JP2010092173A - Process diagnostic method and system thereof - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To diagnose a process on the basis of process information of a system that performs management control in an existing digital instrumentation control system, with less costs for updating process equipment without deciding FMEA information or a parameter. <P>SOLUTION: The process diagnostic system is provided with: DCS equipment 1; a database device 2 for storing at least input information and output information to be managed and controlled by the DCS device 1 and a target value to be controlled into a database; an IAE (Integral Absolute Error) calculation means 4 for calculating the integration value of a difference absolute value between input information and the target value, and for creating diagnostic data; a correlation means 5 for creating plot data by plotting the input information and output information on a two-dimensional plane as X and Y axes; a trend monitoring means 6 for time-sequentially storing the diagnostic data created by the IAE calculation means 4 and the plot data created by the correlation means 5, and for generating trend information; and a display/print means 7 for displaying or printing the trend information generated by the trend monitoring means 6. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a process diagnosis method and system, and more particularly to a process diagnosis method and system for diagnosing process equipment and control logic in a plant that is managed and controlled by a digital instrumentation control system.

  Conventionally, a process data input means for inputting a process signal from each device of the plant and outputting an actual measurement signal corresponding to the process signal, a physical model calculation means for outputting a simulation signal corresponding to the actual measurement signal, an actual measurement signal, An abnormal sign monitoring means for inputting a simulated signal and outputting a monitoring signal for the presence or absence of an abnormal sign based on the difference between the two, and a location indicating the abnormal sign based on the monitoring signal of the abnormal sign monitoring means is determined in advance. There has been proposed a plant diagnostic apparatus including an abnormal sign location identifying means for identifying by logic (see, for example, Patent Document 1).

  A process control system comprising a field device for use in a process control network having a plurality of devices coupled by a two-wire all-digital communication bus to enable communication, the field device comprising: Connector for connecting a device to a two-wire all-digital communication bus, enabling all-digital communication on the bus, memory for storing a diagnostic test routine having a series of device diagnostic test instructions or process diagnostic test instructions, and storing in memory A process control system has been proposed that includes a controller that executes a device diagnostic test instruction or a process diagnostic test instruction that is performed and implements a device or process diagnostic test using a field device (see, for example, Patent Document 2). ).

JP-A-8-6635 (paragraph 0007, FIG. 1) JP 2001-524226 A (summary column, FIG. 11A)

  The technique disclosed in Patent Document 1 compares a parameter determined by process characteristics with an actual signal, and refers to failure mode evaluation analysis information (hereinafter referred to as FMEA information) based on the difference information. To diagnose. Further, the technique disclosed in Patent Document 2 means a sensor or operating means (equipment that actually outputs a control output as a control target) equipped with a fieldbus function. For example, a configuration of a valve and an actuator that operates the valve Body etc.) performs self-diagnosis and sucks up the self-diagnosis information to the host side for analysis diagnosis.

  In both cases, the diagnosis information is often carried out at the site of the customer who performed the diagnosis, and the diagnosis is not carried out continuously over the long term. At this point, the diagnosis is often made for the purpose of pursuing the cause, and the former process diagnosis or the like is often performed as a simulation calculation.

  However, the technique disclosed in Patent Document 1 has a problem that it is very difficult to determine parameters determined by process characteristics, and that considerable effort is required to construct FMEA information. Further, the technique disclosed in Patent Document 2 has a problem that can only be implemented by a sensor or operation means equipped with a fieldbus function. However, there is a problem that the introduction cost is great. Furthermore, there is also a problem that the diagnosis itself is pursuing the cause after some problem.

  The present invention has been made in order to solve the above-described problems, eliminates the need to determine FMEA information and parameters that require labor for construction, and suppresses the update cost of process equipment and the like. The present invention provides a process diagnosis method and system for performing process diagnosis from process information possessed by a system that performs management control in a packaging control system.

  The process diagnosis method according to the present invention is an absolute value of a difference between input information managed and controlled by the digital instrumentation control system and a target value to be controlled in the process diagnosis method for a plant managed and controlled by a digital instrumentation control system. And the process of the plant is diagnosed based on the integrated value of the absolute difference.

  In addition, the process diagnosis system according to the present invention includes input information and output information of a plant, a digital instrumentation control system for managing and controlling at least a target value to be controlled, and input information managed and controlled by the digital instrumentation control system. A database device that at least stores the output information and the target value to be controlled as a database, an IAE calculation means for calculating an integrated value of the difference absolute value between the input information and the target value, and creating diagnostic data, and the input information Correlation means for plotting the output information on the two-dimensional plane with the X and Y axes respectively and creating plot data, diagnostic data created by the IAE calculation means, and plot data created by the correlation means Trend monitoring means for storing trend information and generating trend information, and trend information generated by the trend monitoring means It is obtained and a display and printing means for displaying or printing.

