JP3830807B2

JP3830807B2 - Wastewater disinfection method

Info

Publication number: JP3830807B2
Application number: JP2001347043A
Authority: JP
Inventors: 正雄鮎川; 秀潔吉田; 啓全開発
Original assignee: Ebara Corp
Current assignee: Ebara Corp
Priority date: 2001-11-13
Filing date: 2001-11-13
Publication date: 2006-10-11
Anticipated expiration: 2021-11-13
Also published as: JP2003147844A

Description

【０００１】
【発明の属する技術分野】
本発明は下水、雨水を含む下水及び地表を流下した雨水等を合流式下水道における排水を薬剤により消毒する排水消毒方法に関し、特に薬剤添加量をリアルタイムにて予測するのに好適な排水消毒方法に関するものである。
【０００２】
【従来の技術】
従来、この種の排水消毒装置の制御方法としては、排水消毒装置を設置する処理場内に設けられた測定装置により、排水の流入量及び流入汚濁負荷、降雨量、降雨強度を測定し、該測定した測定値から該排水消毒装置に流入する排水中の大腸菌群数を推定して薬剤の添加量を予測し制御していた。
【０００３】
図１は、従来の排水消毒装置が消毒する排水を収集する合流式下水管路網と処理地域を示す図である。該処理地域Ｘ内で発生した下水、雨水を含む下水及び地表を流下した雨水等の排水は、該処理地域Ｘ内に設けられた下水管１１に流入する。各下水管１１に流入した排水は合流し、該合流した排水は直接処理場１０に設けられた排水消毒装置に流入するか又は各中継ポンプＰ１、Ｐ２、Ｐ３により排水消毒装置に送水される。
【０００４】
しかしながら、従来の排水消毒装置の制御方法では、下記▲１▼〜▲３▼のような問題があり、排水に含まれる大腸菌群の効率的な除去を行うことができないという問題があった。
【０００５】
▲１▼排水の流入量及び流入汚濁負荷、降雨量、降雨強度の測定が同一処理場１０内で行われており、最終的な排水の流入総量及び流入汚濁負荷が予測できないため排水処理装置の薬剤消費量の予測ができない。
【０００６】
▲２▼測定点が処理場１０内の定点であるため、各測定値毎の時系列相関性及び測定値相互の相関性を構築、検証するための時間を要する。
【０００７】
▲３▼降雨量、降雨強度などの降雨情報の測定点と実際の降雨地域との相違から、降雨量と排水の流入量及び水質の相関関係が取りにくい。
【０００８】
【発明が解決しようとする課題】
本発明は上述の点に鑑みてなされたもので、上記従来技術の欠点を除去すべく、排水消毒装置を設置する特定処理地域に設けられた測定点又は該特定処理地域及び隣接する処理地域に設けられた測定点より収集された降雨情報から、薬剤添加量、薬剤消費量及び消毒開始時刻をリアルタイムにて予測することができる排水消毒方法を提供することを目的とする。
【０００９】
【課題を解決するための手段】
上記課題を解決するため請求項１に記載の発明は、排水消毒装置を設置する特定処理地域内の下水、雨水を含む下水及び地表を流下した雨水等を含む排水を薬剤により消毒する排水消毒方法において、特定処理地域に設けられた測定点又は該特定処理地域及び該特定処理地域に隣接する処理地域に設けられた測定点からの降雨情報を収集し、降雨情報から特定処理地域内における降雨開始時刻、降雨総量及び降雨継続時間の予測を行い、予測した降雨開始時刻、降雨総量及び降雨継続時間から特定処理地域の予想降雨量、予想降雨強度及び排水消毒装置に流入する排水の予想流入量を求め、予想降雨量、予想降雨強度、予想流入量及び濁度測定手段で測定した排水消毒装置に流入する排水の流入水濁度から大腸菌群数を推定し、推定した大腸菌群数に対する必要な薬剤添加量を予測することを特徴とする。
【００１０】
上記のように排水消毒方法は、特定処理地域に設けられた測定点又は該特定処理地域及び該特定処理地域に隣接する処理地域に設けられた測定点より収集された降雨情報から特定処理地域内における降雨開始時刻、降雨総量及び降雨継続時間の予測を行い、予測した降雨開始時刻、降雨総量及び降雨継続時間から特定処理地域の予想降雨量、予想降雨強度及び排水消毒装置に流入する排水の予想流入量を求め、予想降雨量、予想降雨強度、予想流入量及び濁度測定手段で測定した排水消毒装置に流入する排水の流入水濁度から大腸菌群数を推定し、推定した大腸菌群数に対する必要な薬剤添加量を予測するので、薬剤添加量をリアルタイムで予測することができる。
【００２１】
【発明の実施の形態】
以下、本発明の実施の形態例を図面に基いて説明する。図２は、本発明にかかる排水消毒装置が消毒する排水を収集する合流式下水管路網と処理地域及び隣接する処理地域を示す図である。同図に示すように、排水消毒装置を設置する処理場１０の処理地域Ｘの周囲には、同様の処理場を有する処理地域Ａ、Ｂ、Ｃ、Ｄ、Ｅが隣接して存在する。なお、本実施形態例における合流式下水管路網の基本的構成は、図１に示す合流式下水管網と同一であるのでその説明は省略する。また、本排水消毒装置の薬剤としては、ハロゲン系の薬剤を用いる。
