JP4517044B2 - Defect inspection method and apparatus - Google Patents

Description

ただし、ΔＶ_sinは参照波形に同期する赤外線強度の変動振幅を表し、ΔＶ_cosは、参照波形と９０度位相がずれたｃｏｓ波に同期する赤外線強度の変動振幅を表す。なお，Ｎは信号処理における取り込みフレーム数である。
【００５１】
表面温度変動が、変動熱負荷の位相と完全に一致している場合には、ΔＶ_cosは０となる。熱拡散などの影響により、表面温度変動が、変動熱負荷の位相からずれる場合には、ΔＶ_cosの成分が表れる。この場合には、次式により温度変動振幅の絶対値ΔＶおよび位相遅れθを求めることができる。
【００５２】
【数２】

ここで、求めたθを、時刻ｔ、単位領域ｉにおける参照波形Ｒ_tとの位相差Ｐ_tiと定義する。
【００５３】
ＣＰＵ３０は、次の単位領域における位相差を求めるため、ｉに１を加算してｉ＋１とする（ステップＳ５０４）。さらに、ｉが全領域数Ｉを越えるまで（ステップＳ５０５，ＹＥＳ）、ステップＳ５０１〜５０４の処理を繰り返し位相差Ｐ_tiを求める（ステップＳ５０５，ＮＯ）。
【００５４】
次に、ＣＰＵ３０は、時刻ｔにΔｔを加算して時刻をｔ＋Δｔとし（ステップＳ５０６）、所定の解析時間Ｔを越えるまで（ステップＳ５０７，ＹＥＳ）、ステップＳ５０１〜５０６を繰り返す（ステップＳ５０７，ＮＯ）。
【００５５】
このように、位相差Ｐ_tiを求める信号処理が、赤外線カメラ２３内の赤外線センサの各ピクセル毎つまり全領域数Ｉ回、赤外線カメラ２３が計測した取り込みフレーム数Ｎ回行われる。
【００５６】
１−４−２．解析画像の表示
計測データの解析処理を終えたＣＰＵ３０は、時刻Ｔにおける位相差Ｐ_{T ｉ}を各領域について呼び出した後、これに基づいて計測領域全体の画像データを生成し（ステップＳ４０５）、ディスプレイ３３に出力を行う（ステップＳ４０６）。すなわち、ＣＰＵ３０は、入力した位相差を所定の表示色に対応させて画像データを生成し、これを表示する。
【００５７】
図６（Ａ）に、上記に示した欠陥検査システムを適用して、人工欠陥を有するコンクリート試験体にかかる欠陥検査を行った場合の画像データの表示の例を示す。なお、この画像は、図６（Ｂ）に示す人工欠陥１〜６を有するコンクリート試験体を計測したものである。前記人工欠陥１〜６は、それぞれ深さと厚さが異なる欠陥をコンクリート中に埋め込まれて作製されている。
【００５８】
図６Ａにおいて、右側の列６１に３つ鮮明にコントラスト差として表示されている部分が、人工欠陥４〜６にそれぞれ対応している。なお、人工欠陥１〜３は、左側の列６０に表示されているが、そのコントラストはあまり鮮明ではない。
【００５９】
これにより、この検査時に設定された熱波動の加熱条件の一つである加熱期間が、深さ２０ｍｍの人工欠陥４〜６を検出するのに適していたと考えられる。
【００６０】
１−５．まとめ
図７は、計測領域の単位領域における計測データと参照波形との位相差をグラフで示した例である。赤外線カメラ２３が計測した計測領域のフレームにおける各単位領域ｉにおける位相差Ｐ_tiは、欠陥部の温度変動曲線７１に近似した参照波形Ｒ₇₁と、健全部の温度変動曲線７３に近似した参照波形Ｒ₇₃との位相差で表現することができる。
【００６１】
画像データとして表示する位相差は、加熱期間と欠陥の深さによって決定されていると考えられることから、被検査体２０の欠陥に応じた加熱期間を設定する必要がある。
【００６２】
２．第２の実施形態
上述したように、画像データとして表示する位相差は、加熱期間と欠陥の深さによって決定されており、検査を行う欠陥の深さに応じて最適な加熱期間を設定する必要がある。図８は、最適な加熱期間を求めることを目的として、加熱条件の一つである加熱期間を変更して前記人工欠陥（図６Ｂ）を繰り返し計測した場合の画像である。
【００６３】
図８Ａ〜Ｄに示すように、欠陥深さ２０ｍｍの欠陥４〜６を示すコントラスト差は、期間Ｔが１０〜３０分において鮮明に表示されており、特に、期間Ｔが２０分のときに最も鮮明にコントラスト差が表示されている。
【００６４】
また、図８Ｂ〜Ｅに示すように、欠陥深さ３０ｍｍの欠陥１〜３を示すコントラスト差は、期間Ｔが２０〜４０分において鮮明に表示されており、特に、期間Ｔが３０分のときに最も鮮明にコントラスト差が表示されている。
【００６５】
上記の結果から考察した、加熱期間と欠陥深さの関係テーブルの例を図９に示す。図９に示すように、各欠陥深さ毎において位相差が最も大きくなるときの加熱期間が、最適な加熱期間であると考えられる。例えば、欠陥深さ「１０ｍｍ」のときの最大位相差は「２．０°」であることより、この欠陥深さを検査する時の最適な加熱期間は、「１０分」である。すなわち、前記最適な加熱期間が、［特許請求の範囲］において示した「相違が顕著となった所定期間」に該当する。
【００６６】
したがって、当該関係テーブルを使用することにより、被検査体２０において検査を行う欠陥深さに応じて、加熱期間を設定することができる。これにより、計測回数の低減を図ることができ検査効率の向上が望める。
【００６７】
本実施形態においては、加熱期間と欠陥深さの関係テーブルを使用して、検査効率を高めた欠陥検査方法について説明する。
【００６８】
２−１．欠陥検査の概要
第１の実施形態においては、人工欠陥を有するコンクリート試験体にかかる欠陥検出を行ったが、本実施形態においては、実際に経年劣化による内部欠陥を有するコンクリート構造物について、本発明による欠陥検査システムを適用した場合について説明する。
【００６９】
なお、欠陥検査を行うコンクリート構造物は、前記コンクリート試験体と同条件の材料・環境で作製されたものとし、図９に示した、欠陥の深さと加熱期間の関係を表した参照テーブルを使用するものとする。
【００７０】
２−２．欠陥深さの推定方法
まず、検査対象となるコンクリート構造物について、その検査範囲におけるコンクリートの厚さや鉄筋かぶりの厚さを調べ、欠陥検査を行う最大深さを決定する。なお、鉄筋かぶりの厚さを調べる際には、超音波、マイクロ波レーダまたは電磁誘導などを利用した検査装置を使用すればよい。
【００７１】