  According to the present invention, diagnosis is performed based on time-series data by performing diagnosis from the process information possessed by the system performing management control in the digital instrumentation control system, and the time of the diagnosis result is By observing the trend of the series, preventive maintenance process diagnosis can be performed, and abnormalities in process equipment, review of control loop parameters, etc. can be provided. Therefore, the production efficiency of the process can always be kept at a high level.

  Preferred embodiments of a process diagnosis method and system according to the present invention will be described below with reference to the accompanying drawings. Note that the present invention is not limited to these embodiments.

Embodiment 1 FIG.
FIG. 1 is a block configuration diagram of a process diagnosis system for explaining a process diagnosis method according to Embodiment 1 of the present invention. In FIG. 1, a process diagnosis system 100 includes a digital instrumentation control system (hereinafter referred to as a DCS device) 1 that performs control calculation and input / output for controlling a process, and a database device 2 connected to the DCS device 1. And a distribution means 3 for extracting process information necessary for process diagnosis from the DCS apparatus 1 or the database apparatus 2 and distributing the extracted data. Further, the process diagnosis system 100 includes an IAE (Integral Absolute Error) calculation unit 4, a correlation unit 5, a trend monitoring unit 6, and a display / printing unit 7.

  As will be described later, the distribution means 3 sends any tag from the DCS device 1 and the database device 2 to the IAE calculation means 4, the correlation means 5, and the trend monitoring means 6 from a certain time to a certain time. The data of (sometimes all tags) is extracted and distributed as specified tag data by looking at the time stamp. The IAE calculation means 4 includes a diagnostic data file 8, and the correlation means 5 includes a plot data file 9.

  The DCS device 1 has a control loop for managing and controlling the process. An input signal (hereinafter referred to as PV) from the sensor is taken into the control loop, the control calculation is performed, and the control calculation result is output. As a signal (hereinafter referred to as MV), for example, a device that actually outputs a control output as a control target, such as a structure including a valve and an actuator that operates the valve, is operated. In addition, the control calculation has a target value (hereinafter referred to as SV) for bringing the process to a certain value, and the DCS device 1 has these PV, SV, MV, and control mode (automatic, manual, etc.). is doing.

The database device 2 stores the information that the DCS device 1 has as a database, and is provided as an internal configuration of the DCS device 1 or as an external device. It is configured so that it can be captured. The database device 2 stores time stamps, tag information, and data in a database. For example, in the case of PV, SV, MV of TC101 at 1: 05: 0 on March 14, 2008,
20080313010500 TC101 PV 100.0
20080313010500 TC101 SV 50.0
20080313010500 TC101 MV 60.0
This set is a database. Note that TC101 is tag information and encodes a diagnosis target such as a heavy oil flow rate, a coal supply amount, and a steam flow rate.

  The IAE calculation means 4 takes in process information distributed by the distribution means 3 from the DCS apparatus 1 or the database apparatus 2 to calculate an integrated value of the absolute difference value of PV-SV and creates a diagnostic data file 8 Specifically, the operation is as shown in the flowchart of FIG.

  That is, in FIG. 2, the tag and period data (PV, SV, MV, mode, etc.) designated via the distribution means 3 are fetched from the DCS device 1 or the database device 2 (step S20), and the PV-SV An integrated value of the absolute difference is calculated (step S21). Then, the variance and standard deviation are calculated (step S22), and the variance and standard deviation are calculated and the automatic mode input rate is calculated (step S23). Thereafter, information for display and storage is filed (step S24), and a diagnostic data file 8 is created.

  The correlation means 5 plots the PV and MV values on the two-dimensional plane with the X and Y axes as the X and Y axes, respectively. That is, the plot data file 9 is created by taking in data for a certain period from the DCS apparatus 1 or the database apparatus 2 via the distribution means 3 and calculating the correlation between PV and MV. It operates as shown in the flowchart of FIG.

  That is, in FIG. 3, the specified tag and period data (PV, MV) are fetched from the DCS device 1 or the database device 2 via the distribution means 3 (step S30), and the PV is normalized to 0-100%. (Because PV is an engineering value, it is normalized to%) (step S31). Then, the normalized PV is taken on the X axis and the MV is taken on the Y axis, and plotted in two dimensions (step S32). Thereafter, information for display and storage is filed (step S33), and the plot data file 9 is created.

