JP2004251765A

JP2004251765A - Provision management method and provision management device

Info

Publication number: JP2004251765A
Application number: JP2003042618A
Authority: JP
Inventors: Tamaki Nishida; 玉城西田
Original assignee: CENTRAL COMP SERVICES CO Ltd; CENTRAL COMPUTER SERVICES CO Ltd; Japan Energy Corp; Azbil Corp
Current assignee: CENTRAL COMP SERVICES CO Ltd; CENTRAL COMPUTER SERVICES CO Ltd; Azbil Corp; Eneos Corp
Priority date: 2003-02-20
Filing date: 2003-02-20
Publication date: 2004-09-09

Abstract

<P>PROBLEM TO BE SOLVED: To provide a provision management method and a provision management method capable of maintenance and replacement of the provision without bringing upon an accident while properly estimating the degradation of the provision and adapting to a variation in the process capacity of an industrial plant and a content of the process. <P>SOLUTION: At the time of a 1st inspection, the provision is subjected to a deterioration inspection with a measurement means, at the time of a 2nd inspection, the provision is subjected to a deterioration measurement with the measurement means, and the deterioration of the provision is estimated with an estimation means, and at the time of the estimation, at or after the 2nd inspection the deterioration of the provision is estimated with the measurement means. The value of the deterioration measurement at the 2nd inspection is corrected based on the ratio of the deterioration estimation value at the 2nd inspection to the estimated deterioration of the provision at the time of estimation, then the provision is managed based on the corrected value. <P>COPYRIGHT: (C)2004,JPO&NCIPI

Description

【０００１】
【発明の属する技術分野】
本発明は、石油精製プラントや石油化学プラント等の産業プラントにおける設備を管理するための設備管理方法及び設備管理装置に関し、特に、腐食性ある流体を用いる配管、塔、槽、反応容器等の設備の劣化を予測して、設備の保守や交換に対する警告を発する設備管理方法及び設備管理装置に関する。
【０００２】
【従来の技術】
石油精製プラントや石油化学プラント等の産業プラントにおいて設備を適切に管理することは、設備における事故を未然に防止し、設備を長く維持する上で重要である。特に、腐食性ある流体を用いる産業プラントでは、定期的に設備を点検して異常がないか検査し、必要に応じて必要な部品を交換して設備を保守することが重要である。
【０００３】
従来の設備管理方法では、設備を検査する際に、予め定められた配管、塔、槽、反応容器等の点検箇所について劣化度合いを測定し、その測定値に基づいて、設備の劣化状態を判断するようにしている。例えば、配管の場合には、配管の劣化が顕著に表れる点検箇所を予め設定し、その予め定められた点検箇所の肉厚を測定する。その肉厚が予め定められた取り替え基準値に達した場合には、取り替え時期に達したと判断し、配管全体又は同様な劣化が予測される配管を交換する。
【０００４】
また、他の従来の設備管理方法では、設備の取り替え時期を推定するために、所定周期で劣化度合いを測定し、その測定値に基づいて、設備の寿命を予測するようにしている。例えば、配管の場合、図７に示すように、配管の劣化が顕著に表れる点検箇所の肉厚を、配管設置時から所定周期毎、例えば、１年毎の点検時期に測定する。配管の肉厚の複数の測定値から最小二乗法等により劣化曲線を推定する。劣化曲線から取り替え基準値に達する時期、すなわち、配管の寿命を推定し、その寿命の推定時期になったときに、配管全体又は同様な劣化が予測される配管を交換する。
【０００５】
【特許文献１】
特開平６−１８５１４号公報
【０００６】
【発明が解決しようとする課題】
産業プラントにおける設備の点検は大がかりな作業であり、多くの人員とコストを必要とする。そして、点検箇所によっては、産業プラントの稼働自体を一時的に停止しなければならない。このため、設備の点検を頻繁に行うことは困難であり、多くとも１年の１回とか２年に１回とかの頻度での点検となる。
【０００７】
したがって、設備の劣化状態を実際に測定して、その測定値から設備の交換時期を判断する従来の方法では、設備の交換が手遅れになるおそれがあり、それを防止するためには、十分な安全係数を見込んで交換時期を決めるしかなく、不必要な設備の交換を招くことがあった。
【０００８】
また、設備の劣化状態の測定値から劣化曲線を推定し、その劣化曲線から設備の寿命を推定する従来の方法では、実際に設備を点検することなく設備の寿命を推定することが可能である。しかしながら、産業プラントでの処理量や処理内容は必要に応じて適宜変更され、設備に多くの負荷がかかるようになる場合もあれば、設備への負荷が軽減される場合もある。このため、従来の方法で予測した劣化曲線よりも設備の劣化が進行する場合もあれば、設備の劣化が進行しない場合もある。
【０００９】
したがって、設備の劣化状態の測定値から劣化曲線を推定し、その劣化曲線から設備の寿命を推定する従来の方法では、設備の交換が手遅れになるおそれがあり、それを防止するためには、十分な安全係数を見込んで交換時期を決めるしかなく、不必要な設備の交換を招くことがあった。また、設備の劣化が進んでいないにもかかわらず不必要な設備の交換を行ってしまうことがあり、適切な時期に設備の保守、交換を行うことができる管理方法が要望されていた。
【００１０】