次に、要求される検査効率から計測する回数を決定し、図９の参照テーブルから前記最大深さに対応する加熱期間を決定して計測を行う。例えば、本実施形態においては、調査の結果、最大深さは３０ｍｍと考えられるので参照テーブルにより、加熱期間を１０〜３０分とし、計測回数を１回とした。
【００７２】
図１０は、コンクリート構造物に本発明による欠陥検査システムを適用することによって得られた画像データを表示したものである。なお、図１０（Ａ）〜（Ｃ）は、それぞれ加熱期間を１０〜３０分と変更して計測しており、それぞれの画像において画像中央部に欠陥が存在していることが明瞭に表示されている。
【００７３】
以下▲１▼〜▲３▼に示すように、これらの画像および前記参照テーブルにより、この欠陥に関する定量的な情報を推定することができる。
【００７４】
▲１▼ 図１０（Ａ）では、画像中心の欠陥の輪郭部１０１が全体に対するコントラスト差として鮮明に表示されている。したがって、参照テーブルによりこの範囲の欠陥深さは、１０ｍｍ前後であると推定できる。すなわち、表面から１０ｍｍ前後において欠陥が存在している。
【００７５】
▲２▼ 図１０（Ｂ）では、画像中心の欠陥の輪郭部１０３を示すコントラスト差が、図１０（Ａ）と比較すると、中心に向かって拡大するように表示されている。したがって、参照テーブルによりこの範囲の欠陥深さは２０ｍｍ前後であり、この範囲における欠陥は１０ｍｍの範囲の欠陥よりも空洞部がより大きいものであると推定することができる。
【００７６】
▲３▼ 図１０（Ｃ）では、画像中心の欠陥の輪郭部１０５を示すコントラスト差が、図１０（Ｂ）と比較すると、さらに中心に向かって拡大するように表示されている。したがって、参照テーブルによりこの範囲の欠陥深さは３０ｍｍ前後であり、この範囲における欠陥は２０ｍｍの範囲の欠陥よりも空洞部がより大きいものであると推定することができる。
【００７７】
これにより、この内部欠陥は、コンクリート構造物の表面から深さ１０ｍｍ〜３０ｍｍの位置に存在し、表面から内部への垂直方向に向かって先細りした形状の浮きであることが推定できる。
【００７８】
なお、図１１に、今回計測したコンクリート構造物の内部欠陥部分を、採取したときの例を示す。図１１（Ａ）に示すように、この内部欠陥部分は、図１０に示した画像における内部欠陥のコントラスト差の輪郭部とほぼ同形状の輪郭を有している。また、図１１（Ｂ）は、この内部欠陥部の側面を示しており、その厚みは２０〜３０ｍｍであった。
【００７９】
このように、本発明を適用した欠陥検査システムを用いてコンクリート構造物の欠陥検査を行うことで、その内部欠陥にかかる深さを同定するとともに、その大きさや厚さなどの内部欠陥の定量的な情報を推定することが可能となる。これにより、欠陥検査における検査効率を高めることができ、欠陥の事故確率に応じて効果的な対策を講じるリスクベースメンテナンスが可能となる。
【００８０】
２−３．欠陥検査制御装置におけるフローチャート
図１２に、２−２．に示した欠陥深さの推定方法を利用して内部欠陥を自動推定する欠陥検査制御装置１０におけるフローチャートを示す。
【００８１】
まず、欠陥検査制御装置１０であるコンピュータ装置２９において、検出する欠陥の最大深さを入力する（ステップＳ１２０１）。なお、この時入力する最大深さは、２−２．に示すように、コンクリート構造物の事前調査によって決定すればよい。
【００８２】
次に、要求される検査効率に基づいて、計測する回数および加熱条件の範囲を入力する（ステップＳ１２０２）。なお、この加熱条件の範囲は、前記最大深さに応じてＣＰＵ３０が自動的に判断するようにしてもよい。
【００８３】
欠陥検査制御装置１０において、コンピュータ装置２９のＣＰＵ３０は、信号発生装置２７に対して加熱条件を出力する（ステップＳ１２０３）。ここで加熱条件とは、被検査体２０に熱負荷を与える時間およびその繰り返し回数を与えるものである。なお、振幅は一定値とし、デューティサイクルは５０％としている。
【００８４】
前記加熱条件は、信号発生装置２７に与えられた後、波形信号に変換されてリレー装置２５に出力される。リレー装置２５は、入力した波形信号に基づいてヒーター２１を作動させる。これにより、所定の加熱条件で被検査体２０に熱負荷を与える。
【００８５】
所定の加熱条件で加熱・加熱停止を行いつつ、赤外線カメラ２３を用いて、特に加熱停止期間における被検査体２０の表面温度を計測する。この計測データは、接続されたコンピュータ装置２９に出力され、ハードディスク３５等に記録される（ステップＳ１２０４）。この計測処理を所定時間毎に繰り返すことにより、加熱停止期間における、計測時刻毎の表面温度の計測データを取得する。なお、計測データは、被検査体２０であるコンクリート構造物における測定領域の各単位領域毎の表面温度データである。
【００８６】
所定の繰り返し回数において上記の処理を行った後、計測を終了し、設定された範囲において加熱期間を変更して（ステップＳ１２１０）、ステップＳ１２０３から同様の処理を繰り返す（ステップＳ１２０５，ＮＯ）。なお、本実施形態においては、加熱・加熱停止を行う繰り返し回数を１回としている。
【００８７】
設定された範囲の加熱条件での計測を終了すると（ステップＳ１２０５，ＹＥＳ）、ＣＰＵ３０は、計測した各加熱期間において、計測データの解析処理を行う（ステップＳ１２０６）。なお、ステップＳ１２０６に示す計測データの解析処理は、第１の実施形態の図４に示した処理と同様である。
【００８８】
各加熱期間における計測データの解析処理を終えたＣＰＵ３０は、時刻Ｔにおける位相差Ｐ_{T ｉ}を各領域について呼び出し、これに基づいて欠陥の有無を判断する。さらに、ＣＰＵ３０は、欠陥であると判断した領域の位相差を示す相関データに基づいて、当該欠陥の存在する深さを判定する（ステップＳ１２０７）。すなわち、各領域の位相差と、加熱期間と欠陥深さの関係を示した参照テーブル１２０とを参照して、欠陥を示していると判断した領域の深さを判定する。
【００８９】
次に、ＣＰＵ３０は、計測領域全体の画像データを生成し（ステップＳ１２０８）、図１０に示す画像データをディスプレイ３３に出力する（ステップＳ１２０９）。なお、本実施形態においては、各画面において欠陥部分の深さの値が同時に表示されているものとする（図示せず）。
