振動データを独立成分分析で信号解析を行い、該大型建造物の独立な振動成分を抽出する信号抽出手段と、
前記信号抽出手段により抽出された独立な振動成分についてスペクトル解析を行うことにより、大型建造物全体の固有振動数を求める固有振動数取得手段と、
予め取得された大型建造物の健全時における健全時固有振動数と前記固有振動数取得手段により取得された大型建造物全体の固有振動数との比較に基づき、大型建造物全体に異常があるかどうかを把握する異常把握手段とを備えたものと、
前記全体異常診断手段による異常診断に基づき、異常箇所の特定及び劣化診断を行う異常部位把握手段であって、
主桁に配置された複数の無線付橋梁センサにより測定された一定期間における加速度信号をＡＲモデル(自己回帰モデル)に基づく入出力を有するシステムとし、該無線付橋梁センサ毎に、該加速度信号を周波数毎に該システムの入力と出力との振幅比で表すＡＲモデルによる伝達関数のボード線図と予め取得した亀裂のない健全大型構造物のボード線図とを比較して、該健全大型構造物の振幅比より大きい振幅比を示す無線付橋梁センサが配置された個所に主桁の亀裂部位があると特定する亀裂部位特定手段を備えたことを特徴とする大型建造物の診断システム。 A diagnostic system for a large building that diagnoses deterioration and / or soundness of a large building that is a bridge or a superstructure of a bridge ,
A plurality of wireless bridge sensors arranged in a predetermined part of a large building;
A recording device that records sensor information measured by a plurality of the wireless bridge sensors and transmitted wirelessly by the wireless bridge sensors;
A diagnostic device for diagnosing deterioration and / or soundness of a large building based on sensor information transferred from the recording device,
The diagnostic device comprises:
An overall abnormality diagnosis means for detecting an abnormality of an entire large building by detecting an independent component change by independent component analysis from a plurality of sensor information ,
A signal extraction means for performing signal analysis by independent component analysis on vibration data of a plurality of locations of a large building, and extracting an independent vibration component of the large building;
By performing spectrum analysis on the independent vibration component extracted by the signal extraction means, natural frequency acquisition means for obtaining the natural frequency of the entire large building,
Whether there is an abnormality in the entire large building based on a comparison between the natural frequency of the healthy large building acquired in advance and the natural frequency of the entire large building acquired by the natural frequency acquisition means. Equipped with an abnormality grasping means to grasp whether or not ,
Based on the abnormality diagnosis by the overall abnormality diagnosis means, it is an abnormal part grasping means for performing an abnormality point identification and deterioration diagnosis ,
The acceleration signal for a certain period measured by a plurality of wireless bridge sensors arranged in the main girder is a system having an input / output based on an AR model (autoregressive model), and the acceleration signal is determined for each wireless bridge sensor. Compare the Bode diagram of the transfer function by the AR model expressed by the amplitude ratio between the input and output of the system for each frequency and the Bode diagram of the healthy large structure without cracks obtained in advance. A diagnostic system for a large building, characterized by comprising crack site specifying means for specifying that there is a crack site of a main girder at a location where a wireless bridge sensor having an amplitude ratio larger than the above is provided .
大型建造物の所定の部位に配置された複数の無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置から転送された複数のセンサ情報から独立成分分析による独立成分の変化を検出して大型建造物全体の異常診断を行う全体異常診断手段であって、
大型建造物の複数箇所の振動データを独立成分分析で信号解析を行い、該大型建造物の独立な振動成分を抽出する信号抽出手段と、
前記信号抽出手段により抽出された独立な振動成分についてスペクトル解析を行うことにより、大型建造物全体の固有振動数を求める固有振動数取得手段と、
予め取得された大型建造物の健全時における健全時固有振動数と前記固有振動数取得手段により取得された大型建造物全体の固有振動数との比較に基づき、大型建造物全体に異常があるかどうかを把握する異常把握手段とを備えた全体異常診断手段、
前記全体異常診断手段による異常診断に基づき、異常箇所の特定及び劣化診断を行う異常部位把握手段であって、
主桁に配置された複数の無線付橋梁センサにより測定された一定期間における加速度信号をＡＲモデル(自己回帰モデル)に基づく入出力を有するシステムとし、該無線付橋梁センサ毎に、該加速度信号を周波数毎に該システムの入力と出力との振幅比で表すＡＲモデルによる伝達関数のボード線図と予め取得した亀裂のない健全大型構造物のボード線図とを比較して、該健全大型構造物の振幅比より大きい振幅比を示す無線付橋梁センサが配置された個所に主桁の亀裂部位があると特定する亀裂部位特定手段として機能させるための大型建造物の診断プログラム。 A plurality of wireless bridge sensors arranged at a predetermined part of a large building which is a bridge or a superstructure of the bridge, and a sensor which is measured by the plurality of wireless bridge sensors and transmitted by radio of the wireless bridge sensor Diagnosis by the diagnostic device in a diagnostic system for a large building comprising a recording device for recording information and a diagnostic device for diagnosing deterioration and / or soundness of a large building based on sensor information transferred from the recording device A diagnostic program for a large-scale building for performing
Independent component analysis from a plurality of sensor information transferred from a recording device that records the sensor information measured by a plurality of wireless bridge sensors arranged in a predetermined part of a large building and transmitted wirelessly by the wireless bridge sensor An overall abnormality diagnosis means for detecting an abnormality of an entire large building by detecting a change in independent component due to ,
A signal extraction means for performing signal analysis by independent component analysis on vibration data of a plurality of locations of a large building, and extracting an independent vibration component of the large building;