本発明の目的は、産業プラントの処理量や処理内容等の変化に適応して、設備の劣化状態を適切に予測し、事故を招くことなく、しかも、無駄のない設備の保守や交換を行うことができる設備管理方法及び装置を提供することにある。
【００１１】
【課題を解決するための手段】
本発明による設備管理方法は、設備の劣化を予測して、その予測に基づいて設備を管理する設備管理方法であって、設備の劣化を測定する測定手段と、設備の劣化をプロセスデータに基づいて予測する予測手段とを設け、設備の劣化検査を行う第１の時点で、前記測定手段により設備の劣化を測定し、前記第１の時点以降の設備の劣化予測を行う第２の時点で、前記予測手段により設備の劣化を予測し、前記第１の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理するようにしたので、産業プラントの処理量や処理内容等の変化に適応して、設備の劣化状態を適切に予測し、事故を招くことなく、しかも、無駄のない設備の保守や交換を行うことができる。
【００１２】
本発明による設備管理方法は、設備の劣化を予測して、その予測に基づいて設備を管理する設備管理方法であって、設備の劣化を測定する測定手段と、設備の劣化をプロセスデータに基づいて予測する予測手段とを設け、設備の劣化検査を行う第１の時点で、前記測定手段により設備の劣化を測定し、前記第１の時点以降の設備の劣化予測を行う第２の時点で、前記予測手段により設備の劣化を予測し、前記第１の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理し、前記第２の時点以降の設備の劣化検査を行う第３の時点で、前記測定手段により設備の劣化を測定し、設備の劣化測定値を更新し、前記第３の時点以降の設備の劣化予測を行う第４の時点で、前記予測手段により設備の劣化を予測し、前記第３の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理するようにしたので、産業プラントの処理量や処理内容等の変化に適応して、設備の劣化状態を適切に予測し、事故を招くことなく、しかも、無駄のない設備の保守や交換を行うことができる。
【００１３】
本発明による設備管理装置は、設備の劣化を予測して、その予測に基づいて設備を管理する設備管理装置であって、設備の劣化を測定する測定手段と、設備の劣化をプロセスデータに基づいて予測する予測手段と、設備の劣化検査を行う第１の時点で、前記測定手段により設備の劣化を測定し、前記第１の時点以降の設備の劣化予測を行う第２の時点で、前記予測手段により設備の劣化を予測し、前記第１の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理する管理手段とを有するので、産業プラントの処理量や処理内容等の変化に適応して、設備の劣化状態を適切に予測し、事故を招くことなく、しかも、無駄のない設備の保守や交換を行うことができる。
【００１４】
本発明による設備管理装置は、設備の劣化を予測して、その予測に基づいて設備を管理する設備管理装置であって、設備の劣化を測定する測定手段と、設備の劣化をプロセスデータに基づいて予測する予測手段と、設備の劣化検査を行う第１の時点で、前記測定手段により設備の劣化を測定し、前記第１の時点以降の設備の劣化予測を行う第２の時点で、前記予測手段により設備の劣化を予測し、前記第１の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理し、前記第２の時点以降の設備の劣化検査を行う第３の時点で、前記測定手段により設備の劣化を測定し、設備の劣化測定値を更新し、前記第３の時点以降の設備の劣化予測を行う第４の時点で、前記予測手段により設備の劣化を予測し、前記第３の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理する管理手段と有するので、産業プラントの処理量や処理内容等の変化に適応して、設備の劣化状態を適切に予測し、事故を招くことなく、しかも、無駄のない設備の保守や交換を行うことができる。
【００１５】
【発明の実施の形態】
本発明の一実施形態による設備管理システムについて図１乃至図６を参照して説明する。
【００１６】
本実施形態による設備管理システムにより管理される対象は、例えば、石油精製プラントや、石油化学プラント等の産業プラントにおける設備である。設備としては、例えば、配管、塔、槽、反応容器等がある。この産業プラントにおいて、ガソリン、灯油、軽油、重油等を精製又は生成する場合には、腐食性ある流体、例えば、硫化水素（Ｈ_２Ｓ）、塩酸（ＨＣｌ）、アンモニア（ＮＨ_３）等を用いることになり、設備の腐食への対処が重要な課題となる。
【００１７】
（設備管理の基本的な考え方）
図１を用いて、産業プラントにおける設備管理の基本的な考え方について説明する。
【００１８】
まず、腐食管理の基本指針を策定する。産業プラントにおける腐食メカニズムを想定し、その腐食メカニズムに基づいて運転仕様を決定する。腐食を加速させる因子を監視項目としてリストアップし、運用時にオンライン計測器を用い、プロセス流体試料のサンプルを分析する。その分析結果に基づいて設備を監視する。腐食を加速される因子については、一部制限値を設けて、これを超えないように運転仕様を決定する。
【００１９】
また、腐食管理の基本方針に基づいて設備検査仕様を決定する。設備検査仕様としては、例えば、検査部位（どこを検査するか）、検査方法（どんな方法で検査するか）、検査周期（どの程度の周期で検査するか）等がある。
【００２０】
腐食管理の基本指針に基づいて、保全管理を決定する。保全管理では、長期的な保全計画を作成し、長期計画に基づいて年度計画を策定する。年度計画に基づいて具体的な設備検査を行う。その検査結果に基づいて設備の余寿命を評価する。設備の余寿命の評価結果に基づいて、保全管理の要領を修正すべきか否かを判定し、必要であれば保全管理の長期計画、年度計画等を修正する。
【００２１】
更に、腐食管理の基本方針に基づいて運転管理を決定する。運転管理では、運転時のプロセスデータ、例えば、温度、圧力、流量、硫化水素（Ｈ_２Ｓ）濃度、塩酸（ＨＣｌ）濃度、アンモニア（ＮＨ_３）濃度等を取得する。また、検査仕様に基づいて、所定周期毎に検査データ、例えば、配管の肉厚等を取得する。このように取得したプロセスデータ及び検査データに基づいて将来の設備の劣化について予測する。
【００２２】
（設備管理システム）
図２を用いて、本実施形態の設備管理システムについて説明する。
【００２３】
石油精製プラントや石油化学プラント等の産業プラント１０には、配管、塔、槽、反応容器等の設備（図示せず）が設けられている。この産業プラント１０では、硫化水素（Ｈ_２Ｓ）、塩酸（ＨＣｌ）、アンモニア（ＮＨ_３）等の腐食性ある流体を用いており、設備の劣化、例えば、腐食に対応するための管理が必要である。
【００２４】
産業プラント１０の運転中においては、オンライン計測器１２により、流体流量、流体温度、流体圧力等の運転データを取得すると共に、プロセス試料分析器１４により、腐食因子（硫化水素（Ｈ_２Ｓ）、塩酸（ＨＣｌ）、アンモニア（ＮＨ_３）等）の濃度等の試料データを取得する。オンライン計測器１２からの運転データと、プロセス流体試料分析器１４からの試料データは、プロセスデータサーバ１６に蓄積される。
【００２５】
