WO1994022025A1 - Detection des parametres d'exploitation par surveillance des densites spectrales de puissance - Google Patents

Detection des parametres d'exploitation par surveillance des densites spectrales de puissance Download PDF

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Publication number
WO1994022025A1
WO1994022025A1 PCT/US1994/003067 US9403067W WO9422025A1 WO 1994022025 A1 WO1994022025 A1 WO 1994022025A1 US 9403067 W US9403067 W US 9403067W WO 9422025 A1 WO9422025 A1 WO 9422025A1
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WO
WIPO (PCT)
Prior art keywords
output signal
current
signal
data
plant
Prior art date
Application number
PCT/US1994/003067
Other languages
English (en)
Inventor
Raymond Donald Bartusiak
Douglas Hugh Nicholson
Original Assignee
Exxon Chemical Patents Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Exxon Chemical Patents Inc. filed Critical Exxon Chemical Patents Inc.
Priority to AU64133/94A priority Critical patent/AU6413394A/en
Publication of WO1994022025A1 publication Critical patent/WO1994022025A1/fr

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Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B21/00—Systems involving sampling of the variable controlled
    • G05B21/02—Systems involving sampling of the variable controlled electric
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16—Spectrum analysis; Fourier analysis
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • G05B23/0229—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
    • H02H3/00—Emergency protective circuit arrangements for automatic disconnection directly responsive to an undesired change from normal electric working condition with or without subsequent reconnection ; integrated protection
    • H02H3/006—Calibration or setting of parameters