【００９０】
また、ステップＳ１２０７において判定した欠陥深さを利用して、図１３に示すような、欠陥形状の推定画面を同時に表示してもよい。これにより、欠陥部位における定量的な情報を画像データとして表示させ、欠陥検査における検査結果の確認が容易となり、特別な判断知識を有していない者であっても内部欠陥を見いだすことができる。なお、図１３においては、欠陥部位を二次元的に表現しているが、三次元形状として表現してもよい。これにより、より詳細な欠陥に関する情報を取得することができる。
【００９１】
３．その他の実施形態
上記実施形態においては、被検査体１としてコンクリート材料を使用しているが、例えば、ＣＦＲＰなどの低熱伝導性材料から構成された複合材料における欠陥検査にも本発明は適用可能である。
【００９２】
上記実施形態においては、加熱・加熱停止を行う繰り返し回数を１回としているが、被検査体の性質によっては複数回繰り返してもよい。なお、この場合、被測定物表面における熱源の反射が影響しなければ、加熱・加熱停止期間の両期間における温度変動を連続して計測すればよい。
【００９３】
上記実施形態においては、欠陥部位を求める際の特徴量として、計測データから得られる波形と所定の参照波形との位相差を用いたが、他の指標を特徴量として用いてもよい。例えば、計測データの時間変化における温度勾配データ、当該温度勾配データの時間変化データ、計測データについてフーリエ解析を行った場合の周波数成分データ、計測データ波形のピーク値または当該ピーク値への到達時間などを特徴量としてもよい。
【００９４】
さらに、これらの特徴量の比較を行う際に、各計測データと所定の参照波形との相関処理によって計測データ同士を間接的に比較しているが、各計測データを直接的に比較してもよい。例えば、各計測データのピーク値を比較すること等がこれに該当する。
【００９５】
上記実施形態においては、加熱期間と欠陥深さの関係テーブルを使用して欠陥部位にかかる定量的な情報を取得しているが、さらに欠陥厚さを加えた関係テーブルを使用してもよい。この場合、より精度の高い欠陥検出が可能となる。
【００９６】
上記実施形態においては、欠陥検査制御装置１０をコンピュータ装置２９および信号発生装置２７から構成したが、当該欠陥検査制御装置１０を、加熱制御手段１１およびデータ記録手段１３を実現するデータ収集装置と欠陥判断手段１５を実現する欠陥判断装置とを、それぞれ別の装置から構成してもよい。例えば、通信回線を利用してこれらの装置を接続することで、欠陥検査における遠隔操作が可能となる。
【図面の簡単な説明】
【図１】この発明の一実施形態による欠陥検出システムの機能ブロック図を示す図である。
【図２】この発明の一実施形態による欠陥検出システムを実現する装置の構成図を示す例である。
【図３】この発明の一実施形態によるコンピュータ装置のハードウェア構成図を示す例である。
【図４】欠陥検査制御装置におけるフローチャートを示す図である。
【図４ａ】加熱制御のための信号と、被検査体の表面における温度変動曲線との関係を示す図である。
【図５】計測データの解析処理におけるフローチャートを示す図である。
【図６】人工欠陥（Ｂ）と、この人工欠陥を計測したときの画像データの表示画面の例（Ａ）である。
【図７】計測領域の単位領域における計測データと参照波形との位相差をグラフで示した例である。
【図８】加熱期間を変更して、人工欠陥を計測したときの画像データの表示画面の例である。
【図９】欠陥の深さ毎に、加熱期間と位相差との関係を示した参照テーブルの例である。
【図１０】加熱期間を変更して、内部欠陥をもつコンクリート構造物を計測したときの画像データの表示画面のである。
【図１１】計測したコンクリート構造物の内部欠陥部分を、採取したときの例である。
【図１２】参照テーブル使用時の欠陥検査制御装置におけるフローチャートを示す図である。
【図１３】欠陥部位にかかる定量的な情報に基づいて、欠陥の形状を推定した画面の例である。
【符号の説明】
１０・・・欠陥検査制御装置
１１・・・加熱制御手段
１３・・・データ記録手段
１５・・・欠陥判断手段
１７・・・加熱装置
１９・・・温度計測器[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a method and an apparatus for detecting an internal defect in an object to be inspected composed of a low thermal conductivity material such as concrete.
[0002]
[Prior art and problems]
Conventionally, a thermography method is known as a method for examining internal defects such as floating and peeling of a concrete structure. In this conventional thermography method, the local temperature change region of the concrete surface that occurs when a thermal load is applied to a concrete structure or the like is measured by infrared thermography, and the measurement data is output as an image to inspect internal defects. Do. In other words, the output image represents the distribution of the measured infrared intensity, and the internal defect can be detected based on the contrast difference between the infrared intensity of the defective part and the healthy part.