【００２２】
〔第一実施形態〕
図３は、本発明にかかる排水消毒装置の制御装置の構成例を示す図である。同図に示すように、処理地域Ａ内には複数の降雨情報測定手段２０、２０…が設けられ、該降雨情報測定手段２０、２０…で処理地域Ａ内の降雨情報２１ａ、２２ａ…が測定できるようになっている。なお、各降雨情報測定手段２０は、図示は省略するが、処理地域Ａ内の中継ポンプが設置されているポンプ場、排水機場、処理場、計測設備を有する施設に設けられている。その他の処理地域Ｂ、Ｃ、Ｄ、Ｅ、Ｘについても、同様な降雨情報測定手段でそれぞれの処理地域の降雨量、降雨強度などの降雨情報を測定するようになっている。該各処理地域Ａ，Ｂ、Ｃ、Ｄ、Ｅ、Ｘで測定された降雨情報は、市販の電話回線を利用したデータ伝送装置やアメダスシステムなどを利用して制御装置３０に連続的又は定期的に伝送されてくるようになっている。
【００２３】
図４は、本発明にかかる排水消毒装置の制御方法に用いられるマッピング処理を示す図で、同図（ａ）は各処理地域Ａ，Ｂ、Ｃ、Ｄ、Ｅ、Ｘで測定された降雨情報をマッピング処理した模式図で、同図（ｂ）は同図（ａ）の時間ｔ経過後の模式図である。上記制御装置３０に入力された処理地域Ａ，Ｂ、Ｃ、Ｄ、Ｅ、Ｘからの降雨情報は、降雨情報マッピング処理手段３１により図４（ａ）に示すような模式図にマッピング処理される。各処理地域Ａ，Ｂ、Ｃ、Ｄ、Ｅ、Ｘで測定された降雨情報は、連続的又は定期的に制御装置３０に伝送されるので、図４（ａ）に示す模式図は時間ｔ経過後に図４（ｂ）に示すような模式図となる。なお、上記マッピング処理された降雨情報は、Ａで示すように降雨強度の強弱で表されている。
【００２４】
次に、連続的又は定期的に伝送されマッピング処理された降雨情報の時系列推移（図４参照）から、降雨情報推定処理手段３２より処理地域Ｘにおける降雨開始時刻、降雨総量及び降雨継続時間の予測を行う。また、該降雨情報推定処理手段３２は、予測した降雨開始時刻、降雨総量及び降雨継続時間から、処理地域Ｘの処理場１０における予想降雨量３３、予想降雨強度３４及び排水消毒装置に流入する排水の予想流入量３５を求める。該求められた予想降雨量３３、予想降雨強度３４及び予想流入量３５は既知の大腸菌群数推定処理手段３６に入力される。また、大腸菌群数推定手段３６には、処理場１０に設置された濁度測定手段５０で測定された排水消毒装置に流入する排水の流入水濁度５１が入力されている。
【００２５】
該大腸菌群数推定処理手段３６は、上記入力された予想降雨量３３、予想降雨強度３４、予想流入量３５及び流入水濁度５１から、大腸菌群数を推定し、それに対する必要な薬剤添加量３６ａ、薬剤消費量３６ｂ及び排水消毒装置運転開始時刻３６ｃの予測を行う。
【００２６】
次に処理地域Ｘの処理場１０に設けられた実測値測定手段５２より、処理場１０における降雨量５３、降雨強度５４、該排水消毒装置に流入する排水の流入水量５５、排水消毒装置に供給されるハロゲン系薬剤の薬剤供給量５６、排水消毒装置から放流される排水の放流水残留薬剤濃度５７を測定する。該測定された降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７を予測値／実測値補正処理手段３７に入力する。
【００２７】
該予測値／実測値補正処理手段３７は、上記入力された降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７から薬剤添加量３６ａ、薬剤消費量３６ｂ、排水消毒装置運転開始時刻３６ｃの各予測値を補正する補正値を求める。該求められた各補正値は、補正値加算処理手段３７ａ、３７ｂ、３７ｃで薬剤添加量３６ａ、薬剤消費量３６ｂ及び排水消毒装置運転開始時刻３６ｃに加算処理され、薬剤添加量４１、薬剤消費量４２及び排水消毒装置運転開始時刻４３が求められる。
【００２８】
制御装置３０は、上記各補正値を加算処理することで求められた薬剤添加量４１、薬剤消費量４２及び排水消毒装置運転開始時刻４３の各予測値により、排水消毒装置の運転、薬剤添加量、薬剤消費量の制御を行う。なお、薬剤添加量４１は、排水消毒装置の実際の薬剤添加量設定値として、薬剤添加のリアルタイム制御に使用される。また、薬剤消費量４２は、処理場１０内にストックされている薬剤の保有量との比較を行い、排水消毒装置に添加する薬剤が不足する場合は警報などを発することで、運転員に薬剤の補充を求める目的で使用される。また、排水消毒装置運転開始時刻４３は、運転員に排水消毒装置運転開始時刻を知らせるとともに、排水消毒装置の自動運転開始指令として使用する。
【００２９】
上記のように、各処理地域Ａ，Ｂ，Ｃ，Ｄ，Ｅ、Ｘ内の各降雨情報測定手段２０で測定された降雨情報をもとに降雨情報推定処理手段３２が、処理地域Ｘ内における降雨開始時刻、降雨総量及び降雨継続時間を予測するとともに処理地域Ｘの処理場１０における予想降雨量３３、予想降雨強度３４、予想流入量３５を求め、この予想降雨量３３、予想降雨強度３４、予想流入量３５から大腸菌群数推定処理手段３６が大腸菌群数を推定し、それに対する排水消毒装置の制御に必要な薬剤添加量３６ａ、薬剤消費量３６ｂ及び排水消毒装置運転開始時刻３６ｃを予測するで、各予測値をリアルタイムにて予測することができる。