予測手段１８は、ＮＮ（ニューラルネットワーク）やＴＣＢＭ（ＴｏｐｏｌｏｇｉｃａｌＣａｓｅＢａｓｅｄＭｏｄｅｌｉｎｇ：事例ベース推論を利用した非線形モデリング手法）等の学習ツールを用い、プロセスデータサーバ１６に蓄積されたプロセスデータに基づいて、腐食メカニズム等を考慮した予測モデルにしたがって設備の腐食速度を推定する。例えば、配管の肉厚の腐食速度を推定する。予測手段１８による腐食速度の推定は、産業プラント１０の運転を中止する必要がないので、必要に応じて適宜行われる。
【００２６】
検査測定手段２０は、産業プラント１０における設備の検査箇所を検査し、所定の検査項目を測定する。例えば、配管の点検箇所における肉厚を測定する。検査測定手段２０により検査測定は、産業プラント１０の運転を中止する必要があるので、決められた周期、例えば、２年に１回、４年に１回のような頻度で行う。
【００２７】
管理手段２２は、検査測定手段２０による検査測定値と、予測手段１８による推定腐食速度とに基づいて、将来における設備の腐食度合いの見込みを求め、それに基づいて設備の管理を行う。
【００２８】
（配管を管理する設備管理システム）
本実施形態の設備管理システムの具体例として配管を管理する場合について図３乃至図６を用いて説明する。
【００２９】
設備の腐食損傷速度は、プロセス条件の変動により変化する場合が多く、プロセス条件の変動を余寿命予測に反映し、設備検査の長期計画又は年度計画を適切に修正することが重要である。プロセスデータの採取とその評価は重要な作業となる。
【００３０】
プロセス条件の変動を余寿命予測に反映する方法として、腐食予測式又は寿命予測モデルを用いて行う。監視項目として取り扱うプロセスデータは、複数存在する場合が多く、また、設備の腐食速度に単位を変換する必要があり、腐食予測式が必要となる。腐食予測式設備の腐食速度が計算されることで、余寿命、検査時期が計算可能となる。
【００３１】
腐食予測式又は腐食予測モデルについては、例えば、腐食実験装置による実験データ等に基づいて作成する。実際の産業プラントの設備に腐食予測式又は腐食予測モデルを適用する場合、実験では取り扱えなかった流動状態や、実験と実際の設備の材質の違い、例えば、微量成分の混合比の違いなどの差異があり、推定誤差発生の要因となることがある。
【００３２】
そこで、本実施形態では、配管の肉厚推定を行う際に、設備検査データで得られた腐食速度を、腐食予測式又は腐食予測モデルの推定値によりチューニングする方法を採用する。
【００３３】
本実施形態による設備の寿命推定方法について図３及び図４を用いて説明する。本実施形態では、検査測定手段２０により予め定められた周期、例えば２年に１回の頻度で設備を検査するものとする。
【００３４】
まず、図３に示すように、設備の設置時に第１回検査として、検査測定手段２０により配管の肉厚（ｔａ１［ｍｍ］）を測定する。その後、予め定められた周期である２年後に、第２回検査として検査測定手段２０により配管の肉厚（ｔａ２［ｍｍ］）を測定する。
【００３５】
第１回検査時の肉厚の測定値（ｔａ１［ｍｍ］）と第２回検査時の肉厚の測定値（ｔａ２［ｍｍ］）から、設備検査データによる腐食速度ＣＲａ１［ｍｍ／ｙｅａｒ］は、次式のようになる。
【００３６】
ＣＲａ１＝（ｔａ２ − ｔａ１）／Ｔ［ｍｍ／ｙｅａｒ］
ただし、Ｔ：検査周期（２［ｙｅａｒ］）
この腐食速度ＣＲａ１に基づいて、図３に示すように、設備検査データによる寿命推定カーブを得る。
【００３７】
一方、第２回検査時に、設備検査データによる腐食速度の計算とは別個に、予測手段１８により、プロセスデータサーバ１６に蓄積されたプロセスデータに基づいて腐食メカニズム等を考慮した予測モデルにしたがって設備の腐食速度推定値（ＣＲｓ１［ｍｍ／ｙｅａｒ］）を求めておく。すなわち、温度、圧力、流速等の運転データと腐食因子濃度データからなるプロセスデータを、文献等による腐食速度推定式又は腐食速度推定モデルを用いて、第１回検査時から第２回検査時の期間について腐食速度推定値（ＣＲｓ１［ｍｍ／ｙｅａｒ］）を求める。
【００３８】
第２回検査時以降は、２年後の第３回検査時までは肉厚の測定ができないので、その間については肉厚を推定することになる。
【００３９】
推定時に、予測手段１８により、プロセスデータサーバ１６に蓄積されたプロセスデータに基づいて腐食メカニズム等を考慮した予測モデルにしたがって設備の腐食速度推定値（ＣＲｓ２［ｍｍ／ｙｅａｒ］）を求める。そして、本具体例では、次式により、推定時の肉厚（ｔｓ２［ｍｍ］）を求める。
【００４０】
ｔｓ２＝ｔａ２ −ＣＲａ１（ＣＲｓ２／ＣＲｓ１）×ｔ
ただし、ｔ：第２回検査時から予測時までの経過時間［ｙｅａｒ］
この推定肉厚（ｔｓ２）が、予め決められた取り替え基準肉厚（ｔｚ）に達した場合は配管の寿命と判断して、配管全体又は同様な劣化が想定される配管を取り替える。
【００４１】
本実施形態では、上式のように、設備検査データによる腐食速度（ＣＲａ１）を基本的には腐食速度の基準とし、それを第２回検査時の腐食速度推定値に対する推定時の腐食速度推定値の比により修正したものを腐食速度とみなし、それに基づいて肉厚変化を推定する点に特徴がある。
【００４２】
推定時の腐食速度推定値（ＣＲｓ２）をそのまま用いて推定した場合、プロセスデータや腐食メカニズムの選択が適切でない場合には、その誤差がそのまま推定肉厚（ｔｓ２）に反映してしまうので、望ましくない。
【００４３】
それに対し、本実施形態では、過去の腐食速度推定値に対する現在の腐食速度推定値の比により設備検査データによる腐食速度を修正するようにしているので、仮に、プロセスデータや腐食メカニズムの選択が適切でなく腐食速度推定値に誤差が生じたとしても、その誤差は腐食速度推定値の比を用いることで相殺されることになる。
【００４４】
次に、図４に示すように、第２回検査時から２年を経過すると第３回検査が行われる。第３回検査時には検査測定手段２０により配管の肉厚（ｔａ３［ｍｍ］）を測定する。
【００４５】
第２回検査時の肉厚の測定値（ｔａ２［ｍｍ］）と第３回検査時の肉厚の測定値（ｔａ３［ｍｍ］）から、設備検査データによる腐食速度ＣＲａ２［ｍｍ／ｙｅａｒ］は、次式のようになる。
【００４６】
ＣＲａ２＝（ｔａ３ − ｔａ２）／Ｔ［ｍｍ／ｙｅａｒ］
ただし、Ｔ：検査周期（２［ｙｅａｒ］）
この腐食速度ＣＲａ２に基づいて、図４に示すように、設備検査データによる寿命推定カーブを得る。
【００４７】
一方、第３回検査時に、設備検査データによる腐食速度の計算とは別個に、予測手段１８により、プロセスデータサーバ１６に蓄積されたプロセスデータに基づいて腐食メカニズム等を考慮した予測モデルにしたがって設備の腐食速度推定値（ＣＲｓ３［ｍｍ／ｙｅａｒ］）を求めておく。すなわち、温度、圧力、流速等の運転データと腐食因子濃度データからなるプロセスデータを、文献等による腐食速度推定式又は腐食速度推定モデルを用いて、第２回検査時から第３回検査時の期間について、腐食速度推定値（ＣＲｓ３［ｍｍ／ｙｅａｒ］）を求める。
【００４８】
第３回検査時以降は、２年後の第４回検査時までは肉厚の測定ができないので、その間については肉厚を推定することになる。
【００４９】
推定時に、予測手段１８により、プロセスデータサーバ１６に蓄積されたプロセスデータに基づいて腐食メカニズム等を考慮した予測モデルにしたがって設備の腐食速度推定値（ＣＲｓ４［ｍｍ／ｙｅａｒ］）を求める。そして、本具体例では、次式により、推定時の肉厚（ｔｓ４［ｍｍ］）を求める。
【００５０】
ｔｓ４＝ｔａ３ −ＣＲａ１（ＣＲｓ４／ＣＲｓ３）×ｔ
又は、
ｔｓ４＝ｔａ３ −ＣＲａ１（ＣＲｓ４／ＣＲｓ２）×ｔ
又は、
ｔｓ４＝ｔａ３ −ＣＲａ１（ＣＲｓ４／ＣＲｓ１）×ｔ
又は、
