JP3811924B2

JP3811924B2 - Control device for automatic coating machine and control method thereof

Info

Publication number: JP3811924B2
Application number: JP00033996A
Authority: JP
Inventors: 田清吉; 辺正実渡
Original assignee: Nissan Motor Co Ltd
Current assignee: Nissan Motor Co Ltd
Priority date: 1996-01-05
Filing date: 1996-01-05
Publication date: 2006-08-23
Anticipated expiration: 2016-01-05
Also published as: JPH09187694A

Description

【０００１】
【発明の属する技術分野】
本発明は、被塗装物を自動的に塗装するのに用いられる自動塗装機の制御方法および制御装置に関するものである。
【０００２】
【従来の技術】
従来において、例えば自動車の車体塗装では、自動塗装機により塗装を行い、塗装後に長時間をかけて塗料を乾燥させたのち、乾燥後の塗装の鮮映性（平滑性、肉持ち性、光沢度）を検査して塗装品質を評価することが行われている。
【０００３】
そして、自動塗装機の制御としては、図１８に示すように、ブロック１０１に示す自動車ボディ等である被塗装物の鮮映性（平滑性）をブロック１０２における平滑性計測手段で評価した後、ブロック１０３における塗装品質判定手段において鮮映値と所定の基準値とを比較し、鮮映値と基準値がずれている場合には、ブロック１０４における塗装条件制御手段により、鮮映性が基準値となるようにブロック１０５の自動塗装機の塗装制御条件（吐出量など）を補正することとなっていた。
【０００４】
この場合、被塗装物の塗装を行う塗装ブースの空調精度がある程度大まかであっても、被塗装物の塗装面の鮮映性（平滑性）の品質を一定に維持することができる。
【０００５】
【発明が解決しようとする課題】
ところで、一般に、被塗装物の塗装品質の良否を決める塗装品質要因としては、塗料吹付け後の塗料の非揮発性成分（以下、「塗着Ｎ．Ｖ」とする）または塗着粘度、塗膜厚、塗粒子の微粒化度、さらに各種塗装ガンの吹付け条件や塗装の焼き付け条件等が挙げられる。そして、これらの塗装品質要因のうち、塗着Ｎ．Ｖ（塗着粘度）、塗膜厚および塗粒子の微粒化度は重要な塗装品質要因であり、これらの塗装品質要因をできるだけ塗布直後に精度良く定量的に把握する必要があり、とくに、自動化ラインで次々に塗装を行うような場合には、塗装状態の良否をできるだけ精度良く計測し、速やかに塗装機にフィードバックして次の塗装条件を改善し、常に最良の塗装状態に保つ必要がある。
【０００６】
しかしながら、上記したような従来の自動塗装機の制御にあっては、被塗装物の塗装品質として鮮映性（平滑性）のみを計測し、その測定した鮮映値が所定の基準値からずれている場合に、鮮映性が基準値となるように自動塗装機の塗装制御条件を補正することとなっていたため、
（１）塗装膜の薄すぎ、塗着Ｎ．Ｖ（粘度）の高すぎというような塗装品質要因を的確に指示できず、塗装ラインの塗装品質を狙い通りの安定した塗装状態に保つことができない。
【０００７】
（２）塗装膜の厚すぎ、塗着Ｎ．Ｖ（粘度）の低すぎというような塗装品質要因を的確に指示できず、無駄塗装のない最適な膜厚等の塗装制御ができない。
【０００８】
という問題があり、これらの問題点を解決することが課題であった。
【０００９】
【発明の目的】
本発明は、上記のごとき従来の課題に着目して成されたもので、塗装された被塗装物における塗装品質要因（塗着Ｎ．Ｖ、微粒化度、塗膜厚）を計測して、自動塗装機をフィードバック制御することにより、狙い通りの安定した塗装状態を保つことができ、且つ最適な塗装制御を行うことができる自動塗装機の制御方法および制御装置を提供することを目的としている。
【００１０】
【課題を解決するための手段】
本発明の請求項１に係わる自動塗装機の制御装置は、図１に基づいて説明すると、空調された塗装ブース内に搬入した被塗装物を自動塗装機により塗装する際の制御装置において、自動塗装機（ブロック５）により所定の塗装条件下で塗装された被塗装物（ブロック１）の塗装品質要因を検知する塗装品質要因計測手段（ブロック２）と、塗装品質要因計測手段によって検知された計測値と予め設定された要因基準値を比較し、検知された計測値が要因基準値とずれている場合に、塗装品質要因が要因基準値となるように自動塗装機の塗装条件の補正を指令する塗装品質判定手段（ブロック３）と、塗装品質判定手段からの補正指令に基づいて塗装面の塗装品質が基準値となるように自動塗装機の塗装条件を制御する塗装条件制御手段（ブロック４）を備えた構成としており、上記の構成を課題を解決するための手段としている。
さらに、本発明に係わる自動塗装機の制御装置は、塗装品質要因計測手段が、塗料の非揮発性成分等の塗料条件を入力する塗料条件入力手段と、吹き付け時の塗料の微粒化度を入力する微粒化度演算手段と、塗料のシンナー蒸発量を入力するシンナー蒸発量入力手段と、塗料条件入力手段からの非揮発性成分、微粒化度演算手段からの微粒化度、およびシンナー蒸発量入力手段からのシンナー蒸発量に基づいて自動塗装機により所定の塗装条件下で塗装された被塗装物の塗布直後の非揮発性成分を算出する第１の塗着Ｎ．Ｖ演算手段１と、第１の塗着Ｎ．Ｖ演算手段で算出された塗布直後の塗膜面の非揮発性成分と塗料条件入力手段からの塗料種情報に基づいて塗布直後の塗膜面の塗料密度を算出する塗料密度演算手段と、測定までの時間を入力する測定時間入力手段と、塗膜面の膜厚を入力する膜厚演算手段と、膜厚演算手段からの膜厚情報、シンナー蒸発量入力手段からのシンナー蒸発量および測定時間入力手段からの測定時間情報に基づいて塗布後の塗膜面の非揮発性成分を算出する第２の塗着Ｎ．Ｖ演算手段を備えている構成としている。
【００１１】
また、本発明の請求項１に係わる自動塗装機の制御装置は、請求項２として、塗装品質要因計測手段が、塗料を塗布した直後の未乾燥塗装表面を撮像する撮像手段と、撮像手段からの画像情報を画像処理する画像処理手段と、画像処理手段で処理された画像処理データに基づいて塗装表面の凹凸波形の波長分布を算出する波長分布演算手段を備え、波長分布演算手段で算出された波長分布に基づいて塗料粒子の微粒化度を算出する手段である構成とし、請求項３として、塗装品質要因計測手段が、塗料の粘度等を入力する塗装条件入力手段と、塗料を塗布した直後の未乾燥塗装表面を撮像する撮像手段と、撮像手段からの画像情報を画像処理する画像処理手段と、画像処理手段で処理された画像処理データに基づいて塗装表面の粗さを算出する表面粗さ演算手段を備え、表面粗さ演算手段で算出された粗さ度と粗さ度の時間変化量と波長分布演算手段で算出された波長と塗装条件入力手段からの塗装条件から塗膜厚を算出する手段である構成とし、請求項４として、塗着Ｎ．Ｖ演算手段が、塗料条件入力手段の塗料の非揮発性成分とシンナー蒸発量入力手段の塗料のシンナー蒸発量と微粒化度演算手段の塗料粒子径から求めた塗料粒子の表面積の関係から塗布直後の塗膜面の非揮発性成分を算出する手段である構成としており、上記の構成を課題を解決するための手段としている。
【００１２】
本発明の請求項５に係わる自動塗装機の制御方法は、上述の自動塗装機の制御装置を用いた自動塗装機の制御方法であって、空調された塗装ブース内に搬入した被塗装物を自動塗装機により塗装するに際し、自動塗装機により所定の塗装条件下で塗装された被塗装物の塗装面の塗装品質要因を検知し、塗装品質要因の計測値と予め設定された要因基準値の差に基づいて得た補正の指令により自動塗装機を制御する構成としており、上記の構成を課題を解決するための手段としている。
【００１３】
【発明の作用】
本発明に係わる自動塗装機の制御方法および制御装置では、塗装品質要因を計測し、これらの計測値に基づいて自動塗装機のフィードバック制御を行うことにより、塗装品質が不良となった塗装品質要因を把握して、その塗装品質要因を解消する正確なフィードバック制御を行い、これにより塗装品質を高めることとなる。
【００１４】
本発明の請求項１に係わる自動塗装機の制御装置によれば、被塗装物の塗装状態が不良の場合に、塗着Ｎ．Ｖ、微粒化度および塗膜厚等の塗装品質要因の各測定値と要因基準値との誤差に見合った補正を行なうことから、塗装状態に合わせた正確なフィードバック制御を行うことができると共に、自動塗装ラインでも狙い通りの安定した塗装品質を確保することができ、さらに、塗膜厚等の最適な塗装制御を行うことができると共に、塗着効率の向上なども実現し得る。
また、被塗装物の塗装状態が良好の場合でも、塗着Ｎ．Ｖが下限基準値以下であるときには、塗着Ｎ．Ｖの計測値と基準値との差に見合った垂れ修正の補正を行なうことができ、微粒化度が下限基準値以下であるときは、微粒化度の計測値と基準値との差に見合った塗着効率補正を行なうことができ、さらに、塗膜厚が基準値以上であるときは、塗膜厚の計測値と基準値との差に見合った厚塗り補正を行なうことができ、安定した塗装品質を確保することができる。
【００１５】
本発明の請求項２〜４に係わる自動塗装機の制御装置によれば、塗装品質要因の計測、つまり、請求項２において塗料の微粒化度の計測、請求項３において塗膜厚の計測、請求項４において塗着Ｎ．Ｖの計測を正確に且つ迅速に行なうことができ、より一層正確なフィードバック制御を行うことができると共に、塗装品質をさらに高めることができる。
【００１６】
本発明の請求項５に係わる自動塗装機の制御方法によれば、塗装された被塗装物における塗装品質要因（塗着Ｎ．Ｖ、微粒化度、塗膜厚）を計測して、計測値と品質基準値との差に基づいて自動塗装機をフィードバック制御することから、狙い通りの安定した塗装状態を保つことができると共に、塗膜厚等の最適な塗装制御を行うことができ、塗装品質を大幅に向上させることができると共に、塗着効率の向上などを図ることができる。
【００１７】
本発明の請求項４〜６に係わる自動塗装機の制御装置によれば、塗装品質要因の計測、つまり、請求項４において塗料の微粒化度の計測、請求項５において塗膜厚の計測、請求項６において塗着Ｎ．Ｖの計測を正確に且つ迅速に行なうことができ、より一層正確なフィードバック制御を行うことができると共に、塗装品質をさらに高めることができる。
【００１８】
【実施例】
図２は本発明の一実施例を示す図であり、本発明を車体の自動塗装ラインに適用した場合を示すブロック図である。
【００１９】
被塗装物１は、上塗り塗装工程における自動車のボディであって、塗装ライン上を所定の速度で移動しながら塗装される。自動塗装機（塗装ガン）５の制御装置は、塗布直後の被塗装物１の塗装状態すなわち塗装品質（鮮映性）とこれを左右する塗装品質要因（塗着Ｎ．Ｖ、微粒化度、塗膜厚）を同時に計測する塗装品質要因計測手段２と、塗装品質要因計測手段２によって検知された計測値と予め設定された要因基準値を比較し、検知された計測値が要因基準値とずれている場合に、塗装品質要因が要因基準値となるように自動塗装機５の塗装条件の補正を指令する塗装品質判定手段３と、塗装品質判定手段３からの補正指令に基づいて塗装面の塗装品質が基準値となるように自動塗装機５の塗装条件を制御する塗装条件制御手段４を備えている。自動塗装機５は、塗装条件制御手段４からの制御信号に基づき、次の被塗装物１への塗装を行う。
【００２０】
上記の制御装置における塗装品質要因計測手段２は、図３に示すように、被塗装物１の塗装表面に対する撮像手段６、画像処理手段７、塗装表面の凹凸波形のパワースペクトルにおける長波長領域のピーク波長を求める波長演算手段８、波長平均処理手段９、塗料吹き付け時の微粒化度を算出する微粒化度演算手段１０、第１の塗着Ｎ．Ｖ演算手段１１、塗布直後の塗膜面の塗料密度を算出する塗料密度演算手段１２、第２の塗着Ｎ．Ｖ演算手段１３、塗装条件入力手段１５、塗料の非揮発性成分等を入力する塗料条件入力手段１６、シンナー蒸発量入力手段１７、測定までの時間を入力する計測時間入力手段１８、表面粗さ演算手段１９、および膜厚演算手段２０を備えている。
【００２１】
次に、塗装品質要因計測手段２の塗着Ｎ．Ｖ演算手段１１，１３における塗膜面の塗着Ｎ．Ｖの演算原理とシンナー蒸発量入力手段１７におけるシンナー蒸発量演算とについて説明する。
【００２２】
図４は、塗装ガン（自動塗装機５）から噴射された塗料粒子が被塗装面に付着するまでの状況を示す図である。塗料粒子からは飛行中および付着後に溶剤（揮発性成分）が蒸発し、塗膜が完全に乾燥した状態では非揮発性成分のみが残ることになる。なお、塗料が塗装ガンから噴射された時点から被塗装物１に付着するまでの時間は、塗装ガンと被塗装体との距離によって変わるが、一般に、０．１秒〜０．５秒である。
【００２３】
上記のごとき状況において、付着直後の塗着Ｎ．ＶをＸ_１とすれば、Ｘ１は下記数式１で与えられる。
【００２４】
【数式１】