【００３０】
また、大腸菌群数推定処理手段３６は予想降雨量３３、予想降雨強度３４、予想流入量３５及び流入水濁度５１から薬剤添加量３６ａ、薬剤消費量３６ｂ及び消毒装置運転開始時刻３６ｃを予測するので、各予測値の予測をさらに正確に行うことができる。
【００３１】
さらに予測値／実測値補正処理手段３７が降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７から補正値を求め、補正値加算処理手段３７ａ、３７ｂ、３７ｃで該各補正値を薬剤添加量３６ａ、薬剤消費量３６ｂ及び消毒装置運転開始時刻３６ｃに加算処理し、薬剤添加量４１、薬剤消費量４２及び消毒装置運転開始時刻４３を求めるので、各予測値の予測をさらに正確に行うことができる。
【００３２】
〔第二実施形態〕
図５は本発明にかかる排水消毒装置の制御装置の他の構成例を示す図である。本排水消毒装置の制御装置の基本的構成は、図３に示す排水消毒装置の制御装置と略同一であるのでその説明は省略する。本排水消毒装置の制御装置が図３に示す排水消毒装置の制御装置と異なる点は、地域特性シミュレーション手段６０を具備する点である。
【００３３】
処理地域Ｘ内の各降雨情報測定手段２０より測定された降雨量、降雨強度などの降雨情報２１ｘ、２２ｘ…は、制御装置３０の降雨情報マッピング処理手段３１に入力されるとともに、地域特性シミュレーション手段６０に入力される。該地域特性シミュレーション手段６０は、市販の地域特性シミュレーションソフトウエアであり、予め登録した処理地域の地形情報、雨水収集ルート、下水管路網、下水排出人口、下水排出種別を設定初期条件として入力し、そして上記降雨情報２１ｘ、２２ｘ…を入力することで、水理・水質解析を行うものである。
【００３４】
上記地域特性シミュレーション手段６０は、処理地域Ｘ内の降雨情報から排水消毒装置に流入する排水の予想流入水量６１及び予想流入汚濁負荷６２を求める。該求められた予想流入水量６１及び予想流入汚濁負荷６２は、実測値測定手段５２により測定された降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７とともに予測値／実測値補正処理手段３７に入力される。
【００３５】
該予測値／実測値補正処理手段３７は、入力された降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７、予想流入量６１及び予想流入汚濁負荷６２から薬剤添加量３６ａ、薬剤消費量３６ｂ及び排水消毒装置運転開始時刻３６ｃを補正する補正値を求める。該各補正値は、補正値加算処理手段３７ａ、３７ｂ、３７ｃで大腸菌群数推定処理手段３６からの薬剤添加量３６ａ、薬剤消費量３６ｂ及び排水消毒装置運転開始時刻３６ｃの各予測値に加算処理され、薬剤添加量４１、薬剤消費量４２及び排水消毒装置運転開始時刻４３の各予測値が求められる。制御装置３０は、該各予測値により、排水消毒装置の運転、薬剤添加量、薬剤消費量の制御を行う。
【００３６】
上記のように予測値／実測値補正処理手段３７が地域特性シミュレーション手段６０で求めた予想流入水量６１及び予想流入汚濁負荷６２から薬剤添加量３６ａ、薬剤消費量３６ｂ及び排水消毒装置運転開始時刻３６ｃを補正する補正値を求め、該各補正値を補正値加算処理手段３７ａ、３７ｂ、３７ｃにより大腸菌群数推定手段３６からの薬剤添加量３６ａ、薬剤消費量３６ｂ及び消毒装置運転開始時刻３６ｃに加算処理することで、薬剤添加量４１、薬剤消費量４２及び消毒装置運転開始時刻４３を求めるので、各予測値の予測をさらに正確に行うことができる。
【００３７】
なお、上記実施形態例では、処理地域Ｘ内の各降雨情報測定手段２０で測定された降雨情報２１ｘ、２２ｘ…のみを地域特性シミュレーション手段６０に入力する場合を説明したが、本発明はこれに限定されるものではなく、処理地域Ｘ及び隣接する処理地域Ａ，Ｂ，Ｃ，Ｄ，Ｅの各降雨情報を入力しても良い。
【００３８】
〔第三実施形態〕
図６は本発明にかかる排水消毒装置の制御装置の他の構成例を示す図である。まず、処理地域Ｘ内の各降雨情報測定手段２０により測定された降雨量、降雨強度などの降雨情報２１ｘ、２２ｘ…は、地域特性シミュレーション手段６０に入力される。
【００３９】
上記地域特性シミュレーション手段６０は、処理地域Ｘ内の降雨情報から排水消毒装置に流入する排水の予想流入水量６１及び予想流入汚濁負荷６２を求める。該求められた予想流入水量６１及び予想流入汚濁負荷６２は、薬剤添加量算出処理手段３８に入力される。
【００４０】
また、薬剤添加量算出処理手段３８には、予め排水消毒装置に流入する排水に対する薬剤添加率を設定する薬剤添加率設定手段３９で設定された薬剤添加率３９ａが入力されるようになっている。該薬剤添加量算出処理手段３８は、入力された薬剤添加率３９ａ、予想流入水量６１及び予想流入汚濁負荷６２から、薬剤添加量３６ａ及び薬剤消費量３６ｂの予測を行う。
【００４１】
