US 6,772,036 B2Grant

Control system using process model

Issue Date:2004-08-03

•18 Claims

•3 Drawing Sheets

Abstract

A control system is provided for controlling a process for making paper or paper pulp. The process has a process product output at an end of the process. The controls include a process variable sensor input configured to receive a process variable related to the process. The controller is configured to provide a control signal to control the process. A process model has a model product output which is a model representation of the process product output. The model process output is a function of the sensed process variable and a product output setpoint representative of a desired process product output. The control signal is a function of the product output setpoint and the modeled product output.

Metadata

Assignee

Fisher-Rosemount Systems, Inc.

Inventors

Evren Eryurek
Kadir Kavaklioglu

Application Information

Application Number:US 09/943,333

Filing Date:2001-08-30

Priority Date:2001-08-30

Art Unit:7

Classifications

IPC:

G06F 1900

Field of Search:

700127700128162 49162238162252162262

Patent Drawings (3 sheets)

Description

Background of the Invention

[0002] The present invention relates to industrial process control. More specifically, the present invention relates to controlling processes which are used to manufacture paper or paper pulp.

[0003] In a control system, including controls systems which are used to control paper and paper pulp manufacturing, the state of a process is monitored by measuring “process variables.” A process variable refers to a variable which is related to the condition of the process such as a flow rate, a level, a temperature, a pressure, etc. Based upon the measured process variable, a controller operates a control element in order to bring the process variable within a target range. For example, in order to achieve a desired flow rate (process variable) a controller adjusts a valve (control element) accordingly.

[0004] One type of process control observes the quality of the product output to adjust the various process variables within the process. The quality measurement is a process variable which is measured at the output of the process. It can be difficult to control paper and pulp manufacturing processes using this technique because there is both a physical distance between the process output and a significant lag time due to the time it takes for a product to move through the process. The physical separation and the separation in time can make controlling the process to achieve a desired quality difficult.

Summary of the Invention

[0005] A control system is provided for controlling a process for making paper or paper pulp. The process has a process product output at an end of the process. The controls include a process variable sensor input configured to receive a process variable related to the process. The controller is configured to provide a control signal to control the process. A process model has a model product output which is a model representation of the process product output. The model process output is a function of the sensed process variable and a product output setpoint representative of a desired process product output. The control signal is a function of the product output setpoint and the modeled product output.

Brief Description of the Drawings

[0006] FIG. 1 is a simplified diagram showing a portion of a paper manufacturing process.

[0007] FIG. 2 is a simplified block diagram of a control system in accordance with one embodiment of the invention.

[0008] FIG. 3 is a simplified block diagram showing a microprocessor used to implement the control system of FIG. 2.

Detailed Description of the Preferred Embodiments

[0009] Typical process control techniques in paper or paper pulp manufacturing rely on the feedback of the product quality to adjust the physical setpoints of the process variables within the manufacturing process. Such measurements are made at the output of the process. Although there are other process variable sensors located at various points along the process, they are typically only used for controlling an immediate process variable, such as a level, to thereby regulate the setpoints for a physical parameter as determined by a process control loop.

[0010] With this configuration, it is difficult to control product quality which is typically measured at the output of the process. The process output may be hundreds of feet away from the rest of the process and corrections can only be made after the fact. Any product output which is out of specification is discarded. Further, due to the dead time associated with the disparate locations between sensors and actuators, the control system cannot tolerate high gain in the control loop. With the present invention, a model is used to model the output of the process based upon one or more process variables measured at one or more locations along the process. The output of the model can be indicative of a quality measurement which related to the quality of the output product which will be obtained if the current process setpoints or control algorithms are not changed. Thus, the model is used to provide an inferred measurement related to a modeled product output. Based upon this inferred measurement related to the “quality” of the process output, the up stream process setpoints or control algorithms can be adjusted accordingly. In a more advanced embodiment, the information from the model can be used to coordinate distributed control algorithms which communicate on local process control loops in which control elements are controlled based upon local surrogate measurements.

[0011] The present invention can reduce the dead time between the control element and the surrogate or inferred measurements such that increased loop gain can be used in the control algorithms to improve the performance of the control loop without destabilizing the process. Further, a deviation in the product quality can be detected prior to actually producing the product and the control algorithms or setpoints can be adjusted to correct and compensate for the variation before the product exits the process. Integration of feed forward control, integrated sensors and inferred measurements with this feedback control technique provide improved control of the process and the quality of the output.

[0012] FIG. 1 is a simplified diagram showing one aspect of a paper sheet fabrication process. In this simplified embodiment, a vacuum pump 12 is coupled to a reservoir 14 through an adjusting valve 16. A receiving chamber 18 couples to the reservoir 14 through a fast acting valve 20 and is configured to receive a supply of paper sheets 22 through a manufacturing process. A drain valve 24 is configured to drain the reservoir 18. A pressure sensor 30, flow sensor 32 and temperature sensor 34 are configured to measure the pressure, flow rate and temperature associated with chamber 18. Information from sensors 30, 32 and 34 are provided to control system 40 which operates in accordance with the present invention.

[0013] In operation, control system 40 has at least one process variable input configured to receive a process variable from a process variable sensor such as sensors 30, 32 or 34. Sensors 30, 32 and 34 can be process variable transmitters coupled to a process control loop such as a two wire process control loop. As discussed below, control system 40 includes a process model and controls the quality of the paper produce manufactured by the process based upon an output from the model and a setpoint. This control is achieved by controlling a control element such as drain 24, fast acting valve 20 or adjusting valve 16. In the process illustrated in FIG. 1, paper sheets are received in receiving chamber 18 and are dried through the operation of drain 24 and vacuum supplied by vacuum pump 12. Excess liquid is collected in reservoir 14. The particular setpoints of the process used to dry the paper 22 can detrimentally effect the quality of the paper produced by the process.