  Further, the trend monitoring means 6 saves the diagnosis results from the IAE calculation means 4 and the correlation means 5 in time series, so that the trend monitoring means 6 saves them with a time stamp, and further, a trend for viewing the tendency of the diagnosis results at a certain point. It generates information and operates in detail as shown in the flowchart of FIG.

  That is, in FIG. 4, a plurality of designated diagnostic data or plot data are fetched from the diagnostic data file 8 created by the IAE calculation means 4 and the plot data file 9 created by the correlation means 5 (step S40). Then, in the case of diagnostic data, the IAE, distribution, and automatic mode input rate are time-seriesd by the number of cases, and in the case of plot data, the display color for each case is changed and defined (step S41), and data display information is created (step S41). Step S41).

  The display / printing means 7 is means for displaying the diagnostic data created by the IAE calculating means 4 and the plot data created by the correlation means 5 on the display / printing means 7 by the trend monitoring means 6. The plot data created by the correlation unit 5 is displayed on the display / printing unit 7 in a superimposed manner with the display color of each case being changed by the trend monitoring unit 6. The diagnostic data created by the IAE calculation means 4 is a mere trend display. For example, the same tag is displayed at 10:00 on May 16, 2008, 11:00 on May 23, 2008, and 17:00 on May 30, 2008. If the diagnosis is performed, information such as IAE that is the result of each diagnosis is displayed on the display / printing means 7 by the trend monitoring means 6 as a trend. If the number of diagnoses is small, several points are displayed on the trend display.

  FIG. 5 shows a display example of diagnostic data created by the IAE calculation means 4, and FIG. 5 will be described next. Although the display order is initially displayed in the order of the tags designated by diagnosis, it can be sorted in the order of increasing IAE value or in order of increasing automatic mode input rate. In the display example, the automatic mode input rate (A input rate in the table) is sorted in descending order of IAE value.

  In FIG. 5, the display items are described from the left column. The tag number to be diagnosed (in FIG. 5, TAG No. is displayed and left blank for convenience), the service name added to the tag name, and the target tag Range lower limit value (RL), upper limit value (RH), unit, and tag type. The information up to this point is unique information of the tag itself, and collects what can be collected at the time of data collection. However, those that could not be collected are not collected nor displayed. A tag number is necessary as a minimum item.

  Next, the maximum period represents a period in which data is collected. If 60, 60 seconds, that is, a period of 1 minute, is collected by the IAE calculation unit 4. The IAE is the IAE value calculated by the IAE calculation means 4, and the constant SV indicates whether the SV has changed or not during the diagnosed period, and indicates that the SV is constant without any change. Display the mark. The average is the average value of the PV values during the diagnosis period, σ and σ (%) are the variance values of PV, and (%) is the variance value normalized by 0-100% because the range is different for each tag. It is shown. The A input rate is a ratio of a period in which the automatic mode is input in the diagnosed period, and 100% indicates that the automatic mode is in the target period. A value that is not 100% indicates that the manual mode has been entered during the period.

  Looking at the IAE value that is the display result, the larger the value, the greater the deviation during the diagnosis target period. A large deviation in control means that control is lacking in stability, indicating that the control parameters are not appropriate, the control system is bad, or that it is greatly affected by other loops. Improvement will be implemented. Further, a large IAE value and a large dispersion σ indicate that PV is greatly swaying, so that it is understood that the stability is lacking.

  The correlation between PV and MV calculated by the correlating means 5 normally operates following the PV value when a valve is considered as the operating means. The X axis is PV and the Y axis is MV. Usually, the region distribution is as shown in FIG. However, unlike the region distribution, if the locus of MV is long and horizontal even though PV is changed, it can be understood that the valve is not functioning normally. If the valve as the operation means does not function normally, the control is not performed normally, and the stability of the control is greatly shaken.

  As described above, according to the process diagnosis method and the system thereof according to the first embodiment, the time series data is obtained by analyzing the process information of the system that performs the management control in the distributed control system. By providing diagnosis results to the base and observing the chronological trend of the diagnosis results, it is possible to perform preventive and maintenance process diagnosis, and to provide process equipment abnormalities and review of control loop parameters. Therefore, the production efficiency of the process can always be kept at a high level.