また、上記のシンナー蒸発速度Ｖは、下記数式２で与えられる。
【００２５】
【数式２】

また、塗料粒子の質量Ｍ_１は、下記数式３で与えられる。
【００２６】
【数式３】

また、塗料粒子表面積Ｓ_１は、下記数式４で与えられる。
【００２７】
【数式４】

したがって、上記の数式３、数式４を数式１に代入することにより、塗着Ｎ．Ｖ＝Ｘ_１（％）を表す数式として下記数式５が得られる。
【００２８】
【数式５】

単位面積当たりのシンナー蒸発量は、蒸発速度Ｖ×時間ｔで示される。このシンナー蒸発量Ｖｔを上記数式１と数式５から求めると、下記数式６に示すようになる。
【００２９】
【数式６】

なお、シンナー蒸発量Ｖｔは上記数式２に示すように、塗装前の塗料のＮ．Ｖ（塗料濃度）Ｘ_０とシンナー混合比Ｃと温度Ｔとの関数であるから、それらの諸量との関係を予め実験で求めて記憶しておき、これを読み出して用いればよいが、上記数式６から求めてもよい。
【００３０】
上記数式５に示すように、塗装条件が一定であれば、付着後の塗着Ｎ．Ｖは、シンナー蒸発量Ｖｔと塗料粒子径Ｒと塗料密度ρ_０から演算で求めることができる。図３の実施例においては、シンナー蒸発量Ｖｔはシンナー蒸発量入力手段１７から入力した値を用い、塗料粒子径Ｒは微粒化度演算手段１０で求めた値を用い、塗料密度ρ_０は塗装条件入力手段１５から入力した値を用いる。
【００３１】
次に、撮像手段６について説明する。図５は、撮像手段６の一例を示す断面図である。
【００３２】
撮像手段６の基本的構成は、光源３１、明暗パターン板３２、反射鏡３３、レンズ３４、ＣＤＤカメラ３５から成る。上記の明暗パターン板３２は、所定間隔（例えば１ｍｍ間隔）で直線状のスリットが設けられた不透明（または透明板に所定間隔で不透明なストライブパターンを印刷したもの）である。そして光源３１空の平行光線を上記明暗パターン板３２と反射鏡３３とレンズ３４とを介して塗装面の斜め方向から照射することにより、被塗装物１上にスリットに対応した縞模様をつくる。この縞模様は、被塗装体上の凹凸に応じて歪んだ波形（例えば図６のごとき）となる。その反射光をＣＣＤカメラ３５で撮像し、上記の歪んだ縞模様、すなわち表面粗さの情報を入力するようになっている。
【００３３】
上記のごとき縞模様の画像情報を画像処理し、パワースペクトル周波数分析（例えば高速フーリエ変換処理：ＦＦＴ）を行なってパワースペクトルＰＳを求める。
【００３４】
図７は、上記パワースペクトルＰＳの周波数特性図であり、縦軸はパワースペクトルＰＳ、横軸は周波数ｆ（波長λの逆数、ｆ＝１／λ）である。
【００３５】
図７において、第１のピーク波形▲１▼は、前記スリットに対応した基本縞による基本波形のパワースペクトル、第２のピーク波形▲２▼は、塗装表面の凹凸波形の長波長領域（１０〜１ｍｍ程度）に対応したパワースペクトル、、第３のピーク波形▲３▼は、凹凸波形の中波長領域（１〜０．１ｍｍ程度）に対応したパワースペクトル、第４のピーク波形▲４▼は、凹凸波形の短波長領域（０．１ｍｍ以下）に対応したパワースペクトルを示す。
【００３６】
上記のパワースペクトル波形において、凹凸波形の長波形領域のピーク波長、すなわち第２のピーク波形▲２▼のピーク値に対応した波長λｐは、後記のごとく微粒化度と相関性があり、それによって微粒化度を測定することができる。
【００３７】
図３の実施例においては、画像処理手段７と波長演算手段８とで上記のごとき画像処理とパワースペクトルの演算を行なっている。
【００３８】
次に、波長平均処理手段９では、次のごとき処理を行なう。
【００３９】
一般に、自動車の車体塗装のような塗装自動化ラインでは、上塗り、中塗り、或いは塗装色の違い等のように、色々な塗料を用いるため、その塗料の種類に応じた条件を入力する必要がある。また、車体のような大型の被塗装体の場合には、吹き付け面積が大きいため、塗装部位によっては塗装条件が必ずしも均一にならない場合がある。したがって精度のよい計測を行なうためには、塗装表面の複数個所を撮像し、それらの各部位におけるピーク波長λｐの平均値を用いて微粒化演算や膜厚演算を行なうことが望ましい。
【００４０】
図３の実施例は、上記の理由により、撮像手段６では塗装面の複数個所の撮像を行なってその画像情報を順次演算処理し、求められた複数のピーク波長λｐを波長平均処理手段９で平均化した値を微粒化度演算手段１０へ送る。また、塗装条件入力手段１５を設けて塗装の種類等に応じた情報を入力し、微粒化度演算手段１０では、上記の平均化したピーク波長λｐの値と塗装条件とに応じて微粒化度を演算するように構成している。
【００４１】
次に、微粒化度演算手段１０における微粒化度計測の原理について説明する。
【００４２】
先ず、図８に基づいて、塗装時における塗装面への塗料粒子の付着と塗装膜面の形成過程について説明する。
【００４３】
図８（ａ）に示すように、塗装ガンから塗装面へ向けて微粒化した塗料粒子を吹き付ける。この際、塗料粒子の平均粒子径は、基本的は、塗装条件である塗料速度（下記▲１▼、▲２▼、▲３▼）と空気速度（下記▲４▼）と塗料物性（下記▲５▼）によって決まる。ただし、上記の▲１▼〜▲５▼は次の通りである。
【００４４】
▲１▼ 塗装ガンの吐出量
▲２▼ 塗装ガンのベル回転数
▲３▼ 印加電圧
▲４▼ エア圧
▲５▼ 塗料物性（粘度、表面張力、密度）
なお、ベル回転数とは塗料を微粒化する回転体の回転数であり、印加電圧とは塗料粒子の静電気を付加するために印加する静電圧（５０ｋＶ程度）であり、エア圧とは、塗料粒子が周辺に飛散しないように周囲に気流の壁を作るための気圧である。
【００４５】
上記のようにして吹き付けられた塗料粒子は、塗装面に衝突し、つぶれた形で付着する。
【００４６】
次に、図８（ｂ）に示すように、塗膜形状の初期には、付着した小さな塗料粒子が大きな塗料粒子に結合され、より大きな粒子を形成する。そして、さらに粒子の結合が進み、表面張力と境界張力とによって初期の塗膜面が形成される。
【００４７】
上記のように粒子の付着と結合によって塗膜が形成されていくため、初期の塗膜表面状況は大きな塗装粒子の粒子径ｒ、粒子衝突速度ｖｘ、塗料物性（表面張力γ、粘度η）等に依存する。例えば、上塗り塗料の場合、初期塗膜表面の凹凸の高さは数〜数十μｍ程度であり、また、凹凸の波長分布は３〜６ｍｍ程度の長波長領域が支配的であることが確認された。そして上記の長波長領域のピーク波長λと大きな塗料粒子の粒子径ｒとには相関性があることが実験によって確認された。
【００４８】
次に、図８（ｃ）に示すように、上記の初期塗膜形成後の塗膜表面は、レベリング力（表面張力γと重量ｇとの合成力）によって次第に平坦化して行く。この平坦化速度は上記のレベリング力と塗料物性（表面張力γ、粘度η）および膜厚ｈによって決定される。例えば、上塗り塗料の場合、平坦化速度は時定数で数十秒〜数百秒であることが確認されている。
【００４９】
次に、塗料粒子径と塗膜面の凹凸との関係について図９〜図１２に基づいて詳細に説明する。
【００５０】
図９に示すように、塗装ガンから吹き付けられた塗料粒子の粒子径をｒとし、それが付着した付着粒子の幅をλ／２、厚さ（ピーク値）をｈとすれば、波長λの凹凸を持つ塗膜面が形成される。なお、上記付着粒子の幅λ／２の波長λとの関係は、実験的に求められたものであり、ほぼこの程度の値になることが確認されている。
【００５１】
上記の場合における塗料粒子径ｒは、下記数式７で示される。
【００５２】
【数式７】

上記の理論式をグラフに示すと、図１０の破線で示すごとき曲線となる。しかし、実際には、付着粒子の結合があるため、図１０の実線で示すような特性となる。この実験で求めた特性を数式で示すと、下記数式８のようになる。
【００５３】
【数式８】

上記のごとき実験で求めた凹凸のピーク波長λｐと塗料粒子径ｒとの関係を、付着粒子の結合を考慮して解析する。
【００５４】
まず、図１１に示すように、付着粒子径Ｒは、塗布時間が大きくなるに従って順次大きくなる。この関係を数式で示すと下記数式９のように成る。
【００５５】
【数式９】

なお、図１１において、塗布時間とは１ケ所に塗布する持続時間であり、初期粒子径とは付着前の塗料粒子径であり、付着粒子径とは最初に付着したときの粒子径である。この付着粒子径Ｒは塗布時間が長くなるに従って順次塗布される粒子が係合するので次第に大きくなる。
【００５６】
また、図１２は、塗布時間と塗膜面の凹凸波長との関係を、実測値（破線）と周波数解析によるパワースペクトルから求めた結果とについて比較した特性図である。同図１２から判るように、パワースペクトルから求めた値は実測値によく一致している。したがってパワースペクトルから求めた凹凸波長（前記長波長のピーク波長λｐ）を用いて付着粒子径Ｒを求めることができる。さらに、自動塗装機においては、塗布時間は一定であるから、下記数式１０によって塗料粒子径ｒも求めることができる。
【００５７】
【数式１０】

上記のごとき考察により、基本的には前記数式８により、パワースペクトルから求めた凹凸の長波長領域のピーク波長λｐを用いて、塗料粒子径ｒを求めることができる。具体的には、実験で前記図１０の特性を求め、それから数式８の各係数ｋｓ、ａ，βを予め求めておけば、撮像画像から求めたピーク波長λｐを用いて塗料粒子径ｒを求めることができる。
【００５８】
なお、塗料粒子の粒子径ｒは塗料の微粒化の程度に対応しているから、塗料粒子の粒子径ｒをそのまま用いて微粒化度を表してもよいし、或いはｒの逆数、もしくは基準値との百分率などを用いて微粒化度を表すこともできる。
【００５９】
次に、表面粗さ演算手段１９と膜厚演算手段２０における膜厚演算について説明する。
【００６０】
図１３は、塗装後の塗膜の断面図である。塗装直後には、（ａ）に示すように、塗装表面は初期の付着粒子の結合によって凹凸状態になっている。そして時間の経過と共に、（ｂ）に示すように、レベリング力によって次第に平滑化され、最終的には、（ｃ）に示すように、平滑化状態となる。本実施例においては、このような平滑化減少に着目し、ウエット状態における塗装表面の凹凸状態を測定し、それによって平滑化後、或いは乾燥後の塗装膜厚を算出するものである。
【００６１】
上記のごときウエット状態における凹凸状態を測定するには、光干渉式表面粗さ計など種々の方法（例えば「機械工学便覧日本機械学会１９８９年９月３０日新版３刷発行Ｂ２編２０７頁〜２０８頁」に記載）があるが、ここでは撮像手段６で塗装表面を撮像し、その情報を画像処理する方法について説明する。
【００６２】
まず、パワースペクトル積分値Ｐによる平滑化特性を説明すると、表面の凹凸（ピーク・ツウ・ピーク値）の面積平均値に相当する表面粗さＲ_ａとパワースペクトル積分値Ｐとは、図１４に示すような関係にあり、下記数式１１、数式１２に示す関係がある。
【００６３】
【数式１１】

