JPH0620173A - Process information display system - Google Patents

Abstract

PURPOSE:To easily understand the abnormality monitoring operation of a plant by an operator and to prevent the abnormality monitoring operation of the plant from being a heavy burden by converting the form of process state values changing corresponding to the lapse of time to a symbolic expression to be edited to a predetermined pattern and displayed to the operator. CONSTITUTION:The changing pattern of information relating to the state of an objective process changing corresponding to the lapse of time is converted to the symbolic expression, the form of the state relating to the state of the process changing corresponding to the lapse of time is trend-displayed at an information display device and the symbolic expression and the trend display are both displayed. The examples of reference patterns are indicated in a figure, For a symbolized result decided from the patterns, symbol titles are determined for the respective reference patterns to be outputted to the information display device as character strings. Also, symbols for expressing the form of the change for the respective display patterns are determined to be displayed. Thus, since the symbolic expression is words and graphics for expressing the feature of the change of trend graphs, the burden of the operator is not increased.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a process information display system for displaying process information such as process status and control status.

[0002]

2. Description of the Related Art There are process state values, target values, process manipulated variables, etc. as elements of plant monitoring. Process flows, alarm summaries, alarm displays can be used to display upper and lower limit values, deviations, and abnormalities of change rates. Is done by.

However, since the response is delayed after the alarms of the upper and lower limits, the deviation, and the rate of change are generated, or a gradual change that takes a long time cannot be detected,
Plant operators are trying to understand the trend of the plant while monitoring the trend screen in parallel. In addition, the tendency judgment of this plant is easily influenced by the subjectivity and experience of each operator who is looking at the trend screen.

[0004]

Nowadays, the operation of a plant is changed from a conventional panel operation to a CRT (Cathode Ray Tu).
be) The form has changed to driving by a display (hereinafter abbreviated as CRT) operation. Along with this, the reduction of the number of operators has become a demand of the times.

Usually, an operator displays a process flow image on a CRT in order to grasp the entire plant, and monitors the process state value displayed there. Of course, if the process state value is in the alarm state, the color has changed, so the alarm state can be grasped.

However, it is difficult to grasp the tendency of process change unless the trend display screen is displayed. Therefore, in order to grasp the entire plant, at least two CRTs are required, such as one on the trend display screen and one on the process flow screen, even in a small plant. Furthermore, in order to monitor a plurality of processes at the same time, it becomes necessary to sequentially switch the display contents of the screen. On the other hand, the change in the trend graph and the grasp of the trend are subjective judgments of the operator, and there is a problem that the operator may have a difference in determining an abnormality. In particular, in a process having a relatively long time constant, it is difficult to find a gradual change over a long period of time, which causes a problem that individual differences among operators become large.

Therefore, in order to make it easy to grasp the plant by CRT monitoring, it is required to display a lot of information on the CRT in an easy-to-see expression and to eliminate individual differences in grasping process changes and trends. ing.

An object of the present invention is to easily grasp a plurality of pieces of information such as a process state value, a target value and a process operation amount and a tendency of the process state value, the target value and the process operation amount at the same time in controlling and monitoring a process. Another object is to provide a process information display system that can be performed without individual differences.

[0009]

To achieve the above object, according to a first aspect of the present invention, there is provided a process information display system including an information display device for displaying a state of a target process, the process information display system comprising: Symbolizing means for converting a change pattern of the information relating to the state of the above that changes over time into a symbolic representation, and the above information display device has a trend in which the information relating to the state of the process changes over time. A process information display system is provided, which is provided with information editing means for displaying, together with the trend display, a symbolic expression which is an output from the symbolizing means.

Further, according to the second aspect of the present invention, there is provided a process information display system including an information display device for displaying the state of a target process, wherein the information relating to the state of the process changes over time. Symbolizing means for converting the change pattern into a symbolic expression, and a flow image showing the configuration of the process on the information display device, and the symbolic expression output from the symbolizing means is combined with the flow image. A process information display system is provided, which comprises: an information editing unit for displaying the process information.

Further, according to the third aspect of the present invention, there is provided a process information display system including an information display device for displaying the state of a target process, wherein the information relating to the state of the process changes with time. Symbolic means for converting the change pattern into a symbolic representation, and the information display device displaying the symbol of the device corresponding to the information relating to the state of the process, and the symbolic representation which is the output from the symbolizing means. Is provided with an information editing unit for displaying in association with the displayed device symbol.

Furthermore, according to a fourth aspect of the present invention, there is provided a process information display system including an information display device for displaying the state of a target process, the information being related to the state of the process over time. Symbolizing means for converting the changing pattern into a symbolic representation, anomaly monitoring means for monitoring the information display device for anomalies in the information related to the process status, and a list of the anomaly contents in an alarm summary format. In addition, there is provided a process information display system characterized by comprising information editing means for displaying the symbolic expression output from the symbolizing means together with the alarm summary of the abnormal content.

In each of the above-mentioned aspects, for example, a symbol mark such as an arrow can be used as the symbolic expression. Also, language expressions such as words can be used.

[0014]

The present invention supports process monitoring by displaying information such as the current process state value and trend graph with information symbolically expressed as information to be provided to the operator. is there. The symbolic expression does not increase the burden on the operator because it is a word or a graphic that expresses the characteristics of changes in the trend graph. Further, since the symbolization is performed by the symbolization device, it is possible to eliminate the individual difference due to the subjective judgment of the operator.

The symbolic representation of process information is
Do the following: First, a temporal change pattern of process-related information such as a process state value, a target amount, and an operation amount is converted into a vector data string by a polygonal line approximation process. The change pattern of this vector data is symbolized. At the time of encoding, prepare a standard change pattern of vector and a symbolic expression for it, compare the vector data obtained by polygonal line approximation with this standard pattern, A static representation as the symbolic representation of the data.

At this time, by performing compression and expansion on the time scale, it is possible to accurately cope with slow changes and rapid changes. Therefore, conventionally, it was difficult to find a gradual change over a long time in a process with a relatively long time constant, but even in such a process, it is possible to provide effective information for supporting control and monitoring.

[0017]

Embodiments of the present invention will now be described in detail with reference to the drawings.

FIG. 18 is a block diagram showing the functional configuration of an embodiment of the process information display system of the present invention.
FIG. 19 is an example of a hardware configuration that realizes this.

The process information display system of this embodiment is
Process input / output device 2 that converts a signal from a sensor installed in the target process 1 into a process state value and outputs the process state value.
A central processing unit 3 for executing various operations and inputs / outputs according to a program in addition to receiving output from the process input / output unit 2; a program executed by the central processing unit 3; and data used or generated at the time of execution Memory 4 used to store information such as
And an auxiliary storage device 5, an input device 6 such as a keyboard for transmitting a request from an operator to the central processing unit 3, and an information display device 7 such as a CRT for transmitting the processing result of the central processing unit 3 to the operator. It is configured using a wear system.

Next, the function of this embodiment realized by using the hardware shown in FIG. 19 will be described with reference to FIG.

The process information display system of this embodiment is
Process state detecting means 101, process state value storage section 102, historical data storage section 103, historical data buffer 104, historical data storage section 105, symbolization section 106, symbolization parameter storage section 107, and symbol The conversion result storage unit 108, the information editing unit 109, and the drawing style storage unit 200 are included.

The process state detecting means 101 fetches the state value from the process input / output device 2 in a constant cycle. This cycle is selected in advance for each measurement point so that a change in state value can be detected within a necessary and sufficient time. The process state value storage unit 102 is provided on the memory 4 in order to refer to the process state value at high speed and efficiently, and stores the current state value of the process fetched from the process input / output device 2 by the process state detection unit 101. I remember. The historical data storage means 103 is a process for accumulating process state values over time, and the process state value storage means 10
The state values from 2 are sequentially accumulated in the historical data buffer 104, and when the state value is full, the state data is further transferred to the historical data storage unit 105.