[0014] Pursuant to one embodiment of the invention, FIG. 2 is a simplified block diagram of control system 40 used, for example, in the process illustrated in FIG. 1. The control system can couple to process devices (sensors or control elements) through one or more process control loops 41. Example control loops include two-wire loops such as 4-20 mA loops, loops in accordance with the Fieldbus standards, HART standards and others. Control system 40 includes a controller 60 which receives a setpoint 62 and provides a control signal output to a control element, such as one of the control elements illustrated in FIG. 1. In accordance with the present invention, control system 40 includes a process model 70 which receives a process variable sensor input 72 and provides a modeled product output 74 to controller 60. As discussed above, controller 60 controls one or more control elements in the process based upon the modeled product output 74 and the setpoint 62. The controller 60 can operate using any control algorithm including neural networks, regressive learning techniques, fuzzy logic, rules, any type of proportional integral and/or derivative control, etc. The present invention is not limited to the particular algorithm or technique implemented in a controller which is used to process the modeled product output. Controller 60 can receive other setpoints 76 and one or more process variables 78 and the control signal output 64 can be a function of these additional inputs. Model 70 can provide the modeled product output 74 as a function of other process signals 80. Examples of other process signals include other process variables, process setpoints, control signals, information related to the type or operation of a particular process sensor or control element, date or time information or any other information related to the operation of the process. The model can be preconfigured or can be generated using learning techniques such as that provided through the use of a neural network.

[0015] FIG. 3 is a simplified block diagram of control system 40 showing one example physical configuration of the control system. In the example of FIG. 3, control system 40 utilizes a microprocessor 100. Microprocessor 100 is configured to receive setpoint 62 which can be stored in memory, such as memory 102. Memory 102 can also contain permanent and/or temporary values such as used for programming or for storing program instructions or temporary storage. The process variable input can be through any type of physical layer such as through standard communication protocols. Example protocols include two-wire based protocols such as HART or Fieldbus. However, the control system can receive the process variable information, or other data, using any appropriate technique. Similarly, the control signal output can be implemented in any type of hardware including hardware which operates in accordance with process control industry standards. Example standards include two-wire based standards such as HART or Fieldbus. However, the control signal output 64 can be in accordance with any appropriate technique.

[0016] Although the present invention has been described with reference to preferred embodiments, workers skilled in the art will recognize that changes may be made in form and detail without departing from the spirit and scope of the invention. The present invention can be implemented in process devices located in the field, or in process devices or controls located at a remote location such as a control room or distant facility. Any appropriate hardware and/or software can implement the present invention including personal computers, microprocessors at various locations or configurations, etc. The invention can be implemented in any appropriate process device 40 including the illustrated control system or other devices which have access to process variables such as transmitters or controllers. The device can be at a remote location or in close physical proximity to a process variable sensor.

Claims

Post-issuance certificates present

The text shown below may not reflect later post-issuance changes.

What is claimed is:

1. A control system for controlling a process for making paper or paper pulp having a process product output at an end of the process, comprising:

a process variable sensor input configured to receive a plurality of process variables related to the process for making paper or pulp paper sensed by a process variable sensor which provides a process variable output, the plurality of process variables measured at a plurality of locations along this process;

a control element output configured to provide a control signal to a control element which controls the process in response to the control signal;

a process model having a model product quality output comprising an inferred measurement of product quality output, the model product quality output comprising a model representation of the process product output in response to the sensed process variables, the process model based upon current process setpoints and current process control algorithms which are directly included in the process model;

a product output quality setpoint representative of a desired process product output quality;

a controller configured to compare the product output setpoint to the modeled product output and responsively provide the control signal to the control element; and

wherein the process variable sensor input couples to a two-wire process control loop.

2. The control system of claim 1 wherein the model comprises a plurality of rules which model the process.

3. The control system of claim 1 wherein the model comprises a neural network which models the process.

4. The control system of claim 1 wherein the model comprises fuzzy logic which models the process.

5. The control system of claim 1 wherein the process variable sensor is in a first two-wire control loop, the control element is in a second two-wire control loop which is down stream from the first two-wire control loop, and wherein the controller corrects for process variations in the first two-wire control loop by adjusting the control element to achieve a desired product quality in the process product output.

6. The control system of claim 1 wherein the controller provides feed forward control as a function of the model product output.

7. The control system of claim 1 wherein the model is implemented in a microprocessor based system.

8. The control system of claim 1 wherein the model is implemented in a process device in physical proximity to the process variable sensor.

9. The control system of claim 1 wherein the process model is coupled to the process variable sensor over a control loop which operates in accordance with Fieldbus.

10. The control system of claim 1 wherein the model is a function of an observed process history.

11. A method for controlling a process for making paper or paper pulp, the process of the type having a process product output at the end of the process, comprising:

generating a control signal as a function of the modeled process product output quality and the setpoint.

obtaining a plurality of process variables related to the process from a two-wire process control loop, the plurality of process variables measured at a plurality of locations along the process;

modeling the process product output quality, the modeled process product output quality comprising an inferred measurement of product quality as a function of at least the obtained process variables, the process model based upon current process setpoints and current process control algorithms which are directly included in the process model;

obtaining a setpoint related to a desired process product output quality; and

12. The method of claim 11 wherein the modeling is based upon a plurality of rules.

13. The method of claim 11 wherein the modeling is based upon a neural network.

14. The method of claim 11 wherein the modeling is based upon fuzzy logic.

15. The method of claim 11 wherein the control signal is generated to correct for potential future deviations in the process product output.

16. The method of claim 11 wherein the modeling is a function of an observed process history.

17. The method of claim 11 including adjusting the process setpoints and control algorithms based upon the modeled process product output quality.

18. The control system of claim 1 wherein the controller coanges the process setpoints and control algorithms based upon the model product output quality.

Patent Citations (297)