【００６４】
【数式１２】

ただし、上式において、Ｑは粗さ補正値、ｋは粗さ変換係数である。
【００６５】
パワースペクトル解析値による平均化理論式の導出では、まず、ウエット塗膜平均化理論式（近似式）として、表面粗さ度Ｒ_ａは下記数式１３で表される。
【００６６】
【数式１３】

ただし、Ｒ_ａ０はＲ_ａの初期値（時点０すなわち塗装直後の値）、ｔは塗装後の経過時間である。また、τは粘性流体の基本式から導出された時定数であり、後記数式１８に示すごときものである。
【００６７】
上記数式１２を数式１３に代入すると、下記数式１４が得られる。
【００６８】
【数式１４】

ただし、Ｐ_０はＰの初期値（時点０における値）であり、Ｑ_０はＱの初期値である。
【００６９】
上記数式１４において、Ｐ、Ｐ_０をそれぞれの補正値Ｑ、Ｑ_０を含んだ値として、（Ｐ_０−Ｑ_０）→Ｐ_０、（Ｐ−Ｑ）→Ｐと示せば、数式１４は下記数式１５のように表せる。
【００７０】
【数式１５】

また、時定数τは下記数式１６で示される。
【００７１】
【数式１６】

ただし、ηは塗料の粘度、λは前記の長波長領域のピーク波長、γは塗膜の表面張力、ｈはウエット状態における膜厚（撮像部分の平均値）である。
【００７２】
以上から、パワースペクトル解析値による塗装膜厚ｈは、下記数式１７で示すようになる。
【００７３】
【数式１７】

ただし、Ｐ_１は時点ｔ_１におけるパワースペクトル積分値Ｐの値、Ｐ_２は時点ｔ_２（ただし−_１＜ｔ_２）におけるＰの値である。なお、τ´_ｉは下記数式１８で示される。
【００７４】
【数式１８】

ただし、ｉ＝１，２であり、η（ｔｉ）は塗料の粘度が塗装後の経過時間の関数であることを示す。すなわち、塗装条件入力手段１５から入力するのは、塗装前における塗料の粘度ηであるが、塗装後の塗着粘度は、塗装後の経過時間に応じて変化する値η（ｔ_ｉ）となる。この値は、塗料組成（塗料内の揮発成分の割合等）や風速などによって定まる値である。
【００７５】
上記数式１７から判るように、塗料の粘度η、塗膜の表面張力γ、凹凸波形の長波長領域のピーク波長λ、塗装後の２つの時点ｔ_１、ｔ_２におけるパワースペクトル積分値Ｐの値から、ウエット状態における膜厚ｈを求めることができる。上記の各数値のうち、塗料の粘度ηと塗膜の表面張力γは、塗料の特性によって定まる値であるから、予め判っている値を入力し、長波長領域のピーク波長λとパワースペクトル積分値Ｐの値は、前記画像情報を処理した値を用いる。
【００７６】
図１５は、上記数式１７を用いた平滑化理論値と測定値を比較したウエット平滑化特性（パワースペクトル積分値Ｐ）を示す特性図である。図１５において、横軸は塗装後の経過時間、縦軸はパワースペクトル積分値Ｐである。
【００７７】
上記の測定は、塗布直後の画像を撮像手段６で撮影し、パワースペクトル解析を行ったものである。図１５から、測定値は理論値とほぼ一致した平滑化特性となっていることがわかる。
【００７８】
また、表１は、膜厚６０μｍと５４μｍの２つのサンプルに対して、上記数式１７の推定式を用いて膜厚ｈを計測した結果を示す表である。
【００７９】
表１に示すように、数μｍの精度で計測可能であることが判る。
【００８０】
【表１】