The symbolizing means 106 converts a change pattern in which the process state value held in the process state value storage section 102 changes with the passage of time into a symbolic expression. The encoding parameter storage unit 107 stores the encoding means 1
The external parameters such as the dimensionless coefficient of the state value for each measurement point and the symbolization execution cycle necessary for the symbolization processing of 06 are held. The encoding result storage unit 108 holds the latest encoding result from the encoding unit 106.

The information editing means 109 extracts the process state value data string before the current time from the historical data buffer 104 and the historical data storage unit 105 to edit the trend graph, and further, the symbolization result storage unit 1
The encoding result from 08 is added to the editing information. The information editing means 109 starts its operation when the operator inputs a request from the input device 6, and outputs the edited result to the information display device 7. At this time, the operator inputs from the input device 6 to instruct which measurement point and how to display the information. The drawing style storage unit 200 stores various kinds of predefined drawing information in order to respond to the display style requested by the operator.

The process state detecting means 101, the historical data storing means 103, the symbolizing means 106, and the information editing means 109 in FIG. 18 are such that the central processing unit 3 executes a program in the hardware configuration in FIG. Can be realized by Here, the process state detection means 101, the historical data storage means 103, and the symbolization means 106 can be repeatedly processed at a cycle determined in advance for each measurement point. Further, each of these means may be operated in synchronization with the execution of the process state detection means 101, or may be realized in an asynchronous manner. A technique of apparently executing a plurality of programs simultaneously with one central processing unit is conventionally used.

Further, the process state value storage unit 102, the symbolization parameter storage unit 107, and the drawing style storage unit 200.
Can be realized as a data storage area on the memory 4.

Next, each function of the embodiment shown in FIG. 18 will be described in more detail.

First, the storage format of historical data will be described. The historical data buffer 104 is
2 is a storage means for a short time realized on the memory 4.
An example of the configuration is shown in 0 (a). In this example, the existence of the process state value 303 is managed by the head data time 301 and the data counter 302. The historical data storage unit 105 is a storage unit for a long time realized on the auxiliary storage device 5, and FIG. 20B shows an example of its configuration. In this example, the data is stored cyclically, and the start pointer 304 and end pointer 3
The presence of the process state value 307 is managed by 05 and the start data time 306. The reason why the encoding unit 106 is divided into short-time and long-time as described above is to reduce the frequency of writing to the auxiliary storage device 5 and increase the processing efficiency. As an example of extracting data from these, consider a case where a data string of process state values before the current time is required. First, the historical data buffer 104
From the historical data storage unit 105, if the previous data is needed. Here, the storage format shown in FIG. 20 is for one state measurement point, and this storage structure is prepared for the required number of measurement points.

Next, regarding an example of the encoding means 107,
This will be described with reference to FIG. 21, the symbolization means 107 includes a polygonal line approximation processing unit 403, a filter storage unit 404, a temporary data storage unit 405, a dictionary search processing unit 406, a standard pattern storage unit 407, and an evaluation value calculation unit 408. Have.

In the polygonal line approximation processing unit 403, the input 401 of the process state value from the process state value storage means 102 (FIG. 18) and the symbolized parameter storage means 107 (FIG. 1).
Parameter input 402 from 8) is input. The filter storage unit 404 holds a filter data string used by the feature extraction unit 403 to extract feature points. What is a feature point?
It is the position of the contact point between the vectors of the change vector sequence approximated by the polygonal line. The polygonal line approximation processing unit 403 extracts the feature relating to the unevenness of the change pattern of the process state value using the filter data stored in the filter storage unit 404, approximates the variation pattern with the polygonal line based on the feature, and calculates the polygonal line. Is expressed by replacing the sequence of change vectors that compose it. An array of vectors expressing this change pattern will be referred to as a change vector series.

The data up to this time, which is generated in the process that the polygonal line approximation processing unit 403 repeatedly executes, is held in the temporary data storage unit 405 for the next processing. As a result, the amount of calculation for the next time can be reduced. The temporary data storage unit 405 stores the process state value from the process state value input 401 a certain number of times in order to capture the change pattern of the state value.

The standard pattern storage unit 407 expresses each of a plurality of standard patterns to be compared with the change pattern of the process state value with a polygonal line, and defines and stores the polygonal line by replacing it with a vector. An array of vectors expressing this one standard pattern will be referred to as a dictionary vector series. The dictionary search processing unit 406 compares the change vector series from the polygonal line approximation processing unit 403 with the dictionary vector series of a plurality of standard patterns in the standard pattern storage unit 407, and changes directions of the change vector series and the dictionary vector series. The section in which is matched is extracted.

The evaluation value calculation unit 408 is a dictionary search processing unit 4
The degree of coincidence of the sections extracted in 06 is evaluated by the value of the degree of similarity and the value of the scale, and the symbolization result 409 selected based on the evaluation result is stored in the symbolization result storage unit 108 (FIG. 1).
Output to 8). The degree of similarity indicates the degree to which the shapes of changes match, and the scale indicates the magnitude of changes, which can be expressed by the following equation, for example.

Similarity = (sum of inner products of change vector series and dictionary vector series) / (total distance of dictionary vector series) / (total distance of change vector series) Scale = (of inner product of change vector series and dictionary vector series) (Sum) ÷ (square of total distance of dictionary vector series) In the dictionary search processing unit 406, a plurality of standard patterns may be selected, but in the evaluation value calculation unit 408, the evaluation value is calculated for each pattern and the scale is calculated. Those smaller than a predetermined threshold value are excluded as a minute change. After that, the one with the highest similarity is determined as the final symbolization result. Here, the pattern having the second or lower similarity may be useful as reference information. This may be added to the symbolization result according to the display form or the request of the operator.

FIG. 22 shows an example of the standard pattern. The symbolization result determined from these patterns defines the symbol name for each standard pattern, and outputs this to the information display device 7 as a character string, so that the operator can identify the state value change. Alternatively, a method may be used in which a symbol symbol expressing the shape of change is defined for each standard pattern and displayed.

FIG. 23 shows an example of display on the information display device 7 in the above embodiment.

In FIG. 23, reference numeral 51-1 is a trend graph relating to the state value of a certain state measurement point of the target process 1, which is displayed by the data from the historical data buffer 104 and the historical data storage unit 105. Reference numeral 52-1 is a symbol symbol which is a graphic representation of the symbolization result stored in the symbolization result storage unit 108. Since the symbolization result displayed here is the last symbolization result, it has a maximum time delay of the symbolization execution cycle, but the symbolization execution cycle is adjusted according to the change characteristics of the state value. By determining, the delay becomes practically negligible.

In this display example, the state change can be judged on behalf of the driver, and individual differences due to the subjective judgment of the driver can be eliminated. Further, since the trend graph is displayed at the same time, the empirical judgment of the operator can be utilized while referring to the symbolization result determined according to a certain procedure.

Another display example in the above embodiment is shown in FIG.

In this display example, in the information editing means 109, the plant flow image graphically showing the configuration of the plant and the symbolization result of each state measurement point are simultaneously edited and output to the information display device 7. . In FIG. 24, 53-1 and 53-2 have shown the equipment element which comprises a plant, and call and display what was drawn beforehand according to the plant. 52-2 is an equipment element 53-1
52-3 indicates the symbolization result of the equipment element 53-2. In this figure, the symbolization result is represented by a symbol symbol that represents it graphically. In this display example, the operator can simultaneously monitor the state change for a plurality of related measurement points on one screen.

FIG. 25 shows still another display example in the above embodiment.