By performing spectrum analysis on the independent vibration component extracted by the signal extraction means, natural frequency acquisition means for obtaining the natural frequency of the entire large building,
Whether there is an abnormality in the entire large building based on a comparison between the natural frequency of the healthy large building acquired in advance and the natural frequency of the entire large building acquired by the natural frequency acquisition means. An overall abnormality diagnosis means comprising an abnormality grasping means for grasping whether or not ,
Based on the abnormality diagnosis by the overall abnormality diagnosis means, it is an abnormal part grasping means for performing an abnormality point identification and deterioration diagnosis ,
The acceleration signal for a certain period measured by a plurality of wireless bridge sensors arranged in the main girder is a system having an input / output based on an AR model (autoregressive model), and the acceleration signal is determined for each wireless bridge sensor. Compare the Bode diagram of the transfer function by the AR model expressed by the amplitude ratio between the input and output of the system for each frequency and the Bode diagram of the healthy large structure without cracks obtained in advance. A diagnostic program for a large-scale building for functioning as a crack part specifying means for specifying that there is a crack part of a main girder at a place where a wireless bridge sensor having an amplitude ratio larger than the above is provided .
大型建造物の所定の部位に配置された複数の無線付橋梁センサにより計測され該無線付橋梁センサの無線により送信されたセンサ情報を記録する記録装置から転送された複数のセンサ情報から独立成分分析による独立成分の変化を検出して大型建造物全体の異常診断を行う全体異常診断ステップであって、
大型建造物の複数箇所の振動データを独立成分分析で信号解析を行い、該大型建造物の独立な振動成分を抽出する信号抽出ステップと、
前記信号抽出ステップＳで抽出された独立な振動成分についてスペクトル解析を行うことにより、大型建造物全体の固有振動数を求める固有振動数取得ステップと、
予め取得された大型建造物の健全時における健全時固有振動数と前記固有振動数取得ステップで取得された大型建造物全体の固有振動数との比較に基づき、大型建造物全体に異常があるかどうかを把握する異常把握ステップとを備えたものと、
前記全体異常診断ステップによる異常診断に基づき、異常箇所の特定及び劣化診断を行う異常部位把握ステップであって、
主桁に配置された複数の無線付橋梁センサにより測定された一定期間における加速度信号をＡＲモデル(自己回帰モデル)に基づく入出力を有するシステムとし、該無線付橋梁センサ毎に、該加速度信号を周波数毎に該システムの入力と出力との振幅比で表すＡＲモデルによる伝達関数のボード線図と予め取得した亀裂のない健全大型構造物のボード線図とを比較して、該健全大型構造物の振幅比より大きい振幅比を示す無線付橋梁センサが配置された個所に主桁の亀裂部位があると特定する亀裂部位特定ステップとを備えたことを特徴とする大型建造物の診断方法。 A plurality of wireless bridge sensors arranged at a predetermined part of a large building which is a bridge or a superstructure of the bridge, and a sensor which is measured by the plurality of wireless bridge sensors and transmitted by radio of the wireless bridge sensor A diagnostic method for a large building using a recording device for recording information and a diagnostic device for diagnosing deterioration and / or soundness of a large building based on sensor information transferred from the recording device,
Independent component analysis from a plurality of sensor information transferred from a recording device that records the sensor information measured by a plurality of wireless bridge sensors arranged in a predetermined part of a large building and transmitted wirelessly by the wireless bridge sensor An overall abnormality diagnosis step for detecting an abnormality of an entire large building by detecting a change in independent components due to ,
A signal extraction step of performing signal analysis by independent component analysis on vibration data of a plurality of locations of the large building, and extracting an independent vibration component of the large building;
A natural frequency acquisition step for obtaining a natural frequency of the entire large building by performing spectrum analysis on the independent vibration component extracted in the signal extraction step S;
Whether there is an abnormality in the entire large building based on a comparison between the natural frequency of the healthy large building acquired in advance and the natural frequency of the entire large building acquired in the natural frequency acquisition step. An abnormality grasping step for grasping whether or not ,
Based on the abnormality diagnosis by the overall abnormality diagnosis step, it is an abnormal part grasping step for performing abnormality diagnosis and deterioration diagnosis ,
The acceleration signal for a certain period measured by a plurality of wireless bridge sensors arranged in the main girder is a system having an input / output based on an AR model (autoregressive model), and the acceleration signal is determined for each wireless bridge sensor. Compare the Bode diagram of the transfer function by the AR model expressed by the amplitude ratio between the input and output of the system for each frequency and the Bode diagram of the healthy large structure without cracks obtained in advance. A method for diagnosing a large-scale building comprising: a crack site specifying step for specifying that there is a crack portion of a main girder at a location where a wireless bridge sensor having an amplitude ratio larger than the amplitude ratio is arranged .
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