【００８１】
図３の実施例においては、撮像手段６、画像処理手段７、波長演算手段８、表面粗さ演算手段１９、膜厚演算手段２０において、上記のごとき処理を行ない、撮像個所の膜厚ｈを求める。
【００８２】
また、前記数式１７においては、塗装後の２つの時点ｔ_１とｔ_２における２つの値Ｐ_１、Ｐ_２を用い、粗さ情報の時間変化量を用いて演算している。そのため、塗装後の２つの時点で同一個所を撮像する必要がある。このためには、塗装ライン上の車体の移動に合わせて撮像手段６を移動させる必要があるので、装置が複雑になる。それを避けるためには、次のような方法がある。すなわち、被塗装体である車体の他に、テストピースを用意して被塗装体と同じ条件で塗装を行ない、時点ｔ_１（例えばｔ_１＝１０秒、ｔ_１＜ｔ_２）における値Ｐ_１は、テストピースの画像情報を処理して求めた値を用いるようにする。このようにすれば、撮像手段６は時点ｔ_２（例えば塗装１〜２分後）において１回のみの撮像を行なえばよい。
【００８３】
次に、塗装品質判定手段３は、上述のように計測された塗装品質要因計測手段２からの塗装品質要因（塗着Ｎ．Ｖ、微粒化、塗膜厚）測定値と所定の各要因基準値とを比較して、測定値が各要因基準値に対して誤差がある場合は要因基準値との差に見合った補正値を塗装条件制御手段４に送る。ここで、各補正方法は自動塗装機ごとに求められる感度特性を用いる。塗着Ｎ．Ｖの測定値が所定の基準値よりはずれている場合は、図１７（ａ）に示すような塗着Ｎ．Ｖ〜シンナー混合比特性に基づいて、塗料の低沸点シンナーおよび高沸点シンナーの混合比の補正値を決定する。また、微粒化度の測定値が所定の基準値よりはずれている場合は、図１７（ｂ）に示すような塗料の微粒化度〜塗装機回転数特性に基づいて、塗装機回転数の補正値を決定する。また、塗膜厚の測定値が所定の基準値よりはずれている場合は、図１７（ｃ）に示すような塗膜厚〜塗装機の塗料吐出量特性に基づいて、吐出量の補正値を決定する。
【００８４】
そして、塗装条件制御手段４は上記の塗装品質判定手段３からの各補正値に基づいて自動塗装機５の塗装条件を変更する。自動塗装機５は上記塗装条件制御手段４からの制御信号に基づき、次の被塗装物１への自動塗装を行なう。以上の自動塗装機５の制御を行なうことにより、自動塗装ラインでも狙い通りの安定した塗装品質の確保と無駄塗装のない最適な塗装制御が行なわれる。
【図面の簡単な説明】
【図１】本発明の基本的構成を説明するブロック図である。
【図２】本発明の一実施例を説明するブロック図である。
【図３】塗装品質要因計測手段を説明するブロック図である。
【図４】粒子飛行過程における溶剤の蒸発を示す説明図である。
【図５】撮像手段の一例を示す断面図である。
【図６】撮像手段において被塗装物上に形成されるスリットの縞模様を示す図である。
【図７】パワースペクトルの周波数特性を示すグラフである。
【図８】塗料粒子の付着と塗装面の形成過程を示す断面説明図である。
【図９】塗料の飛行粒子と付着粒子の関係を示す説明図である。
【図１０】塗料粒子の平均径と波長との関係を示すグラフである。
【図１１】塗料粒子径と塗布時間の関係を示すグラフである。
【図１２】波長と塗布時間の関係を示すグラフである。
【図１３】塗膜表面の平坦化現象を示す説明図である。
【図１４】表面粗さとパワースペクトルの関係を示すグラフである。
【図１５】平滑化理論と測定値の比較を示すグラフである。
【図１６】波長とウエット膜厚の関係を示すグラフである。
【図１７】塗着Ｎ．Ｖと塗料シンナー混合比の関係を示すグラフ（ａ）、塗膜厚と自動塗装機の塗料吐出量の関係を示すグラフ（ｂ）、および微粒化度と自動塗装機の回転数の関係を示すグラフ（ｃ）である。
【図１８】従来例を説明するブロック図である。
【符号の説明】
１被塗装物（ボディ）
２塗装品質要因計測手段
３塗装条件判定手段
４塗装条件制御手段
５自動塗装機
６撮像手段
７画像処理手段
８波長演算手段
９波長平均処理手段
１０微粒化度演算手段
１１第１塗着Ｎ．Ｖ演算手段
１２塗料密度演算手段
１３第２塗着Ｎ．Ｖ演算手段
１５塗装条件入力手段
１６塗料条件入力手段
１７シンナー蒸発量入力手段
１８測定時間入力手段
１９表面粗さ演算手段
２０膜厚演算手段[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a control method and control device for an automatic coating machine used for automatically coating an object to be coated.
[0002]
[Prior art]
Conventionally, for example, in car body painting of automobiles, painting is performed by an automatic painting machine, and after the paint is dried for a long time after painting, the sharpness of the paint after drying (smoothness, fleshiness, glossiness) ) To inspect the coating quality.
[0003]
And as control of an automatic coating machine, as shown in FIG. 18, after evaluating the sharpness (smoothness) of the object to be painted such as the automobile body shown in the block 101 by the smoothness measuring means in the block 102, The painting quality determination means in block 103 compares the sharpness value with a predetermined reference value, and if the sharpness value and the reference value are different, the painting condition control means in block 104 determines the sharpness value as the reference value. Thus, the coating control conditions (discharge amount, etc.) of the automatic coating machine of block 105 are to be corrected.
[0004]
In this case, the quality of the sharpness (smoothness) of the painted surface of the object to be coated can be maintained constant even if the air conditioning accuracy of the painting booth for painting the object to be painted is somewhat rough.
[0005]
[Problems to be solved by the invention]
By the way, in general, the paint quality factors that determine the quality of the paint to be coated include non-volatile components (hereinafter referred to as “coating NV”) or coating viscosity, The film thickness, the degree of atomization of the coating particles, the spraying conditions of various coating guns, the baking conditions of coating, and the like can be mentioned. Of these coating quality factors, the coating N.D. V (coating viscosity), coating thickness, and atomization degree of coating particles are important coating quality factors, and it is necessary to accurately and quantitatively grasp these coating quality factors as soon as possible, especially in automation. When painting continuously on the line, it is necessary to measure the quality of the paint as accurately as possible and feed back to the coating machine as soon as possible to improve the next paint condition and always maintain the best paint condition. .
[0006]
However, in the control of the conventional automatic coating machine as described above, only the sharpness (smoothness) is measured as the coating quality of the object to be coated, and the measured sharpness value deviates from the predetermined reference value. The painting control conditions of the automatic coating machine were corrected so that the sharpness would be the reference value.
(1) The coating film is too thin. The paint quality factor such as V (viscosity) being too high cannot be accurately indicated, and the paint quality of the paint line cannot be maintained in a stable state as intended.
[0007]
(2) The coating film is too thick. The coating quality factor such as V (viscosity) is too low cannot be accurately indicated, and coating control such as optimum film thickness without wasteful coating cannot be performed.
[0008]
It was a problem to solve these problems.
[0009]
OBJECT OF THE INVENTION
The present invention was made paying attention to the conventional problems as described above, and measures the coating quality factor (coating NV, atomization degree, coating thickness) in the coated object to be coated, It is an object of the present invention to provide a control method and a control device for an automatic coating machine that can maintain a stable coating state as intended by feedback control of the automatic coating machine and can perform optimum coating control. .
[0010]
[Means for Solving the Problems]
The control device for an automatic coating machine according to claim 1 of the present invention will be described with reference to FIG. 1. In the control device for coating an object to be coated in an air-conditioned coating booth by an automatic coating machine, The coating quality factor measuring means (block 2) for detecting the coating quality factor of the object (block 1) painted under the predetermined coating conditions by the coating machine (block 5) and the coating quality factor measuring means. Compare the measured value with the preset factor reference value, and if the detected measurement value deviates from the factor reference value, correct the coating condition of the automatic coating machine so that the coating quality factor becomes the factor reference value. The coating quality determination means (block 3) to be commanded and the coating condition control means (block 3) for controlling the coating conditions of the automatic coating machine based on the correction command from the coating quality determination means so that the coating quality of the painted surface becomes the reference value. Click 4) Configuration and to have equipped with, and the means for solving the problems of the above configuration.
Furthermore, in the automatic coating machine control apparatus according to the present invention, the coating quality factor measuring means inputs the paint condition input means for inputting the paint conditions such as the non-volatile components of the paint, and the atomization degree of the paint at the time of spraying. Non-volatile components from the paint condition input means, atomization degree from the atomization degree calculation means, and thinner evaporation amount input First coating N. for calculating a non-volatile component immediately after application of an object coated under a predetermined coating condition by an automatic coating machine based on a thinner evaporation amount from the means V calculation means 1 and first coating N.V. Paint density calculation means for calculating the paint density of the paint film surface immediately after application based on the non-volatile component of the paint film surface immediately after application calculated by the V calculation means and the paint type information from the paint condition input means, and measurement Measurement time input means for inputting the time until, film thickness calculation means for inputting the film thickness of the coating film surface, film thickness information from the film thickness calculation means, thinner evaporation amount from the thinner evaporation amount input means, and measurement time Second coating N. for calculating the non-volatile component of the coated film surface after coating based on the measurement time information from the input means. It is set as the structure provided with V calculating means.
[0011]