[0003]
However, the conventional thermography method can detect only the presence or absence of an internal defect, and cannot obtain quantitative information such as the depth, thickness or size of the defective portion. In addition, because defects are detected based only on adiabatic temperature field measurements, high-precision detection is suitable for detecting internal defects with small thermal insulation effects, such as honeycombs, artificial cracks, and cold joints. I can't do it.
[0004]
The present invention has been made in order to solve such a problem, and detects an internal defect of an object to be inspected composed of a low thermal conductivity material such as a concrete structure, and the depth and shape of the defective portion. It is an object of the present invention to provide a defect inspection method and apparatus capable of quantitatively and accurately detecting such information.
[0005]
[Means for Solving the Problems and Effects of the Invention]
(1) In the defect inspection method according to the present invention, the surface of the object to be inspected is heated simultaneously over the entire measurement region, and at least in the heating stop period after the heating is stopped, for each unit region of the measurement region The method is characterized in that a time change in the surface temperature is measured, and a defect in the inspection object is found based on a relative difference between the unit regions with respect to a time change in the surface temperature in each unit region.
[0006]
Therefore, it is possible to perform measurement in consideration of the surface reflection heat of the object to be inspected generated in the heating process. That is, since the measurement is performed in the cooling process that is the heating stop period, the surface temperature of the object to be inspected can be measured more accurately. Thereby, the relative difference of the surface temperature between each unit area | region can be correctly detected as a defect in a to-be-inspected object.
[0007]
(2) The defect inspection method according to the present invention is characterized in that the object to be inspected is composed of a low thermal conductivity material.
[0008]
Therefore, it can be applied to defect inspection of concrete structures and composite materials having low thermal conductivity. Moreover, since the temperature fluctuation is gentle due to the low thermal conductivity, the number of times of measurement can be reduced. For example, even when measuring a plurality of continuous measurement areas, the measurement efficiency can be improved by performing heating and measurement in order for each measurement area.
[0009]
(3) In the defect inspection method according to the present invention, the position of the defect in the object to be inspected is specified based on the relative difference between the unit regions with respect to the temporal change of the surface temperature in each unit region. It is said.
[0010]
Therefore, an accurate defect position can be specified by clearly expressing the difference between the unit areas.
[0011]
(4) The defect inspection method according to the present invention is characterized in that a relative difference between the unit regions with respect to a temporal change of the surface temperature in each unit region is presented as a visually recognizable image.
[0012]
Therefore, by associating each unit area with a constituent unit of image data, the entire measurement area can be output as image data, and the defect position can be identified visually. For example, the relative difference between the unit areas can be expressed as a contrast difference on the image data.
[0013]
(5) The defect inspection method according to the present invention is characterized in that the relative difference is determined based on a comparison of a feature amount in a predetermined waveform and a waveform due to a temporal change in surface temperature in each unit region.
[0014]
Therefore, even if disturbance data is included in the measurement data, highly accurate defect detection can be performed by referring to the predetermined waveform. For example, in the case of an inspected object such as a concrete structure, disturbance data may be generated due to dirt, solar radiation or reflection of concrete surface such as soot and free lime, and whether the disturbance is compared with a predetermined waveform. Judgment can be made.
[0015]
(6) In the defect inspection method according to the present invention, the comparison of the feature values is performed by using a specific value indicating a correlation between both waveforms of the waveform due to the time change of the surface temperature in each unit region and a predetermined waveform, or both waveforms It is characterized by being performed based on the phase difference.
[0016]
Therefore, when comparing feature amounts, information regarding defects can be acquired as a quantitative value corresponding to the degree of the comparison result. In other words, accurate defect inspection can be performed by using various indexes indicated by the waveforms as feature quantities.
[0017]
(7) In the defect inspection method according to the present invention, heating and heating stop are performed for a predetermined period, and the predetermined period is changed and measured, and a difference in relative temperature change between the unit regions becomes significant. The depth of the defect is estimated based on the predetermined period.
[0018]
Therefore, it is possible to accurately estimate the depth at which the internal defect exists. Moreover, the depth of the internal defect can be estimated more accurately by changing the predetermined period and repeating the measurement. Furthermore, the size and thickness of internal defects can be estimated simultaneously.
[0019]
(8) The defect inspection method according to the present invention is characterized in that the defect depth is estimated based on a table in which the defect depth is associated with the predetermined period in advance.
[0020]
Therefore, a more accurate depth of the internal defect can be estimated by referring to the table. Thereby, the number of measurements can be reduced and the inspection efficiency can be improved.
[0021]
(9) In the defect inspection control apparatus according to the present invention, the heating control means for giving a heating start command to the heating apparatus for simultaneously heating the entire surface of the object to be inspected over the entire measurement region, and the temperature measurement after the heating is stopped Data recording means for inputting data from the vessel and recording it as temperature data of each unit region, and based on the recorded temperature data, the relative difference between the unit regions with respect to the temporal change of the surface temperature in each unit region And defect determination means for determining defects in the object to be inspected.
[0022]
Therefore, it is possible to perform measurement in consideration of the surface reflection heat of the object to be inspected generated in the heating process. That is, since the measurement is performed in the cooling process that is the heating stop period, the surface temperature of the object to be inspected can be measured more accurately. Thereby, the defect of a to-be-inspected object can be detected correctly.
[0023]
(10) In the data collection device according to the present invention, the heating control means for giving a heating start command to the heating device that simultaneously heats the entire surface of the object to be inspected over the measurement region, and the temperature measuring device after the heating is stopped And a data recording means for recording the temperature data of each unit area as data.
[0024]
Therefore, it is possible to perform measurement in consideration of the surface reflection heat of the object to be inspected generated in the heating process. That is, since the measurement is performed in the cooling process that is the heating stop period, the surface temperature of the object to be inspected can be measured more accurately.
[0025]
(11) In the defect determination device according to the present invention, based on the temperature data of each unit area of the measurement area recorded after the heating of the surface of the object to be inspected, the time change of the surface temperature in each unit area Defect determining means for detecting a relative difference between the unit areas and determining a defect in the object to be inspected is provided.
