JP2011184121A5 - - Google Patents
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- JP2011184121A5 JP2011184121A5 JP2010049160A JP2010049160A JP2011184121A5 JP 2011184121 A5 JP2011184121 A5 JP 2011184121A5 JP 2010049160 A JP2010049160 A JP 2010049160A JP 2010049160 A JP2010049160 A JP 2010049160A JP 2011184121 A5 JP2011184121 A5 JP 2011184121A5
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Claims (18)
該イベント抽出部で抽出した複数のイベントの時系列データから構成される作業の、複数の時系列情報のサンプルを用いて、個々のイベントの内容とその滞在時間から、確率変数が変化する状態遷移の遷移確率密度関数を算出する学習部と、
一連の作業手順である正規作業手順について状態と遷移で示される作業グラフと、前記イベント抽出部で抽出したイベントデータの時系列情報とから、前記状態に対する事後確率を前記学習部で算出した遷移確率密度関数を用いて求める作業推定部と
と備えたことを特徴とする作業内容推定装置。 An event extraction unit that extracts event data with time when an electronic device such as a predetermined sensor satisfies a predetermined output condition;
State transition in which a random variable changes from the contents of each event and its stay time using a sample of a plurality of time-series information of work composed of time-series data of a plurality of events extracted by the event extraction unit A learning unit for calculating a transition probability density function of
Transition probabilities calculated by the learning unit for posterior probabilities for the state from a work graph indicated by states and transitions for a regular work procedure that is a series of work procedures and time series information of event data extracted by the event extraction unit A work content estimation device comprising: a work estimation unit for obtaining using a density function .
プル度数分布に対して乗じることで前記遷移確率密度関数を算出することを特徴とする請
求項１に記載の作業内容推定装置。 The learning unit calculates the transition probability density function by multiplying a coefficient obtained as a solution of the restricted optimization problem by a sample frequency distribution of each event stay time. The work content estimation apparatus described in 1.
在時間が複数サンプルの平均から所定以上のばらつきがあるときには、前記遷移確率密度
関数を０より大きい一定値とすることを特徴とする請求項１または２に記載の作業内容推
定装置。 The learning unit sets the transition probability density function to a constant value greater than 0 when the actual event stay time varies more than a predetermined value from the average of a plurality of samples with respect to the sample frequency distribution of each event stay time. The work content estimation apparatus according to claim 1, wherein the work content is estimated.
前記作業推定部に事後確率を求めさせるための作業候補を、前記作業グラフ中から選択す
る候補選択部を備えたことを特徴とする請求項１乃至３のいずれかに記載の作業内容推定
装置。 A candidate selection unit for selecting a work candidate for causing the work estimation unit to obtain a posterior probability from the work graph shown in the regular work procedure and a currently estimated work, from the work graph. The work content estimation apparatus according to claim 1, further comprising a work content estimation apparatus.
を用いて、前記作業推定部によって求められた事後確率が最大となる作業について、前記
事後確率が最大となる作業の事後確率が所定の閾値以下であった場合、前記候補選択部は
、前回選択した前記作業候補よりも多い作業候補を、前記作業グラフ中から選択すること
を特徴とする請求項４に記載の作業内容推定装置。 Using the task candidate for causing the task estimation unit selected by the candidate selection unit to determine the posterior probability, for the task having the maximum posterior probability determined by the task estimation unit, the posterior probability is maximum. The candidate selection unit selects, from the work graph, more work candidates than the previously selected work candidates when the posterior probability of the work to be performed is equal to or less than a predetermined threshold. Described work content estimation device.
をもつ前記作業グラフから、前記作業推定部によって求められた事後確率が最大となる作
業について、前記事後確率が最大となる作業の事後確率が所定の閾値以下であった場合、
または、所定の閾値を超えているが、前記作業グラフから現在推定されている作業と次の
作業との間が一つ遷移のみではなく、かつ前記作業グラフから現在推定されている作業か
ら次の作業へ到達できない場合は、手順誤りであると判定する作業判定部を備えたことを
特徴とする請求項１乃至５に記載の作業内容推定装置。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, the work having the maximum posterior probability obtained by the work estimation unit is the largest posterior probability. If the posterior probability of the work is less than a predetermined threshold,
Or, a predetermined threshold value is exceeded, but not only one transition between the work currently estimated from the work graph and the next work, and the next work from the work currently estimated from the work graph. 6. The work content estimation apparatus according to claim 1, further comprising a work determination unit that determines that a procedure error occurs when the work cannot be reached.