According to a first aspect of the present invention, there is provided a control device for an automatic coating machine according to the second aspect, wherein the coating quality factor measuring means includes an imaging means for imaging the undried coating surface immediately after the coating is applied, and an imaging means. Image processing means for image processing of the image information, and wavelength distribution calculation means for calculating the wavelength distribution of the uneven waveform on the coating surface based on the image processing data processed by the image processing means, and calculated by the wavelength distribution calculation means According to a third aspect of the present invention, the paint quality factor measuring means applies the paint condition input means for inputting the viscosity of the paint and the like, and the paint is applied. An imaging unit that images the immediately-dried painted surface, an image processing unit that performs image processing on image information from the imaging unit, and a roughness of the coating surface based on image processing data processed by the image processing unit The coating film is provided with surface roughness calculating means, and calculated from the roughness calculated by the surface roughness calculating means, the time variation of the roughness, the wavelength calculated by the wavelength distribution calculating means, and the coating conditions from the coating condition input means. According to a fourth aspect of the present invention, the coating N.I. Immediately after application, the V calculating means is based on the relationship between the non-volatile component of the paint in the paint condition input means, the thinner evaporation amount of the paint in the thinner evaporation amount input means, and the paint particle surface area obtained from the paint particle diameter of the atomization degree calculating means. The configuration is a means for calculating a non-volatile component of the coating film surface, and the above configuration is a means for solving the problem.
[0012]
An automatic coating machine control method according to claim 5 of the present invention is an automatic coating machine control method using the above-described automatic coating machine control device, and an object to be coated carried into an air-conditioned coating booth is provided. When painting with the automatic coating machine, the coating quality factor of the coated surface of the object painted under the predetermined coating conditions is detected by the automatic coating machine, and the measured value of the coating quality factor and the preset factor reference value are detected. The automatic coating machine is controlled by a correction command obtained based on the difference, and the above configuration is used as a means for solving the problem.
[0013]
[Effects of the Invention]
In the control method and control device for an automatic coating machine according to the present invention, the coating quality factor is measured by measuring the coating quality factor and performing feedback control of the automatic coating machine based on these measured values. And accurate feedback control to eliminate the paint quality factor, thereby improving the paint quality.
[0014]
According to the control device for an automatic coating machine according to claim 1 of the present invention, when the coating state of the object to be coated is poor, the coating N.D. Since the correction corresponding to the error between each measured value of the coating quality factor such as V, atomization degree and coating thickness and the factor reference value is performed, accurate feedback control according to the coating state can be performed, The automatic coating line can ensure the stable coating quality as intended, and furthermore, the optimal coating control such as the coating thickness can be performed and the coating efficiency can be improved.
In addition, even when the coating state of the object to be coated is good, the coating N.D. When V is equal to or lower than the lower limit reference value, the coating N.V. The droop correction can be corrected according to the difference between the measured value of V and the reference value. If the atomization degree is below the lower limit reference value, the difference between the measurement value of the atomization degree and the reference value is met. In addition, when the coating thickness is greater than or equal to the reference value, the thickness coating correction can be performed according to the difference between the measured value of the coating thickness and the reference value. It is possible to ensure the finished coating quality.
[0015]
According to the control device for an automatic coating machine according to claims 2 to 4 of the present invention, the measurement of the coating quality factor, that is, the measurement of the atomization degree of the paint in claim 2, the measurement of the coating film thickness in claim 3, The coating N.I. The measurement of V can be performed accurately and promptly, more accurate feedback control can be performed, and the coating quality can be further improved.
[0016]
According to the control method of the automatic coating machine according to claim 5 of the present invention, the coating quality factor (coating NV, atomization degree, coating thickness) in the coated object is measured, and the measured value Since the automatic coating machine is feedback controlled based on the difference between the value and the quality standard value, it is possible to maintain a stable coating state as intended, and to perform optimum coating control such as the coating thickness. The quality can be greatly improved and the coating efficiency can be improved.
[0017]
According to the control device for an automatic coating machine according to claims 4 to 6 of the present invention, the measurement of the paint quality factor, that is, the measurement of the atomization degree of the paint in claim 4, the measurement of the coating film thickness in claim 5, The coating N.I. The measurement of V can be performed accurately and promptly, more accurate feedback control can be performed, and the coating quality can be further improved.
[0018]
【Example】
FIG. 2 is a diagram showing an embodiment of the present invention, and is a block diagram showing a case where the present invention is applied to an automatic painting line for a vehicle body.
[0019]
The object to be coated 1 is a body of an automobile in a top coating process, and is coated while moving on a coating line at a predetermined speed. The control device of the automatic coating machine (painting gun) 5 applies the coating state of the article 1 immediately after coating, that is, the coating quality (clearness) and the coating quality factors (coating NV, atomization degree, The coating quality factor measuring means 2 that simultaneously measures the coating thickness), the measured value detected by the coating quality factor measuring means 2 and a preset factor reference value are compared, and the detected measurement value is compared with the factor reference value. If there is a deviation, the coating quality determination means 3 that commands correction of the coating conditions of the automatic coating machine 5 so that the coating quality factor becomes the factor reference value, and the coating surface based on the correction command from the coating quality determination means 3 Is provided with a coating condition control means 4 for controlling the coating conditions of the automatic coating machine 5 so that the coating quality of the ink becomes a reference value. The automatic coating machine 5 performs coating on the next object 1 based on the control signal from the coating condition control means 4.
[0020]
As shown in FIG. 3, the coating quality factor measuring means 2 in the above-described control device includes an imaging means 6, an image processing means 7 for the coating surface of the object 1, and a long wavelength region in the power spectrum of the corrugated waveform on the coating surface. A wavelength calculating means 8 for determining a peak wavelength, a wavelength averaging processing means 9, a atomization degree calculating means 10 for calculating the atomization degree at the time of spraying the paint, a first coating N.N. V calculating means 11, paint density calculating means 12 for calculating the paint density of the paint film surface immediately after application, second coating N.V. V calculation means 13, coating condition input means 15, paint condition input means 16 for inputting non-volatile components of paint, thinner evaporation amount input means 17, measurement time input means 18 for inputting time until measurement, surface roughness Calculation means 19 and film thickness calculation means 20 are provided.
[0021]
Next, the coating N.I. Coating of paint film surface in V calculation means 11 and 13 The calculation principle of V and the thinner evaporation amount calculation in the thinner evaporation amount input means 17 will be described.
[0022]
FIG. 4 is a view showing a state until the paint particles sprayed from the paint gun (automatic painting machine 5) adhere to the surface to be painted. From the paint particles, the solvent (volatile component) evaporates during and after the flight, and only the non-volatile component remains when the coating film is completely dried. The time from when the paint is sprayed from the painting gun until it adheres to the object 1 varies depending on the distance between the painting gun and the object to be coated, but is generally 0.1 seconds to 0.5 seconds. .
[0023]
In the situation as described above, the coating N. V to X ₁ Then, X1 is given by Equation 1 below.
[0024]
[Formula 1]

