Source: http://www.google.com/patents/US6907383?dq=7069184
Timestamp: 2014-03-11 23:38:33
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Patent US6907383 - Flow diagnostic system - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsA flow diagnostic system for a flow sensing element and impulse lines. A pressure transmitter coupled to the impulse lines provides digital pressure data to a control system. The control system provides the pressure data and real time clock readings to a diagnostic application. The diagnostic application...http://www.google.com/patents/US6907383?utm_source=gb-gplus-sharePatent US6907383 - Flow diagnostic systemAdvanced Patent SearchPublication numberUS6907383 B2Publication typeGrantApplication numberUS 09/852,102Publication dateJun 14, 2005Filing dateMay 9, 2001Priority dateMar 28, 1996Fee statusPaidAlso published asCN1514928A, CN100507465C, EP1407233A1, EP1407233B1, US20020029130, WO2002090894A1Publication number09852102, 852102, US 6907383 B2, US 6907383B2, US-B2-6907383, US6907383 B2, US6907383B2InventorsEvren Eryurek, Kadir KavakliogluOriginal AssigneeRosemount Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (125), Non-Patent Citations (104), Referenced by (25), Classifications (27), Legal Events (3) External Links: USPTO, USPTO Assignment, EspacenetFlow diagnostic systemUS 6907383 B2Abstract A flow diagnostic system for a flow sensing element and impulse lines. A pressure transmitter coupled to the impulse lines provides digital pressure data to a control system. The control system provides the pressure data and real time clock readings to a diagnostic application. The diagnostic application calculates a difference between current pressure data and its moving average. A condition of the primary element or impulse lines is diagnosed from a current pressure data set relative to an historical data set. The diagnostic application is downloadable from an application service provider (ASP). The application can run on the control system, a remote computer or the ASP. A diagnostic report is preferably provided.
10. The flow diagnostic system of claim 1 wherein the moving average is calculated according to the series A j = ∑ k = 0 m ⁢ ( P j + k ) ⁢ ( W k ) where A is the moving average, P is a series of sensed pressure values, and W is a weight for a sensed pressure value, m is a number of previous sensed pressure values in the series.
CROSS-REFERENCE TO RELATED APPLICATIONS This is a Continuation-In-Part of U.S. application Ser. No. 09/257,896, filed Feb. 25, 1999 now abandoned which is a Continuation-In-Part of U.S. application Ser. No. 08/623,569, filed Mar. 28, 1996, now U.S. Pat. No. 6,017,143, and this application is also a Continuation-In-Part of U.S. application Ser. No. 09/383,828, filed Aug. 27, 1999 now U.S. Pat. No. 6,654,697.
FIELD OF THE INVENTION The present invention relates to fluid process control systems. In particular, the present invention relates to diagnostic systems for fluid flow in process control systems.
SUMMARY OF THE INVENTION A flow diagnostic system is disclosed for coupling to a primary flow sensing element via impulse lines. The flow diagnostic system may include a pressure transmitter that couples to the impulse lines and generates digital pressure data representing pressure.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic illustration of a flow diagnostic system that diagnoses the condition of impulse lines and/or a primary flow element.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the present invention, a flow diagnostic system is provided that can diagnose the condition of either the primary element or impulse lines connected to a pressure transmitter. A diagnostic application is downloadable over a network from an application service provider (ASP), or can be obtained from a computer-readable medium such as a CD-ROM or removable disc. The diagnostic application can run on the control system, a remote computer or the ASP and provide a diagnostic report. The diagnostic application runs on a processor that is high powered relative to the low power embedded processor found in the pressure transmitter. With the use of the high powered processor, sophisticated diagnostics can be performed in real time and provide prompt reports to a plant operator about the condition of primary elements or impulse lines or both. There is no need to use processing time on the processor imbedded in the transmitter for diagnostics, and the transmitter can perform its measurement tasks rapidly.