処理地域Ｘの処理場１０に設けられた実測値測定手段５２より、処理場１０における降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７を測定する。該測定された降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７は、制御装置３０の予測値／実測値補正処理手段３７に入力される。
【００４２】
該予測値／実測値補正処理手段３７は、薬剤添加量算出処理手段３８からの薬剤添加量３６ａ及び薬剤消費量３６ｂの各予測値を補正する補正値を上記入力された降雨量５３、降雨強度５４、流入水量５５、薬剤供給量５６、放流水残留薬剤濃度５７から求める。該各補正値は、補正値加算処理手段３７ａ、３７ｂで薬剤添加量算出処理手段３８からの薬剤添加量３６ａ及び薬剤消費量３６ｂの各予測値に加算処理され、薬剤添加量４１及び薬剤消費量４２を求める。制御装置３０は、薬剤添加量４１及び薬剤消費量４２より排水消毒装置の制御を行う。
【００４３】
上記のように、処理地域Ｘ内の各降雨情報測定手段２０で測定された降雨情報２１ｘ、２２ｘ…から地域特性シミュレーション手段６０により予想流入水量６１及び予想流入汚濁負荷６２を求め、薬剤添加量算出手段３８が該予想流入水量６１、予想流入汚濁負荷６２及び薬剤添加率設定手段３９で設定された薬剤添加率３９ａから薬剤添加量４１及び薬剤消費量４２を予測するので、各予測値をリアルタイムにて予測することができる。
【００４４】
なお、上記実施形態例では、処理地域Ｘ内の各降雨情報測定手段２０で測定された降雨情報２１ｘ、２２ｘ…のみを地域特性シミュレーション手段６０に入力する場合を説明したが、本発明はこれに限定されるものではなく、処理地域Ｘ及び隣接する処理地域Ａ，Ｂ，Ｃ，Ｄ，Ｅの各降雨情報を入力しても良い。
【００４５】
また、本実施形態例では、排水を消毒する薬剤にハロゲン系薬剤を用いたが、本発明はこれに限定されるものではなく、他の排水を消毒する薬剤であっても良い。
【００４６】
【発明の効果】
以上、説明したように各請求項に記載の発明によれば下記のような優れた効果が得られる。
【００４７】
請求項１に記載の発明によれば、特定処理地域に設けられた測定点又は該特定処理地域及び該特定処理地域に隣接する処理地域に設けられた測定点より収集された降雨情報から特定処理地域内における降雨開始時刻、降雨総量及び降雨継続時間の予測を行い、予測した降雨開始時刻、降雨総量及び降雨継続時間から特定処理地域の予想降雨量、予想降雨強度及び排水消毒装置に流入する排水の予想流入量を求め、予想降雨量、予想降雨強度、予想流入量及び濁度測定手段で測定した排水消毒装置に流入する排水の流入水濁度から大腸菌群数を推定し、推定した大腸菌群数に対する必要な薬剤添加量を予測するので、薬剤添加量をリアルタイムで予測することができる。
【図面の簡単な説明】
【図１】従来の排水消毒装置が消毒する排水を収集する合流式下水管路網と処理地域を示す図である。
【図２】本発明にかかる排水消毒装置が消毒する排水を収集する合流式下水管路網と処理地域及び隣接する処理地域を示す図である。
【図３】本発明にかかる排水消毒装置の制御装置の構成例を示す図である。
【図４】本発明にかかる排水消毒装置の制御方法に用いられるマッピング処理を示す図で、同図（ａ）は各処理地域Ａ，Ｂ、Ｃ、Ｄ、Ｅ、Ｘで測定された降雨情報をマッピング処理した模式図で、同図（ｂ）は同図（ａ）の時間ｔ後の模式図である。
【図５】本発明にかかる排水消毒装置の制御装置の他の構成例を示す図である。
【図６】本発明にかかる排水消毒装置の制御装置の他の構成例を示す図である。
【符号の説明】
１０処理場
１１下水管
２１ａ処理地域Ａの降雨情報
２１ｘ処理地域Ｘの降雨情報
２２ａ処理地域Ａの降雨情報
２２ｘ処理地域Ｘの降雨情報
３０制御装置
３１降雨情報マッピング処理手段
３２降雨情報推定処理手段
３３予想降雨量
３４予想降雨強度
３５予想流入量
３６大腸菌群数推定処理手段
３６ａ薬剤添加量
３６ｂ薬剤消費量
３６ｃ排水消毒装置運転開始時刻
３７実測値補正処理手段
３７ａ補正値加算処理手段
３７ｂ補正値加算処理手段
３７ｃ補正値加算処理手段
３８薬剤添加量算出処理手段
３９薬剤添加率設定手段
３９ａ薬剤添加率
４１薬剤添加量
４２薬剤消費量
４３排水消毒装置運転開始時刻
５０濁度測定手段
５１流入水濁度
５２予測値／実測値測定手段
５３降雨量
５４降雨強度
５５流入水量
５６薬剤供給量
５７放流水残留薬剤濃度
６０地域特性シミュレーション手段
６１予想流入水量
６２予想流入汚濁負荷[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a wastewater disinfection method for disinfecting wastewater in a combined sewer with chemicals, such as sewage, sewage containing rainwater, and rainwater flowing down the surface of the ground, and more particularly to a drainage disinfection method suitable for predicting the amount of chemical addition in real time. Is.