Conventionally, since the operation of the feedback controller installed on site is performed in the driver's cab, a picture on the controller operation panel is displayed on the information display device 7, and various settings for the controller such as target values are input from the input device 6. Things are being done. In the display example of FIG. 25, the symbolization result of the state value change at the state value measuring point controlled by the controller is added thereto. In FIG. 25, 54-1 is an identification symbol such as the name of the state measurement point, 52-
4 is a symbol symbol representing the symbolization result from the symbolization result storage unit 108, and 55-1 is the process state value storage unit 10.
It is the state value of the state measurement point from 2. As a result, the operator can see the plant state value in a familiar expression format, and at the same time, know the symbolization result. Also,
The information display device 7 is generally installed in the driver's cab, but if the symbolization result is directly output to the display means of the controller installed on the site, the symbolization result of the change in the state value with the passage of time can be known on the site. You can

Next, FIG. 26 shows a block diagram of another embodiment.

The system of the embodiment shown in FIG. 26 has a process state detecting means 101 and a process state value storage section 102.
, Encoding means 106, and encoding parameter storage unit 10
7, a symbolization result storage unit 108, and an information editing unit 109
An abnormality monitoring unit 901 that includes an image drawing mode storage unit 200, and that monitors each piece of data from the process state value storage unit 102 and that monitors abnormal information such as upper and lower limit abnormalities, deviation abnormalities, and change rate abnormalities. An abnormality monitoring specification storage unit 902 that defines the type of monitoring used by the abnormality monitoring unit 901, the range of abnormal values, and the like, the abnormality content when the abnormality monitoring unit 901 determines that a certain state measurement point is abnormal, and And an abnormal state storage unit 903 that collectively stores the symbolized information of the state measurement points whose changes are detected at that time. Further, similar to the embodiment shown in FIG. 18, the process input / output device 2, the input device 6 and the information display device are provided.

An example of the operation of the abnormality monitoring means 901 will be described with reference to the flowchart of FIG.

The abnormality monitoring means 901 first sets the loop counter i for sequentially pointing the state measurement points to be monitored to the initial value (step 2705). And 1 for i
Is added to switch to the next state measurement point (step 2710). Abnormality monitoring specification storage unit 902
The monitoring specifications such as the monitoring cycle, the type of monitoring, and the abnormal value range stored in are retrieved (step 2715). The monitoring cycle is stored in the abnormality monitoring specification storage unit 902 at n times the basic cycle for each measurement point. Next, it is checked whether or not only the monitoring cycle has passed since the last time (step 2720).
The determination of the monitoring period is a process of determining whether or not the basic period × n = the monitoring period has elapsed from the previous process for the i-th measurement point, and if it has not elapsed, the process to the next measurement point is performed. Transition.

Next, the abnormality monitoring means 901 determines the abnormality at the corresponding measurement point according to the above-mentioned monitoring specifications (step 2).
725), if normal, the process moves to the next measurement point. In the case of abnormality, the symbolization result existing in the symbolization result storage unit 108 at that time is added to the content of the abnormality and stored in the abnormal state storage unit 903 (step 2730). The symbolization result added here only indicates that there is a change, and the symbolization result that means constant is not necessary.

Then, it is determined whether or not i has reached the maximum value, and if i has reached the maximum value, it is determined that a series of processing has been completed (step 2735). The abnormality monitoring means 901 repeats the series of processes described above each time a basic cycle elapses. For this reason,
If i has not reached the final value and the basic period has not elapsed, a pause for adjusting the time is made until the basic period elapses (step 2740).

FIG. 28 shows a display example in the above embodiment.

In the figure, 56-1 is the time when the abnormality occurred,
54-2 is an identification symbol of a state measurement point where an abnormality occurs, 55
-2 is the state value at that time, and 57-1 is the content of the abnormality.
Further, 54-3 is an identification symbol of the measurement point whose change was detected by the symbolization means 106 at the time when the abnormality occurred. Reference numeral 58-1 is a symbol name indicating the symbolization result of the change pattern. Here, the measurement point where the state value has changed at the time when the abnormality occurs can be considered as a candidate for the cause of the abnormality, and this display example is an example of reporting the candidate to the operator.

FIG. 29 shows a block diagram of still another embodiment of the process information display system of the present invention.

The system of the embodiment shown in FIG. 29 has a process state detecting means 101 and a process state value storage section 102.
, Historical data storage means 103, historical data buffer 104, historical data storage section 105, symbolization means 106, symbolization parameter storage section 107, information editing means 109, and drawing style storage section 2
00, and the process input / output device 2, the input device 6 and the information display device.

In the embodiment shown in FIG. 29, when the operator inputs a display request from the input device 6, the information editing means 109 requests the symbolizing means 106 to perform symbolization, whereby the symbolizing means 106 symbolizes. Information conversion means 109
It should be reported to. At this time, the process state value data string to be encoded is extracted by the information editing means 109 from the historical data buffer 104 and the historical data storage unit 105, and is transmitted to the encoding means 106 collectively. The time range in which the information editing unit 109 extracts historical data and the sampling interval are
It may be determined in advance, or may be input at the same time when the operator makes a display request. The functions of the other elements are the same as those shown in FIG.

The symbolization result can be displayed in the same manner as in FIGS. 23, 24 and 25. According to this embodiment, the operator can arbitrarily execute the symbolization from the past data many times. As a result, the regularity of the accumulated data can be easily understood with a symbolic expression, which can be useful for predicting future plant state changes.

Next, still another example of display of process information by the process information display system of the present invention will be shown.

First, the function of the information editing means 109 used in the embodiment shown in FIG. 18 or FIG. 29 is to extract measurement points having the same symbolization result from a plurality of state measurement points, and to group them. There is a thing to display collectively. According to this example, when distinguishing the measurement point that has caused the change from the measurement point that has changed due to the influence, the operator can narrow down the survey target. The display example is shown in FIG. In FIG. 30, reference numeral 52-5 is a symbol symbol representing the symbolization result, and 54-4 is an identification symbol of the state measurement point that has obtained the corresponding symbolization result.

Secondly, in the embodiment shown in FIG. 18 or 26, the symbolization result being displayed may have a mark or the like so that the operator can distinguish whether it has been confirmed or not.
As a result, it is possible to prevent the operator from omitting treatment. This is, for example, the information editing means 1 shown in FIG.
09 can be realized by having a function of storing the confirmation of each measurement point in response to the confirmation input of the operator.

When a symbolization result of a new change is detected at a certain measurement point, the symbolization means 106 erases the confirmed memory to restore the unconfirmed state. FIG. 31 shows a display example of the unconfirmed mark. FIG. 31 shows the display example of FIG. 24 with an unconfirmed mark 59-1 added. If confirmed, another type of mark is displayed at the position of the unconfirmed mark, or the symbol symbol 52-
It can be indicated by leaving 2 blank.

Thirdly, in the embodiment of FIG.
There is another example in which the symbolization result of the past time range using the historical data is displayed at the same time. As a result, the operator can continuously know the progress of changes from the past to the present. FIG. 32 is an example of the display, 52-6 is a symbol symbol showing the current encoding result,
52-7 is a symbol symbol indicating a symbolization result from the historical data. Reference numeral 60-1 is an arrow indicating that the symbolization result 52-7 is generated in that section.
-2 is a trend graph of historical data.

Fourthly, in the embodiment shown in FIG. 18, the coding means 106 performs global coding for a long time range, and at the same time performs local coding for a part of the time range. There is a case where the editing means 109 simultaneously combines and edits the two pieces of symbolized information and the two trend graphs. This makes it possible to monitor both long-term gradual changes that are difficult to detect visually and sudden and sudden changes. FIG. 33 is an example of the display, 51-3 is a long-term trend graph, 51-4 is a short-time trend graph, 52-8 is a symbol symbol showing the coding result of the long-term range, and 52-9 is the short-term range. It is a symbolic symbol indicating the result of encoding.

Next, an embodiment of a symbolization device that can be suitably used as the symbolization means in the process information display system of the present invention will be described with reference to the drawings.
Here, the encoding means is described as an independent encoding device, but it goes without saying that it can be configured as one component of the process information display system as in the above-described embodiment.