FIG. 1 is a schematic illustration of a generalized example of a flow diagnostic system 100 that diagnoses the condition of impulse lines 104 and/or a primary flow element 106 placed in a fluid piping system 108. The impulse lines 104 and the primary element 106 are referred to collectively as a �pressure generator.�
The term �pressure generator� as used in this application means a primary element (e.g., an orifice plate, a pitot tube, a nozzle, a venturi, a shedding bar, a bend in a pipe or other flow discontinuity adapted to cause a pressure drop in flow) together with impulse pipes or impulse passageways that couple the pressure drop from locations near the primary element to a location outside the flow pipe. The spectral and statistical characteristics of this pressure presented by this defined �pressure generator� at a location outside the flow pipe to a connected pressure transmitter 102 can be affected by the condition of the primary element as well as on the condition of the impulse pipes. The connected pressure transmitter can be a self-contained unit, or it can be fitted with remote seals as needed to fit the application. A flange on the pressure transmitter 102 (or its remote seals) couples to a flange adapter on the impulse lines 104 to complete the pressure connections in a conventional manner. The pressure transmitter 102 couples to a primary flow element 106 via impulse lines 104 to sense flow. Primary element 106, as illustrated, is an orifice plate clamped between pipe flanges 105.
In difference algorithm 540, the moving average is calculated according to the series in Eq. 1: A j = ∑ k = 0 m ⁢ ( P j + k ) ⁢ ( W k ) Eq. 1 where A is the moving average, P is a series of sequentially sensed pressure values, and W is a numerical weight for a sensed pressure value, m is a number of previous sensed pressure values in the series. Provision can also be made in difference circuit 540 to filter out spikes and other anomalies present in the sensed pressure. In FIG. 5, the historical data comprises statistical data, for example, the mean (μ) and standard deviation (σ) of the difference output or other statistical measurements, and the diagnostic output 558 indicates impulse line plugging. The diagnostic application switches between a training mode when it is installed and a monitoring mode when it is in use measuring flow as illustrated by switch 550. The calculate algorithm 554 stores historical data in the training mode. The diagnostic data output 558 indicates a real time condition of the pressure generator. In FIG. 5, statistical data, such as the mean μ and standard deviation σ, are calculated based on a relatively large number of data points or flow measurements. The corresponding sample statistical data, such as sample mean X and sample standard deviation s, are calculated from a relatively smaller number of data points. Typically, hundreds of data points are used to calculate statistical data such as μ and σ, while only about 10 data points are used to calculate sample statistical data such as X and s. The number of data points during monitoring is kept smaller in order to provide diagnostics that is real time, or completed in about 1 second. Diagnostic algorithm 556 indicates line plugging if the sample standard deviation s deviates from the standard deviation σ by a preset amount, for example 10%.
Power spectral density, Fi, can also be calculated using Welch's method of averaged periodograms for a given data set. The method uses a measurement sequence x(n) sampled at fs samples per second, where n=1, 2, . . . N. A front end filter with a filter frequency less than fs/2 is used to reduce aliasing in the spectral calculations. The data set is divided into Fk,i as shown in Eq. 2: F k , i = ( 1 / M ) ⁢  ∑ n = 1 M ⁢ X k ⁡ ( n ) ⁢ ⅇ - j2 ⁢ ⁢ π ⁢ ⁢ ⅈ ⁢ ⁢ Δ ⁢ ⁢ f ⁢ ⁢ n  2 Eq. 2 There are Fk,i overlapping data segments and for each segment, a periodogram is calculated where M is the number of points in the current segment. After all periodograms for all segments are evaluated, all of them are averaged to calculate the power spectrum: F ⁢ ⁢ i = ( 1 / L ) ⁢ ∑ k = 1 L ⁢ F k , i Eq. 3 Once a power spectrum is obtained for a training mode, this sequence is stored in memory, preferably EEPROM, as the baseline power spectrum for comparison to real time power spectrums. Fi is thus the power spectrum sequence and i goes from 1 to N which is the total number of points in the original data sequence. N, usually a power of 2, also sets the frequency resolution of the spectrum estimation. Therefore, Fi is also known as the signal strength at the ith frequency. The power spectrum typically includes a large number points at predefined frequency intervals, defining a shape of the spectral power distribution as a function of frequency.