Patent	Date	Inventor	Cited By
US3096434(A)	1963-07-01	King	Applicant
US3404264(A)	1968-10-01	Kugler	Applicant
US3468164(A)	1969-09-01	Sutherland	Applicant
US3590370(A)	1971-06-01	Fleischer	Applicant
US3618592(A)	1971-11-01	Stewart et al.	Applicant
US3688190(A)	1972-08-01	Blum	Applicant
US3691842(A)	1972-09-01	Akeley	Applicant
US3701280(A)	1972-10-01	Stroman	Applicant
US3849637(A)	1974-11-01	Caruso et al.	Applicant
US3855858(A)	1974-12-01	Cushing	Applicant
US3952759(A)	1976-04-01	Ottenstein	Applicant
US3973184(A)	1976-08-01	Raber	Applicant
USRE29383(E)	1977-09-01	Gallatin et al.	Applicant
US4058975(A)	1977-11-01	Gilbert et al.	Applicant
US4099413(A)	1978-07-01	Ohte et al.	Applicant
US4102199(A)	1978-07-01	Talpouras	Applicant
US4122719(A)	1978-10-01	Carlson et al.	Applicant
US4249164(A)	1981-02-01	Tivy	Applicant
US4250490(A)	1981-02-01	Dahlke	Applicant
US4279013(A)	1981-07-01	Cameron et al.	Applicant
US4337516(A)	1982-06-01	Murphy et al.	Applicant
US4399824(A)	1983-08-01	Davidson	Applicant
US4417312(A)	1983-11-01	Cronin et al.	Applicant
US4517468(A)	1985-05-01	Kemper et al.	Applicant
US4528869(A)	1985-07-01	Kubo et al.	Applicant
US4530234(A)	1985-07-01	Cullick et al.	Applicant
US4540468(A)	1985-09-01	Genco et al.	Examiner
US4571689(A)	1986-02-01	Hildebrand et al.	Applicant
US4635214(A)	1987-01-01	Kasai et al.	Applicant
US4642782(A)	1987-02-01	Kemper et al.	Applicant
US4644479(A)	1987-02-01	Kemper et al.	Applicant
US4649515(A)	1987-03-01	Thompson et al.	Applicant
US4668473(A)	1987-05-01	Agarwal	Applicant
US4707796(A)	1987-11-01	Calabro et al.	Applicant
US4720806(A)	1988-01-01	Schippers et al.	Applicant
US4736367(A)	1988-04-01	Wroblewski et al.	Applicant
US4736763(A)	1988-04-01	Britton et al.	Applicant
US4758308(A)	1988-07-01	Carr	Examiner
US4777585(A)	1988-10-01	Kokawa et al.	Applicant
US4807151(A)	1989-02-01	Citron	Applicant
US4818994(A)	1989-04-01	Orth et al.	Applicant
US4831564(A)	1989-05-01	Suga	Applicant
US4841286(A)	1989-06-01	Kummer	Applicant
US4853693(A)	1989-08-01	Eaton-Williams	Applicant
US4873655(A)	1989-10-01	Kondraske	Applicant
US4907167(A)	1990-03-01	Skeirik	Applicant
US4924418(A)	1990-05-01	Bachman et al.	Applicant
US4934196(A)	1990-06-01	Romano	Applicant
US4939753(A)	1990-07-01	Olson	Applicant
US4964125(A)	1990-10-01	Kim	Applicant
US4988990(A)	1991-01-01	Warrior	Applicant
US4992965(A)	1991-02-01	Holter et al.	Applicant
US5005142(A)	1991-04-01	Lipchak et al.	Applicant
US5019760(A)	1991-05-01	Chu et al.	Applicant
US5043862(A)	1991-08-01	Takahashi et al.	Applicant
US5053815(A)	1991-10-01	Wendell	Applicant
US5067099(A)	1991-11-01	McCown et al.	Applicant
US5081598(A)	1992-01-01	Bellows et al.	Applicant
US5089979(A)	1992-02-01	McEachern et al.	Applicant
US5089984(A)	1992-02-01	Struger et al.	Applicant
US5098197(A)	1992-03-01	Shepard et al.	Applicant
US5099436(A)	1992-03-01	McCown et al.	Applicant
US5103409(A)	1992-04-01	Shimizu et al.	Applicant
US5111531(A)	1992-05-01	Grayson et al.	Applicant
US5121467(A)	1992-06-01	Skeirik	Applicant
US5122794(A)	1992-06-01	Warrior	Applicant
US5122976(A)	1992-06-01	Bellows et al.	Applicant
US5130936(A)	1992-07-01	Sheppard et al.	Applicant
US5134574(A)	1992-07-01	Beaverstock et al.	Applicant
US5137370(A)	1992-08-01	McCullock et al.	Applicant
US5142612(A)	1992-08-01	Skeirik	Applicant
US5143452(A)	1992-09-01	Maxedon et al.	Applicant
US5148378(A)	1992-09-01	Shibayama et al.	Applicant
US5150289(A)	1992-09-01	Badavas	Examiner
US5167009(A)	1992-11-01	Skeirik	Applicant
US5175678(A)	1992-12-01	Frerichs et al.	Applicant
US5193143(A)	1993-03-01	Kaemmerer et al.	Applicant
US5197114(A)	1993-03-01	Skeirik	Applicant
US5197328(A)	1993-03-01	Fitzgerald	Applicant
US5212765(A)	1993-05-01	Skeirik	Applicant
US5214582(A)	1993-05-01	Gray	Applicant
US5224203(A)	1993-06-01	Skeirik	Applicant
US5228780(A)	1993-07-01	Shepard et al.	Applicant
US5235527(A)	1993-08-01	Ogawa et al.	Applicant
US5265031(A)	1993-11-01	Malczewski	Applicant
US5265222(A)	1993-11-01	Nishiya et al.	Applicant
US5269311(A)	1993-12-01	Kirchner et al.	Applicant
US5274572(A)	1993-12-01	O'Neill et al.	Applicant
US5282131(A)	1994-01-01	Rudd et al.	Applicant
US5282261(A)	1994-01-01	Skeirik	Applicant
US5293585(A)	1994-03-01	Morita	Applicant
US5303181(A)	1994-04-01	Stockton	Applicant
US5305230(A)	1994-04-01	Matsumoto et al.	Applicant