ｔｓ４＝ｔａ３ −ＣＲａ２（ＣＲｓ４／ＣＲｓ３）×ｔ
又は、
ｔｓ４＝ｔａ３ −ＣＲａ２（ＣＲｓ４／ＣＲｓ２）×ｔ
又は、
ｔｓ４＝ｔａ３ −ＣＲａ２（ＣＲｓ４／ＣＲｓ１）×ｔ
ただし、ｔ：第３回検査時から予測時までの経過時間［ｙｅａｒ］
この推定肉厚（ｔｓ４）が、予め決められた取り替え基準肉厚（ｔｚ）に達した場合は配管の寿命と判断して、配管全体又は同様な劣化が想定される配管を取り替える。
【００５１】
本実施形態では、上式のように、設備検査データによる腐食速度（ＣＲａ１又はＣＲａ２）を基本的には腐食速度の基準とし、それを過去の腐食速度推定値（ＣＲｓ３、ＣＲｓ２、又はＣＲｓ１）に対する推定時の腐食速度推定値（ＣＲｓ４）の比により修正したものを腐食速度とみなし、それに基づいて肉厚変化を推定している。これにより、プロセスデータや腐食メカニズムの選択が適切でなく、仮に、腐食速度推定値に誤差が生じたとしても、その誤差は腐食速度推定値の比を用いることで相殺されることになる。
【００５２】
なお、設備検査データによる腐食速度として、第１回検査時の肉厚の測定値（ｔａ１［ｍｍ］）と第３回検査時の肉厚の測定値（ｔａ３［ｍｍ］）から、次式により、設備検査データによる腐食速度ＣＲａ３［ｍｍ／ｙｅａｒ］を求める。
【００５３】
ＣＲａ３＝（ｔａ３ − ｔａ１）／２Ｔ［ｍｍ／ｙｅａｒ］
ただし、Ｔ：検査周期（２［ｙｅａｒ］）
この腐食速度ＣＲａ３を、腐食速度ＣＲａ２の代わりに用いてもよい。
【００５４】
図５に、比較例として、推定時の腐食速度推定値をそのまま用いて推定した場合について説明する。
【００５５】
第２回検査時以降は、２年後の第３回検査時までは肉厚の測定ができないので、その間については肉厚を推定することになる。推定時に、予測手段１８により、プロセスデータサーバ１６に蓄積されたプロセスデータに基づいて腐食メカニズム等を考慮した予測モデルに従って設備の腐食速度推定値（ＣＲｓ２［ｍｍ／ｙｅａｒ］）を求める。そして、本比較例では、次式により、推定時の肉厚（ｔｓ２［ｍｍ］）を求める。
【００５６】
ｔｓ２＝ｔａ２ −ＣＲｓ２ ×ｔ
ただし、ｔ：第２回検査時から予測時までの経過時間［ｙｅａｒ］
この推定肉厚（ｔｓ２）が、予め決められた取り替え基準肉厚（ｔｚ）に達した場合は配管の寿命と判断して、配管全体又は同様な劣化が想定される配管を取り替える。
【００５７】
しかしながら、本比較例では、推定時の腐食速度推定値（ＣＲｓ２）をそのまま用いて推定しているので、プロセスデータや腐食メカニズムの選択が適切でない場合には、その誤差がそのまま推定肉厚（ｔｓ２）に反映してしまうことになる。
【００５８】
図６は、ある設備の配管について、ある検査時以降について１か月毎に、本実施形態による推定肉厚と、比較例による推定肉厚を求めたものである。本実施形態による推定肉厚を実線で示し、比較例による推定肉厚を波線で示している。更に、その配管の肉厚についてほぼ１か月毎に検査した測定値もあわせて図６に示す。図６から明らかなように、本実施形態による推定肉厚の方が、比較例による推定肉厚よりも、肉厚の実測値に適合していることがわかる。
【００５９】
本発明は上記実施形態に限らず種々の変形が可能である。例えば、上記実施形態では、予測手段の学習ツールとして、ＮＮ（ニューラルネットワーク）やＴＣＢＭ（ＴｏｐｏｌｏｇｉｃａｌＣａｓｅＢａｓｅｄＭｏｄｅｌｉｎｇ）を用いたが、他の学習ツールを用いてもよい。
【００６０】
また、上記実施形態では、配管の肉厚を推測することにより配管の管理する場合について説明したが、設備として配管以外のものを管理する場合にも本発明を適用できることはいうまでもない。
【００６１】
【発明の効果】
以上の通り、本発明によれば、設備の劣化を測定する測定手段と、設備の劣化をプロセスデータに基づいて予測する予測手段とを設け、設備の劣化検査を行う第１の時点で、前記測定手段により設備の劣化を測定し、前記第１の時点以降の設備の劣化予測を行う第２の時点で、前記予測手段により設備の劣化を予測し、前記第１の時点での設備の劣化測定値を、過去の時点での設備の劣化予測値に対する今回の時点での設備の劣化予測値の比に基づいて修正し、その修正した修正値に基づいて設備を管理するようにしたので、産業プラントの処理量や処理内容等の変化に適応して、設備の劣化状態を適切に予測し、事故を招くことなく、しかも、無駄のない設備の保守や交換を行うことができる。
【図面の簡単な説明】
【図１】産業プラントにおける設備管理の基本的な考え方についての説明図である。
【図２】本発明の一実施形態による設備管理システムの構成を示す図である。
【図３】本発明の一実施形態による配管の肉厚推定方法の説明図（その１）である。
【図４】本発明の一実施形態による配管の肉厚推定方法の説明図（その２）である。
【図５】比較例による配管の肉厚推定方法の説明図である。
【図６】本発明の一実施形態による配管の推定肉厚と比較例による配管の推定肉厚と配管の肉厚測定値とを示すグラフである。
【図７】従来の設備管理方法による配管の肉厚推定方法の説明図である。
【符号の説明】
１０…産業プラント
１２…オンライン計測器
１４…プロセス試料分析器
１６…プロセスデータサーバ
１８…予測手段
２０…検査測定手段
２２…管理手段[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to an equipment management method and equipment management apparatus for managing equipment in an industrial plant such as a petroleum refining plant or a petrochemical plant, and particularly to equipment such as pipes, towers, tanks, and reaction vessels using a corrosive fluid. TECHNICAL FIELD The present invention relates to a facility management method and a facility management apparatus that predict deterioration of a device and issue a warning for maintenance or replacement of the facility.
[0002]
[Prior art]
Proper management of equipment in an industrial plant such as a petroleum refining plant or a petrochemical plant is important for preventing accidents in the equipment and maintaining the equipment for a long time. In particular, in an industrial plant using a corrosive fluid, it is important to periodically inspect the equipment to check for any abnormalities, replace necessary parts as necessary, and maintain the equipment.