Definitions

  • This invention relates to process control systems, and more particularly, to a system for determining whether a process parameter is in a steady or unsteady state through a use of the parameter's power spectral density.
  • process control systems In controlling dynamic plant process, it is often necessary to know whether process variables are in a steady state or in an unsteady state. While, many process control systems monitor plant variables and compare them against predetermined set points, it is often more important to know whether deviations of a plant variable, over time, away from a set point are significantly different from normal. It is also important to be able to predict whether a plant parameter output exhibits an incipient condition which may lead to an unsteady state.
  • US-A-4,303,979 discloses a system for monitoring frequency spectrum variations in output signals.
  • the system initially determines a root mean square (RMS) average frequency value for an input signal.
  • RMS root mean square
  • the system determines RMS values for each of a plurality of frequency subranges within the input signal.
  • the system then monitors an input test signal and obtains its RMS value and the average frequency of the overall input signal. If the determined reference and test frequencies differ substantially in their RMS and average frequency values, the RMS value and average frequency values, the RMS value and average frequency of an anomalous frequency component peak is calculated.
  • the average of the anomalous frequency component is then compared to boundary frequency values to determine in which frequency range the anomalous value lies.
  • the RMS value of the thus determined frequency range and the average frequency are then employed to determine correction parameters.
  • US-A-4,965,757 discloses a process and device for decoding a received, encoded signal.
  • the received signal is first filtered, sampled and digitized before being stored. Digitized samples of each successive signal block are transposed to the frequency domain by a fast Fourier transform. The thus computed spectra are compared with stored theoretical values for each possible code signal in order to identify the received encoded signal.
  • US-A-3,883,726 discloses a fast Fourier transform algorithm computer that utilizes an attenuated input data window.
  • An input buffer receives input time samples, a cosine square attenuator superimposes a cosine squared shape on the input data samples, and then the resultant signal is passed to the fast Fourier analysis computer.
  • a delay device, adders and an output buffer are provided for removing the effect of the attenuating input data window.
  • US-A-4,975,633 discloses a spectrum analyzer that displays spectrum data and power values of a radio frequency (RF) or optical signal.
  • An input signal is directed down one path where it is subjected to a spectrum analysis, and down a second path where its power value is determined.
  • Display means indicates both the spectrum data and the power value.
  • RF radio frequency
  • US-A-5,087,873 discloses apparatus for detecting a corrosion state of buried metallic pipe.
  • a spectrum analyzer receives input signals from a pair of magnetometers.
  • the magnetic field is determined by conducting a fast Fourier transform on the received signals, with the resulting spectrum indicating the amplitude and phase of the magnetic field. Those values are used to determine the condition of the buried pipe.
  • US-A-4,824,016 discloses an acoustical process for monitoring the operating state of a feed nozzle injecting a mixture of liquid and gas into a process vessel.
  • the system initially determines a reference power spectrum for the nozzle when it is performing in a standard condition. Then, a second determination is made at a later time, a current power spectrum, when it is suspected that performance has deteriorated. Based on the difference between the reference and current power spectras action may be taken, which may include adjustment of the flow rates to the nozzle, so that the nozzle operates under the original reference power spectra.
  • the analysis methods for examination of the power spectra include a human observer, a simple computer pattern recognition algorithm, or time variation of the signal.
  • US-A-5,201,292 describes a system for detecting vibration patterns and indicates the derivation of spectral components and energy levels. Its spectral components are combined into a single value (by auto correlation) and are not individually utilized (see col. 3, lines 55-61). The single value is compared with immediately preceding threshold spectra which has been dynamically adapted in accordance with changed system conditions. (See col. 5, lines 33-42). Substantial lengths are taken to adapt the reference threshold to take into account the most recent changes in the monitored plant data.
  • a method for determining a current state of a plant process variable output signal and whether the output signal is within acceptable limits comprising the steps of:
  • step (f) further indicates the common frequency for which the signal is issued.
  • the signal in step (f) is issued after a ratio of energies of each common frequency is determined and it is determined that at least one ratio exceeds a predetermined factor. Steps (b) and/or (e) may perform the method as recited above using
  • the method of the invention may be performed in plants which utilize process control systems, such as in refineries or petrochemical plants. DESCRIPTION OF THE DRAWINGS
  • Fig. 1 is a block diagram of a system for performing the method of the invention
  • Figs. 2a and 2b are high level flow diagrams illustrating the method of the invention
  • Fig. 3 is a plot of a variation in flow over time in an exemplary plant
  • Fig. 4 is a semi-log plot of energy versus frequency derived from the signal shown in Fig. 3;
  • Fig. 5 is a plot of flow vs. time showing a negative-going ramp disturbance;
  • Fig. 6 is a semi-log plot of energy vs. frequency of the plot of Fig. 5 indicating [the] that the ramp disturbance produces the most severe violation of plotted energy thresholds in the low frequency range;
  • Fig. 7 is a plot of flow vs. time showing a "U" type disturbance in the flow signal;
  • Fig. 8 is a semi-log plot of energy vs. frequency of the plot of Fig. 7 indicating, at one energy threshold, that a disturbance exceeds the threshold.
  • the system and method for carrying out the invention determine whether a plant process is operating within a steady state or a non-steady state condition.
  • the system determines a reference power spectral density (PSD) of a process variable, during a time that the process variable is in a steady state.
  • PSD power spectral density
  • the reference PSD is then compared with a current PSD derived when the process variable is in operation.
  • a power spectral density is a representation of an energy content of a signal as a function of its component frequencies and is computed via a fast Fourier transform (FFT) which converts a time-domain signal into its frequency-domain representation.
  • FFT fast Fourier transform
  • flow monitors 10 and 12 continuously monitor the state of flow in a pair of pipes 14 and 16, respectively.
  • Pipes 14 and 16 form portions of a plant whose process variables are continuously monitored to determine if any one has moved from a steady state to an unsteady state.
  • system variables e.g. pressure, volume, temperature, etc.
  • the outputs from each of flow monitors 10 and 12 are fed to respectively connected analog to digital converters (A/D) 18, 20 whose outputs are, in turn, connected to a bus 22 that forms the main communication pathway in a control data processing system.
  • A/D analog to digital converters
  • a central processing unit (CPU) 24 is interconnected with bus 22 and also is connected to A/D converters 18 and 20 to enable timed, sample signals to be derived therefrom.
  • a read only memory (ROM) 24 is connected to bus 22 and contains a procedure for operating CPU 24 to monitor sensors 10, 12 and a procedure for enabling CPU 24 to perform a fast Fourier transform (FFT) of input data received from A/D converters 18 and 20.
  • a random access memory (RAM) 26 is connected to bus 22 and contains allocated memory for storing: raw input data from A/D converters 18 and 20; reference PSD data determined during a time that a process variable being monitored is in a steady state; and current PSD data that is determined when the process variable is being currently monitored.
  • a steady state (i.e. reference) PSD is determined for a monitored process variable.
  • the steady state PSD is derived by initially sampling a process variable output signal when the plant is operating in a steady state condition (box 30). To avoid contamination of the steady state PSD, the output signal is filtered to remove any aperiodic signals therefrom (box 32). The filtered, periodic signal is then subjected to an FFT analysis by central processor 24, under control of a procedure read out from ROM 24 (box 34).
  • the result of the PSD analysis is a series of frequency values ( ⁇ j) for the filtered steady state signal, each frequency value ( ⁇ j) having an attribute associated therewith that is equivalent to the energy contained in the particular frequency signal.
  • Those frequencies and energy value attributes are stored in RAM 26 as steady state (or reference) PSD data.
  • a user-supplied multiplier factor is accessed that is to be applied to each energy value attribute of the steady state PSD.
  • the multiplier factor enables the derivation of an energy threshold which is the amount that a process variable's current PSD must exceed a reference PSD to be considered in an unsteady state (box 36).
  • Fig. 1 now switches to a "current" monitor state wherein it monitors the outputs of sensors 10, 12, etc.
  • a sensor e.g. 10
  • CPU 24 commences the current monitor state by sampling output signals from a sensor (e.g. 10) during operation of the plant (Box 38). After sufficient samples have been accumulated, CPU 24 filters the sampled current output signal to remove aperiodic components (box 39), and then computes a PSD ( ⁇ j) for the sampled current output signal using an FFT procedure (box 40).
  • Figs. 3-8 contain examples of the procedure described above.
  • a process variable flow
  • a reference flow during steady state of the same process variable was monitored and a reference PSD was derived (e.g. dotted trace 100 in Fig. 4).
  • Reference PSD trace 100 has been quantized into ten "bins" so as to enable averaged comparisons to be made.
  • the PSD for the signal of Fig. 3 is then calculated (trace 102) and is seen to exhibit considerable variations in power over the frequency spectrum. Note that no portion of current PSD trace 102 exceeds reference PSD trace 100, so it is assumed that the system flow signal indicated in Fig. 3 is within the steady state.
  • a ramp disturbance 103 is plotted (flow vs. time). Furthermore, for exemplary purposes only, it is assumed that two multiplier factors (e.g. 1.0 and 1.5) have been utilized to derive energy PSD thresholds 108, 110 respectively.
  • the conversion of ramp signal 103 to a PSD results in energy versus frequency trace 106 shown in Fig. 6. Note that the ramp disturbance 103 produces the most severe violation of both PSD energy thresholds 108 and 110 in the low frequency range. Under such conditions, an alarm is generated.
  • the system may be adjusted such that an alarm in inhibited from issuance if only energy threshold 108 is exceeded, however the frequencies at which the energy exceeds threshold 108 may be output for user monitoring of a possibly incipient instability mode.
  • a "U" disturbance 113 is depicted in a plot of flow versus time. Over the span of the time during which the flow is monitored in Fig. 7, the flow difference is not large and yet it is clear that a disturbance does occur. As shown by Fig. 8, such disturbance is picked up by comparison of the peak corresponding PSD trace 112 with energy threshold 114.
  • the method of the invention may be performed in plants which utilize process control systems, including but not limited to, refineries and petrochemical plants.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Mathematical Physics (AREA)
  • Testing And Monitoring For Control Systems (AREA)