US5311421(A)	1994-05-01	Nomura et al.	Applicant
US5317520(A)	1994-05-01	Castle	Applicant
US5327357(A)	1994-07-01	Feinstein et al.	Applicant
US5333240(A)	1994-07-01	Matsumoto et al.	Applicant
US5347843(A)	1994-09-01	Orr et al.	Applicant
US5349541(A)	1994-09-01	Alexandro, Jr. et al.	Applicant
US5357449(A)	1994-10-01	Oh	Applicant
US5361628(A)	1994-11-01	Marko et al.	Applicant
US5365423(A)	1994-11-01	Chand	Applicant
US5365787(A)	1994-11-01	Hernandez et al.	Applicant
US5367612(A)	1994-11-01	Bozich et al.	Applicant
US5384699(A)	1995-01-01	Levy et al.	Applicant
US5386373(A)	1995-01-01	Keeler et al.	Applicant
US5388465(A)	1995-02-01	Okaniwa et al.	Applicant
US5394341(A)	1995-02-01	Kepner	Applicant
US5394543(A)	1995-02-01	Hill et al.	Applicant
US5404064(A)	1995-04-01	Mermelstein et al.	Applicant
US5408406(A)	1995-04-01	Mathur et al.	Applicant
US5408586(A)	1995-04-01	Skeirik	Applicant
US5414645(A)	1995-05-01	Hirano	Applicant
US5419197(A)	1995-05-01	Ogi et al.	Applicant
US5430642(A)	1995-07-01	Nakajima et al.	Applicant
US5434774(A)	1995-07-01	Seberger	Applicant
US5436705(A)	1995-07-01	Raj	Applicant
US5440478(A)	1995-08-01	Fisher et al.	Applicant
US5442639(A)	1995-08-01	Crowder et al.	Applicant
US5467355(A)	1995-11-01	Umeda et al.	Applicant
US5469070(A)	1995-11-01	Koluvek	Applicant
US5469156(A)	1995-11-01	Kogura	Applicant
US5469735(A)	1995-11-01	Watanabe	Applicant
US5469749(A)	1995-11-01	Shimada et al.	Applicant
US5481199(A)	1996-01-01	Anderson et al.	Applicant
US5483387(A)	1996-01-01	Bauhahn et al.	Applicant
US5485753(A)	1996-01-01	Burns et al.	Applicant
US5486996(A)	1996-01-01	Samad et al.	Applicant
US5488697(A)	1996-01-01	Kaemmerer et al.	Applicant
US5489831(A)	1996-02-01	Harris	Applicant
US5495769(A)	1996-03-01	Broden et al.	Applicant
US5510779(A)	1996-04-01	Maltby et al.	Applicant
US5511004(A)	1996-04-01	Dubost et al.	Applicant
US5526293(A)	1996-06-01	Mozumder et al.	Applicant
US5539638(A)	1996-07-01	Keeler et al.	Applicant
US5548528(A)	1996-08-01	Keeler et al.	Applicant
US5560246(A)	1996-10-01	Bottinger et al.	Applicant
US5561599(A)	1996-10-01	Lu	Applicant
US5570300(A)	1996-10-01	Henry et al.	Applicant
US5572420(A)	1996-11-01	Lu	Applicant
US5573032(A)	1996-11-01	Lenz et al.	Applicant
US5591922(A)	1997-01-01	Segeral et al.	Applicant
US5598521(A)	1997-01-01	Kilgore et al.	Applicant
US5600148(A)	1997-02-01	Cole et al.	Applicant
US5608650(A)	1997-03-01	McClendon et al.	Applicant
US5623605(A)	1997-04-01	Keshav et al.	Applicant
US5633809(A)	1997-05-01	Wissenbach et al.	Applicant
US5637802(A)	1997-06-01	Frick et al.	Applicant
US5640491(A)	1997-06-01	Bhat et al.	Applicant
US5661668(A)	1997-08-01	Yemini et al.	Applicant
US5665899(A)	1997-09-01	Willcox	Applicant
US5669713(A)	1997-09-01	Schwartz et al.	Applicant
US5671335(A)	1997-09-01	Davis et al.	Applicant
US5672247(A)	1997-09-01	Pangalos et al.	Examiner
US5675504(A)	1997-10-01	Serodes et al.	Applicant
US5675724(A)	1997-10-01	Beal et al.	Applicant
US5680109(A)	1997-10-01	Lowe et al.	Applicant
US5682317(A)	1997-10-01	Keeler et al.	Applicant
US5700090(A)	1997-12-01	Eryurek	Applicant
US5703575(A)	1997-12-01	Kirkpatrick	Applicant
US5704011(A)	1997-12-01	Hansen et al.	Applicant
US5705978(A)	1998-01-01	Frick et al.	Applicant
US5708211(A)	1998-01-01	Jepson et al.	Applicant
US5708585(A)	1998-01-01	Kushion	Applicant
US5710370(A)	1998-01-01	Shanahan et al.	Applicant
US5713668(A)	1998-02-01	Lunghofer et al.	Applicant
US5719378(A)	1998-02-01	Jackson, Jr. et al.	Applicant
US5736649(A)	1998-04-01	Kawasaki et al.	Applicant
US5741074(A)	1998-04-01	Wang et al.	Applicant
US5742845(A)	1998-04-01	Wagner	Applicant
US5746511(A)	1998-05-01	Eryurek et al.	Applicant
US5747701(A)	1998-05-01	Marsh et al.	Applicant
US5752008(A)	1998-05-01	Bowling	Applicant
US5764891(A)	1998-06-01	Warrior	Applicant
US5781878(A)	1998-07-01	Mizoguchi et al.	Applicant
US5801689(A)	1998-09-01	Huntsman	Applicant
US5805442(A)	1998-09-01	Crater et al.	Applicant
US5817950(A)	1998-10-01	Wiklund et al.	Applicant
US5825664(A)	1998-10-01	Warrior et al.	Examiner
US5828567(A)	1998-10-01	Eryurek et al.	Applicant
US5829876(A)	1998-11-01	Schwartz et al.	Applicant
US5848383(A)	1998-12-01	Yunus	Applicant
US5859964(A)	1999-01-01	Wang et al.	Applicant
US5876122(A)	1999-03-01	Eryurek	Applicant
US5880376(A)	1999-03-01	Sai et al.	Applicant
