Predictive control system and method for brown washing treatment in pulp mills

    公开(公告)号:US12077911B2

    公开(公告)日:2024-09-03

    申请号:US17097957

    申请日:2020-11-13

    CPC classification number: D21C3/228 D21C3/24 D21C9/02 D21C9/06 G01N33/343

    Abstract: A system and method are provided for predictive control of brown stock treatment at a pulp mill. Various online sensors generate output signals representative of actual values for respective process characteristics, each of which are directly or indirectly affected by adjustments to corresponding process variables. A controller uses the output signals or associated measurement data to dynamically set target values for the process characteristics based on a predicted impact of control responses for corresponding process variables. The controller further generates control signals to actuators associated with the respective process variables based on detected variations between the respective actual values and target values. Exemplary brown stock washing control systems may optimize various types of brown stock washing configurations, including for example vacuum drum washers, compaction baffle washers, chemiwashers, direct displacement washers and wash presses. Cloud-based analytics and machine learning may also be implemented to improve the control algorithms over time.

    Real time regulation of yankee dryer coating based on predicted natural coating transfer

    公开(公告)号:US10329715B2

    公开(公告)日:2019-06-25

    申请号:US15655545

    申请日:2017-07-20

    Abstract: A method is provided for decision support in regulating an adhesive coating applied to Yankee dryers. Online sensors are configured to continuously measure stock characteristics, and additional sensors provide actual stock flow rate and machine speed. A controller predicts potential natural coating application from a fibrous sheet generated from the stock to the Yankee dryer surface, substantially in real time, based on the measured characteristics and sensed actual machine values. An output signal may be provided to a display unit, wherein an optimal adhesive coating feed rate may be determined and displayed for operator decision support. The controller may in an automatic mode be configured to regulate the adhesive coating feed rate based on a comparison of one or more determined optimal values associated with respective actual values. The method may include identifying fiber source changes in real time, and predicting a natural coating potential based partly on predetermined correlations.

    Predictive systems and methods for proactive intervention in chemical processes

    公开(公告)号:US11857939B2

    公开(公告)日:2024-01-02

    申请号:US17466310

    申请日:2021-09-03

    Abstract: Various embodiments of the present disclosure relate to proactive dosing optimization chemical feed units producing an output solution (such as an oxidizing biocide) therefrom. Online sensors generate signals corresponding to directly measured variables for respective process components. Information is selectively retrieved from models relating combinations of input variables to respective industrial process states, wherein various current process states may be indirectly determined based on directly measured variables for respective system components. An output feedback signal is automatically generated corresponding to a detected intervention event based on the indirectly determined process state. A controller may receive the signal and implement, e.g., regulation of oxidizing biocide feed for optimization of end products and/or performance metrics.

    PREDICTIVE CONTROL SYSTEM AND METHOD FOR BROWN WASHING TREATMENT IN PULP MILLS

    公开(公告)号:US20210148047A1

    公开(公告)日:2021-05-20

    申请号:US17097957

    申请日:2020-11-13

    Abstract: A system and method are provided for predictive control of brown stock treatment at a pulp mill. Various online sensors generate output signals representative of actual values for respective process characteristics, each of which are directly or indirectly affected by adjustments to corresponding process variables. A controller uses the output signals or associated measurement data to dynamically set target values for the process characteristics based on a predicted impact of control responses for corresponding process variables. The controller further generates control signals to actuators associated with the respective process variables based on detected variations between the respective actual values and target values. Exemplary brown stock washing control systems may optimize various types of brown stock washing configurations, including for example vacuum drum washers, compaction baffle washers, chemiwashers, direct displacement washers and wash presses. Cloud-based analytics and machine learning may also be implemented to improve the control algorithms over time.

    PREDICTIVE SYSTEMS AND METHODS FOR PROACTIVE INTERVENTION IN CHEMICAL PROCESSES

    公开(公告)号:US20220072500A1

    公开(公告)日:2022-03-10

    申请号:US17466310

    申请日:2021-09-03

    Abstract: Various embodiments of the present disclosure relate to proactive dosing optimization chemical feed units producing an output solution (such as an oxidizing biocide) therefrom. Online sensors generate signals corresponding to directly measured variables for respective process components. Information is selectively retrieved from models relating combinations of input variables to respective industrial process states, wherein various current process states may be indirectly determined based on directly measured variables for respective system components. An output feedback signal is automatically generated corresponding to a detected intervention event based on the indirectly determined process state. A controller may receive the signal and implement, e.g., regulation of oxidizing biocide feed for optimization of end products and/or performance metrics.

    Real time regulation of Yankee dryer coating based on predicted natural coating transfer

    公开(公告)号:US10941522B1

    公开(公告)日:2021-03-09

    申请号:US16106194

    申请日:2018-08-21

    Abstract: A method is provided for decision support in regulating an adhesive coating applied to Yankee dryers. Online sensors are configured to continuously measure stock characteristics, and additional sensors provide actual stock flow rate and machine speed. A controller predicts potential natural coating application from a fibrous sheet generated from the stock to the Yankee dryer surface, substantially in real time, based on the measured characteristics and sensed actual machine values. An output signal may be provided to a display unit, wherein an optimal adhesive coating feed rate may be determined and displayed for operator decision support. The controller may in an automatic mode be configured to regulate the adhesive coating feed rate based on a comparison of one or more determined optimal values associated with respective actual values. The method may include identifying fiber source changes in real time, and predicting a natural coating potential based partly on predetermined correlations.

    REAL TIME REGULATION OF YANKEE DRYER COATING BASED ON PREDICTED NATURAL COATING TRANSFER

    公开(公告)号:US20190024316A1

    公开(公告)日:2019-01-24

    申请号:US15655545

    申请日:2017-07-20

    Abstract: A method is provided for decision support in regulating an adhesive coating applied to Yankee dryers. Online sensors are configured to continuously measure stock characteristics, and additional sensors provide actual stock flow rate and machine speed. A controller predicts potential natural coating application from a fibrous sheet generated from the stock to the Yankee dryer surface, substantially in real time, based on the measured characteristics and sensed actual machine values. An output signal may be provided to a display unit, wherein an optimal adhesive coating feed rate may be determined and displayed for operator decision support. The controller may in an automatic mode be configured to regulate the adhesive coating feed rate based on a comparison of one or more determined optimal values associated with respective actual values. The method may include identifying fiber source changes in real time, and predicting a natural coating potential based partly on predetermined correlations.

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