The flow diagnostics system can also be used with a transmitter (not illustrated) which connects to taps near the bottom and top of a tank. The transmitter provides an output that represents a time integral of flow in and out of the tank. The transmitter includes circuitry, or alternatively software, that measures the differential pressure between the taps and computes the integrated flow as a function of the sensed differential pressure and a formula stored in the transmitter relating the sensed pressure to the quantity of fluid in the tank. This formula is typically called a strapping function and the quantity of fluid which has flowed into or out of the tank can be integrated as either volumetric or mass flow, depending on the strapping function stored in transmitter. The transmitter can be located either near the bottom or the top of tank, with a tube going to the other end of the tank, often called a �leg.� This leg can be either a wet leg filled with the fluid in the tank, or a dry leg filled with gas. Remote seals can also be used with such a transmitter.
FIG. 11 is a block diagram of a discrete wavelet transformation. FIG. 11 illustrates an example in which an original set of digital pressure data or signal S is decomposed using a sub-band coder of a Mallet algorithm. The signal S has a frequency range from 0 to a maximum of fMAX. The signal is passed simultaneously through a first high pass filter 250 having a frequency range from � fMAX to fMAX, and a low pass filter 252 having a frequency range from 0 to � fMAX. This process is called decomposition. The output from the high pass filter provides �level 1� discrete wavelet transform coefficients 254. The �level 1� coefficients 254 represent the amplitude as a function of time of that portion of the input signal which is between � fMAX and fMAX. The output from the 0-1/2 fMAX low pass filter 252 is passed through subsequent high pass (� fMAX-� fMAX) filter 256 and low pass (0-� fMAX) filter 258, as desired, to provide additional levels (beyond �level 1�) of discrete wavelet transform coefficients. The outputs from each low pass filter can be subjected to further decompositions offering additional levels of discrete wavelet transformation coefficients as desired. This process continues until the desired resolution is achieved or the number of remaining data samples after a decomposition yields no additional information. The resolution of the wavelet transform is chosen to be approximately the same as the sensor or the same as the minimum signal resolution required to monitor the signal. Each level of DWT coefficients is representative of signal amplitude as a function of time for a given frequency range. Coefficients for each frequency range are concatenated to form a graph such as that shown in FIG. 10.
FIG. 17 illustrates a computer platform 1 that connects via an interface 2 to one of several Hart interchange Devices 4. Interface 2 can be an RS232-RS485 converter, an ethernet connection, an intranet or internet connection, or other suitable interface that communicates information to the computer platform 1. The computer platform 1 is typically a personal computer located in a maintenance shop area that includes application software such as an Asset Management Solutions (AMS) software application from Rosemount Inc. Each Hart interchange devices 4 couples to one or more pressure transmitters 6 via a termination panel 8. The Hart interchange devices 4 are coupled via a DIN rail or bus 10 to a control system 12. A diagnostic application 14 as described above in connection with FIGS. 1-16 also resides on computer platform 1. Computer platform 1 provides a diagnostic report as explained above. The arrangement illustrated in FIG. 17 allows substantially all of the diagnostic software to run on computer platform 1 (which is a small control system) rather than place additional overhead on control system 12. The term �control system� as used in this application includes control systems such as control system 112 in FIG. 1 which provide electrical feedback to a fluid processing plant as well as computers that perform a monitoring function such as computer platform 1, where the feedback to the fluid processing plant comprises human intervention based on a diagnostic report generated by the computer platform 1.