US5887978(A)	1999-03-01	Lunghofer et al.	Applicant
US5908990(A)	1999-06-01	Cummings	Applicant
US5923557(A)	1999-07-01	Eidson	Applicant
US5924086(A)	1999-07-01	Mathur et al.	Applicant
US5926778(A)	1999-07-01	Pöppel	Applicant
US5936514(A)	1999-08-01	Anderson et al.	Applicant
US5940290(A)	1999-08-01	Dixon	Applicant
US5956663(A)	1999-09-01	Eryurek et al.	Applicant
US5970430(A)	1999-10-01	Burns et al.	Applicant
US6014902(A)	2000-01-01	Lewis et al.	Applicant
US6016523(A)	2000-01-01	Zimmerman et al.	Applicant
US6016706(A)	2000-01-01	Yamamoto et al.	Applicant
US6017143(A)	2000-01-01	Eryurek et al.	Examiner
US6023399(A)	2000-02-01	Kogure	Applicant
US6038579(A)	2000-03-01	Sekine	Applicant
US6045260(A)	2000-04-01	Schwartz et al.	Applicant
US6047220(A)	2000-04-01	Eryurek	Applicant
US6047222(A)	2000-04-01	Burns et al.	Applicant
US6052655(A)	2000-04-01	Kobayashi et al.	Applicant
US6072150(A)	2000-06-01	Sheffer	Applicant
US6112131(A)	2000-08-01	Ghorashi et al.	Applicant
US6119047(A)	2000-09-01	Eryurek et al.	Applicant
US6119529(A)	2000-09-01	DiMarco et al.	Applicant
US6139180(A)	2000-10-01	Usher et al.	Applicant
US6151560(A)	2000-11-01	Jones	Applicant
US6179964(B1)	2001-01-01	Begemann et al.	Examiner
US6192281(B1)	2001-02-01	Brown et al.	Applicant
US6195591(B1)	2001-02-01	Nixon et al.	Applicant
US6199018(B1)	2001-03-01	Quist et al.	Applicant
US6236948(B1)	2001-05-01	Eck et al.	Applicant
US6263487(B1)	2001-07-01	Stripf et al.	Applicant
US6298377(B1)	2001-10-01	Hartikainen et al.	Applicant
US6311136(B1)	2001-10-01	Henry et al.	Applicant
US6327914(B1)	2001-12-01	Dutton	Applicant
US6347252(B1)	2002-02-01	Behr et al.	Applicant
US6360277(B1)	2002-03-01	Ruckley et al.	Applicant
US6370448(B1)	2002-04-01	Eryurek	Applicant
US6397114(B1)	2002-05-01	Eryurek et al.	Applicant
US6425038(B1)	2002-07-01	Sprecher	Applicant
US2003/0033040(A1)	2003-02-01	Billings	Examiner
CA999950	1976-11-01		Examiner
DE3213866(A1)	1983-10-01		Applicant
DE3540204(C1)	1986-09-01		Applicant
DE4008560(A1)	1990-09-01		Applicant
DE4343747	1994-06-01		Applicant
DE4433593(A1)	1995-06-01		Applicant
DE19502499(A1)	1996-08-01		Applicant
DE29600609(U1)	1997-03-01		Applicant
DE19704694(A1)	1997-08-01		Applicant
DE19930660(A1)	1999-07-01		Applicant
DE29917651(U1)	2000-12-01		Applicant
EP122622(A1)	1984-10-01		Applicant
EP413814(A1)	1991-02-01		Applicant
EP487419(A2)	1992-05-01		Applicant
EP512794(A2)	1992-05-01		Applicant
EP594227(A1)	1994-04-01		Applicant
EP624847(A1)	1994-11-01		Applicant
EP644470(A2)	1995-03-01		Applicant
EP825506(A2)	1997-07-01		Applicant
EP827096(A2)	1997-09-01		Applicant
EP838768(A2)	1997-09-01		Applicant
EP807804(A2)	1997-11-01		Applicant
EP1058093(A1)	1999-05-01		Applicant
EP1022626(A2)	2000-07-01		Applicant
FR2302514	1976-09-01		Applicant
FR2334827	1977-07-01		Applicant
GB928704	1963-06-01		Applicant
GB1534280	1978-11-01		Applicant
GB2310346(A)	1997-08-01		Applicant
GB2347323(A)	2000-01-01		Applicant
GB2342453	2000-04-01		Applicant
JP58-129316	1983-08-01		Applicant
JP59-116811	1984-07-01		Applicant
JP59163520	1984-09-01		Applicant
JP59-211196	1984-11-01		Applicant
JP59-211896	1984-11-01		Applicant
JP60-507	1985-01-01		Applicant
JP60-76619	1985-05-01		Applicant
JP60-131495	1985-07-01		Applicant
JP60174915	1985-09-01		Applicant
JP62-30915	1987-02-01		Applicant
JP64-1914	1989-01-01		Applicant
JP64-72699	1989-03-01		Applicant
JP2-5105	1990-01-01		Applicant
JP3229124	1991-11-01		Applicant
JP5-122768	1993-05-01		Applicant
JP6242192	1994-09-01		Applicant
JP7-63586	1995-03-01		Applicant
JP7234988	1995-09-01		Applicant
JP8-54923	1996-02-01		Applicant
JP8-136386	1996-05-01		Applicant
JP8-166309	1996-06-01		Applicant
JP8247076	1996-09-01		Applicant
JP2712625	1997-10-01		Applicant
JP2712701	1997-10-01		Applicant
JP2753592	1998-03-01		Applicant
JP7225530	1998-05-01		Applicant
JP10-232170	1998-09-01		Applicant
JP11083575	1999-03-01		Applicant
WO94/25933	1994-11-01		Applicant
WO96/11389	1996-04-01		Applicant
WO96/12993	1996-05-01		Applicant
WO96/39617	1996-12-01		Applicant
WO97/21157	1997-06-01		Applicant
WO97/25603	1997-07-01		Applicant
WO98/06024	1998-02-01		Applicant
WO98/13677	1998-04-01		Applicant
WO98/20469	1998-05-01		Applicant
WO98/39718	1998-09-01		Applicant
WO99/19782	1998-10-01		Applicant
WO/55700	2000-03-01		Applicant
WO/70531	2000-11-01		Applicant