をもつ前記作業グラフから、前記作業推定部によって求められた事後確率が最大となる作
業について、前記事後確率が最大となる作業の事後確率は、所定の閾値を超えているが、
前記作業グラフから現在推定されている作業と次の作業との間が一つ遷移のみではなく、
前記作業グラフから現在推定されている作業から次の作業へ到達できる場合は、作業ぬけ
であると判定する作業判定部を備えたことを特徴とする請求項１乃至５に記載の作業内容
推定装置。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, the work having the maximum posterior probability obtained by the work estimation unit is the largest posterior probability. The posterior probability of the work that exceeds the predetermined threshold,
Not only one transition between the work currently estimated from the work graph and the next work,
6. The work content estimation apparatus according to claim 1, further comprising a work determination unit that determines that a work is skipped when the next work can be reached from the work currently estimated from the work graph. .
をもつ前記作業グラフから、前記作業推定部によって求められた事後確率が最大となる作
業について、前記事後確率が最大となる作業の事後確率は、所定の閾値を超えているが、
前記作業グラフから現在推定されている作業と次の作業とが重複する場合は、作業重複で
あると判定する作業判定部を備えたことを特徴とする請求項１乃至５に記載の作業内容推
定装置。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, the work having the maximum posterior probability obtained by the work estimation unit is the largest posterior probability. The posterior probability of the work that exceeds the predetermined threshold,
The work content estimation according to claim 1, further comprising: a work determination unit that determines that the work currently estimated from the work graph and the next work are duplicated. apparatus.
をもつ前記作業グラフから、前記作業推定部によって求められた事後確率が最大となる作
業について、前記事後確率が最大となる作業の事後確率は、所定の閾値を超えており、か
つ前記作業グラフから現在推定されている作業と次の作業との間が一つ遷移のみである場
合は、正常作業であると判定する作業判定部を備えたことを特徴とする請求項１乃至５に
記載の作業内容推定装置。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, the work having the maximum posterior probability obtained by the work estimation unit is the largest posterior probability. If the posterior probability of a given work exceeds a predetermined threshold and there is only one transition between the work currently estimated from the work graph and the next work, it is determined that the work is a normal work. The work content estimation apparatus according to claim 1, further comprising a work determination unit.
データを抽出するイベント抽出ステップと、
複数のイベントの時系列データから構成される作業の、複数の時系列情報のサンプルを
用いて、個々のイベントの内容とその滞在時間から、確率変数が変化する状態遷移の遷移確率密度関数を算出する学習ステップと、
一連の作業手順である正規作業手順について状態と遷移で示される作業グラフと、実際
のイベントデータの時系列情報とから、前記状態に対する事後確率を前記学習部で算出した遷移確率密度関数を用いて求める作業推定ステップと
を有することを特徴とする作業内容推定方法。 An event extraction step of extracting event data with time by an electronic device such as a predetermined sensor meeting a predetermined output condition;
Using a sample of multiple time-series information of work consisting of time-series data of multiple events, calculate the transition probability density function of state transitions with varying random variables from the content of each event and its stay time Learning steps to
Using the transition probability density function that the posterior probability for the state is calculated by the learning unit from the work graph indicated by the state and transition for the regular work procedure that is a series of work procedures and the time series information of the actual event data A work content estimation method comprising: a work estimation step to be obtained.
在時間のサンプル度数分布に対して乗じることで前記遷移確率密度関数を有することを特
徴とする請求項１０に記載の作業内容推定方法。 11. The transition probability density function according to claim 10, wherein, in the learning step, the transition probability density function is obtained by multiplying a coefficient obtained as a solution of the limited optimization problem by a sample frequency distribution of each event stay time. Described work content estimation method.