[0003]
In the conventional equipment management method, when inspecting equipment, the degree of deterioration is determined for inspection points such as predetermined pipes, towers, tanks, and reaction vessels, and the deterioration state of the equipment is determined based on the measured values. I am trying to do it. For example, in the case of a pipe, an inspection point where deterioration of the pipe appears remarkably is set in advance, and the thickness of the predetermined inspection point is measured. When the wall thickness reaches a predetermined replacement reference value, it is determined that the replacement time has come, and the entire pipe or a pipe in which similar deterioration is predicted is replaced.
[0004]
In another conventional equipment management method, the degree of deterioration is measured at a predetermined cycle in order to estimate the replacement time of equipment, and the life of the equipment is predicted based on the measured value. For example, in the case of piping, as shown in FIG. 7, the thickness of the inspection location where deterioration of the piping is noticeable is measured at predetermined intervals from the time of installation of the piping, for example, at an inspection time every year. A deterioration curve is estimated from a plurality of measured values of the wall thickness of the pipe by a least square method or the like. When the replacement reference value is reached from the deterioration curve, that is, the service life of the pipe is estimated, and when the service life estimation time comes, the entire pipe or a pipe whose similar deterioration is predicted is replaced.
[0005]
[Patent Document 1]
JP-A-6-18514
[Problems to be solved by the invention]
Inspection of equipment in an industrial plant is a major task and requires a large number of people and costs. Then, depending on the inspection location, the operation itself of the industrial plant must be temporarily stopped. For this reason, it is difficult to inspect the equipment frequently, and the inspection is performed at most once a year or once every two years.
[0007]
Therefore, the conventional method of actually measuring the deterioration state of the equipment and judging the replacement time of the equipment from the measured value may cause the replacement of the equipment to be too late. There is no choice but to determine the replacement time in consideration of the safety factor, which may lead to unnecessary replacement of equipment.
[0008]
In addition, in the conventional method of estimating a deterioration curve from a measured value of the deterioration state of the equipment and estimating the life of the equipment from the deterioration curve, it is possible to estimate the life of the equipment without actually inspecting the equipment. . However, the processing amount and processing contents in the industrial plant are appropriately changed as necessary, and a large load may be applied to the equipment, or the load on the equipment may be reduced. For this reason, the deterioration of the equipment may progress more than the deterioration curve predicted by the conventional method, or the deterioration of the equipment may not progress.
[0009]
Therefore, in the conventional method of estimating the deterioration curve from the measured value of the deterioration state of the equipment and estimating the life of the equipment from the deterioration curve, there is a possibility that the replacement of the equipment may be delayed, and in order to prevent it, The replacement time must be determined in anticipation of a sufficient safety factor, which may lead to unnecessary equipment replacement. Further, unnecessary equipment replacement may be performed even though the deterioration of the equipment has not progressed, and there has been a demand for a management method capable of performing maintenance and replacement of the equipment at an appropriate time.
[0010]
SUMMARY OF THE INVENTION An object of the present invention is to appropriately predict a deterioration state of equipment by adapting to a change in a throughput or a processing content of an industrial plant, and to perform maintenance and replacement of equipment without causing an accident and without waste. An object of the present invention is to provide a facility management method and apparatus capable of performing the above.
[0011]
[Means for Solving the Problems]
An equipment management method according to the present invention is a equipment management method for predicting equipment deterioration and managing equipment based on the prediction, wherein a measuring means for measuring equipment deterioration, and equipment deterioration based on process data. At a first point in time when a deterioration inspection of the equipment is performed at the first point in time when the deterioration of the equipment is measured by the measuring means, and at a second point in time when the deterioration of the equipment is predicted after the first point in time. Predicting the deterioration of the equipment by the prediction means, and calculating the deterioration measurement value of the equipment at the first time to the ratio of the predicted deterioration value of the equipment at the current time to the predicted deterioration value of the equipment at a past time. Based on the corrected value, the equipment is managed based on the corrected value, so that it is possible to appropriately predict the deterioration state of the equipment, Without inviting and lean It is possible to perform the Bei of maintenance or replacement.
[0012]
An equipment management method according to the present invention is a equipment management method for predicting equipment deterioration and managing equipment based on the prediction, wherein a measuring means for measuring equipment deterioration, and equipment deterioration based on process data. At a first point in time when a deterioration inspection of the equipment is performed at the first point in time when the deterioration of the equipment is measured by the measuring means, and at a second point in time when the deterioration of the equipment is predicted after the first point in time. Predicting the deterioration of the equipment by the prediction means, and calculating the deterioration measurement value of the equipment at the first time to the ratio of the predicted deterioration value of the equipment at the current time to the predicted deterioration value of the equipment at a past time. Based on the corrected value, manage the equipment based on the corrected value, and at a third point in time to perform a deterioration inspection of the equipment after the second time, measure the deterioration of the equipment by the measuring means, Updating the deterioration measurement value and starting from the third time point At a fourth point in time when the deterioration prediction of the equipment is performed, the prediction means predicts the deterioration of the equipment, and the measured deterioration value of the equipment at the third time point is compared with the predicted deterioration value of the equipment at the past time. Corrected based on the ratio of the predicted deterioration value of the equipment at the point of time, and the equipment was managed based on the corrected correction value, so that it was adapted to changes in the processing amount and processing content of the industrial plant, The deterioration state of the equipment can be appropriately predicted, and the maintenance and replacement of the equipment can be performed without causing an accident and without waste.
[0013]
An equipment management apparatus according to the present invention is a equipment management apparatus that predicts deterioration of equipment and manages equipment based on the prediction, and includes a measurement unit that measures deterioration of equipment, and a method that measures deterioration of equipment based on process data. At a first point in time when a deterioration inspection of the equipment is performed, and at a second point in time when the deterioration of the equipment is measured by the measurement unit and the deterioration of the equipment is predicted after the first point in time. The prediction means predicts the deterioration of the equipment, and the measured value of the deterioration of the equipment at the first time is based on the ratio of the predicted value of the deterioration of the equipment at the current time to the predicted value of the deterioration of the equipment at a past time. It has a management means for correcting and managing the equipment based on the corrected value, so that it can appropriately predict the deterioration state of the equipment, Without inviting, and useless It is possible to perform equipment maintenance or replacement.
[0014]
An equipment management apparatus according to the present invention is a equipment management apparatus that predicts deterioration of equipment and manages equipment based on the prediction, and includes a measurement unit that measures deterioration of equipment, and a method that measures deterioration of equipment based on process data. At a first point in time when a deterioration inspection of the equipment is performed, and at a second point in time when the deterioration of the equipment is measured by the measurement unit and the deterioration of the equipment is predicted after the first point in time. The prediction means predicts the deterioration of the equipment, and the measured value of the deterioration of the equipment at the first time is based on the ratio of the predicted value of the deterioration of the equipment at the current time to the predicted value of the deterioration of the equipment at a past time. At a third point in time when the equipment is corrected, the equipment is managed based on the corrected value, and the equipment is inspected for deterioration after the second time, the deterioration of the equipment is measured by the measuring means, and the deterioration of the equipment is measured. Update the value and set the values after the third time point. At a fourth point in time when the deterioration of the equipment is predicted by the prediction means, and the measured deterioration value of the equipment at the third time point is compared to the estimated deterioration value of the equipment at a previous time point at the current time point. And the management means for managing the equipment based on the corrected value of the deterioration of the equipment. It is possible to appropriately predict the deterioration state of the equipment and perform maintenance and replacement of the equipment without causing an accident and without waste.