Non-Patent Literature (120)

International Search Report for International application No. PCT/US 02/14934, filed May 8, 2002, Search Report dated Apr. 28, 2002.Applicant
International Search Report for International application No. PCT/US 02/14560, filed May 8, 2002, Search Report dated Sep. 3, 2002.Applicant
Journal of Intelligent Manufacturing (1997) 8, 271-276 article entitled “On-line tool condition monitoring system with wavelet fuzzy neural network”.Applicant
“Approval Standards For Explosionproof Electrical Equipment General Requirements”, Factory Mutual Research, Cl. No. 3615, Mar. 1989, pp. 1-34.Applicant
“Approval Standard Intrinsically Safe Apparatus and Associated Apparatus For Use In Class I, II, and III, Division 1 Hazardous (Classified) Locations”, Factory Mutual Research, Cl. No. 3610, Oct. 1988, pp. 1-70.Applicant
“Automation On-line” by, Phillips et al., Plant Services, Jul. 1997, pp. 41-45.Applicant
“Climb to New Heights by Controlling your PLCs Over the Internet” by, Phillips et al., Intech, Aug. 1998, pp. 50-51.Applicant
“CompProcessor For Piezoresistive Sensors” MCA Technologies Inc. (MCA7707), pp. 1-8.Applicant
“Ethernet emerges as viable, inexpensive fieldbus”, Paul G. Schreier, Personal Engineering, Dec. 1997, p. 23-29.Applicant
“Ethernet Rules Closed-loop System” by, Eidson et al., Intech, Jun. 1998, pp. 39-42.Applicant
“Fieldbus Standard for Use in Industrial Control Systems Part 2: Physical Layer Specification and Service Definition”, ISA-S50.02-1992, pp. 1-93.Applicant
“Fieldbus Standard for Use in Industrial Control Systems Part 3: Data Link Service Definition”, ISA-S50.02-1997, Part 3, Aug. 1997, pp. 1-159.Applicant
Fieldbus Standard For Use in Industrial Control Systems Part 4: Data Link Protocol Specification, ISA-S50.02-1997, Part 4, Aug. 1997, pp. 1-148.Applicant
“Fieldbus Support For Process Analysis” by, Blevins et al., Fisher-Rosemount Systems, Inc., 1995, pp. 121-128.Applicant
“Fieldbus Technical Overview Understanding FOUNDATION™ fieldbus technology”, Fisher-Rosemount, 1998, pp. 1-23.Applicant
“Hypertext Transfer Protocol—HTTP/1.0” by, Berners-Lee et al., MIT/LCS, May 1996, pp. 1-54.Applicant
“Infranets, Intranets, and the Internet” by, Pradip Madan, Echelon Corp, Sensors, Mar. 1997, pp. 46-50.Applicant
“Internet Technology Adoption into Automation” by, Fondl et al., Automation Business, pp. 1-5.Applicant
“Internet Protocol Darpa Internet Program Protocol Specification” by, Information Sciences Institute, University of Southern California, RFC 791, Sep. 1981, pp. 1-43.Applicant
“Introduction to Emit”, emWare, Inc., 1997, pp. 1-22.Applicant
“Introduction to the Internet Protocols” by, Charles L. Hedrick, Computer Science Facilities Group, Rutgers University, Oct. 3, 1988, pp. 1-97.Applicant
“Is There A Future For Ethernet in Industrial Control?”, Miclot et al., Plant Engineering, Oct. 1988, pp. 44-46, 48, 50.Applicant
LFM/SIMA Internet Remote Diagnostics Research Project Summary Report, Stanford University, Jan. 23, 1997, pp. 1-6.Applicant
“Managing Devices with the Web” by, Howard et al., Byte, Sep. 1997, pp. 45-64.Applicant
“Modular Microkernel Links GUI And Browser For Embedded Web Devices” by, Tom Williams, pp. 1-2.Applicant
“PC Software Gets Its Edge From Windows, Components, and the Internet”, Wayne Labs, I&CS, Mar. 1997, pp. 23-32.Applicant
Proceedings Sensor Expo, Aneheim, California, Produced by Expocon Managemnet Associates, Inc., Apr. 1996, pp. 9-21.Applicant
Proceedings Sensor Expo, Boston, Massachuttes, Produced by Expocon Management Associates, Inc., May 1997, pp. 1-416.Applicant
“Smart Sensor Network of the Future” by, Jay Warrior, Sensors, Mar. 1997, pp. 40-45.Applicant
“The Embedded Web Site” by, John R. Hines, IEEE Spectrum, Sep. 1996, p. 23.Applicant
“Transmission Control Protocol: Darpa Internet Program Protocol Specification” Information Sciences Institute, Sep. 1981, pp. 1-78.Applicant
“On-Line Statistical Process Control for a Glass Tank Ingredient Scale,” by R.A. Weisman, IFAC real Time Programming, 1985, pp. 29-38.Applicant
“The Performance of Control Charts for Monitoring Process Variation,” by C. Lowry et al., Commun. Statis.—Simula., 1995, pp. 409-437.Applicant
“A Knowledge-Based Approach for Detection and Diagnosis of Out-Of-Control Events in Manufacturing Processes,” by P. Love et al., IEEE, 1989, pp. 736-741.Applicant
“Advanced Engine Diagnostics Using Universal Process Modeling”, by P. O'Sullivan, Presented at the 1996 SAE Conference on Future Transportation Technology, pp. 1-9.Applicant
Parallel, Fault-Tolerant Control and Diagnostics System for Feedwater Regulation in PWRS, by E. Eryurek et al., Proceedings of the American Power Conference.Applicant
“Programmable Hardware Architectures for Sensor Validation”, by M.P. Henry et al., Control Eng. Practice, vol. 4, No. 10., pp. 1339-1354, (1996).Applicant
“Sensor Validation for Power Plants Using Adaptive Backpropagation Neural Network,” IEEE Transactions on Nuclear Science, vol. 37, No. 2, by E. Eryurek et al. Apr. 1990, pp. 1040-1047.Applicant
“Signal Processing, Data Handling and Communications: The Case for Measurement Validation”, by M.P. Henry, Department of Engineering Science, Oxford University.Applicant
“Smart Temperature Measurement in the '90s”, by T. Kerlin et al., C&I, (1990).Applicant
“Software-Based Fault-Tolerant Control Design for Improved Power Plant Operation,” IEEE/IFAC Joint Symposium on Computer-Aided Control System Design, Mar. 7-9, 1994 pp. 585-590.Applicant
A Standard Interface for Self-Validating Sensors, by M.P. Henry et al., Report No. QUEL 1884/91, (1991).Applicant