The details of the first embodiment of the coding apparatus according to the present invention will be described with reference to FIGS. 1 to 12.

FIG. 1 is a block diagram showing the configuration of the symbolization device. In the figure, a communication device 110 receives an identification number of a pattern data to be processed, a sampling cycle, a processing target section, a conversion coefficient, etc. through a communication network. A data storage device 120 stores information indicating the state of the process. In the process control field such as a power generation plant, a chemical plant, a water treatment plant, etc., the information representing the process state is, for example, time-series data such as temperature, pressure, and flow rate of each process part or data of a spatial distribution pattern. However, in the process of processing data in fields such as finance, securities, and distribution,
Stores time-series data or pattern data such as economic indicators, sales information, and management information.

An input processing unit 130 is activated by a signal from the communication device 110. Input processing unit 13
0 is a memory for extracting the corresponding data from the data storage device 120 from the processing target section at a given sampling cycle based on the identification number, the sampling cycle, and the processing target section information sent from the communication device 110. Send to 140.

The polygonal line approximation processing unit 150 has a memory 140.
The input pattern stored in 1 is approximated by a polygonal line, converted into a vector series of line segments forming the polygonal line, and the result is sent to the integration processing unit 160. 155 is a filter storage unit,
A feature extraction filter used by the polygonal line approximation processing unit 150 is stored.

Reference numeral 160 denotes an integration processing unit, which integrates the series of polygonal line vectors obtained by the polygonal line approximation processing unit 150 and sends them to the dictionary search processing unit 170. An integration parameter 165 stores integration parameters used in the integration processing unit 160.

The dictionary search processing unit 170 is the integration processing unit 16
0 and the standard pattern storage unit 1
Comparing the vector series of events stored in 75,
Search the corresponding candidate vector series. A standard pattern storage unit 175 stores a standard pattern corresponding to an event name for identifying an input pattern as a polygonal line approximated vector series and a name for each vector series. The standard pattern and the name corresponding to it are prepared in advance in the system. The user may register an arbitrary name. Further, as the standard pattern, an arbitrary pattern may be registered together with its name.

Reference numeral 180 denotes a similarity calculation processing unit, which calculates the similarity and scale between the vector sequence of the correspondence candidate obtained by the dictionary search processing unit 170 and the vector sequence of the event stored in the standard pattern storage unit 175. The event name, the similarity, the scale, and the corresponding data section of the standard pattern having the scale within a certain range and the similarity being a certain value or more are calculated and sent to the memory 190.

The processing result stored in the memory 190 is transmitted to another information processing system or the like via the communication device 110.

The symbolization device of this embodiment is a central processing unit,
It is configured by a computer system having a main storage device, an auxiliary storage device, various interface devices, and the like. Various functions of the symbolization device of this embodiment are realized by the central processing unit executing a program stored in the main storage device, and the following operations are executed. As the hardware system for realizing the symbol or the device, for example, a system as shown in FIG. 19 can be used.

Next, the operation of each part of the symbolization device based on the above configuration will be described in detail. FIG. 2 is a flowchart showing the operation of the polygonal line approximation processing unit 150. Broadly speaking, the pattern f (t) of the input data and the feature extraction filter W
By using the pattern division processing 210 that calculates the unevenness of the pattern by the product-sum calculation with 2 (x) and obtains the point τp at which the pattern is divided into polygonal lines, and the feature extraction filter W0 (x),
Obtain the average value of the data in the vicinity of the dividing points of the pattern,
A pattern is formed by using an estimation process 220 for obtaining an estimated value fe (τp) of data at a division point, a both-ends estimation process 230 for obtaining an estimation value at both ends from a regression line at both ends of the data section, and an estimation value at the division point and both ends. And a vector series calculation processing 240 for calculating a vector series when the line approximation is performed.

In the pattern division processing 210, the input data is first multiplied by the conversion coefficient sent through the communication network to normalize the data, and the processed data f (t) (t
= 0, 1, ..., T) is generated. Next, for the data f (t) of the input pattern (t = 0, 1, ..., T), the feature extraction filter W2 stored in the filter storage unit 155.
Sum of products calculation using (x)

[0073]

[Equation 1]

Thus, the feature amount g2 (t) indicating the degree of unevenness is obtained.
To calculate. Here, a is a constant indicating the spread of the filter. For the example of the input pattern shown in FIG.
FIG. 3B shows the result of product-sum calculation performed by the feature extraction filter W2 (x) shown in FIG. Obtaining dividing points τp (p = 1, 2, ..., K) of the input pattern by extracting points having positive and negative extreme values whose absolute values are larger than appropriate constants from the calculation result shown in Expression 1. You can In the example of FIG. 3B, τp (p = 1, 2, ..., 9) is obtained as a division point.

In the estimation process 220, the feature extraction filter W0 stored in the filter storage unit 155 at the division point τp obtained by the pattern division process 210.
Sum of products calculation using (x)

[0076]

[Equation 2]

Thus, the feature value g0 (τp) representing the average value
To calculate. FIG. 5B shows an example of the feature extraction filter W0 (x). Estimated value fe of the pattern at the division point τp
(τp) is obtained by using a feature amount g2 (τp) indicating unevenness and a feature amount g0 (τp) indicating an average value.

[0078]

## EQU00003 ## fe (.tau.p) = W0 (0) .g0 (.tau.p) + W2 (0) .g2 (.tau.p) ... (Equation 3)

In both-ends estimation processing 230, estimated values at both ends of the input pattern are obtained. The estimated values (τ1, fe (τ1)) of the division points obtained in the estimation process 220 and (τ
Regression lines passing through k, fe (τk))

[0080]

[Equation 4]

[0081]

[Equation 5]

It is calculated by

In equations 4 and 5, t = 0 and t = T, respectively.
By substituting for the estimated value f at both ends of the input pattern
e (0) (= h1 (0)) and fe (T) (= h2 (T)) are obtained.

In the vector series calculation processing 240,
A sequence of points (0, fe (0)), (τp, fe (τp)) (p = 1, obtained by the estimation processing 220 and the both-ends estimation processing 230.
2, ..., k), (T, fe (T)) to approximate the input waveform Ai = (Pi, Qi) (i = 1,2 ,.
k + 1),

[0085]

[Equation 6]

Determined by An example of the obtained vector series is illustrated in FIG. Each vector is named the closest standard vector (having the closest gradient) of the standard vectors shown in FIG. That is, the inner product of each vector and the standard vector is obtained, and the standard vector having the maximum inner product is selected as the closest standard vector and given the name. Each named vector is shown in Figure 3.
It is sent to the integrated processing unit 160 as data as shown in (d).

Next, details of the processing in the integration processing section 160 will be described. The integration processing is performed when the number of vectors is two or more in the processing result of the polygonal line approximation processing unit 150. The process consists of three steps as shown in FIG. 710 is a step of integrating adjacent vectors having the same name, 720 is a step of integrating short "balanced" vectors, and 730 is a step of integrating short vectors other than "balanced". The details of the processing in each step will be described below.

(1) Step 710: Combine adjacent vectors having the same name. For example, in the case of FIG.
Two consecutive "balanced" vectors are combined into one "balanced" vector.

(2) Step 720: A vector given the name "balance" and having a length equal to or shorter than a fixed value is integrated with another vector.

(2-1) If there is a vector having a change width of a fixed value or less stored in the integrated parameter storage unit 165 before and after, it is integrated with that vector. For example, in FIG.
In the case of (b), since there is a short "falling" vector before the short "balanced" vector, the two are integrated to generate a new "falling" vector.

(2-2) If the angle formed by the front and rear vectors is less than or equal to a fixed value stored in the integrated parameter storage unit 165, the vector is integrated. For example, in the case of FIG. 8C, since cos (θ1)> cos (θ2), the “equilibrium” vector is integrated with the previous “falling” vector to form a new “falling” vector.