Abstract

L'invention se rapporte à un procédé pour déterminer à quel moment un signal de sortie variable se trouve dans un état de régime permanent ou dans un état de régime non permanent, la technique de détection du signal étant dépendante des densités spectrales de puissance. A cet effet, on établit des données de référence d'abord en échantillonnant un signal de sortie variable du processus d'exploitation, pendant que l'installation d'exploitation fonctionne en régime permanent. Le signal de sortie ainsi échantillonné est ensuite analysé pour dériver les données de référence relatives notamment à un contenu en énergie de chacune de ses composantes de fréquence. On établit ensuite une base de données de fonctionnement en cours, en échantillonnant un signal variable de processus, pendant que l'installation d'exploitation est en fonctionnement. Le signal de sortie en cours ainsi échantillonné est analysé pour dériver des données en cours qui se réfèrent notamment à un contenu en énergie de chacune de ses composantes de fréquence. Pour chaque composante de fréquence commune des données de référence et des données en cours, le système établit une comparaison entre les contenus en énergie et émet un signal de régime non permanent lorsque la comparaison indique que les contenus en énergie comparés dépassent une limite prédéterminée.
PCT/US1994/003067 1993-03-22 1994-03-22 Detection des parametres d'exploitation par surveillance des densites spectrales de puissance WO1994022025A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU64133/94A AU6413394A (en) 1993-03-22 1994-03-22 Plant parameter detection by monitoring of power spectral densities