The thinner evaporation rate V is given by the following formula 2.
[0025]
[Formula 2]

Also, the mass M of the paint particles ₁ Is given by Equation 3 below.
[0026]
[Formula 3]

In addition, paint particle surface area S ₁ Is given by Equation 4 below.
[0027]
[Formula 4]

Therefore, by substituting Equation 3 and Equation 4 into Equation 1, the coating N.D. V = X ₁ The following formula 5 is obtained as a formula representing (%).
[0028]
[Formula 5]

The thinner evaporation amount per unit area is expressed by evaporation speed V × time t. When the thinner evaporation amount Vt is obtained from the above formulas 1 and 5, the following formula 6 is obtained.
[0029]
[Formula 6]

Note that the thinner evaporation amount Vt is equal to the N.V. V (Paint concentration) X ₀ And the thinner mixture ratio C and temperature T, the relationship between these quantities can be obtained in advance through experiments and stored and read and used. .
[0030]
As shown in the above formula 5, if the coating conditions are constant, the coating N.D. V is the thinner evaporation amount Vt, paint particle diameter R, paint density ρ ₀ Can be obtained by calculation. In the embodiment of FIG. 3, the thinner evaporation amount Vt uses the value input from the thinner evaporation amount input means 17, the paint particle diameter R uses the value obtained by the atomization degree calculating means 10, and the paint density ρ. ₀ The value input from the coating condition input means 15 is used.
[0031]
Next, the imaging means 6 will be described. FIG. 5 is a cross-sectional view showing an example of the imaging means 6.
[0032]
The basic configuration of the imaging unit 6 includes a light source 31, a light / dark pattern plate 32, a reflecting mirror 33, a lens 34, and a CDD camera 35. The light / dark pattern plate 32 is opaque (or is obtained by printing an opaque stripe pattern at a predetermined interval on a transparent plate) provided with linear slits at a predetermined interval (for example, 1 mm interval). A striped pattern corresponding to the slit is formed on the object to be coated 1 by irradiating parallel light beams in the sky of the light source 31 from the oblique direction of the painted surface through the light / dark pattern plate 32, the reflecting mirror 33, and the lens 34. This striped pattern has a waveform (for example, as shown in FIG. 6) distorted according to the unevenness on the object to be coated. The reflected light is imaged by the CCD camera 35, and the above-described distorted stripe pattern, that is, information on the surface roughness is input.
[0033]
The image information of the striped pattern as described above is subjected to image processing, and power spectrum frequency analysis (for example, fast Fourier transform processing: FFT) is performed to obtain a power spectrum PS.
[0034]
FIG. 7 is a frequency characteristic diagram of the power spectrum PS, where the vertical axis represents the power spectrum PS and the horizontal axis represents the frequency f (reciprocal of wavelength λ, f = 1 / λ).
[0035]
In FIG. 7, the first peak waveform {circle around (1)} is the power spectrum of the basic waveform due to the basic stripes corresponding to the slits, and the second peak waveform {circle around (2)} is the long wavelength region (10 to 10) The power spectrum corresponding to the middle wavelength region (about 1 to 0.1 mm) of the concavo-convex waveform and the fourth peak waveform {circle around (4)} are The power spectrum corresponding to the short wavelength area | region (0.1 mm or less) of an uneven | corrugated waveform is shown.
[0036]
In the above power spectrum waveform, the peak wavelength of the long waveform region of the concavo-convex waveform, that is, the wavelength λp corresponding to the peak value of the second peak waveform {circle around (2)} is correlated with the degree of atomization as described later. The degree of atomization can be measured.
[0037]
In the embodiment of FIG. 3, the image processing means 7 and the wavelength calculation means 8 perform the image processing and the power spectrum calculation as described above.
[0038]
Next, the wavelength average processing means 9 performs the following processing.
[0039]
Generally, in a coating automation line such as a car body coating of an automobile, various paints such as top coat, intermediate coat, or paint color difference are used, so it is necessary to input conditions according to the type of the paint. . Further, in the case of a large object to be coated such as a vehicle body, since the spraying area is large, the coating conditions may not always be uniform depending on the coating site. Therefore, in order to perform measurement with high accuracy, it is desirable to image a plurality of locations on the coating surface and perform atomization calculation and film thickness calculation using the average value of the peak wavelength λp at each of these portions.
[0040]
In the embodiment shown in FIG. 3, for the above reason, the image pickup means 6 picks up images of a plurality of places on the painted surface, sequentially calculates the image information, and the obtained plurality of peak wavelengths λp are obtained by the wavelength average processing means 9. The averaged value is sent to the atomization degree calculating means 10. Further, the coating condition input means 15 is provided to input information according to the type of coating, etc., and the atomization degree calculating means 10 determines the degree of atomization according to the averaged peak wavelength λp and the coating conditions. Is configured to calculate.
[0041]
Next, the principle of the atomization degree measurement in the atomization degree calculating means 10 will be described.
[0042]
First, based on FIG. 8, the adhesion process of the paint particles to the painted surface and the process of forming the painted film surface during painting will be described.
[0043]
As shown in FIG. 8A, atomized paint particles are sprayed from the paint gun toward the paint surface. At this time, the average particle size of the paint particles is basically determined by the paint speed (1), (2), (3) below, the air speed (4) below, and the physical properties of the paint (below ▲). 5 ▼). However, the above (1) to (5) are as follows.
[0044]
▲ 1 ▼ Discharge amount of paint gun
▲ 2 ▼ Bell rotation speed of paint gun
(3) Applied voltage
▲ 4 ▼ Air pressure
(5) Paint physical properties (viscosity, surface tension, density)
The bell rotation speed is the rotation speed of the rotating body that atomizes the paint, the applied voltage is the static voltage (about 50 kV) applied to apply static electricity to the paint particles, and the air pressure is the paint pressure Air pressure is used to create a wall of airflow around the particles so that the particles do not scatter around.
[0045]
The paint particles sprayed as described above collide with the paint surface and adhere in a crushed form.
[0046]
Next, as shown in FIG. 8B, at the initial stage of the coating film shape, the attached small paint particles are combined with the large paint particles to form larger particles. Further, the bonding of the particles further proceeds, and an initial coating film surface is formed by the surface tension and the boundary tension.
[0047]
Since the coating film is formed by the adhesion and bonding of the particles as described above, the initial coating film surface condition is such that the particle diameter r of the large coating particle, the particle collision speed vx, the physical properties of the paint (surface tension γ, viscosity η), etc. Depends on. For example, in the case of top coating, it is confirmed that the height of the unevenness on the surface of the initial coating film is about several to several tens of μm, and the wavelength distribution of the unevenness is dominant in the long wavelength region of about 3 to 6 mm. It was. It was confirmed by experiments that there is a correlation between the peak wavelength λ in the long wavelength region and the particle diameter r of the large paint particles.
[0048]
Next, as shown in FIG. 8C, the surface of the coating film after the initial coating film formation is gradually flattened by the leveling force (the combined force of the surface tension γ and the weight g). This flattening speed is determined by the leveling force, the physical properties of the paint (surface tension γ, viscosity η) and the film thickness h. For example, in the case of top coating, it has been confirmed that the flattening speed is several tens of seconds to several hundreds seconds in terms of time constant.
[0049]
Next, the relationship between the paint particle diameter and the unevenness of the coating film surface will be described in detail with reference to FIGS.
[0050]
As shown in FIG. 9, if the particle diameter of the paint particles sprayed from the coating gun is r, the width of the adhering particles attached thereto is λ / 2, and the thickness (peak value) is h, the wavelength λ A coating surface having irregularities is formed. The relationship between the width λ / 2 of the adhered particles and the wavelength λ is experimentally determined, and it has been confirmed that the value is almost this value.
[0051]
The paint particle diameter r in the above case is expressed by the following mathematical formula 7.
[0052]
[Formula 7]