[0015]
BEST MODE FOR CARRYING OUT THE INVENTION
An equipment management system according to an embodiment of the present invention will be described with reference to FIGS.
[0016]
The object managed by the equipment management system according to the present embodiment is, for example, equipment in an industrial plant such as a petroleum refining plant or a petrochemical plant. The equipment includes, for example, pipes, towers, tanks, reaction vessels, and the like. In this industrial plant, when refining or producing gasoline, kerosene, light oil, heavy oil, or the like, a corrosive fluid such as hydrogen sulfide (H ₂ S), hydrochloric acid (HCl), ammonia (NH ₃ ), or the like is used. Therefore, dealing with equipment corrosion is an important issue.
[0017]
(Basic concept of equipment management)
The basic concept of equipment management in an industrial plant will be described with reference to FIG.
[0018]
First, formulate basic guidelines for corrosion control. Assuming a corrosion mechanism in an industrial plant, an operation specification is determined based on the corrosion mechanism. The factors that accelerate corrosion are listed as monitoring items, and a sample of the process fluid sample is analyzed using an online instrument during operation. The equipment is monitored based on the analysis results. For the factors that accelerate corrosion, some limit values are set, and the operation specifications are determined so as not to exceed the limit values.
[0019]
In addition, equipment inspection specifications are determined based on the basic policy of corrosion control. The equipment inspection specifications include, for example, an inspection part (where to inspect), an inspection method (how to inspect), an inspection cycle (how often the inspection is performed), and the like.
[0020]
Determine maintenance management based on basic guidelines for corrosion management. In maintenance management, a long-term maintenance plan is created, and an annual plan is formulated based on the long-term plan. Conduct specific equipment inspections based on the annual plan. The remaining life of the equipment is evaluated based on the inspection results. Based on the evaluation result of the remaining life of the equipment, it is determined whether or not the maintenance management procedure should be revised, and if necessary, the long-term maintenance plan and annual plan of the maintenance management are revised.
[0021]
Furthermore, operation management is determined based on the basic policy of corrosion management. In operation management, process data during operation, such as temperature, pressure, flow rate, hydrogen sulfide (H ₂ S) concentration, hydrochloric acid (HCl) concentration, and ammonia (NH ₃ ) concentration, are acquired. Further, based on the inspection specification, the inspection data, for example, the wall thickness of the pipe, is acquired at predetermined intervals. Based on the process data and the inspection data acquired in this way, the future deterioration of the equipment is predicted.
[0022]
(Facility management system)
The equipment management system according to the present embodiment will be described with reference to FIG.
[0023]
An industrial plant 10 such as a petroleum refining plant or a petrochemical plant is provided with facilities (not shown) such as pipes, towers, tanks, and reaction vessels. In the industrial plant 10, corrosive fluids such as hydrogen sulfide (H ₂ S), hydrochloric acid (HCl), and ammonia (NH ₃ ) are used, and management for responding to deterioration of equipment, for example, corrosion is required. It is.
[0024]
During operation of the industrial plant 10, operation data such as fluid flow rate, fluid temperature, fluid pressure and the like are acquired by the online measuring device 12, and corrosion factors (hydrogen sulfide (H ₂ S), Sample data such as the concentration of hydrochloric acid (HCl), ammonia (NH ₃ ), etc. is obtained. Operation data from the online meter 12 and sample data from the process fluid sample analyzer 14 are stored in a process data server 16.
[0025]
The prediction means 18 uses a learning tool such as NN (Neural Network) or TCBM (Topological Case Based Modeling: a non-linear modeling method using case-based reasoning), and based on the process data stored in the process data server 16, Estimate the corrosion rate of the equipment according to a prediction model that considers the mechanism. For example, the corrosion rate of the pipe thickness is estimated. The estimation of the corrosion rate by the predicting means 18 is appropriately performed as necessary because the operation of the industrial plant 10 does not need to be stopped.
[0026]
The inspection / measurement unit 20 inspects an inspection location of equipment in the industrial plant 10 and measures a predetermined inspection item. For example, the thickness of the pipe at the inspection point is measured. Since the inspection and measurement by the inspection and measurement means 20 needs to stop the operation of the industrial plant 10, the inspection and measurement are performed at a predetermined cycle, for example, once every two years or once every four years.
[0027]
The management unit 22 obtains a prospect of the degree of corrosion of the facility in the future based on the inspection measurement value by the inspection and measurement unit 20 and the estimated corrosion rate by the prediction unit 18, and manages the facility based thereon.
[0028]
(Equipment management system for managing piping)
A case of managing pipes as a specific example of the equipment management system of the present embodiment will be described with reference to FIGS.
[0029]
The corrosion damage rate of equipment often changes due to the change in process conditions, and it is important to reflect the change in process conditions in the estimation of the remaining life and appropriately modify the long-term plan or annual plan of the equipment inspection. The collection and evaluation of process data is an important task.
[0030]
As a method of reflecting the change in the process condition in the prediction of the remaining life, a method of predicting corrosion or a life prediction model is used. In many cases, a plurality of process data handled as monitoring items exist, and it is necessary to convert the unit into the corrosion rate of the equipment, and a corrosion prediction formula is required. By calculating the corrosion rate of the corrosion prediction type equipment, the remaining life and the inspection time can be calculated.
[0031]
The corrosion prediction formula or the corrosion prediction model is created based on, for example, experimental data obtained by a corrosion test apparatus. When applying the corrosion prediction formula or corrosion prediction model to actual industrial plant equipment, differences in flow conditions that could not be handled in experiments, differences in materials between experiments and actual equipment, such as differences in the mixing ratio of trace components, etc. And may cause an estimation error.
[0032]
Thus, in the present embodiment, when estimating the wall thickness of the pipe, a method is adopted in which the corrosion rate obtained from the equipment inspection data is tuned by an estimated value of a corrosion prediction formula or a corrosion prediction model.
[0033]
A method for estimating the service life of equipment according to the present embodiment will be described with reference to FIGS. In the present embodiment, the equipment is inspected at a predetermined cycle by the inspection and measurement means 20, for example, once every two years.
[0034]
First, as shown in FIG. 3, the thickness (ta1 [mm]) of the pipe is measured by the inspection and measurement means 20 as a first inspection when the equipment is installed. Thereafter, two years after a predetermined cycle, the thickness of the pipe (ta2 [mm]) is measured by the inspection and measurement means 20 as a second inspection.