“Taking Full Advantage of Smart Transmitter Technology Now,” by G. Orrison, Control Engineering, vol. 42, No. 1, Jan. 1995.Applicant
“Using Artificial Neural Networks to Identify Nuclear Power Plant States,” by Israel E. Alguindigue et al., pp. 1-4.Applicant
“Application of Neural Computing Paradigms for Signal Validation,” by B.R. Upadhyaya et al., Department of Nuclear Engineering, pp. 1-18.Applicant
“Application of Neural Networks for Sensor Validation and Plant Monitoring,” by B. Upadhyaya et al., Nuclear Technology, vol. 97, No. 2, Feb. 1992 pp. 170-176.Applicant
“Automated Generation of Nonlinear System Characterization for Sensor Failure Detection,” by B.R. Upadhyaya et al., ISA, 1989 pp. 269-274.Applicant
“In Situ Claibration of Nuclear Plant Platinum Resistance Thermometers Using Johnson Noise Methods,” EPRI, Jun. 1983.Applicant
“Johnson Noise Thermometer for High Radiation and High-Temperature Environments,” by L. Oakes et al., Fifth Symposium on Space Nuclear Power Systems, Jan. 1988, pp. 2-23.Applicant
“Development of a Resistance Thermometer For Use Up to 1600° C”, by M.J. de Groot et al., CAL LAB, Jul./Aug. 1996, pp. 38-41.Applicant
“Survey, Applications, And Prospects of Johnson Noise Thermometry,” by T. Blalock et al., Electrical Engineering Department, 1981 pp. 2-11.Applicant
“Noise Thermometry for Industrial and Metrological Applications at KFA Julich,” by H. Brixy et al., 7th International Symposium on Temperature, 1992.Applicant
“Johnson Noise Power Thermometer and its Application in Process Temperature Measurement,” by T.V. Blalock et al., American Institute of Physics 1982, pp. 1249-1259.Applicant
“Field-based Architecture is Based on Open Systems, Improves Plant Performance”, by P. Cleaveland, I&CS, Aug. 1996, pp. 73-74.Applicant
“Tuned-Circuit Dual-Mode Johnson Noise Thermometers,” by R.L. Shepard et al., Apr. 1992.Applicant
“Tuned-Circuit Johnson Noise Thermometry,” by Michael Roberts et al., 7th Symposium on Space Nuclear Power Systems, Jan. 1990.Applicant
“Smart Field Devices Provide New Process Data, Increase System Flexibility,” by Mark Boland, I&CS, Nov. 1994, pp. 45-51.Applicant
“Wavelet Analysis of Vibration, Part I: Theory1,” by D.E. Newland, Journal of Vibration and Acoustics, vol. 116, Oct. 1994, pp. 409-416.Applicant
“Wavelet Analysis of Vibration, Part 2: Wavelet Maps,” by D.E. Newland, Journal of Vibration and Acoustics, vol. 116, Oct. 1994, pp. 417-425.Applicant
“Development of a Long-Life, High-Reliability Remotely Operated Johnson Noise Thermometer,” by R.L. Shepard et al., ISA, 1991, pp. 77-84.Applicant
“Application of Johnson Noise Thermometry to Space Nuclear Reactors,” by M.J. Roberts et al., Presented at the 6th Symposium on Space Nuclear Power Systems, Jan. 9-12, 1989.Applicant
“A Decade of Progress in High Temperature Johnson Noise Thermometry,” by T.V. Blalock et al., American Institute of Physics, 1982 pp. 1219-1223.Applicant
“Sensor and Device Diagnostics for Predictive and Proactive Maintenance”, by B. Boynton, A Paper Presented at the Electric Power Research Institute—Fossil Plant Maintenance Conference in Baltimore, Maryland, Jul. 29-Aug. 1, 1996, pp. 50-1—50-6.Applicant
“Detection of Hot Spots in Thin Metal Films Using an Ultra Sensitive Dual Channel Noise Measurement System,” by G.H. Massiha et al., Energy and Information Technologies in the Southeast, vol. 3 of 3, Apr. 1989, pp. 1310-1314.Applicant
“Detecting Blockage in Process Connections of Differential Pressure Transmitters”, by E. Taya et al., SICE, 1995, pp. 1605-1608.Applicant
“Development and Application of Neural Network Algorithms For Process Diagnostics,” by B.R. Upadhyaya et al., Proceedings of the 29th Conference on Decision and Control, 1990, pp. 3277-3282.Applicant
“A Fault-Tolerant Interface for Self-Validating Sensors”, by M.P. Henry, Colloquium, pp. 3/1-3/2 (Nov. 1990).Applicant
“Fuzzy Logic and Artificial Neural Networks for Nuclear Power Plant Applications,” by R.C. Berkan et al., Proceedings of the American Power Conference.Applicant
“Fuzzy Logic and Neural Network Applications to Fault Diagnosis”, by P. Frank et al., International Journal of Approximate Reasoning, (1997), pp. 68-88.Applicant
“Keynote Paper: Hardware Compilation-A New Technique for Rapid Prototyping of Digital Systems-Applied to Sensor Validation”, by M.P. Henry, Control Eng. Practice, vol. 3, No. 7., pp. 907-924, (1995).Applicant
“The Implications of Digital Communications on Sensor Validation”, by M. Henry et al., Report No. QUEL 1912/92, (1992).Applicant
“In-Situ Response Time Testing of Thermocouples”, ISA, by H.M. Hashemian et al., Paper No. 89-0056, pp. 587-593, (1989).Applicant
“An Integrated Architecture For Signal Validation in Power Plants,” by B.R. Upadhyaya et al., Third IEEE International Symposium on Intelligent Control, Aug. 24-26, 1988, pp. 1-6.Applicant
“Integration of Multiple Signal Validation Modules for Sensor Monitoring,” by B. Upadhyaya et al., Department of Nuclear Engineering, Jul. 8, 1990, pp. 1-6.Applicant
“Intelligent Behaviour for Self-Validating Sensors”, by M.P. Henry, Advances In Measurement, pp. 1-7, (May 1990).Applicant
“Measurement of the Temperature Fluctuation in a Resistor Generating 1/F Fluctuation,” by S. Hashiguchi, Japanese Journal of Applied Physics, vol. 22, No. 5, Part 2, May 1983, pp. L284-L286.Applicant
“Check of Semiconductor Thermal Resistance Elements by the Method of Noise Thermometry”, by A. B. Kisilevskii et al., Measurement Techniques, vol. 25, No. 3, Mar. 1982, New York, USA, pp. 244-246.Applicant
“Neural Networks for Sensor Validation and Plant Monitoring,” by B. Upadhyaya, International Fast Reactor Safety Meeting, Aug. 12-16, 1990, pp. 2-10.Applicant