(3) Step 730: A vector having a name other than "balance" and a small change width is integrated with another vector.

(3-1) If there is a short vector whose variation width is below a certain value stored in the integrated parameter storage unit 165, it is integrated with that vector. For example,
In the case of FIG. 9A, a short “falling” vector and a short “rising” vector are integrated to generate a new “balanced” vector.

(3-2) If the angle formed by the vectors in front of and behind is less than or equal to a certain value stored in the integrated parameter storage unit 165, the vector is integrated. For example,
In the case of FIG. 9 (b), cos (θ1)> cos (θ2), so the short “rise” vector is combined with the previous “fall” vector to generate a new “balance” vector.

In the above cases (2) and (3), the name of the newly generated vector is changed to the name of the standard vector (FIG. 6) having the smallest angle with the vector. FIG. 4A shows the vector series after integration. This vector series is sent to the dictionary search processing section 170 as data as shown in FIG.

Next, the operation of the dictionary search processing section 170 will be described. FIG. 10 is a flowchart showing the operation of the dictionary search processing section 170. As shown in FIG. 11, the standard pattern storage unit 175 is provided with a number for each event name to be identified and stored in numerical order. Further, each vector of the vector series constituting the event is composed of a vector having the same slope as the standard vector of FIG. 6, and the name of the corresponding standard vector is given. FIG. 11 shows the standard pattern storage unit 175.
Examples of event names stored in are shown below. In FIG. 11, the event name “rise in steps” is stored as number 1,
The event name “from rising to falling” is stored as number 2.

Details of the processing of the dictionary search processing section 170 shown in FIG. 10 will be described. First, in step 1010, a vector series Ai (i =
1, 2, ..., M) and the series of names are input from the integration processing unit 160. Then, in step 1020,
The number N of the event name to be searched is set to 1 and the search is started. In the search process 1030, when a vector series similar to the event in the standard pattern dictionary is selected as a correspondence candidate from the vector series of the input pattern, step 10
By 40, the flow of processing moves to the transmission processing 1050, and the event name number N and the corresponding candidate vector series are sent to the similarity calculation processing unit 180. If there is no correspondence candidate, it is determined in step 1060 whether the search has been completed for all event names (the number of standard patterns is Nmax). If the search for all standard patterns is not completed, the event name number is updated “N = N + 1” in step 1070, and the search for the next standard pattern is continued by the search process 1030.

FIG. 12 is a flow chart for explaining the details of the processing in the search processing 1030. Where Ai
(I = 1, 2, ..., M) is a vector sequence constituting the input pattern, Vj (j =
1, 2, ..., N) are vector series of standard patterns of events stored in the standard pattern storage unit 175. First, in order to search the vector of the standard pattern corresponding to the first vector of the input pattern, “is = 1” is set in step 1210. Next, step 12
20 sets "j = 1, i = is" and the search is started. The vector number of the standard pattern being searched is m
When it becomes +1, the search ends in step 1230. The name of the vector Ai of the input pattern and the name of the vector Vj of the standard pattern are compared in step 1240. If they do not match, the process goes to step 1245,
A comparison is made with the next vector of input patterns. If there is a match, the pair of Ai and Vj is stored in the temporary storage 1255 in step 1250. In step 1260, it is determined whether the search has been completed for all the vectors of the standard pattern. If j ≠ n, then step 1270
The processing "i = i + 1, j = j + 1" is performed, and the search for the next vector is continued. When j = n, the process “is = ik + 1” of step 1280 is performed, and i
From the sth input vector, the search process with the standard pattern is performed. Here, ik is the number of the vector of the latest input pattern in which the name of the vector Vj of the standard pattern matches, and is the vector number of the vector of the latest input pattern to which Vj corresponds among the corresponding candidate columns stored in the temporary storage. It is a number.

In the similarity calculation processing section 180, as shown in FIG.
2, the similarity S and the scale K between the input pattern and the standard pattern are

[0100]

[Equation 7]

[0101]

[Equation 8]

It is calculated by Where Vi (i =
1, 2, ..., M) are standard pattern vector series, Ai
j is a correspondence candidate of the vector series of the input pattern, and V
i and Aij (i = 1, 2, ..., Ni) are correspondence candidates. S in the equation 7 is for calculating the correlation coefficient between vector sequences, and is 1.0 if the patterns are completely similar. Expression 8 is a scale (scale factor) when the vector series of the input pattern best matches the vector series of the standard pattern. A certain range in which the similarity and the scale for the standard pattern obtained by the similarity calculation processing unit 180 are defined

[0103]

## EQU00009 ## Event names of standard patterns satisfying Smax.ltoreq.S, Kmin.ltoreq.K.ltoreq.Kmax (Equation 9) are stored in the memory 190, arranged in descending order of similarity. Figure 4
An example of the symbolization result is shown in (c).

The symbolization result (event name, similarity, scale, and matched data section) stored in the memory 190 is transmitted to another information processing system or the like through the communication device 110.

In the symbolization device according to the present embodiment, the candidate part of the input pattern that matches the standard pattern can be searched using the name of the vector, which not only requires a small amount of calculation processing but also causes an error. This has the effect of searching for a small number of candidates. Furthermore, since the correlation coefficient is calculated between the vector sequences to obtain the similarity, it is possible to search for similar patterns, and it is possible to reduce the number of event patterns stored in the standard pattern storage unit 175. ing.

A second embodiment of the coding device according to the present invention will be described with reference to FIGS. 13 to 15. The first embodiment is an embodiment in which pattern data stored in a database or the like is collectively converted into a symbol, whereas the second embodiment converts data obtained from a process into symbols every moment. This is an example of conversion. In this case, the data up to the immediately preceding data in the sampling cycle has already been converted into the vector series, and therefore the processing by adding one data may be performed for each sampling cycle.

The configuration of the symbolization device of this embodiment is shown in FIG. In the figure, 1310 is a communication device similar to 110, and receives the identification number of the pattern data to be processed and the like through the communication network. Reference numeral 1320 denotes a data storage device, which stores process data and a vector series, an event name, and the like, which are the processing results up to the previous sampling period. The input processing unit 1330 is activated by a signal from the communication device 1310, and the data storage device 1
Data information (processing results up to the previous sampling data and the latest sampling data) corresponding to the identification number is read from 320 and sent to the memory 1340.

Reference numeral 1350 is a polygonal line approximation processing unit. Thirteen
55 is a filter storage unit, which is a polygonal line approximation processing unit 135.
The feature extraction filter used in 0 is stored. In the present embodiment, as real-time processing, processing is performed from the latest data to the past data, so a feature filter as shown in FIG. 15 is used. The polygonal line approximation processing unit 1350 performs feature extraction from a portion including the latest data of the input pattern stored in the memory 1340, approximates the pattern data with a polygonal line, and converts the pattern data into a vector series of line segments forming the polygonal line.

An integration processing unit 1360 integrates the series of polygonal line vectors obtained by the polygonal line approximation processing unit 1350, and sends them to the dictionary search processing unit 1370. 1365
Stores the integrated parameters used by the integrated processing unit 1360.

The dictionary search processing unit 1370 compares the vector series of the input pattern sent from the polygonal line approximation processing unit 1350 of FIG. 13 with the vector series of the standard pattern stored in the standard pattern dictionary 1375, and determines the correspondence candidate. Search vector series. Standard pattern storage unit 1375
Similar to the first embodiment, the event name, the vector series thereof and the name of each vector are stored as in the first embodiment. 1380 is a similarity calculation processing unit,
The similarity and scale between the vector sequence of the correspondence candidate obtained by the dictionary search processing unit 1370 and the vector sequence of the standard pattern are calculated. If the obtained event name is different from that at the time of previous sampling, and the scale is within a certain range and the similarity is a certain value or more, the standard pattern number, the corresponding input pattern number, and the similarity degree , And the measure are stored in memory 1390. The result stored in the memory 1390 is transmitted to another information processing system or the like via the communication device 1310.