[0035]
From the measured value of the thickness at the first inspection (ta1 [mm]) and the measured value of the thickness at the second inspection (ta2 [mm]), the corrosion rate CRa1 [mm / year] according to the equipment inspection data is obtained. Is as follows:
[0036]
CRa1 = (ta2-ta1) / T [mm / year]
Here, T: inspection cycle (2 [year])
Based on the corrosion rate CRa1, a life estimation curve based on the equipment inspection data is obtained as shown in FIG.
[0037]
On the other hand, at the time of the second inspection, separately from the calculation of the corrosion rate based on the equipment inspection data, the prediction means 18 sets the equipment according to a prediction model in which the corrosion mechanism and the like are considered based on the process data stored in the process data server 16. Of the corrosion rate (CRs1 [mm / year]) is obtained in advance. That is, process data consisting of operating data such as temperature, pressure, flow rate and the like and corrosion factor concentration data are converted from the first inspection to the second inspection using a corrosion rate estimation formula or a corrosion rate estimation model according to literatures. An estimated corrosion rate (CRs1 [mm / year]) is obtained for the period.
[0038]
Since the thickness cannot be measured after the second inspection until the third inspection two years later, the thickness is estimated during that time.
[0039]
At the time of estimation, the prediction means 18 obtains an estimated corrosion rate (CRs2 [mm / year]) of the equipment based on the process data stored in the process data server 16 in accordance with a prediction model that takes into account the corrosion mechanism and the like. Then, in this specific example, the thickness (ts2 [mm]) at the time of estimation is obtained by the following equation.
[0040]
ts2 = ta2−CRa1 (CRs2 / CRs1) × t
Here, t: elapsed time from the time of the second inspection to the time of the prediction [year]
When the estimated thickness (ts2) reaches a predetermined replacement reference thickness (tz), the life of the pipe is determined, and the entire pipe or a pipe in which similar deterioration is assumed is replaced.
[0041]
In this embodiment, as shown in the above equation, the corrosion rate (CRa1) based on the equipment inspection data is basically used as a reference for the corrosion rate, and the corrosion rate is estimated based on the corrosion rate estimated value in the second inspection. The characteristic is that the value corrected by the value ratio is regarded as the corrosion rate, and the change in wall thickness is estimated based on the rate.
[0042]
If the estimation is made using the estimated corrosion rate (CRs2) as it is, if the process data or the corrosion mechanism is not properly selected, the error is directly reflected in the estimated wall thickness (ts2). Absent.
[0043]
On the other hand, in the present embodiment, the corrosion rate based on the equipment inspection data is corrected based on the ratio of the current corrosion rate estimation value to the past corrosion rate estimation value. However, if an error occurs in the estimated corrosion rate, the error will be offset by using the ratio of the estimated corrosion rate.
[0044]
Next, as shown in FIG. 4, the third inspection is performed two years after the second inspection. At the time of the third inspection, the thickness (ta3 [mm]) of the pipe is measured by the inspection measuring means 20.
[0045]
From the thickness measurement value (ta2 [mm]) at the second inspection and the thickness measurement value (ta3 [mm]) at the third inspection, the corrosion rate CRa2 [mm / year] according to the equipment inspection data is obtained. Is as follows:
[0046]
CRa2 = (ta3−ta2) / T [mm / year]
Here, T: inspection cycle (2 [year])
Based on the corrosion rate CRa2, a life estimation curve based on the equipment inspection data is obtained as shown in FIG.
[0047]
On the other hand, at the time of the third inspection, separately from the calculation of the corrosion rate based on the equipment inspection data, the prediction means 18 sets the equipment according to a prediction model in which the corrosion mechanism and the like are considered based on the process data stored in the process data server 16. Of the corrosion rate (CRs3 [mm / year]) is determined in advance. That is, process data consisting of operating data such as temperature, pressure, and flow rate and corrosion factor concentration data are converted from the second inspection to the third inspection using a corrosion rate estimation formula or a corrosion rate estimation model according to literatures. For the period, an estimated corrosion rate (CRs3 [mm / year]) is determined.
[0048]
Since the thickness cannot be measured after the third inspection until the fourth inspection two years later, the thickness is estimated during that period.
[0049]
At the time of estimation, the prediction means 18 obtains an estimated corrosion rate (CRs4 [mm / year]) of the equipment based on the process data stored in the process data server 16 according to a prediction model that considers the corrosion mechanism and the like. Then, in this specific example, the thickness (ts4 [mm]) at the time of estimation is obtained by the following equation.
[0050]
ts4 = ta3−CRa1 (CRs4 / CRs3) × t
Or
ts4 = ta3−CRa1 (CRs4 / CRs2) × t
Or
ts4 = ta3−CRa1 (CRs4 / CRs1) × t
Or
ts4 = ta3−CRa2 (CRs4 / CRs3) × t
Or
ts4 = ta3−CRa2 (CRs4 / CRs2) × t
Or
ts4 = ta3−CRa2 (CRs4 / CRs1) × t
Here, t: elapsed time from the third inspection to the prediction time [year]
When the estimated thickness (ts4) reaches a predetermined replacement reference thickness (tz), the life of the pipe is determined, and the entire pipe or a pipe in which similar deterioration is assumed is replaced.
[0051]
In this embodiment, as shown in the above equation, the corrosion rate (CRa1 or CRa2) based on the equipment inspection data is basically used as a reference for the corrosion rate, and is used as a reference for the past corrosion rate estimated value (CRs3, CRs2, or CRs1). The value corrected by the ratio of the estimated corrosion rate (CRs4) at the time of estimation is regarded as the corrosion rate, and the thickness change is estimated based on the corrected rate. As a result, even if the selection of the process data or the corrosion mechanism is not appropriate, and even if an error occurs in the corrosion rate estimation value, the error is canceled by using the ratio of the corrosion rate estimation value.
[0052]
In addition, as the corrosion rate based on the equipment inspection data, from the measured value of the thickness at the first inspection (ta1 [mm]) and the measured value of the thickness at the third inspection (ta3 [mm]), And the corrosion rate CRa3 [mm / year] based on the equipment inspection data.
[0053]
CRa3 = (ta3-ta1) / 2T [mm / year]
Here, T: inspection cycle (2 [year])
This corrosion rate CRa3 may be used instead of the corrosion rate CRa2.
[0054]
FIG. 5 illustrates, as a comparative example, a case where the estimation is performed using the estimated corrosion rate value at the time of estimation as it is.
[0055]
Since the thickness cannot be measured after the second inspection until the third inspection two years later, the thickness is estimated during that time. At the time of estimation, the prediction means 18 obtains an estimated corrosion rate (CRs2 [mm / year]) of the equipment based on the process data stored in the process data server 16 according to a prediction model that considers a corrosion mechanism and the like. In this comparative example, the thickness at the time of estimation (ts2 [mm]) is obtained by the following equation.
[0056]
ts2 = ta2−CRs2 × t
Here, t: elapsed time from the time of the second inspection to the time of the prediction [year]
When the estimated thickness (ts2) reaches a predetermined replacement reference thickness (tz), the life of the pipe is determined, and the entire pipe or a pipe in which similar deterioration is assumed is replaced.