[0026]
Therefore, the defect can be accurately detected based on the measured surface temperature data of the object to be inspected.
[0027]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to the drawings.
[0028]
1. First embodiment
When a thermal load that fluctuates at a constant period is applied to the object, wave-like heat transfer occurs inside the object, and the surface temperature of the object also fluctuates at a constant period and amplitude. If a defect exists in the object, the influence of the defect also appears in the surface temperature distribution that fluctuates in a wave shape. In the present embodiment, a method of measuring such a surface temperature fluctuation with a constant period in time series and identifying a defect based on a correlation process between the measurement data and a predetermined waveform will be described.
[0029]
For example, the correlation processing is performed by synchronizing the measurement data of the surface temperature fluctuation with the reference waveform having the same period as the applied thermal load, and the difference in phase delay value (phase difference) from the reference waveform in each unit region Is output as correlation data. That is, a unit region where a phase difference is generated represents a site where an internal defect exists. Therefore, it is possible to perform defect inspection by converting the correlation data into image data that can be easily recognized visually, and displaying a portion where an internal defect exists as a contrast difference on the image data.
[0030]
1-1. Overview of defect inspection system
FIG. 1 is a functional block diagram showing a schematic configuration of a defect inspection system for realizing the present invention. In this figure, the defect inspection control device 10 inputs heating control means 11 for controlling heating / stopping heating to the heating device 17 and measurement data of the surface temperature of the object measured by the temperature measuring device 19. Data recording means 13 for recording and defect determination means 15 for reading the measurement data recorded in the data recording means 13 and comparing the feature quantity with a predetermined reference waveform to determine an internal defect.
[0031]
1-2. Defect inspection system equipment configuration
FIG. 2 shows a configuration diagram of an apparatus for realizing the defect inspection system. The inspected object 20 represents a concrete wall for inspecting internal defects. A heater 21 that applies a thermal load to the inspection object 20 is installed opposite to the inspection object 20. The heater 21 is connected to a relay device 25 that can adjust the output of the thermal load in order to give a uniform thermal load to the device under test 20. By providing the relay device 25, the irradiation amount at the center of the heater 21 is adjusted so that the center of the device under test 20 does not become hotter than the periphery.
[0032]
The signal generator 27 is connected to the relay device 25 and the computer device 29, and generates a signal for controlling the relay device 25 based on the heating start command received from the computer device 29.
[0033]
The infrared camera 23 is installed opposite to the inspection object 1 and is connected to the computer device 29, measures the surface temperature of the inspection object 1 in time series, and outputs the measurement data to the computer device 29. To do.
[0034]
In response to the output of the measurement data, the computer device 29 records the measurement data by the data recording unit 13, determines the internal defect of the inspection object 20 by the defect determination unit 15, and outputs an image.
[0035]
1 is realized by a computer device 29 and a signal generator 27. The heating device 17 is realized by the heater 17 and the relay device 25. The temperature measuring device 19 is realized by the infrared camera 23.
[0036]
1-3. Hardware configuration diagram of computer device
FIG. 3 shows a hardware configuration diagram of the computer device 29. This apparatus includes a CPU 30, a memory 31, a display 33, a hard disk 35 (storage device), a keyboard / mouse 37, and a communication circuit 39.
[0037]
The communication circuit 39 is a circuit for connecting with other devices. The hard disk 35 stores a program for determining a defect, a reference waveform, a program for displaying an image, and the like.
[0038]
1-4. Flow chart in defect inspection control device
FIG. 4 shows a flowchart in the defect inspection control apparatus 10 when performing defect inspection. First, in the defect inspection control device 10, the CPU 30 of the computer device 29 outputs a preset heating condition to the signal generating device 27 (step S401). Here, the heating condition refers to the time for applying a thermal load to the device under test 20 and the number of repetitions thereof. The amplitude is a constant value and the duty cycle is 50%.
[0039]
The heating condition is given to the signal generator 27, converted into a waveform signal, and output to the relay device 25. The relay device 25 operates the heater 21 based on the input waveform signal. Thereby, a thermal load is given to the to-be-inspected object 20 on predetermined heating conditions.
[0040]
While performing heating / heating stop under predetermined heating conditions, the surface temperature of the inspection object 20 is measured using the infrared camera 23, particularly during the heating stop period.
[0041]
FIG. 4 a shows the relationship between the heating control signal 40 output from the relay device 25 to the heater 21 and the temperature fluctuation curve 41 on the surface of the test object 20 heated based on the signal 40. That is, the temperature fluctuation data in the measurement period 45 shown in FIG. 4a is measured.
[0042]
The measurement data is output to the connected computer device 29 and recorded on the hard disk 35 or the like (step S402). By repeating this measurement process every predetermined time, measurement data of the surface temperature fluctuation at each measurement time in the heating stop period is acquired. The measurement data is surface temperature data for each unit region of the measurement region in the inspection object 20.
[0043]
After performing the above processing for a predetermined number of repetitions, the measurement is terminated (step S403). In the present embodiment, the number of repetitions of heating / stopping heating is set to one.
[0044]
Upon completion of the measurement, the CPU 30 of the computer device 29 performs measurement data analysis processing (step S404).
[0045]
1-4-1. Analysis processing of measurement data
FIG. 4 is a flowchart of measurement data analysis processing. Here, the surface temperature data for each unit region of the measurement region in the inspection object 20 is represented by K, and the temperature at the time t and the unit region i is represented by K._tiAnd CPU30 is this K_tiIs called from the hard disk 35 for each area and stored in the memory 31 (step S501).
[0046]
CPU 30 performs reference waveform R at time t._tIs called from the hard disk 35 (step S502). The reference waveform R_tIs an analog signal having the same period as the thermal load applied to the device under test 20.
[0047]
CPU 30 determines reference waveform R at time t, region i._tPhase difference P_tiIs calculated (step S503). In the following, the phase difference P_tiThe calculation process of is shown.