Next, the operation of the symbolization device based on the above configuration will be described in detail.

FIG. 14 shows the polygonal line approximation processing unit 1350.
3 is a flowchart showing the operation of FIG. Broadly speaking, the pattern division processing 1410 for calculating the unevenness of the pattern by calculating the sum of products of the input pattern f (t) and the feature extraction filter W2 (x), and obtaining the point τp at which the pattern is divided into polygonal lines
And feature extraction filters W0 (x), W1 (x), and W2
Using (x), the average value of the data in the vicinity of the dividing points of the pattern is calculated, and the estimated value fe (τ
p), an estimation process 1430 for obtaining a p), an end estimation process 1450 for obtaining an estimated value of the end from a regression line at the end of the data section, and a vector series when the pattern is approximated to a polygonal line using the dividing point and the estimated value of the end And a vector sequence calculation process 1460 for calculation.

First, in the pattern division processing 1410, the data f (t) of the input pattern (t = -T, -T +
1, ..., 0) for the sum of products using the feature extraction filter W2 (x) stored in the filter storage unit 1355

[0114]

[Equation 10]

Thus, the feature amount g2 (0) indicating the degree of unevenness in the vicinity of the current time is calculated. Here, a is a constant indicating the spread of the filter. With respect to the example of the input pattern shown in FIG. 16A, the sum of products calculation by the feature extraction filter W2 (x) shown in FIG.

[0116]

[Equation 11]

When the above condition is satisfied, t = -b (b is a constant value determined by the filter) becomes a new division point. According to processing step 1420, if a new dividing point has not been generated, the process proceeds to processing step 1450, and if a dividing point has been generated, the process proceeds to processing step 1430.

In the estimation processing 1430, the feature extraction filter Wk (x) (k = 0, 1, 2) stored in the filter storage unit 1355 is used at the division point τp obtained by the pattern division processing 1410. Sum of products calculation

[0119]

[Equation 12]

Thus, the feature value g0 (τ
p), a feature amount g1 (τp) indicating the inclination, and a feature amount g2 (τp) indicating the unevenness are calculated. FIG. 15 shows an example of the feature extraction filters W0 (x), W1 (x), and W2 (x). The estimated value fe (τp) of the pattern at the division point τp is

[0121]

[Equation 13]

It is calculated by

Next, in the end estimation processing 1440,
Obtain an estimated value of the end of the input pattern. Estimation process 143
The estimated value (τp, fe (τ
p))

[0124]

[Equation 14]

It is calculated by

By substituting t = 0 into the equation 14, the estimated value fe (0) (= h of the end (t = 0) of the input pattern is obtained.
(0)) is required.

In the vector sequence calculation processing 1440, the point sequences (τp, fe (τp)), (0, fe (0)) obtained in the estimation processing 1430 and the terminal estimation processing 1430.
From the vector sequence Aj = (P
j, Qj)

[0128]

[Equation 15]

Calculated by FIG. 16B shows a vector series obtained from an example of a point sequence when a new division point τp is generated. Each of these vectors is given the name of the closest vector (similar in gradient) of the standard vectors shown in FIG. 6 and sent to the integration processing unit 1360.

Next, details of the processing in the integration processing unit 1360 will be described. The integration processing is performed by the polygonal line approximation processing unit 135.
As a result of 0, when the number of vectors is three or more, it is performed for the vector two before the latest vector. The content of the process is the same as the process shown in FIG. 7. An example of the processing result is shown in FIG.

The operation of the dictionary search processing unit 1370 is the same as that of the dictionary search processing unit 170 of FIG.
The operation of 380 is the same as the similarity 180 of FIG. An example of the obtained symbols is shown in FIG.

The symbolization results (event name, similarity, scale, and matched data section) stored in the memory 1390 are as follows:
It is transmitted to another information processing system or the like through the communication device 1310.

In the symbolization device according to the present embodiment, not only the same effects as those of the first embodiment but also the processing is simple,
Since a symbolic representation of data can be obtained at high speed, a large amount of process data can be processed by an inexpensive processing device.

In order to better understand the embodiment of the symbolizer and to evaluate its inherent possibilities and advantages, the following provides a brief mathematical background and basis for the technique used to implement the embodiment. Present. The formulas introduced also give an insight into the functionality of the embodiment.

The feature extraction filters W0 (x), W1 (x), and W2 (x) stored in the filter storage unit 155 or 1355 and used in the polygonal line approximation processing unit 150 or 1350, W0 (x) is a pattern. W1 (x) is a filter for obtaining an average value, W1 (x) is a filter for obtaining an average inclination, and W2 (x) is a filter for obtaining an average unevenness of a pattern. Below, W0 (x), W1 (x), and W2
The method of obtaining (x) is organized and shown.

As a pattern data expansion method,

[0137]

[Equation 16]

The polynomial Hm (x) defined by is used. Where E (x) is a suitable differentiable function, a and b
Is a constant indicating a defined section. At this time,

[0139]

[Equation 17]

Putting it aside,

[0141]

[Equation 18]

Constitutes an orthonormal function system.

Using the orthonormal function system ψm (x) as it is and expanding the time series data f (t) near the time t,
In order to obtain a good approximation of the original data, it is necessary to find even higher order terms. In order to avoid this, the time series data is centered around the time t.

[0144]

[Formula 19]

It will be converted into and treated.

When the expansion using the orthogonal function system of the equation 18 is performed with respect to the equation 19,

[0147]

[Equation 20]

It becomes: Here, the expansion coefficient am (t) (m =
0,1, ..., ∞) is

[0149]

[Equation 21]

It is calculated by From Equations 19 and 20, the time series data f (t) is

[0151]

[Equation 22]

It means that it has been expanded to.

The differentiable function E (x) is

[0154]

[Equation 23]

When the exponential function represented by [0155] and b = -a, Hm (x) is a Hermite polynomial of degree m from Eq. Further, from Equation 22, the time series data f (t) is expanded into a polynomial in the vicinity of time t. The expansion filter Wm (x) at this time is expressed by the following equations 21 and 18:
By substituting

[0156]

[Equation 24]

Since,

[0158]

[Equation 25]

It is represented by

The time-series data estimated value fe (t) at time t is obtained using the result of the polynomial expansion by the feature extraction filter expressed by the equation 25. Substituting x = 0 into Equation 22, fe (t) is

[0161]

[Equation 26]

Is obtained.

The quadratic term a2 (t) of the expansion coefficient according to equation 26
Indicates the unevenness of the time-series data near time t. Therefore, for time series data f (t),
By obtaining the expansion coefficient a2 (t) of the quadratic polynomial according to 4, and extracting the time having the extreme value, the time when the gradient of the time series data changes can be obtained.

The method of obtaining the degree of similarity and the scale will be described below. The vector sequence of one symbol stored in the standard pattern storage unit 175 or 1375 is Vi (i =
1, 2, ..., M), and a vector sequence of correspondence candidates included in the time-series data is Ai (i = 1, 2, ..., M). When the vector series stored in the standard pattern storage unit 175 or 1375 is multiplied by K, 2 between both vector series is obtained.
The multiplication error E is

[0165]

[Equation 27]

It is represented as follows. First, a scale K that minimizes the squared error E is obtained. Expanding equation 27,

[0167]

[Equation 28]

It becomes: Here, (,) indicates the inner product of the vectors. Since Equation 28 is a quadratic equation in which the quadratic coefficient of K is positive, the scale K that gives the minimum value of the squared error E is

[0169]

[Equation 29]

From the above,

[0171]

[Equation 30]

Given as The squared error E at that time is obtained by substituting Equation 30 into Equation 28,

[0173]

[Equation 31]

Is given by Squared error E in equation 31
Is normalized with respect to the vector series of the time series pattern,

[0175]

[Equation 32]

It becomes: Therefore, the evaluation index of the degree of correspondence by the squared error E normalized by the scale K is defined by the similarity S using the square root of the second term of Expression 32.