[0002]
[Prior art]
Conventionally, as a control method for this type of wastewater disinfection device, the inflow amount of wastewater, the inflow pollution load, the rainfall amount, the rainfall intensity are measured by a measuring device provided in the treatment plant where the wastewater disinfection device is installed, and the measurement is performed. Based on the measured values, the number of coliforms in the wastewater flowing into the wastewater disinfection device was estimated to control and control the amount of drug added.
[0003]
FIG. 1 is a diagram showing a combined sewage pipe network for collecting wastewater to be disinfected by a conventional wastewater disinfection device and a treatment area. Wastewater such as sewage generated in the treatment area X, sewage containing rainwater, and rainwater flowing down the ground surface flows into a sewage pipe 11 provided in the treatment area X. The waste water flowing into each sewage pipe 11 joins, and the joined waste water flows directly into a waste water disinfection device provided in the treatment plant 10 or is sent to the waste water disinfection device by each relay pump P1, P2, P3.
[0004]
However, the conventional control method of the wastewater disinfection device has the following problems (1) to (3), and there is a problem that the E. coli group contained in the wastewater cannot be efficiently removed.
[0005]
(1) The amount of wastewater inflow and inflow pollution load, rainfall, and rainfall intensity are measured in the same treatment plant 10, and the final total amount of wastewater inflow and inflow pollution load cannot be predicted. Drug consumption cannot be predicted.
[0006]
(2) Since the measurement point is a fixed point in the processing place 10, it takes time to construct and verify the time-series correlation and the correlation between the measurement values for each measurement value.
[0007]
(3) Due to the difference between the rainfall information measurement points such as rainfall and rainfall intensity and the actual rainfall area, it is difficult to correlate the rainfall with the inflow of water and the water quality.
[0008]
[Problems to be solved by the invention]
The present invention has been made in view of the above points, and in order to eliminate the disadvantages of the above-described conventional technology, the measurement points provided in the specific processing area where the drainage disinfection device is installed, or the specific processing area and the adjacent processing area. It is an object of the present invention to provide a drainage disinfection method capable of predicting in real time a drug addition amount, a drug consumption amount and a disinfection start time from rainfall information collected from provided measurement points.
[0009]
[Means for Solving the Problems]
In order to solve the above-mentioned problem, the invention described in claim 1 is a wastewater disinfection method for disinfecting wastewater including sewage, rainwater containing rainwater, rainwater flowing down the ground surface, etc. in a specific treatment area where a wastewater disinfection device is installed with a chemical. in collects rainfall information from the measurement point arranged in the processing area adjacent the measuring point or the specific processing area and the specific processing region provided in a specific processing area, starting rainfall in a particular processing area from rainfall information Estimate the time, total amount of rainfall, and the duration of rainfall, and use the predicted start time, total amount of rainfall, and duration of rain to calculate the expected amount of rainfall in the specific treatment area, the expected rainfall intensity, and the expected inflow amount of wastewater flowing into the drainage disinfection device. Estimate the number of coliforms from the estimated ingested rainfall, expected rainfall intensity, expected inflow, and the inflow turbidity of the wastewater flowing into the wastewater disinfection device measured by the turbidity measuring means. Characterized by predicting the drug amount necessary for the number of the group.
[0010]
Wastewater disinfection method as described above, specific process measurement provided to local points or the specific processing area and the specific processing specification process area from the collected rainfall information from the measurement point arranged in the processing area adjacent to the area Prediction of rainfall start time, total amount of rainfall, and duration of rainfall in Japan, and forecast of expected rainfall, specific rainfall intensity, and drainage water flowing into drainage disinfection equipment in the specific treatment area from the predicted rainfall start time, total amount of rainfall, and rainfall duration Obtain the inflow, estimate the number of coliforms from the estimated rainfall, expected rainfall intensity, expected inflow, and the inflow turbidity of the wastewater flowing into the wastewater disinfection device measured by the turbidity measuring means, and Since the required drug addition amount is predicted, the drug addition amount can be predicted in real time.
[0021]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to the drawings. FIG. 2 is a diagram showing a combined sewage pipe network that collects waste water to be disinfected by the waste water disinfecting apparatus according to the present invention, a processing area, and an adjacent processing area. As shown in the figure, processing areas A, B, C, D, and E having similar processing plants are present adjacent to each other around the processing zone X of the processing plant 10 where the waste water disinfection device is installed. In addition, since the basic structure of the confluence | merging type sewer network in this example is the same as the confluence type sewer network shown in FIG. 1, the description is abbreviate | omitted. Moreover, a halogen-type chemical | medical agent is used as a chemical | medical agent of this waste water disinfection apparatus.
[0022]
[First embodiment]
FIG. 3 is a diagram illustrating a configuration example of the control device of the drainage disinfection device according to the present invention. As shown in the figure, a plurality of rainfall information measuring means 20, 20 ... are provided in the processing area A, and the rainfall information 21a, 22a ... in the processing area A is measured by the rain information measuring means 20, 20 ... It can be done. Although not shown, each rainfall information measuring means 20 is provided in a facility having a pump station, a drainage station, a treatment plant, and a measurement facility in which a relay pump in the treatment area A is installed. For other processing areas B, C, D, E, and X, rainfall information such as rainfall amount and rainfall intensity in each processing area is measured by the same rainfall information measuring means. The rainfall information measured in each processing area A, B, C, D, E, X is continuously or periodically transmitted to the control device 30 using a data transmission device or an AMeDAS system using a commercially available telephone line. To be transmitted.