Applications Claiming Priority (2)

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US3405893A 1993-03-22 1993-03-22
US08/034,058 1993-03-22

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1996006360A1 (fr) * 1994-08-25 1996-02-29 Siemens Aktiengesellschaft Procede et systeme permettant de surveiller des reseaux d'alimentation en courant
WO1996018110A1 (fr) * 1994-12-09 1996-06-13 Exxon Chemical Patents Inc. Evaluation des parametres d'une installation par controle continu des densites spectrales de puissance
US5824888A (en) * 1995-01-11 1998-10-20 Linnhoff March Limited Fluid efficiency
FR2780498A1 (fr) * 1998-06-29 1999-12-31 Didier Cugy Procede de representation cartographique de spectre energetique et systeme permettant la mise en oeuvre de ce procede
EP2386867A3 (fr) * 2010-05-13 2013-07-03 Tektronix, Inc. Reconnaissance et déclenchement de signaux utilisant des techniques de vision informatique
US8995080B1 (en) 2014-09-30 2015-03-31 Seagate Technology Llc Non-destructive detection of slider contamination
CN113739841A (zh) * 2021-06-22 2021-12-03 西安西热节能技术有限公司 一种基于不确定度理论的多变量稳态检测方法及***

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS5690220A (en) * 1979-12-24 1981-07-22 Hitachi Ltd Abnormal oscillation diagnostic device
US4303979A (en) * 1977-04-18 1981-12-01 Hitachi, Ltd. Frequency spectrum variation monitoring system
JPS62245931A (ja) * 1986-04-18 1987-10-27 Toshiba Corp 振動監視装置
US5032826A (en) * 1987-10-29 1991-07-16 Westinghouse Electric Corp. Core monitor that uses rotor shaft voltages

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4303979A (en) * 1977-04-18 1981-12-01 Hitachi, Ltd. Frequency spectrum variation monitoring system
JPS5690220A (en) * 1979-12-24 1981-07-22 Hitachi Ltd Abnormal oscillation diagnostic device
JPS62245931A (ja) * 1986-04-18 1987-10-27 Toshiba Corp 振動監視装置
US5032826A (en) * 1987-10-29 1991-07-16 Westinghouse Electric Corp. Core monitor that uses rotor shaft voltages

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
PATENT ABSTRACTS OF JAPAN vol. 12, no. 119 (P - 689) 14 April 1988 (1988-04-14) *
PATENT ABSTRACTS OF JAPAN vol. 5, no. 157 (P - 083) 8 October 1981 (1981-10-08) *

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1996006360A1 (fr) * 1994-08-25 1996-02-29 Siemens Aktiengesellschaft Procede et systeme permettant de surveiller des reseaux d'alimentation en courant
US5966675A (en) * 1994-08-25 1999-10-12 Siemens Aktiengesellschaft Method and device for monitoring power supply networks
WO1996018110A1 (fr) * 1994-12-09 1996-06-13 Exxon Chemical Patents Inc. Evaluation des parametres d'une installation par controle continu des densites spectrales de puissance
AU699254B2 (en) * 1994-12-09 1998-11-26 Exxon Chemical Patents Inc. Plant parameter detection by monitoring of power spectral densities
US5824888A (en) * 1995-01-11 1998-10-20 Linnhoff March Limited Fluid efficiency
FR2780498A1 (fr) * 1998-06-29 1999-12-31 Didier Cugy Procede de representation cartographique de spectre energetique et systeme permettant la mise en oeuvre de ce procede
EP2386867A3 (fr) * 2010-05-13 2013-07-03 Tektronix, Inc. Reconnaissance et déclenchement de signaux utilisant des techniques de vision informatique
US9164131B2 (en) 2010-05-13 2015-10-20 Tektronix, Inc. Signal recognition and triggering using computer vision techniques
US8995080B1 (en) 2014-09-30 2015-03-31 Seagate Technology Llc Non-destructive detection of slider contamination
CN113739841A (zh) * 2021-06-22 2021-12-03 西安西热节能技术有限公司 一种基于不确定度理论的多变量稳态检测方法及***

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