[0177]

[Expression 33]

In the equation 32, the squared error E is the same whether the scale K according to the equation 30 is positive or negative. But,
When a symbol name is given to the time series data, the degree of similarity must be small when they are inverted and matched. Number 33
By considering the square root of the second term on the right side of Equation 32,
It is possible to obtain an appropriate degree of similarity. The similarity S represented by the equation 32 satisfies −1.0 ≦ S ≦ 1.0, has a form similar to an ordinary correlation coefficient, and is considered as a correlation coefficient between vector sequences. be able to.

As described above, the equations of the similarity S and the scale K are obtained on the assumption that the vector series of the time series data and the vector series of the standard pattern have a one-to-one correspondence. In general, there is a case where one vector and a plurality of vectors correspond to each other between the standard pattern vector series and the time series data vector series. In this case, the similarity S and the scale K shown in Expressions 33 and 30 are

[0180]

[Equation 34]

[0181]

[Equation 35]

It is used after being modified. Here, the vector series of the pattern data corresponding to the standard pattern vector Vj is Aij (j = 1, 2, ..., Ni).

The symbolization method according to the present embodiment is characterized in that by converting the time series data into a vector series and handling it, it is possible to carry out the collation in consideration of the positional deviation of the pattern and the change of the shape.

In the examples of the symbolizing device shown in FIGS. 1 to 18, the characters are used as the symbolic expression, but a symbol symbol (for example, see FIG. 22) that can express a certain meaning is used. It can also be used.

[0185]

As described above, according to the present invention, the shape in which the process state value changes with the passage of time is converted into a symbolic expression, which is edited in a predetermined format and the operator is informed. By providing it, it is possible to realize a process information display method that is easy to understand and does not place a heavy burden on the plant abnormality monitoring work. In addition, the subjective judgment of the operator can be eliminated in the judgment of the change tendency.

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of an embodiment of a symbolization device used for converting process data into a symbolic representation in the present invention.

FIG. 2 is a flowchart showing an operation of a polygonal line approximation processing unit in the symbolization device.

FIG. 3 is an explanatory view (No. 1) for explaining a symbolization process in the symbolization device.

FIG. 4 is an explanatory view (No. 2) for explaining the process of symbolization in the symbolization device.

FIG. 5 is an explanatory diagram showing an example of a feature extraction filter used in the symbolization device.

FIG. 6 is an explanatory diagram showing an example of standard vectors used in the symbolization device.

FIG. 7 is a flowchart illustrating processing in an integrated processing unit in the symbolization device.

FIG. 8 is an explanatory diagram illustrating an example of integration processing in an integration processing unit.

FIG. 9 is an explanatory diagram illustrating an example of integration processing in an integration processing unit.

FIG. 10 is a flowchart illustrating processing in a dictionary search processing unit of the symbolization device.

FIG. 11 is an explanatory diagram showing an example of a standard pattern dictionary used in a dictionary search processing unit.

FIG. 12 is a flowchart illustrating a procedure of search processing in the dictionary search processing unit.

FIG. 13 is a block diagram showing the configuration of another embodiment of a symbolization device used for converting process data into a symbolic representation in the present invention.

FIG. 14 is a flowchart showing an operation of a polygonal line approximation processing unit in the symbolization device.

FIG. 15 is an explanatory diagram showing an example of a feature extraction filter used in a polygonal line approximation processing unit.

FIG. 16 is an explanatory diagram illustrating a process of symbolization in a polygonal line approximation processing unit.

FIG. 17 is an explanatory diagram illustrating a result of symbolization.

FIG. 18 is a block diagram showing the configuration of an embodiment of the process information display system of the present invention.

FIG. 19 is an explanatory diagram showing a hardware configuration example of the present invention.

FIG. 20 is an explanatory diagram showing an example of a historical data storage format.

FIG. 21 is a detailed block diagram of an encoding unit.

FIG. 22 is an explanatory diagram showing an example of a standard pattern.

23 is an explanatory diagram showing a display example of a symbolization result in the embodiment of FIG.

FIG. 24 is an explanatory diagram showing another display example of the symbolization result in the embodiment of FIG.

FIG. 25 is an explanatory diagram showing still another symbolization result display example in the embodiment of FIG. 18.

FIG. 26 is a block diagram showing another embodiment of the present invention.

FIG. 27 is a flowchart supplementing FIG. 26.

28 is an explanatory diagram showing a display example of symbolization results in the embodiment of FIG.

FIG. 29 is a block diagram showing still another embodiment of the present invention.

FIG. 30 is an explanatory view showing still another symbolization result display example according to the embodiment of the present invention.

FIG. 31 is an explanatory view showing still another symbolization result display example according to the embodiment of the present invention.

FIG. 32 is an explanatory diagram showing still another symbolization result display example according to the embodiment of the present invention.

FIG. 33 is an explanatory diagram showing still another symbolization result display example according to the embodiment of the present invention.

[Explanation of symbols]

1: target process, 2: process input / output device, 3: central processing unit, 4: memory, 5: auxiliary storage device, 6: information display device, 7: input device, 51-1 to 4: trend graph, 52- 1-9: sign symbol, 53-1-2: equipment element, 54-1-4: status measurement point identification code, 55-2:
Status value, 56-1: Abnormality occurrence time, 57-1: Abnormality content, 58-1: Symbol name, 59-1: Unconfirmed mark, 6
0-1: Encoding result generation section, 101: Process state detection means, 102: Process state value storage section, 103: Historical data storage section, 104: Historical data buffer, 105: Historical data storage section, 10
6: symbolization means, 107: symbolization parameter storage unit, 1
08: symbolization result storage unit, 109: information editing means, 20
0: drawing style storage unit, 301: start data time, 30
2: data counter, 303: process state value, 30
4: head pointer, 305: tail counter, 30
6: head data time, 307: process state value, 40
1: process state value input, 402: other input of symbolization parameter, 403: polygonal line approximation processing unit, 404: filter storage unit, 405: temporary data storage unit, 406: dictionary search processing unit, 407: standard pattern storage Part, 408: evaluation value calculation part, 409: symbolization result output, 901: abnormality monitoring means, 902: abnormality monitoring specification storage part, 903: abnormal state storage means, 100-1 to 4: trend graph, 101-1
-10: sign symbol, 102-1 and 2-2: equipment element, 1
03-1 to 3-3: state measurement point identification symbol, 104: state value,
105: abnormality occurrence time, 106: abnormality content, 106: symbolization result occurrence section.

─────────────────────────────────────────────────── ───

[Procedure amendment]

[Submission date] July 23, 1993

[Procedure Amendment 1]

[Document name to be amended] Statement

[Correction target item name] 0185

[Correction method] Change

[Correction content]

[0185]

As described above, according to the present invention, the shape in which the process state value changes with the passage of time is converted into a symbolic expression, which is edited in a predetermined format and the operator is informed. By providing it, it is possible to realize a process information display method that is easy to understand and does not place a heavy burden on the plant abnormality monitoring work. In addition, the subjective judgment of the operator can be eliminated in the judgment of the change tendency.

[Procedure Amendment 2]

[Document name to be amended] Statement

[Name of item to be corrected] Brief description of the drawing

[Correction method] Change

[Correction content]

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of an embodiment of a symbolization device used for converting process data into a symbolic representation in the present invention.

FIG. 2 is a flowchart showing an operation of a polygonal line approximation processing unit in the symbolization device.

FIG. 3 is an explanatory view (No. 1) for explaining a symbolization process in the symbolization device.

FIG. 4 is an explanatory view (No. 2) for explaining the process of symbolization in the symbolization device.