[0048]
The CPU 30 uses the reference waveform R_tIs converted into a square wave, and sine wave and cos wave digital data Sin (t) and Cos (t) having the same frequency are generated.
[0049]
Next, at time t, the temperature K in the unit region i_tiThe arithmetic processing of the following equation is performed between the digital signal V (t) determined by the above and the reference waveforms Sin (t) and Cos (t).
[0050]
[Expression 1]

However, ΔV_sinRepresents the fluctuation amplitude of the infrared intensity synchronized with the reference waveform, and ΔV_cosRepresents the fluctuation amplitude of the infrared intensity synchronized with the cosine wave 90 degrees out of phase with the reference waveform. N is the number of frames taken in signal processing.
[0051]
If the surface temperature variation is completely in phase with the fluctuating heat load, ΔV_cosBecomes 0. If the surface temperature fluctuations are out of phase with the fluctuating heat load due to the effects of thermal diffusion, etc._cosThe component of appears. In this case, the absolute value ΔV and the phase delay θ of the temperature fluctuation amplitude can be obtained by the following equations.
[0052]
[Expression 2]

Here, the obtained θ is the reference waveform R at time t and unit region i._tPhase difference P_tiIt is defined as
[0053]
The CPU 30 adds 1 to i to obtain i + 1 in order to obtain the phase difference in the next unit area (step S504). Further, until i exceeds the total number of regions I (YES in step S505), the processing in steps S501 to S504 is repeated to obtain the phase difference P._tiIs obtained (step S505, NO).
[0054]
Next, the CPU 30 adds Δt to the time t to set the time to t + Δt (step S506), and repeats steps S501 to S506 until the predetermined analysis time T is exceeded (step S507, YES) (step S507, NO). .
[0055]
Thus, the phase difference P_tiIs performed for each pixel of the infrared sensor in the infrared camera 23, that is, the total number of areas I times, and the number of captured frames N times measured by the infrared camera 23.
[0056]
1-4-2. Analysis image display
After completing the measurement data analysis process, the CPU 30 determines the phase difference P at time T._{T i}Is called for each area, and based on this, image data of the entire measurement area is generated (step S405) and output to the display 33 (step S406). That is, the CPU 30 generates image data by associating the input phase difference with a predetermined display color and displays it.
[0057]
FIG. 6A shows an example of display of image data when the defect inspection system described above is applied and a defect inspection is performed on a concrete specimen having an artificial defect. In addition, this image measures the concrete test body which has the artificial defects 1-6 shown in FIG.6 (B). The artificial defects 1 to 6 are produced by embedding defects having different depths and thicknesses in concrete.
[0058]
In FIG. 6A, three portions clearly displayed as contrast differences in the right column 61 correspond to the artificial defects 4 to 6, respectively. Although the artificial defects 1 to 3 are displayed in the left column 60, the contrast is not so clear.
[0059]
Thereby, it is considered that the heating period, which is one of the heating conditions of the heat wave set at the time of the inspection, was suitable for detecting the artificial defects 4 to 6 having a depth of 20 mm.
[0060]
1-5. Summary
FIG. 7 is an example in which the phase difference between the measurement data and the reference waveform in the unit area of the measurement area is shown as a graph. Phase difference P in each unit region i in the frame of the measurement region measured by the infrared camera 23_tiIs a reference waveform R approximating the temperature fluctuation curve 71 of the defective part.₇₁And a reference waveform R approximating the temperature fluctuation curve 73 of the healthy part₇₃And the phase difference.
[0061]
Since the phase difference displayed as image data is considered to be determined by the heating period and the depth of the defect, it is necessary to set the heating period according to the defect of the inspection object 20.
[0062]
2. Second embodiment
As described above, the phase difference displayed as image data is determined by the heating period and the depth of the defect, and it is necessary to set an optimum heating period according to the depth of the defect to be inspected. FIG. 8 is an image when the artificial defect (FIG. 6B) is repeatedly measured while changing the heating period, which is one of the heating conditions, for the purpose of obtaining the optimum heating period.
[0063]
As shown in FIGS. 8A to 8D, the contrast difference indicating the defects 4 to 6 having a defect depth of 20 mm is clearly displayed in the period T of 10 to 30 minutes, and particularly when the period T is 20 minutes. The contrast difference is clearly displayed.
[0064]
8B to 8E, the contrast difference indicating the defects 1 to 3 having a defect depth of 30 mm is clearly displayed in the period T of 20 to 40 minutes, particularly when the period T is 30 minutes. The contrast difference is displayed most clearly.
[0065]
FIG. 9 shows an example of the relationship table between the heating period and the defect depth, which is considered from the above results. As shown in FIG. 9, the heating period when the phase difference becomes the largest for each defect depth is considered to be the optimum heating period. For example, since the maximum phase difference at the defect depth “10 mm” is “2.0 °”, the optimum heating period when inspecting the defect depth is “10 minutes”. In other words, the optimum heating period corresponds to the “predetermined period in which the difference becomes significant” shown in [Claims].
[0066]
Therefore, by using the relationship table, the heating period can be set according to the defect depth to be inspected in the inspection object 20. Thereby, the number of times of measurement can be reduced, and improvement in inspection efficiency can be expected.
[0067]
In the present embodiment, a defect inspection method with improved inspection efficiency will be described using a relationship table between the heating period and the defect depth.
[0068]
2-1. Overview of defect inspection
In the first embodiment, the defect detection is performed on the concrete specimen having an artificial defect. However, in this embodiment, the defect inspection system according to the present invention is actually used for a concrete structure having an internal defect due to aging. The case where is applied will be described.
[0069]
It should be noted that the concrete structure to be inspected for defects is made of the same material and environment as the concrete test specimen, and uses a reference table showing the relationship between the depth of the defect and the heating period shown in FIG. It shall be.
[0070]
2-2. Defect depth estimation method
First, for the concrete structure to be inspected, the thickness of the concrete and the thickness of the reinforcing bar cover in the inspection range are examined, and the maximum depth for defect inspection is determined. Note that when examining the thickness of the reinforcing bar cover, an inspection device using ultrasonic waves, microwave radar, electromagnetic induction, or the like may be used.