When the above theoretical formula is shown in a graph, it becomes a curve as shown by a broken line in FIG. However, in actuality, there is a bond as shown in FIG. The characteristic obtained in this experiment is expressed by the following mathematical formula 8.
[0053]
[Formula 8]

The relationship between the peak wavelength λp of the unevenness obtained by the experiment as described above and the paint particle diameter r is analyzed in consideration of the bonding of adhered particles.
[0054]
First, as shown in FIG. 11, the adhered particle diameter R increases sequentially as the coating time increases. This relationship is represented by the following mathematical formula 9.
[0055]
[Formula 9]

In FIG. 11, the application time is the duration of application at one location, the initial particle diameter is the paint particle diameter before adhesion, and the adhesion particle diameter is the particle diameter when first attached. The adhered particle diameter R gradually increases as the coating time is increased because the sequentially applied particles are engaged.
[0056]
FIG. 12 is a characteristic diagram comparing the relationship between the coating time and the uneven wavelength on the coating film surface with respect to the measured value (broken line) and the result obtained from the power spectrum by frequency analysis. As can be seen from FIG. 12, the value obtained from the power spectrum is in good agreement with the actually measured value. Therefore, the adhered particle diameter R can be obtained using the uneven wavelength obtained from the power spectrum (the long wavelength peak wavelength λp). Further, in the automatic coating machine, since the coating time is constant, the paint particle diameter r can also be obtained by the following formula 10.
[0057]
[Formula 10]

Based on the above considerations, basically, the paint particle diameter r can be obtained by using the peak wavelength λp in the long wavelength region of the unevenness obtained from the power spectrum, using Equation 8 above. Specifically, if the characteristics of FIG. 10 are obtained through experiments, and the coefficients ks, a, and β of Expression 8 are obtained in advance, the paint particle diameter r is obtained using the peak wavelength λp obtained from the captured image. be able to.
[0058]
Since the particle diameter r of the paint particles corresponds to the degree of atomization of the paint, the particle diameter r of the paint particles may be used as it is, or the degree of atomization may be expressed, or the reciprocal of r or a reference value The degree of atomization can also be expressed using a percentage of
[0059]
Next, the film thickness calculation in the surface roughness calculation means 19 and the film thickness calculation means 20 will be described.
[0060]
FIG. 13 is a cross-sectional view of the coated film after painting. Immediately after coating, as shown in (a), the coated surface is in an uneven state due to the bonding of the initial adhered particles. Then, as time passes, as shown in (b), it is gradually smoothed by the leveling force, and finally it becomes a smoothed state as shown in (c). In the present embodiment, paying attention to such smoothing reduction, the uneven state of the coating surface in the wet state is measured, thereby calculating the coating film thickness after smoothing or drying.
[0061]
In order to measure the concavo-convex state in the wet state as described above, various methods such as an optical interference type surface roughness meter (for example, “Mechanical Engineering Handbook, September 30, 1989, New Edition 3 Printing, B2 pp.207-208 However, here, a method of imaging the painted surface with the imaging means 6 and image processing the information will be described.
[0062]
First, the smoothing characteristic by the power spectrum integrated value P will be described. The surface roughness R corresponding to the area average value of the surface irregularities (peak-to-peak value). _a And the power spectrum integral value P are in a relationship as shown in FIG. 14 and in the following equations 11 and 12.
[0063]
[Formula 11]

[0064]
[Formula 12]

In the above equation, Q is a roughness correction value, and k is a roughness conversion coefficient.
[0065]
In the derivation of the averaged theoretical formula based on the power spectrum analysis value, first, the surface roughness R _a Is expressed by Equation 13 below.
[0066]
[Formula 13]

However, R _a0 Is R _a The initial value (time 0, that is, the value immediately after painting), t is the elapsed time after painting. Further, τ is a time constant derived from the basic equation of the viscous fluid, and is as shown in Equation 18 below.
[0067]
Substituting Equation 12 into Equation 13 yields Equation 14 below.
[0068]
[Formula 14]

However, P ₀ Is the initial value of P (the value at time 0), and Q ₀ Is the initial value of Q.
[0069]
In the above formula 14, P, P ₀ For each correction value Q, Q ₀ As a value including (P ₀ -Q ₀ ) → P ₀ , (PQ) → P, Equation 14 can be expressed as Equation 15 below.
[0070]
[Formula 15]

The time constant τ is expressed by the following formula 16.
[0071]
[Formula 16]

Where η is the viscosity of the paint, λ is the peak wavelength in the long wavelength region, γ is the surface tension of the coating film, and h is the film thickness in the wet state (average value of the imaging portion).
[0072]
From the above, the coating film thickness h based on the power spectrum analysis value is expressed by the following mathematical formula 17.
[0073]
[Formula 17]

However, P ₁ Is the time t ₁ The value of the power spectrum integral value P at ₂ Is the time t ₂ (However- ₁ <T ₂ ) In P). Τ ′ _i Is represented by Equation 18 below.
[0074]
[Formula 18]

However, i = 1, 2 and η (ti) indicates that the viscosity of the paint is a function of the elapsed time after painting. That is, what is input from the coating condition input means 15 is the viscosity η of the paint before painting, but the coating viscosity after painting is a value η (t that changes according to the elapsed time after painting. _i ) This value is determined by the paint composition (such as the proportion of volatile components in the paint) and the wind speed.
[0075]
As can be seen from Equation 17, the viscosity η of the paint, the surface tension γ of the coating film, the peak wavelength λ in the long wavelength region of the corrugated waveform, and two time points t after coating ₁ , T ₂ The film thickness h in the wet state can be obtained from the value of the power spectrum integral value P in FIG. Among the above numerical values, the viscosity η of the paint and the surface tension γ of the coating film are values determined by the characteristics of the paint, so input a known value, the peak wavelength λ in the long wavelength region, and the power spectrum integration As the value P, a value obtained by processing the image information is used.
[0076]
FIG. 15 is a characteristic diagram showing a wet smoothing characteristic (power spectrum integrated value P) in which the theoretical value and the measured value using the mathematical formula 17 are compared. In FIG. 15, the horizontal axis represents the elapsed time after painting, and the vertical axis represents the power spectrum integrated value P.
[0077]
In the above measurement, an image immediately after coating is taken by the imaging means 6 and power spectrum analysis is performed. From FIG. 15, it can be seen that the measured value has a smoothing characteristic that substantially matches the theoretical value.
[0078]
Table 1 is a table showing the results of measuring the film thickness h for the two samples having a film thickness of 60 μm and 54 μm by using the estimation formula of the mathematical formula 17.
[0079]
As shown in Table 1, it can be seen that measurement is possible with an accuracy of several μm.
[0080]
[Table 1]