[0023]
FIG. 4 is a diagram showing a mapping process used in the control method of the drainage disinfecting apparatus according to the present invention. FIG. 4 (a) shows rainfall information measured in each processing area A, B, C, D, E, X. (B) is a schematic view after the elapse of time t in FIG. (A). The rain information from the processing areas A, B, C, D, E, and X input to the control device 30 is mapped by the rain information mapping processing means 31 into a schematic diagram as shown in FIG. . Since the rainfall information measured in each processing area A, B, C, D, E, X is transmitted to the control device 30 continuously or periodically, the schematic diagram shown in FIG. Later, a schematic diagram as shown in FIG. Note that the rain information subjected to the mapping process is represented by the strength of the rain intensity as indicated by A.
[0024]
Next, from the time series transition (see FIG. 4) of the rainfall information that is continuously or periodically transmitted and mapped, the rainfall information estimation processing means 32 determines the rainfall start time, total rainfall amount, and rainfall duration in the processing area X. Make a prediction. Further, the rainfall information estimation processing means 32 uses the predicted rainfall start time, the total rainfall amount, and the rain duration time to estimate the expected rainfall amount 33, the predicted rainfall intensity 34, and the drainage water flowing into the drainage disinfection device at the treatment plant 10 in the processing area X. The expected inflow 35 is calculated. The calculated expected rainfall 33, predicted rainfall intensity 34, and expected inflow 35 are input to known coliform group number estimation processing means 36. In addition, the inflow water turbidity 51 of the wastewater flowing into the wastewater disinfection device measured by the turbidity measurement means 50 installed in the treatment plant 10 is input to the coliform group number estimation means 36.
[0025]
The Escherichia coli group number estimation processing means 36 estimates the number of coliform groups from the input predicted rainfall 33, predicted rainfall intensity 34, predicted inflow 35 and inflow water turbidity 51, and the necessary amount of drug added thereto. 36a, the medicine consumption 36b, and the drainage disinfection operation start time 36c are predicted.
[0026]
Next, from the measured value measuring means 52 provided in the treatment plant 10 in the treatment area X, the amount of rainfall 53, the rainfall intensity 54, the inflow amount 55 of the wastewater flowing into the wastewater disinfection device, and the wastewater disinfection device are supplied. The chemical supply amount 56 of the halogen-based chemical to be discharged and the discharged water residual chemical concentration 57 of the waste water discharged from the waste water disinfection device are measured. The measured rainfall amount 53, rainfall intensity 54, inflow water amount 55, drug supply amount 56, and discharged water residual drug concentration 57 are input to the predicted value / actual value correction processing means 37.
[0027]
The predicted value / actual value correction processing means 37 is configured to calculate the amount of added medicine 36a, the amount of medicine consumed 36b from the input rainfall amount 53, rainfall intensity 54, inflow water amount 55, drug supply amount 56, and discharged water residual drug concentration 57. A correction value for correcting each predicted value of the drainage disinfection device operation start time 36c is obtained. The obtained correction values are added and processed by the correction value addition processing means 37a, 37b, and 37c to the drug addition amount 36a, the drug consumption amount 36b, and the drainage disinfection device operation start time 36c. 42 and the drainage disinfection operation start time 43 are obtained.
[0028]
The control device 30 operates the drainage disinfection device and adds the amount of medicine based on the predicted values of the drug addition amount 41, the drug consumption amount 42, and the drainage disinfection device operation start time 43 obtained by adding the correction values. Control of drug consumption. The drug addition amount 41 is used for real-time control of drug addition as an actual drug addition amount setting value of the drainage disinfection device. Further, the medicine consumption 42 is compared with the amount of medicine stocked in the treatment plant 10, and when the medicine to be added to the waste water disinfection device is insufficient, an alarm or the like is issued to the operator. Used to seek replenishment. The drainage disinfection device operation start time 43 is used to inform the operator of the drainage disinfection device operation start time and as an automatic operation start command for the drainage disinfection device.
[0029]
As described above, the rainfall information estimation processing means 32 based on the rainfall information measured by the rainfall information measuring means 20 in each processing area A, B, C, D, E, X The rainfall start time, the total amount of rainfall, and the rainfall duration time are predicted, and the predicted rainfall 33, the predicted rainfall intensity 34, and the predicted inflow 35 in the treatment plant 10 in the processing area X are obtained. The coliform group number estimation processing means 36 estimates the coliform group number from the predicted inflow 35, and predicts the chemical addition amount 36a, the chemical consumption amount 36b, and the drainage disinfection device operation start time 36c necessary for the control of the drainage disinfection device. Thus, each predicted value can be predicted in real time.
[0030]
Further, the coliform group number estimation processing means 36 predicts the drug addition amount 36a, the drug consumption amount 36b, and the sterilizer operation start time 36c from the predicted rainfall amount 33, the predicted rainfall intensity 34, the predicted inflow amount 35, and the influent water turbidity 51. Therefore, prediction of each predicted value can be performed more accurately.