[0071]
Next, the number of times of measurement is determined from the required inspection efficiency, and the heating period corresponding to the maximum depth is determined from the reference table of FIG. For example, in the present embodiment, as a result of the investigation, the maximum depth is considered to be 30 mm, so the heating period is set to 10 to 30 minutes and the number of measurements is set to 1 by the reference table.
[0072]
FIG. 10 shows image data obtained by applying the defect inspection system according to the present invention to a concrete structure. 10A to 10C are measured by changing the heating period to 10 to 30 minutes, respectively, and it is clearly displayed that a defect exists in the center of the image in each image. ing.
[0073]
As shown in (1) to (3) below, quantitative information related to this defect can be estimated from these images and the reference table.
[0074]
(1) In FIG. 10 (A), the outline 101 of the defect at the center of the image is clearly displayed as a contrast difference with respect to the whole. Therefore, the defect depth in this range can be estimated to be around 10 mm from the reference table. That is, a defect exists around 10 mm from the surface.
[0075]
(2) In FIG. 10 (B), the contrast difference indicating the defect contour 103 at the center of the image is displayed so as to expand toward the center as compared with FIG. 10 (A). Therefore, it can be estimated from the reference table that the defect depth in this range is around 20 mm, and the defect in this range has a larger cavity than the defect in the range of 10 mm.
[0076]
(3) In FIG. 10C, the contrast difference indicating the defect contour 105 at the center of the image is displayed so as to further expand toward the center as compared with FIG. 10B. Therefore, it can be estimated from the reference table that the defect depth in this range is around 30 mm, and the defect in this range has a larger cavity than the defect in the range of 20 mm.
[0077]
Thereby, this internal defect exists in the position of depth 10mm-30mm from the surface of a concrete structure, and it can be estimated that it is a float of the shape which tapered toward the perpendicular direction from the surface to the inside.
[0078]
In addition, in FIG. 11, the example when the internal defect part of the concrete structure measured this time is extract | collected is shown. As shown in FIG. 11A, the internal defect portion has a contour that is substantially the same shape as the contour portion of the contrast difference of the internal defect in the image shown in FIG. Moreover, FIG. 11 (B) has shown the side surface of this internal defect part, and the thickness was 20-30 mm.
[0079]
In this way, by performing a defect inspection of a concrete structure using the defect inspection system to which the present invention is applied, the depth of the internal defect is identified, and the internal defect such as its size and thickness is quantitatively determined. It is possible to estimate accurate information. As a result, inspection efficiency in defect inspection can be increased, and risk-based maintenance can be performed in which effective countermeasures are taken according to the defect probability of defects.
[0080]
2-3. Flow chart in defect inspection control device
In FIG. 12, 2-2. 6 is a flowchart in the defect inspection control apparatus 10 that automatically estimates internal defects using the defect depth estimation method shown in FIG.
[0081]
First, in the computer device 29 that is the defect inspection control device 10, the maximum depth of the defect to be detected is input (step S1201). The maximum depth input at this time is 2-2. As shown in Fig. 4, it may be determined by a preliminary survey of concrete structures.
[0082]
Next, based on the required inspection efficiency, the number of times of measurement and the range of heating conditions are input (step S1202). Note that the range of the heating condition may be automatically determined by the CPU 30 according to the maximum depth.
[0083]
In the defect inspection control device 10, the CPU 30 of the computer device 29 outputs a heating condition to the signal generator 27 (step S1203). Here, the heating condition refers to the time for applying a thermal load to the device under test 20 and the number of repetitions thereof. The amplitude is a constant value and the duty cycle is 50%.
[0084]
The heating condition is given to the signal generator 27, converted into a waveform signal, and output to the relay device 25. The relay device 25 operates the heater 21 based on the input waveform signal. Thereby, a thermal load is given to the to-be-inspected object 20 on predetermined heating conditions.
[0085]
While performing heating / heating stop under predetermined heating conditions, the surface temperature of the inspection object 20 is measured using the infrared camera 23, particularly during the heating stop period. The measurement data is output to the connected computer device 29 and recorded on the hard disk 35 or the like (step S1204). By repeating this measurement process every predetermined time, surface temperature measurement data for each measurement time in the heating stop period is acquired. The measurement data is surface temperature data for each unit region of the measurement region in the concrete structure that is the inspection object 20.
[0086]
After performing the above processing for a predetermined number of repetitions, the measurement is ended, the heating period is changed within the set range (step S1210), and the same processing is repeated from step S1203 (step S1205, NO). In the present embodiment, the number of repetitions of heating / stopping heating is set to one.
[0087]
When the measurement under the heating condition in the set range is completed (step S1205, YES), the CPU 30 performs measurement data analysis processing in each measured heating period (step S1206). The measurement data analysis process shown in step S1206 is the same as the process shown in FIG. 4 of the first embodiment.
[0088]
CPU30 which completed the analysis process of the measurement data in each heating period is the phase difference P at time T_{T i}Is called for each area, and based on this, the presence or absence of a defect is determined. Further, the CPU 30 determines the depth at which the defect exists based on the correlation data indicating the phase difference of the area determined to be a defect (step S1207). That is, referring to the phase difference of each region and the reference table 120 showing the relationship between the heating period and the defect depth, the depth of the region determined to indicate a defect is determined.
[0089]
Next, the CPU 30 generates image data of the entire measurement area (step S1208), and outputs the image data shown in FIG. 10 to the display 33 (step S1209). In the present embodiment, it is assumed that the value of the depth of the defective portion is simultaneously displayed on each screen (not shown).
[0090]
Further, a defect shape estimation screen as shown in FIG. 13 may be displayed simultaneously using the defect depth determined in step S1207. Thereby, quantitative information on the defective part is displayed as image data, and it is easy to confirm the inspection result in the defect inspection, and even a person who does not have special judgment knowledge can find the internal defect. In addition, in FIG. 13, although the defective part is expressed two-dimensionally, you may express as a three-dimensional shape. As a result, more detailed information on the defect can be acquired.