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(1997).104Web Pages from www.triant.com (3 pgs.).* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS7231305 *Aug 5, 2004Jun 12, 2007Schlumberger Technology CorporationFlow rate determinationUS7254518 *Mar 15, 2004Aug 7, 2007Rosemount Inc.Pressure transmitter with diagnosticsUS7289863Aug 18, 2005Oct 30, 2007Brooks Automation, Inc.System and method for electronic diagnostics of a process vacuum environmentUS7349746Aug 26, 2005Mar 25, 2008Exxonmobil Research And Engineering CompanySystem and method for abnormal event detection in the operation of continuous industrial processesUS7406387 *Mar 22, 2007Jul 29, 2008Yokogawa Electric CorporationApparatus and method for detecting blockage of impulse linesUS7424395Aug 26, 2005Sep 9, 2008Exxonmobil Research And Engineering CompanyApplication of abnormal event detection technology to olefins recovery trainsUS7451003 *Mar 4, 2004Nov 11, 2008Falconeer Technologies LlcMethod and system of monitoring, sensor validation and predictive fault analysisUS7480577Feb 21, 2007Jan 20, 2009Murray F FellerMultiple sensor flow meterUS7567887Aug 26, 2005Jul 28, 2009Exxonmobil Research And Engineering CompanyApplication of abnormal event detection technology to fluidized catalytic cracking unitUS7577543 *Feb 6, 2006Aug 18, 2009Honeywell International Inc.Plugged impulse line detectionUS7680460 *Jan 3, 2005Mar 16, 2010Rosemount Inc.Wireless process field device diagnosticsUS7680549Apr 4, 2006Mar 16, 2010Fisher-Rosemount Systems, Inc.Diagnostics in industrial process control systemUS7720641Apr 13, 2007May 18, 2010Exxonmobil Research And Engineering CompanyApplication of abnormal event detection technology to delayed coking unitUS7756678 *May 29, 2008Jul 13, 2010General Electric CompanySystem and method for advanced condition monitoring of an asset systemUS7761172Mar 16, 2007Jul 20, 2010Exxonmobil Research And Engineering CompanyApplication of abnormal event detection (AED) technology to polymersUS7765873Jul 18, 2008Aug 3, 2010Rosemount Inc.Pressure diagnostic for rotary equipmentUS7770459Jul 18, 2008Aug 10, 2010Rosemount Inc.Differential pressure diagnostic for process fluid pulsationsUS7835295Jul 19, 2005Nov 16, 2010Rosemount Inc.Interface module with power over Ethernet functionUS7949495 *Aug 17, 2005May 24, 2011Rosemount, Inc.Process variable transmitter with diagnosticsUS7957708Mar 2, 2005Jun 7, 2011Rosemount Inc.Process device with improved power generationUS8000816 *Feb 28, 2004Aug 16, 2011Abb Research LtdProcess control system and method for operating a system of this typeUS8005645Feb 23, 2007Aug 23, 2011Exxonmobil Research And Engineering CompanyApplication of abnormal event detection technology to hydrocracking unitsUS8032234May 16, 2006Oct 4, 2011Rosemount Inc.Diagnostics in process control and monitoring systemsUS8188359Sep 28, 2006May 29, 2012Rosemount Inc.Thermoelectric generator assembly for field process devicesUS20090044181 *Aug 6, 2007Feb 12, 2009Vrba Joseph AGraphics Tools for Interactive Analysis of Three-Dimensional Machine Data* Cited by examinerClassifications U.S. Classification702/183, 702/47, 73/1.57, 73/1.71, 702/100International ClassificationG05B23/02, G01F25/00, G01F1/00, G01F1/34, G01L19/00, G05B21/02, G01F1/50, G05B13/02, G01F1/36, G05D7/06Cooperative ClassificationG05B13/0275, G01F1/363, G05D7/0617, G01F25/0007, G05B21/02, G01F1/50European ClassificationG01F25/00A, G01F1/36A, G05B21/02, G01F1/50, G05D7/06F, G05B13/02C2Legal EventsDateCodeEventDescriptionDec 14, 2012FPAYFee paymentYear of fee payment: 8Dec 11, 2008FPAYFee paymentYear of fee payment: 4May 9, 2001ASAssignmentOwner name: ROSEMOUNT INC., MINNESOTAFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ERYUREK, EVREN;KAVAKLIOGLU, KADIR;REEL/FRAME:011800/0646Effective date: 20010504Owner name: ROSEMOUNT INC. 12001 TECHNOLOGY DRIVEEDEN PRAIRIE,Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ERYUREK, EVREN /AR;REEL/FRAME:011800/0646RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google