[0031]
Further, the predicted value / actual value correction processing means 37 obtains correction values from the rainfall amount 53, the rainfall intensity 54, the inflow water amount 55, the chemical supply amount 56, and the discharged water residual chemical concentration 57, and correction value addition processing means 37a, 37b, 37c. Thus, each correction value is added to the drug addition amount 36a, the drug consumption amount 36b, and the disinfection device operation start time 36c to obtain the drug addition amount 41, the drug consumption amount 42, and the disinfection device operation start time 43. Can be predicted more accurately.
[0032]
[Second Embodiment]
FIG. 5 is a diagram showing another configuration example of the control device for the wastewater disinfection device according to the present invention. The basic configuration of the control device of the present drainage disinfection device is substantially the same as that of the drainage disinfection device shown in FIG. The control device of the present drainage disinfection device is different from the control device of the drainage disinfection device shown in FIG. 3 in that a regional characteristic simulation means 60 is provided.
[0033]
The rainfall information 21x, 22x, etc. measured by each rainfall information measuring means 20 in the processing area X is input to the rainfall information mapping processing means 31 of the control device 30, and also the regional characteristic simulation means. 60. The regional characteristic simulation means 60 is a commercially available regional characteristic simulation software, and inputs pre-registered terrain information, rainwater collection route, sewage pipe network, sewage discharge population, and sewage discharge type as preset initial conditions. Then, hydraulic / water quality analysis is performed by inputting the rain information 21x, 22x.
[0034]
The regional characteristic simulation means 60 obtains an expected inflow amount 61 and an expected inflow pollution load 62 of the wastewater flowing into the wastewater disinfection device from the rainfall information in the treatment area X. The determined expected inflow water amount 61 and the expected inflow pollution load 62 are predicted together with the rainfall amount 53, the rainfall intensity 54, the inflow water amount 55, the drug supply amount 56, and the discharged water residual drug concentration 57 measured by the actual measurement means 52. Value / actual value correction processing means 37.
[0035]
The predicted value / actual value correction processing means 37 is based on the input rainfall amount 53, rainfall intensity 54, influent water amount 55, drug supply amount 56, effluent water residual drug concentration 57, expected inflow amount 61, and expected inflow pollution load 62. Correction values for correcting the drug addition amount 36a, the drug consumption amount 36b, and the drainage disinfection device operation start time 36c are obtained. The correction values are added to the predicted values of the drug addition amount 36a, the drug consumption amount 36b, and the drainage disinfection device operation start time 36c from the coliform group number estimation processing means 36 by the correction value addition processing means 37a, 37b, 37c. Then, predicted values of the drug addition amount 41, the drug consumption amount 42, and the drainage disinfection device operation start time 43 are obtained. The control device 30 controls the operation of the drainage disinfection device, the amount of added medicine, and the amount of consumed medicine according to each predicted value.
[0036]
As described above, the predicted amount / actual value correction processing means 37 calculates the chemical addition amount 36a, the chemical consumption amount 36b, and the drainage disinfection device operation start time 36c from the expected inflow water amount 61 and the expected inflow pollution load 62 obtained by the regional characteristic simulation means 60. Correction values are obtained, and the respective correction values are added to the drug addition amount 36a, the drug consumption amount 36b, and the disinfection device operation start time 36c from the coliform group number estimation means 36 by the correction value addition processing means 37a, 37b, 37c. By processing, since the medicine addition amount 41, the medicine consumption amount 42, and the disinfection apparatus operation start time 43 are obtained, prediction of each predicted value can be performed more accurately.
[0037]
In the above embodiment example, the case where only the rainfall information 21x, 22x... Measured by each of the rainfall information measuring means 20 in the processing area X is input to the regional characteristic simulation means 60 has been described. It is not limited, and each rainfall information of the processing area X and the adjacent processing areas A, B, C, D, and E may be input.
[0038]
[Third embodiment]
FIG. 6 is a diagram showing another example of the configuration of the control device of the drainage disinfection device according to the present invention. First, rainfall information 21x, 22x, etc., such as rainfall amount and rainfall intensity measured by each rainfall information measuring means 20 in the processing area X is input to the regional characteristic simulation means 60.
[0039]
The regional characteristic simulation means 60 obtains an expected inflow amount 61 and an expected inflow pollution load 62 of the wastewater flowing into the wastewater disinfection device from the rainfall information in the treatment area X. The obtained expected inflow water amount 61 and the expected inflow pollution load 62 are input to the chemical addition amount calculation processing means 38.
[0040]
Further, the medicine addition amount calculation processing means 38 is inputted with the medicine addition rate 39a set in advance by the medicine addition rate setting means 39 for setting the medicine addition rate with respect to the waste water flowing into the waste water sterilizer. . The medicine addition amount calculation processing means 38 predicts the medicine addition amount 36a and the medicine consumption amount 36b from the inputted medicine addition rate 39a, the predicted inflow water amount 61 and the expected inflow pollution load 62.
[0041]
From the measured value measuring means 52 provided in the treatment plant 10 in the treatment area X, the rainfall amount 53, the rainfall intensity 54, the inflow water amount 55, the chemical supply amount 56, and the discharged water residual chemical concentration 57 in the treatment plant 10 are measured. The measured rainfall amount 53, rainfall intensity 54, inflow water amount 55, chemical supply amount 56, and discharged water residual chemical concentration 57 are input to the predicted value / actual value correction processing means 37 of the control device 30.