[0091]
3. Other embodiments
In the above embodiment, a concrete material is used as the object 1 to be inspected. However, the present invention can also be applied to a defect inspection in a composite material composed of a low thermal conductivity material such as CFRP, for example.
[0092]
In the above-described embodiment, the number of repetitions of heating / stopping heating is set to one. In this case, if the reflection of the heat source on the surface of the object to be measured is not affected, the temperature fluctuation in both the heating and heating stop periods may be continuously measured.
[0093]
In the above-described embodiment, the phase difference between the waveform obtained from the measurement data and the predetermined reference waveform is used as the feature amount when obtaining the defective part. However, another index may be used as the feature amount. For example, temperature gradient data in time change of measurement data, time change data of the temperature gradient data, frequency component data when Fourier analysis is performed on the measurement data, peak value of measurement data waveform or time to reach the peak value, etc. May be used as the feature amount.
[0094]
Furthermore, when comparing these feature quantities, the measurement data is indirectly compared by correlation processing between each measurement data and a predetermined reference waveform, but even if each measurement data is directly compared, Good. For example, this corresponds to comparing peak values of measurement data.
[0095]
In the above-described embodiment, quantitative information relating to the defective part is acquired using the relationship table between the heating period and the defect depth, but a relationship table in which the defect thickness is further added may be used. In this case, it is possible to detect a defect with higher accuracy.
[0096]
In the above-described embodiment, the defect inspection control device 10 includes the computer device 29 and the signal generation device 27. However, the defect inspection control device 10 includes a data collection device that realizes the heating control means 11 and the data recording means 13, and a defect. The defect determination device that realizes the determination unit 15 may be configured by different devices. For example, by connecting these devices using a communication line, remote operation in defect inspection becomes possible.
[Brief description of the drawings]
FIG. 1 is a functional block diagram of a defect detection system according to an embodiment of the present invention.
FIG. 2 is an example showing a configuration diagram of an apparatus for realizing a defect detection system according to an embodiment of the present invention.
FIG. 3 is an example showing a hardware configuration diagram of a computer device according to an embodiment of the present invention;
FIG. 4 is a flowchart of the defect inspection control apparatus.
FIG. 4A is a diagram showing a relationship between a signal for heating control and a temperature fluctuation curve on the surface of an object to be inspected.
FIG. 5 is a flowchart illustrating measurement data analysis processing;
FIG. 6 is an example (A) of a display screen of an artificial defect (B) and image data when the artificial defect is measured.
FIG. 7 is an example of a graph showing a phase difference between measurement data and a reference waveform in a unit area of the measurement area.
FIG. 8 is an example of a display screen of image data when an artificial defect is measured by changing the heating period.
FIG. 9 is an example of a reference table showing a relationship between a heating period and a phase difference for each defect depth.
FIG. 10 is a display screen of image data when a concrete structure having internal defects is measured by changing the heating period.
FIG. 11 is an example when an internal defect portion of a measured concrete structure is sampled.
FIG. 12 is a diagram showing a flowchart in the defect inspection control apparatus when using a reference table.
FIG. 13 is an example of a screen in which the shape of a defect is estimated based on quantitative information relating to a defective part.
[Explanation of symbols]
10. Defect inspection control device
11 ... Heating control means
13: Data recording means
15 ... Defect judgment means
17 ... Heating device
19 ... Temperature measuring instrument

Claims (11)

Heat the entire surface of the object to be inspected at the same time,
At least in the heating stop period after stopping the heating, for each unit region of the measurement region, measure the time change of the surface temperature,
The period during which the heating is performed is not included, and based on the relative difference between the unit regions regarding the temporal change of the surface temperature in each unit region in the heating stop period after the heating is stopped, A defect inspection method characterized by finding defects. The defect inspection method according to claim 1,
The object to be inspected is composed of a low thermal conductivity material. The defect inspection method according to claim 1 or 2,
The position of a defect in the object to be inspected is specified based on a relative difference between the unit regions with respect to a temporal change in surface temperature in each unit region. In the defect inspection method in any one of Claims 1-3,
The present invention presents a relative difference between the unit regions with respect to the temporal change of the surface temperature in each unit region as a visually recognizable image. The defect inspection method according to claim 4,
The relative difference is determined on the basis of a comparison of a feature value in a predetermined waveform and a waveform due to a temporal change in surface temperature in each unit region. In the defect inspection method of claim 5,
The feature amount comparison is performed based on a specific value indicating a correlation between both waveforms of a waveform due to a time change of the surface temperature in each unit region and a predetermined waveform or a phase difference between the two waveforms. thing. In the defect inspection method in any one of Claims 1-6,
While performing heating and heating stop for a predetermined period, changing the predetermined period and measuring,
Defect depth is estimated based on a predetermined period in which a difference in relative temperature change between each unit region becomes significant. The defect inspection method according to claim 7,
Further, the depth of the defect is estimated based on a table in which the depth of the defect is associated with a predetermined period in advance. A heating control means for giving a heating start command to a heating device that simultaneously heats the entire surface of the object to be inspected over the measurement region;
Data recording means that does not include the period during which the heating is performed , records data as temperature data of each unit area by inputting data from a temperature measuring instrument after heating is stopped,
Based on the recorded temperature data, detecting a relative difference between each unit region with respect to the time change of the surface temperature in each unit region, and a defect determining means for determining a defect in the inspection object,
A defect inspection control apparatus comprising: A heating control means for giving a heating start command to a heating device that simultaneously heats the entire surface of the object to be inspected over the measurement region;
Data recording means that does not include the period during which the heating is performed , records data as temperature data of each unit area by inputting data from a temperature measuring instrument after heating is stopped,
A data collection device for defect inspection, comprising: It does not include the period during which the surface of the object to be inspected is heated, and based on the temperature data of each unit area of the measurement area recorded after stopping the heating, between the unit areas regarding the time change of the surface temperature in each unit area A defect judging means for detecting a relative difference between the two and judging a defect in the inspected object,
A defect determination apparatus for defect inspection, comprising:

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