のイベント滞在時間が複数サンプルの平均から所定異常のばらつきがあるときには、前記
遷移確率密度関数を０より大きい一定値とすることを特徴とする請求項１０または１１に
記載の作業内容推定方法。 In the learning step, when the actual event stay time varies from the average of a plurality of samples to the sample frequency distribution of each event stay time, the transition probability density function is set to a constant value greater than zero. The work content estimation method according to claim 10 or 11, characterized in that:
前記作業推定部に事後確率を求めさせるための作業候補を、前記作業グラフ中から選択す
る候補選択ステップを有することを特徴とする請求項１０乃至１２のいずれかに記載の作
業内容推定方法。 A candidate selection step of selecting, from the work graph, a work candidate for causing the work estimation unit to obtain a posterior probability next from the work graph shown in the regular work procedure and the currently estimated work. 13. The work content estimation method according to claim 10, further comprising:
業候補を用いて、前記作業推定部によって求められた事後確率が最大となる作業について
、前記事後確率が最大となる作業の事後確率が所定の閾値以下であった場合、前記候補選
択部は、前回選択した前記作業候補よりも多い作業候補を、前記作業グラフ中から選択す
ることを特徴とする請求項１３に記載の作業内容推定方法。 Using the task candidate for causing the task estimation unit selected by the candidate selection step to determine the posterior probability, the task having the maximum posterior probability determined by the task estimation unit is the maximum posterior probability. The candidate selection unit selects, from the work graph, more work candidates than the previously selected work candidates when the posterior probability of the work to be performed is equal to or less than a predetermined threshold. Described work content estimation method .
をもつ前記作業グラフから、前記作業推定ステップによって求められた事後確率が最大と
なる作業について、前記事後確率が最大となる作業の事後確率が所定の閾値以下であった
場合、または、所定の閾値を超えているが、前記作業グラフから現在推定されている作業
と次の作業との間が一つ遷移のみではなく、かつ前記作業グラフから現在推定されている
作業から次の作業へ到達できない場合は、手順誤りであると判定する作業判定ステップを
有することを特徴とする請求項１０乃至１４に記載の作業内容推定方法。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, the work having the maximum posterior probability obtained by the work estimation step has the maximum posterior probability. If the posterior probability of the work is less than or equal to a predetermined threshold, or exceeds the predetermined threshold, the transition between the work currently estimated from the work graph and the next work is not only one transition The work content estimation according to claim 10, further comprising: a work determination step that determines that a procedure error occurs when the next work cannot be reached from the work currently estimated from the work graph. Method.
をもつ前記作業グラフから、前記事後確率が最大となる作業推定ステップによって求めら
れた事後確率が最大となる作業について、前記作業の事後確率は、所定の閾値を超えてい
るが、前記作業グラフから現在推定されている作業と次の作業との間が一つ遷移のみでは
なく、前記作業グラフから現在推定されている作業から次の作業へ到達できる場合は、作
業ぬけであると判定する作業判定ステップを有することを特徴とする請求項１０乃至１４
に記載の作業内容推定方法。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, for work that has the maximum posterior probability obtained by the work estimation step that maximizes the posterior probability, The posterior probability of the work exceeds a predetermined threshold, but the current work is estimated from the work graph as well as one transition between the work currently estimated from the work graph and the next work. 15. A work determination step for determining that the work is skipped when the work can reach the next work.
The work content estimation method described in 1.
をもつ前記作業グラフから前記作業推定ステップによって求められた事後確率が最大とな
る作業について、前記事後確率が最大となる作業の事後確率は、所定の閾値を超えている
が、前記作業グラフから現在推定されている作業と次の作業とが重複する場合は、作業重
複であると判定する作業判定ステップを有することを特徴とする請求項１０乃至１４に記
載の作業内容推定方法。 The posterior probability is maximized with respect to the work having the maximum posterior probability obtained by the work estimation step from the work graph having transitions having front-rear constraints that cannot be duplicated for the same work as indicated in the regular work procedure The posterior probability of work exceeds a predetermined threshold, but when the work currently estimated from the work graph overlaps with the next work, the work posterior probability includes a work determination step for determining that the work is duplicated. The work content estimation method according to claim 10, wherein the work content is estimated.
をもつ前記作業グラフから、前記作業推定ステップによって求められた事後確率が最大と
なる作業について、前記事後確率が最大となる作業の事後確率は、所定の閾値を超えてお
り、かつ前記作業グラフから現在推定されている作業と次の作業との間が一つ遷移のみで
ある場合は、正常作業であると判定する作業判定ステップを有することを特徴とする請求
項１０乃至１４に記載の作業内容推定方法。 From the work graph shown in the regular work procedure and having a transition having a front-rear constraint that cannot be duplicated for the same work, the work having the maximum posterior probability obtained by the work estimation step has the maximum posterior probability. If the posterior probability of a given work exceeds a predetermined threshold and there is only one transition between the work currently estimated from the work graph and the next work, it is determined that the work is a normal work. The work content estimation method according to claim 10, further comprising a work determination step.