[0042]
The predicted value / actual value correction processing means 37 sets the correction values for correcting the predicted values of the drug addition amount 36a and the drug consumption amount 36b from the drug addition amount calculation processing means 38 as the input rainfall amount 53 and rainfall intensity. 54, the inflow water amount 55, the chemical supply amount 56, and the discharged water residual chemical concentration 57. The correction values are added to the predicted values of the drug addition amount 36a and the drug consumption amount 36b from the drug addition amount calculation processing means 38 by the correction value addition processing means 37a and 37b, and the drug addition amount 41 and the drug consumption amount are added. 42 is obtained. The control device 30 controls the drainage disinfection device based on the drug addition amount 41 and the drug consumption amount 42.
[0043]
As described above, the expected inflow water amount 61 and the expected inflow pollution load 62 are obtained by the regional characteristic simulation means 60 from the rainfall information 21x, 22x... Measured by the respective rain information measuring means 20 in the treatment area X, and the chemical addition amount is calculated. The means 38 predicts the drug addition amount 41 and the drug consumption amount 42 from the predicted inflow water amount 61, the expected inflow pollution load 62 and the drug addition rate 39a set by the drug addition rate setting means 39, so that each predicted value is set in real time. Can be predicted.
[0044]
In the above embodiment example, the case where only the rainfall information 21x, 22x... Measured by each of the rainfall information measuring means 20 in the processing area X is input to the regional characteristic simulation means 60 has been described. It is not limited, and each rainfall information of the processing area X and the adjacent processing areas A, B, C, D, and E may be input.
[0045]
In this embodiment, a halogen-based chemical is used as a chemical for disinfecting waste water. However, the present invention is not limited to this, and other chemicals for disinfecting waste water may be used.
[0046]
【The invention's effect】
As described above, according to the invention described in each claim, the following excellent effects can be obtained.
[0047]
According to the invention described in claim 1, a specific process from the collected rainfall information from the measurement point arranged in the processing area adjacent the measuring point or the specific processing area and the specific processing region provided in a specific processing area Predicts the rainfall start time, total rainfall , and rainfall duration in the area, and uses the predicted rainfall start time, total rainfall, and rainfall duration to predict the expected rainfall, specific rainfall intensity, and drainage that flows into the drainage disinfection device Estimated number of coliforms from estimated inflow, estimated rainfall intensity, expected inflow, estimated inflow and turbidity of wastewater flowing into wastewater disinfection device measured by turbidity measurement means Since the required amount of drug added to the number is predicted, the amount of drug added can be predicted in real time.
[Brief description of the drawings]
FIG. 1 is a diagram showing a combined sewage pipe network for collecting waste water to be disinfected by a conventional waste water disinfection device and a treatment area.
FIG. 2 is a diagram showing a combined sewage pipe network that collects waste water to be disinfected by the waste water disinfecting apparatus according to the present invention, a processing area, and an adjacent processing area.
FIG. 3 is a diagram showing a configuration example of a control device of a drainage disinfection device according to the present invention.
FIG. 4 is a diagram showing a mapping process used in the method for controlling a drainage disinfecting apparatus according to the present invention, in which FIG. 4 (a) shows rainfall information measured in each processing area A, B, C, D, E, X; (B) is a schematic diagram after time t in FIG. (A).
FIG. 5 is a diagram showing another configuration example of the control device of the drainage disinfection device according to the present invention.
FIG. 6 is a diagram showing another configuration example of the control device for the wastewater disinfection device according to the present invention.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 10 Treatment site 11 Sewer pipe 21a Rainfall information 21x of processing area A Rainfall information 22a of processing area X Rainfall information 22x of processing area A Rainfall information 30 of processing area X Controller 31 Rainfall information mapping processing means 32 Rainfall information estimation processing means 33 Expected rainfall 34 Expected rainfall intensity 35 Expected inflow 36 E. coli group number estimation processing means 36a Drug addition 36b Drug consumption 36c Drainage disinfection device operation start time 37 Actual value correction processing means 37a Correction value addition processing means 37b Correction value addition processing Means 37c Correction value addition processing means 38 Drug addition amount calculation processing means 39 Drug addition rate setting means 39a Drug addition rate 41 Drug addition amount 42 Drug consumption 43 Drainage disinfection device operation start time 50 Turbidity measurement means 51 Inflow water turbidity 52 Predicted value / measured value measurement means 53 Rainfall 54 Rainfall intensity 55 Inflow water amount 56 Drug supply amount 57 Discharge water residual chemical concentration 60 Regional characteristic simulation means 61 Expected inflow water amount 62 Expected inflow pollution load

Claims

In the wastewater disinfection method of disinfecting wastewater including sewage, rainwater containing rainwater and rainwater flowing down the ground surface with chemicals in a specific treatment area where a wastewater disinfection device is installed ,
Collect rainfall information from the measurement point arranged in the processing area adjacent the measuring point or the specific processing area and the specific processing region provided in the specific processing region,
Predicting the rain start time, the total amount of rainfall and the rainfall duration in the specific processing area from the rain information,
From the predicted rainfall start time, total rainfall and rainfall duration , obtain the expected rainfall of the specific treatment area, the expected rainfall intensity, and the expected inflow of drainage flowing into the drainage disinfection device,
Estimating the number of coliforms from the influent turbidity of the wastewater flowing into the wastewater disinfection device measured by the expected rainfall, the expected rainfall intensity, the expected inflow, and the turbidity measuring means,
A drainage disinfection method characterized by predicting a necessary amount of drug addition to the estimated number of coliforms .