[0081]
In the embodiment shown in FIG. 3, the imaging unit 6, the image processing unit 7, the wavelength calculation unit 8, the surface roughness calculation unit 19 and the film thickness calculation unit 20 perform the above-described processing to set the film thickness h at the imaging location. Ask.
[0082]
Further, in Equation 17, two time points t after painting ₁ And t ₂ Two values P in ₁ , P ₂ And using the amount of change in roughness information over time. Therefore, it is necessary to image the same part at two time points after painting. For this purpose, it is necessary to move the imaging means 6 in accordance with the movement of the vehicle body on the painting line, so that the apparatus becomes complicated. To avoid this, there are the following methods. In other words, in addition to the body to be coated, a test piece is prepared and painted under the same conditions as the body to be coated. ₁ (Eg t ₁ = 10 seconds, t ₁ <T ₂ ) Value P ₁ Uses the value obtained by processing the image information of the test piece. In this way, the imaging means 6 ₂ It is only necessary to perform imaging once (for example, after 1-2 minutes of painting).
[0083]
Next, the coating quality judgment means 3 measures the coating quality factor (coating NV, atomization, coating thickness) measured from the coating quality factor measuring means 2 measured as described above and predetermined factor criteria. When the measured value has an error with respect to each factor reference value, a correction value corresponding to the difference from the factor reference value is sent to the coating condition control means 4. Here, each correction method uses sensitivity characteristics required for each automatic coating machine. Application N. When the measured value of V deviates from a predetermined reference value, the coating N.V. as shown in FIG. Based on the V to thinner mixing ratio characteristic, a correction value for the mixing ratio of the low-boiling thinner and the high-boiling thinner of the paint is determined. Further, when the measured value of the atomization degree deviates from a predetermined reference value, the correction of the coating machine rotation speed is performed based on the atomization degree of the paint to the coating machine rotation speed characteristics as shown in FIG. Determine the value. In addition, when the measured value of the coating film thickness deviates from the predetermined reference value, the discharge amount correction value is set based on the coating film thickness to the coating material discharge amount characteristic of the coating machine as shown in FIG. decide.
[0084]
The painting condition control means 4 changes the painting conditions of the automatic painting machine 5 based on the correction values from the painting quality judgment means 3. The automatic coating machine 5 performs automatic coating on the next object 1 based on the control signal from the coating condition control means 4. By controlling the automatic coating machine 5 as described above, it is possible to ensure stable coating quality as intended and optimal coating control without wasteful coating even in an automatic coating line.
[Brief description of the drawings]
FIG. 1 is a block diagram illustrating a basic configuration of the present invention.
FIG. 2 is a block diagram illustrating an embodiment of the present invention.
FIG. 3 is a block diagram for explaining a coating quality factor measuring means.
FIG. 4 is an explanatory diagram showing the evaporation of the solvent during the particle flight process.
FIG. 5 is a cross-sectional view showing an example of an imaging unit.
FIG. 6 is a diagram showing a stripe pattern of slits formed on an object to be coated in the imaging means.
FIG. 7 is a graph showing frequency characteristics of a power spectrum.
FIG. 8 is a cross-sectional explanatory view showing the process of adhesion of paint particles and formation of a painted surface.
FIG. 9 is an explanatory diagram showing a relationship between flying particles of paint and attached particles.
FIG. 10 is a graph showing the relationship between the average diameter of paint particles and the wavelength.
FIG. 11 is a graph showing the relationship between paint particle diameter and application time.
FIG. 12 is a graph showing the relationship between wavelength and coating time.
FIG. 13 is an explanatory view showing a flattening phenomenon of a coating film surface.
FIG. 14 is a graph showing the relationship between surface roughness and power spectrum.
FIG. 15 is a graph showing a comparison between smoothing theory and measured values.
FIG. 16 is a graph showing the relationship between wavelength and wet film thickness.
FIG. A graph (a) showing the relationship between V and paint thinner mixing ratio, a graph (b) showing the relationship between the coating thickness and the paint discharge amount of the automatic coating machine, and a relationship between the atomization degree and the rotation speed of the automatic coating machine It is a graph (c).
FIG. 18 is a block diagram illustrating a conventional example.
[Explanation of symbols]
1 Object to be painted (body)
2 Paint quality factor measurement means
3 Coating condition judgment means
4 Coating condition control means
5 Automatic coating machines
6 Imaging means
7 Image processing means
8 Wavelength calculation means
9 Wavelength average processing means
10 Atomization degree calculation means
11 First coating N.P. V calculation means
12 Paint density calculation means
13 Second coating N.P. V calculation means
15 Coating condition input means
16 Paint condition input means
17 Thinner evaporation input means
18 Measurement time input means
19 Surface roughness calculation means
20 Thickness calculation means

Claims

In a control device for painting an object to be coated in an air-conditioned painting booth using an automatic painting machine,
A coating quality factor measuring means for detecting a coating quality factor of an object to be painted under a predetermined coating condition by an automatic coating machine;
Compare the measurement value detected by the paint quality factor measurement means with the preset factor reference value, and if the detected measurement value deviates from the factor reference value, the paint quality factor becomes the factor reference value. Painting quality judgment means to command correction of painting conditions of automatic painting machine,
Based on the correction command from the paint quality judging means, equipped with a paint condition control means for controlling the paint conditions of the automatic painting machine so that the paint quality of the paint surface becomes the reference value,
The coating quality factor measuring means is
Paint condition input means for inputting paint conditions such as non-volatile components of the paint;
Atomization degree calculating means for inputting the atomization degree of the paint at the time of spraying;
A thinner evaporation amount input means for inputting a thinner evaporation amount of the paint;
Based on the non-volatile components from the paint condition input means, the atomization degree from the atomization degree calculating means, and the thinner evaporation amount from the thinner evaporation amount input means, the coating material coated under predetermined coating conditions by the automatic coating machine. First coating for calculating a non-volatile component immediately after application of a coated material V calculation means 1,
First coating N.N. Paint density calculation means for calculating the paint density of the paint film surface immediately after application based on the non-volatile component of the paint film surface immediately after application calculated by the V calculation means and the paint type information from the paint condition input means;
Measurement time input means for inputting the time until measurement, film thickness calculation means for inputting the film thickness of the coating film surface,
A second component for calculating a non-volatile component of the coated film surface after coating based on the film thickness information from the film thickness calculation means, the thinner evaporation amount from the thinner evaporation amount input means, and the measurement time information from the measurement time input means Coating N. V calculation means;
A control device for an automatic coating machine, characterized by comprising:

The coating quality factor measuring means includes an image pickup means for picking up an image of an undried paint surface immediately after coating, an image processing means for image processing image information from the image pickup means, and image processing data processed by the image processing means. A wavelength distribution calculating means for calculating the wavelength distribution of the corrugated waveform on the coating surface based on the wavelength distribution calculating means, and a means for calculating the atomization degree of the paint particles based on the wavelength distribution calculated by the wavelength distribution calculating means. The control apparatus of the automatic coating machine of Claim 1.

The coating quality factor measuring means inputs the coating condition input means for inputting the viscosity of the paint, the imaging means for imaging the wet coating surface immediately after the coating is applied, and the image processing means for image processing image information from the imaging means And surface roughness calculating means for calculating the roughness of the coating surface based on the image processing data processed by the image processing means,
It is a means for calculating the coating thickness from the roughness calculated by the surface roughness calculating means, the time variation of the roughness, the wavelength calculated by the wavelength distribution calculating means, and the coating conditions from the coating condition input means. The control device for an automatic coating machine according to claim 1 or 2.

Coating N. Immediately after application, the V calculating means is based on the relationship between the non-volatile component of the paint in the paint condition input means, the thinner evaporation amount of the paint in the thinner evaporation amount input means, and the paint particle surface area obtained from the paint particle diameter of the atomization degree calculating means. The control device for an automatic coating machine according to claim 1, wherein the control unit is a means for calculating a non-volatile component of the coating film surface.

An automatic coating machine control method using the automatic coating machine control device according to any one of claims 1 to 4,
When painting an object that has been brought into an air-conditioned painting booth using an automatic painting machine, the automatic painting machine detects the painting quality factor of the painted surface of the painting object that has been painted under the specified painting conditions, and the painting quality An automatic coating machine control method, comprising: controlling an automatic coating machine according to a correction command obtained based on a difference between a measured value of a factor and a preset factor reference value.