“Neural Networks for Sensor Validation and Plantwide Monitoring,” by E. Eryurek, 1992.Applicant
“A New Method of Johnson Noise Thermometry”, by C.J. Borkowski et al., Rev. Sci. Instrum., vol. 45, No. 2, (Feb. 1974) pp. 151-162.Applicant
“Thermocouple Continuity Checker,” IBM Technical Disclosure Bulletin, vol. 20, No. 5, pp. 1954 (Oct. 1977).Applicant
“A Self-Validating Thermocouple,” Janice C-Y et al., IEEE Transactions on Control Systems Technology, vol. 5, No. 2, pp. 239-253 (Mar. 1997).Applicant
Instrument Engineers' Handbook, Chapter IV entitled “Temperature Measurements,” by T.J. Claggett, pp. 266-333 (1982).Applicant
“emWare's Releases EMIT 3.0, Allowing Manufacturers to Internet and Network Enable Devices Royalty Free,” 3 pages, PR Newswire (Nov. 4, 1998).Applicant
Warrier, J., “The IEEE P1451.1 Object Model Network Independent Interfaces for Sensors and Actuators,” pp. 1-14, Rosemount Inc. (1997).Applicant
Warrior, J., “The Collision Between the Web and Plant Floor Automation,” 6Th. WWW Conference Workshop on Embedded Web Technology, Santa Clara, CA (Apr. 7, 1997).Applicant
Microsoft Press Computer Dictionary, 3rd Edition, p. 124.Applicant
“Internal Statistical Quality Control for Quality Monitoring Instruments”, by P. Girling et al., ISA, 15 pgs., 1999.Applicant
Web Pages from www.triant.com (3 pgs.).Applicant
“Statistical Process Control (Practice Guide Series Book)”, Instrument Society of America, 1995, pp. 1-58 and 169-204.Applicant
“Time-Frequency Analysis of Transient Pressure Signals for a Mechanical Heart Valve Cavitation Study,” ASAIO Journal, by Alex A. Yu et al., vol. 44, No. 5, pp. M475-M479, (Sep.—Oct. 1998).Applicant
“Transient Pressure Signals in Mechanical Heart Valve Caviation,” by Z.J. Wu et al., pp. M555-M561 (undated).Applicant
“Caviation in Pumps, Pipes and Valves,” Process Engineering, by Dr. Ronald Young, pp. 47-49 (Jan. 1990).Applicant
“Quantification of Heart Valve Cavitation Based on High Fidelity Pressure Measurements,” Advances in Bioengineering 1994, by Laura A. Garrison et al., BED-vol. 28, pp. 297-298 (Nov. 6-11, 1994).Applicant
“Monitoring and Diagnosis of Cavitation in Pumps and Valves Using the Wigner Distribution,” Hydroaccoustic Facilities, Instrumentation, and Experimental Techniques, NCA-vol. 10, pp. 31-36 (1991).Applicant
“Developing Predictive Models for Cavitation Erosion,” Codes and Standards in A Global Environment, PVP-vol. 259, pp. 189-192 (1993).Applicant
“Self-Diagnosing Intelligent Motors: A Key Enabler for Next Generation Manufacturing System,” by Fred M. Discenzo et al., pp. 3/1-3/4 (1999).Applicant
“A Microcompuer-Based Instrument for Applications in Platinum Resistance Thermomety,” by H. Rosemary Taylor and Hector A. Navarro, Journal of Physics E. Scientific Instrument, vol. 16, No. 11, pp. 1100-1104 (1983).Applicant
“Experience in Using Estelle for the Specification and Verification of a Fieldbus Protocol: FIP,” by Barretto et al., Computer Networking, pp. 295-304 (1990).Applicant
“Computer Stimulation of H1 Field Bus Transmission,” by Utsumi et al., Advances in Instrumentation and Control, vol. 46, Part 2, pp. 1815-1827 (1991).Applicant
“Progress in Fieldbus Developments for Measuring and Control Application,” by A. Schwaier, Sensor and Actutors, pp. 115-119 (1991).Applicant
“Ein Emulationssystem zur Leitstungsanalyse von Feldbussystemen, Teil 1,” by R. Hoyer, pp. 335-336 (1991).Applicant
“Simulatore Integrato: Controllo su bus di campo,” by Barabino et al., Automazione e Strumentazione, pp. 85-91 (Oct. 1993).Applicant
“Ein Modulares, verteiltes Diagnose-Expertensystem für die Fehlerdiagnose in lokalen Netzen,” by Jürgen M. Schröder, pp. 557-565 (1990).Applicant
“Fault Diagnosis of Fieldbus Systems,” by Jürgen Quade, pp. 577-581 (10/92).Applicant
“Ziele und Anwndungen von Feldbussystemen,” by T. Pfeifer et al., pp. 549-557 (10/87).Applicant
“PROFIBUS-Infrastrukturmaβnahmen,” by Tilo Pfeifer et al., pp. 416-419 (8/91).Applicant
“Simulation des Zeitverhaltens von Feldbussystemen,” by O. Schnelle, pp. 440-442 (1991).Applicant
“Modélisation et simulation d'un bus de terrain: FIP,” by Song et al, pp. 5-9 (undated).Applicant
“Feldbusnetz für Automatisierungssysteme mit intelligenten Funktionseinheiten,” by W. Kriesel et al., pp. 486-489 (1987).Applicant
“Bus de campo para la inteconexión del proceso con sistemas digitales de control,” Tecnología, pp. 141-147 (1990).Applicant
“Dezentrale Installation mit Echtzeit-Feldbus,” Netzwerke, Jg. Nr.3 v. 14.3, 4 pages (1990).Applicant
“Process Measurement and Analysis,” by Liptak et al., Instrument Engineers' Handbook, Third Edition, pp. 528-530, (1995).Applicant
“Improving Dynamic Performance of Temperature Sensors With Fuzzy Control Techniques,” by Wang Lei et al., pp. 872-873 (1992).Applicant
IEEE Transactions on Magnetics, vol. 34, No. 5, Sep. 1998, “Optical Design of the Coils of an Electromagnetic Flow Meter,” pp. 2563-2566.Applicant
IEEE Transactions on Magnetics, vol. 30, No. 2, Mar. 1994, “Magnetic Fluid Flow Meter for Gases,” pp. 936-938.Applicant
IEEE Instrumentation and Measurement, “New approach to a main error estimation for primary transducer of electromagnetic flow meter,” pp. 1093-1097.Applicant
“Additional Information From Flowmeters via Signal Analysis,” by J.E. Amadi-Echendu and E.H. Higham, pp. 187-193.Applicant
“Notification of Transmittal of the International Search Report or the Declaration” for PCT/US01/40791.Applicant
“Notification of Transmittal of the International Search Report or the Declaration” for PCT/US01/40782.Applicant

Abstract