Embodiment 2. FIG.
Next, a process diagnosis method and system according to Embodiment 2 of the present invention will be described. FIG. 7 is a block diagram of a process diagnosis system for explaining a process diagnosis method according to Embodiment 2 of the present invention. The process diagnosis method and system according to the second embodiment are configured so that the process information necessary for the process diagnosis extracted from the DCS device and the database device described in the first embodiment is not a network location, but a network. Is a process diagnosis method and system for collecting the data in a server of a diagnosis center connected by, performing sequential diagnosis, and submitting the result as a diagnosis report to a customer in which a DCS device is installed.

  The process diagnosis method and system according to the second embodiment will be described below with reference to FIG. In FIG. 7, the process diagnosis system 200 has a configuration in which a plurality of DCS devices 1 or a plurality of database devices 2 are connected to a network 70 and a distribution unit 3 is connected. The distribution unit 3, the IAE calculation unit 4, the correlation unit 5, the trend monitoring unit 6, and the display / printing unit 7 are provided in the diagnostic center 71. Note that the configuration and operation of each device and each unit are as described in the first embodiment, and the same reference numerals are given and redundant description is omitted.

  The process diagnosis system 200 according to the second embodiment performs a diagnosis, submits the diagnosis result as a report to the customer of each DCS device 1 and each database device 2, and periodically diagnoses it. It becomes possible to estimate which point of the process has deteriorated. The deterioration mentioned here is not only mechanical deterioration but also that IAE is increasing in time series, and it is predicted that the parameter for the control calculation of the control loop is not the optimum value. That is, this is parameter degradation. Furthermore, there is a point of deterioration of logic that may be a review of the control arithmetic logic itself, not the parameters.

  In the PV-MV correlation, the plotted points are usually arranged on a certain curve. However, if the sensor is unstable, the zero point drifts, the signal is fixed due to a failure, etc. It will deviate from the curve. On the other hand, if the operation means does not operate according to the specified MV due to mechanical looseness or distortion, it deviates from the normal curve. Thereby, abnormality of a sensor or an operation means can be detected.

  As described above, according to the process diagnosis method and system thereof according to the second embodiment, the diagnosis is not performed at the customer site, but is performed at the diagnosis center 71 connected by the network 70, and the result is periodically transmitted. Can be promoted to preventive maintenance.

  The process diagnosis method and system according to the present invention are applied to a plant system that manages the operation of a sensor or a valve so that the oil feed amount is always within a certain range, like an oil feed device in an oil plant system. Available.

1 is a block configuration diagram of a system for explaining a process diagnosis method according to Embodiment 1 of the present invention. It is an operation | movement flowchart of an IAE calculation means. It is an operation | movement flowchart of a correlation means. It is an operation | movement flowchart of a tendency monitoring means. It is a figure which shows the example of a display of the diagnostic data produced by the IAE calculation means. It is explanatory drawing about the correlation of the input signal calculated by a correlation means, and an output signal. It is a block block diagram explaining the process diagnostic system which concerns on Embodiment 2 of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Digital instrumentation control system 2 Database apparatus 3 Distribution means 4 IAE calculation means 5 Correlation means 6 Trend monitoring apparatus 7 Display / printing means 8 Diagnosis data file 9 Plot data files 100 and 200 Process diagnosis system

Claims (4)

  In a process diagnosis method for a plant managed and controlled by a digital instrumentation control system, an absolute value of a difference between input information managed and controlled by the digital instrumentation control system and a target value to be controlled is integrated, and the absolute value of the difference is calculated. A process diagnosis method characterized by diagnosing the process of the plant based on an integrated value.   In a process diagnosis method for a plant managed and controlled by a digital instrumentation control system, an absolute value of a difference between input information managed and controlled by the digital instrumentation control system and a target value to be controlled is integrated, and the absolute value of the difference is calculated. A process diagnosis method characterized by monitoring the trend of the correlation between the input information and the output information managed and controlled by the digital instrumentation control system in a time series together with the integrated value.   A process diagnosis method for collecting information obtained by the process diagnosis method according to claim 1 or 2 on a server of a diagnosis center connected by a network, sequentially performing diagnosis, and using the result as a diagnosis report. A digital instrumentation control system that at least manages and controls plant input and output information and target values to be controlled;
A database device that at least forms a database of input information and output information managed and controlled by the digital instrumentation control system and a target value to be controlled;
An IAE calculating means for calculating an integrated value of the difference absolute value between the input information and the target value, and creating diagnostic data;
Correlation means for plotting the input information and output information on a two-dimensional plane with the X and Y axes respectively and creating plot data;
Trend monitoring means for storing diagnostic data created by the IAE calculating means and plot data created by the correlating means in time series, and generating trend information;
And a display / printing means for displaying or printing the trend information generated by the trend monitoring means.

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