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| JP2010049160A JP5463964B2 (en) | 2010-03-05 | 2010-03-05 | Work content estimation apparatus and work content estimation method |
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| JP2010049160A JP5463964B2 (en) | 2010-03-05 | 2010-03-05 | Work content estimation apparatus and work content estimation method |
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| JP2011184121A JP2011184121A (en) | 2011-09-22 |
| JP2011184121A5 true JP2011184121A5 (en) | 2012-10-18 |
| JP5463964B2 JP5463964B2 (en) | 2014-04-09 |
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Families Citing this family (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5930189B2 (en) * | 2012-05-25 | 2016-06-08 | 三菱電機ビルテクノサービス株式会社 | Maintenance work estimation device and maintenance work estimation method |
| JP6061811B2 (en) * | 2013-03-26 | 2017-01-18 | 三菱電機株式会社 | Data processing apparatus, data processing method, and program |
| JP6154542B2 (en) * | 2014-03-26 | 2017-06-28 | 株式会社日立製作所 | Time-series data management method and time-series data management system |
| JP6398879B2 (en) * | 2015-06-09 | 2018-10-03 | 三菱電機ビルテクノサービス株式会社 | Elevator work status monitoring device and work status monitoring method |
| JP6074079B1 (en) * | 2016-02-09 | 2017-02-01 | 東芝エレベータ株式会社 | Maintenance work safety device |
| JP6862844B2 (en) * | 2016-06-17 | 2021-04-21 | 株式会社リコー | Information processing systems, equipment, and programs |
| JP6787090B2 (en) * | 2016-12-02 | 2020-11-18 | 横河電機株式会社 | Maintenance management equipment, maintenance management methods, maintenance management programs and recording media |
| CN109484934B (en) * | 2017-09-11 | 2022-06-28 | 奥的斯电梯公司 | Tracking of maintenance trajectories for elevator systems |
| JP6950505B2 (en) * | 2017-12-08 | 2021-10-13 | 富士通株式会社 | Discrimination program, discrimination method and discrimination device |
| JP6369664B1 (en) * | 2017-12-20 | 2018-08-08 | 三菱電機ビルテクノサービス株式会社 | Elevator maintenance work support device and elevator maintenance work support system |
| EP3591521B1 (en) * | 2018-07-05 | 2023-07-26 | Honda Research Institute Europe GmbH | Assistance system, method, and program for assisting a user in fulfilling a task |
| JP7073596B2 (en) * | 2018-12-26 | 2022-05-24 | 株式会社ウィーブ | Bridal event video sales business management system, bridal event video sales business management method and bridal event video sales business management program |
| WO2021053738A1 (en) * | 2019-09-18 | 2021-03-25 | 三菱電機株式会社 | Work element analysis device and work element analysis method |
| JP7016454B2 (en) * | 2019-11-20 | 2022-02-04 | 三菱電機株式会社 | Judgment device, judgment method and judgment program |
| JP7401280B2 (en) * | 2019-12-06 | 2023-12-19 | ファナック株式会社 | Work process discrimination device and work process discrimination system |
| WO2021192084A1 (en) * | 2020-03-25 | 2021-09-30 | 株式会社日立製作所 | Work learning model generation device, work inference device, and work learning model generation method |
| US20230075705A1 (en) * | 2020-06-18 | 2023-03-09 | Mitsubishi Electric Corporation | Work support device and work support method |
| CN111717753A (en) * | 2020-06-29 | 2020-09-29 | 浙江新再灵科技股份有限公司 | Self-adaptive elevator fault early warning system and method based on multi-dimensional fault characteristics |
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| JP2003281297A (en) * | 2002-03-22 | 2003-10-03 | National Institute Of Advanced Industrial & Technology | Information presenting device and information presenting method |
| JP4474529B2 (en) * | 2004-11-29 | 2010-06-09 | 独立行政法人産業技術総合研究所 | Work status recording apparatus, recording method thereof, and recording program |
| JP2007328435A (en) * | 2006-06-06 | 2007-12-20 | Mitsubishi Electric Corp | Device fot analyzing mobile behavior |
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