[0057]
However, in the present comparative example, the estimation is performed using the estimated corrosion rate value (CRs2) at the time of estimation. Therefore, if the selection of the process data or the corrosion mechanism is not appropriate, the error is directly reflected in the estimated thickness (ts2). ).
[0058]
FIG. 6 shows the estimated wall thickness according to the present embodiment and the estimated wall thickness according to a comparative example obtained every month after a certain inspection for a pipe of a certain facility. The estimated thickness according to the present embodiment is indicated by a solid line, and the estimated thickness according to the comparative example is indicated by a wavy line. FIG. 6 also shows the measured values of the thickness of the piping, which were inspected almost every month. As is clear from FIG. 6, the estimated thickness according to the present embodiment is more suitable for the actual measured value of the thickness than the estimated thickness according to the comparative example.
[0059]
The present invention is not limited to the above embodiment, and various modifications are possible. For example, in the above embodiment, NN (Neural Network) or TCBM (Topological Case Based Modeling) is used as a learning tool of the prediction means, but another learning tool may be used.
[0060]
Further, in the above embodiment, the case where the pipe is managed by estimating the wall thickness of the pipe has been described. However, it goes without saying that the present invention can also be applied to a case where something other than the pipe is managed as equipment.
[0061]
【The invention's effect】
As described above, according to the present invention, the measuring means for measuring the deterioration of the equipment and the predicting means for estimating the deterioration of the equipment based on the process data are provided. Deterioration of the equipment is measured by the measuring means, and the deterioration of the equipment is predicted by the predicting means at a second time when the deterioration of the equipment is predicted after the first time. Since the measured value was corrected based on the ratio of the predicted deterioration value of the equipment at this time to the predicted deterioration value of the equipment at the past time, the equipment was managed based on the corrected correction value, It is possible to appropriately predict the deterioration state of the equipment by adapting to changes in the processing amount and processing contents of the industrial plant, and perform maintenance and replacement of the equipment without causing an accident and without waste.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram of a basic concept of equipment management in an industrial plant.
FIG. 2 is a diagram showing a configuration of a facility management system according to an embodiment of the present invention.
FIG. 3 is an explanatory view (No. 1) of a pipe thickness estimation method according to an embodiment of the present invention.
FIG. 4 is an explanatory view (No. 2) of a pipe wall thickness estimation method according to an embodiment of the present invention.
FIG. 5 is an explanatory diagram of a pipe thickness estimation method according to a comparative example.
FIG. 6 is a graph showing an estimated wall thickness of a pipe according to an embodiment of the present invention and a measured wall thickness of the pipe according to a comparative example.
FIG. 7 is an explanatory diagram of a method of estimating a pipe wall thickness by a conventional facility management method.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 10 ... Industrial plant 12 ... On-line measuring instrument 14 ... Process sample analyzer 16 ... Process data server 18 ... Predicting means 20 ... Inspection measuring means 22 ... Managing means

Claims

An equipment management method for predicting deterioration of equipment and managing equipment based on the prediction,
Providing measurement means for measuring the deterioration of the equipment, and prediction means for predicting the deterioration of the equipment based on the process data,
At a first point in time when the equipment is inspected for deterioration, equipment deterioration is measured by the measuring means,
At a second time point at which the deterioration of the equipment is predicted after the first time point, the prediction means predicts the deterioration of the equipment, and the measured value of the deterioration of the equipment at the first time point is used as the equipment at the past time point. A correction method based on the ratio of the predicted deterioration value of the equipment at this time to the predicted deterioration value of the equipment, and managing the equipment based on the corrected correction value.

An equipment management method for predicting deterioration of equipment and managing equipment based on the prediction,
Providing measurement means for measuring the deterioration of the equipment, and prediction means for predicting the deterioration of the equipment based on the process data,
At a first point in time when the equipment is inspected for deterioration, equipment deterioration is measured by the measuring means,
At a second time point at which the deterioration of the equipment is predicted after the first time point, the prediction means predicts the deterioration of the equipment, and the measured value of the deterioration of the equipment at the first time point is used as the equipment at the past time point. Correction based on the ratio of the deterioration prediction value of the equipment at this time to the deterioration prediction value of the current time, managing the equipment based on the corrected correction value,
At a third time point for performing the deterioration inspection of the equipment after the second time point, the deterioration of the equipment is measured by the measuring means, and the measured deterioration value of the equipment is updated.
At a fourth time point at which the deterioration of the equipment is predicted after the third time point, the prediction means predicts the deterioration of the equipment, and the measured value of the deterioration of the equipment at the third time point is used as the equipment at the previous time point. A correction method based on the ratio of the predicted deterioration value of the equipment at this time to the predicted deterioration value of the equipment, and managing the equipment based on the corrected correction value.

An equipment management device that predicts deterioration of equipment and manages equipment based on the prediction,
Measuring means for measuring the deterioration of the equipment;
Prediction means for predicting equipment deterioration based on process data;
At a first point in time when equipment deterioration inspection is performed, equipment deterioration is measured by the measurement means. At a second point in time when equipment deterioration prediction is performed after the first time point, equipment deterioration is estimated by the prediction means. Predicting and correcting the equipment deterioration measurement value at the first time based on the ratio of the equipment deterioration prediction value at this time to the equipment deterioration prediction value at a past time, and the corrected correction And a management means for managing the equipment based on the value.

An equipment management device that predicts deterioration of equipment and manages equipment based on the prediction,
Measuring means for measuring the deterioration of the equipment;
Prediction means for predicting equipment deterioration based on process data;
At a first point in time when equipment deterioration inspection is performed, equipment deterioration is measured by the measurement means. At a second point in time when equipment deterioration prediction is performed after the first time point, equipment deterioration is estimated by the prediction means. Predicting and correcting the equipment deterioration measurement value at the first time based on the ratio of the equipment deterioration prediction value at this time to the equipment deterioration prediction value at a past time, and the corrected correction Managing the equipment based on the values, at a third point in time performing the equipment deterioration inspection after the second time, measuring the equipment deterioration by the measuring means, updating the equipment deterioration measurement value, At a fourth time point at which the equipment deterioration is predicted after the third time point, the prediction means predicts the deterioration of the equipment, and the measured value of the equipment deterioration at the third time point is used as the deterioration time of the equipment at the past time point. Based on the ratio of the predicted value of equipment deterioration at this time to the predicted value, And, facility management apparatus characterized by comprising a managing means for managing the facilities based on the modified value thereof modified.

A first step of predicting the deterioration of the equipment by a prediction algorithm for predicting the deterioration of the equipment based on the process data at a second time of performing the deterioration prediction of the equipment after the first time of performing the deterioration inspection of the equipment;
A second step of correcting the equipment deterioration measurement value at the first time point based on a ratio of the equipment deterioration prediction value at the current time point to the equipment deterioration prediction value at a past time point. Program characterized by the following.