FIG. 5 is an explanatory diagram showing an example of a feature extraction filter used in the symbolization device.

FIG. 6 is an explanatory diagram showing an example of standard vectors used in the symbolization device.

FIG. 7 is a flowchart illustrating processing in an integrated processing unit in the symbolization device.

FIG. 8 is an explanatory diagram illustrating an example of integration processing in an integration processing unit.

FIG. 9 is an explanatory diagram illustrating an example of integration processing in an integration processing unit.

FIG. 10 is a flowchart illustrating processing in a dictionary search processing unit of the symbolization device.

FIG. 11 is an explanatory diagram showing an example of a standard pattern dictionary used in a dictionary search processing unit.

FIG. 12 is a flowchart illustrating a procedure of search processing in the dictionary search processing unit.

FIG. 13 is a block diagram showing the configuration of another embodiment of a symbolization device used for converting process data into a symbolic representation in the present invention.

FIG. 14 is a flowchart showing an operation of a polygonal line approximation processing unit in the symbolization device.

FIG. 15 is an explanatory diagram showing an example of a feature extraction filter used in a polygonal line approximation processing unit.

FIG. 16 is an explanatory diagram illustrating a process of symbolization in a polygonal line approximation processing unit.

FIG. 17 is an explanatory diagram illustrating a result of symbolization.

FIG. 18 is a block diagram showing the configuration of an embodiment of the process information display system of the present invention.

FIG. 19 is an explanatory diagram showing a hardware configuration example of the present invention.

FIG. 20 is an explanatory diagram showing an example of a historical data storage format.

FIG. 21 is a detailed block diagram of an encoding unit.

FIG. 22 is an explanatory diagram showing an example of a standard pattern.

23 is an explanatory diagram showing a display example of a symbolization result in the embodiment of FIG.

FIG. 24 is an explanatory diagram showing another display example of the symbolization result in the embodiment of FIG.

FIG. 25 is an explanatory diagram showing still another symbolization result display example in the embodiment of FIG. 18.

FIG. 26 is a block diagram showing another embodiment of the present invention.

FIG. 27 is a flowchart supplementing FIG. 26.

28 is an explanatory diagram showing a display example of symbolization results in the embodiment of FIG.

FIG. 29 is a block diagram showing still another embodiment of the present invention.

FIG. 30 is an explanatory view showing still another symbolization result display example according to the embodiment of the present invention.

FIG. 31 is an explanatory view showing still another symbolization result display example according to the embodiment of the present invention.

FIG. 32 is an explanatory diagram showing still another symbolization result display example according to the embodiment of the present invention.

FIG. 33 is an explanatory diagram showing still another symbolization result display example according to the embodiment of the present invention.

[Explanation of Codes] 1: Target process, 2: Process input / output device, 3: Central processing unit, 4: Memory, 5: Auxiliary storage device, 6: Information display device, 7: Input device, 51-1 to 5-4: Trend graph, 52-1 to 9: Symbol symbol, 53-1 to 2: Equipment element, 54-1 to 4: State measurement point identification symbol, 55-2:
Status value, 56-1: Abnormality occurrence time, 57-1: Abnormality content, 58-1: Symbol name, 59-1: Unconfirmed mark, 6
0-1: Encoding result generation section, 101: Process state detection means, 102: Process state value storage section, 103: Historical data storage section, 104: Historical data buffer, 105: Historical data storage section, 10
6: symbolization means, 107: symbolization parameter storage unit, 1
08: symbolization result storage unit, 109: information editing means, 20
0: drawing style storage unit, 301: start data time, 30
2: data counter, 303: process state value, 30
4: head pointer, 305: tail counter, 30
6: head data time, 307: process state value, 40
1: process state value input, 402: other input of symbolization parameter, 403: polygonal line approximation processing unit, 404: filter storage unit, 405: temporary data storage unit, 406: dictionary search processing unit, 407: standard pattern storage Part, 408: evaluation value calculation part, 409: symbolization result output, 901: abnormality monitoring means, 902: abnormality monitoring specification storage part, 903: abnormal state storage means, 100-1 to 4: trend graph, 101-1
-10: sign symbol, 102-1 and 2-2: equipment element, 1
03-1 to 3-3: state measurement point identification symbol, 104: state value,
105: abnormality occurrence time, 106: abnormality content, 106: symbolization result occurrence section.

 ─────────────────────────────────────────────────── ─── Continuation of front page (72) Inventor Satoshi Oishi 5-2-1 Omika-cho, Hitachi-shi, Ibaraki Hitachi Ltd. Omika factory

Claims (12)

[Claims] 1. A process information display system comprising an information display device for displaying the status of a target process,
Symbolizing means for converting a change pattern of the information relating to the state of the process that changes over time into a symbolic representation, and the information display device having a form in which the information relating to the state of the process changes over time. A process information display system comprising a trend display and an information editing means for displaying a symbolic expression which is an output from the symbolization means together with the trend display. 2. A process information display system comprising an information display device for displaying the state of a target process,
Symbolizing means for converting a change pattern of information relating to the state of the process, which changes with time, into a symbolic representation, and a flow image showing the structure of the process is displayed on the information display device, and from the symbolizing means. A process information display system comprising: an information editing unit for displaying a symbolic expression which is an output together with the flow image. 3. A process information display system including an information display device for displaying the state of a target process,
Symbolizing means for converting a change pattern of the information relating to the state of the process that changes over time into a symbolic representation, and displaying on the information display device a symbol of a device corresponding to the information relating to the state of the process A process information display system, comprising: an information editing means for displaying a symbolic expression output from the symbolizing means in association with a displayed device symbol. 4. A process information display system including an information display device for displaying the state of a target process,
Symbolizing means for converting a change pattern of information relating to the state of the process, which changes over time, into a symbolic expression; and an abnormality monitoring means for monitoring the information display device for any abnormality in the information relating to the state of the process. A process for displaying a list of abnormal contents in an alarm summary format and an information editing unit for displaying a symbolic expression output from the symbolizing unit together with an alarm summary of the abnormal contents Information display system. 5. The information editing means according to claim 1, 2, 3 or 4, extracting a plurality of process information points having the same symbolic expression from among a plurality of symbolic symbolic expressions, A process information display system having a function of collectively displaying information point names, occurrence times, and symbolized information for a plurality of process information points. 6. The method according to claim 1, 2, 3, 4 or 5.
About the symbolic expressions displayed now and in the past,
The information editing means further includes a confirmed storage means for storing information on whether or not the operator has confirmed, and a confirmation operation means for the operator to confirm the symbolic expression of the unconfirmed state. About the symbolic expressions
A process information display system having a function of displaying with a distinction whether it is in a confirmed state or not. 7. The historical data storage means according to claim 1, 2, 3, 4, 5 or 6, wherein information relating to a process state is stored in time series as historical data, and a designated sampling interval and time range. And a data extracting means for extracting historical data in the above, wherein the symbolizing means converts a change pattern of the extracted historical data into a symbolic expression, and the information editing means displays the historical data as a trend. , A process information display system having a function of displaying a symbolic expression which is an output from a symbolization means together with a trend display of historical data. 8. The information editing means according to claim 7,
The output from the symbolizing means is displayed as a symbol indicating the current state, and the change pattern of the historical data extracted from the historical data storage means is converted into a symbolic representation, and the other output from the symbolizing means is converted to the past state. A process information display system having a function of displaying as a symbol indicating. 9. The encoding means as set forth in claim 1, wherein the encoding means entirely encodes a long time range of information relating to a state of a process and, at the same time, locally encodes a part of the time range. Characterized by having a function to perform,
Process information display system. 10. The process information display according to claim 9, wherein the information editing means has a function of displaying the two symbolic expressions and a trend graph for the two time ranges together. system. 11. Claims 1, 2, 3, 4, 5, 6, 7,
8. The process information display system according to 8, 9, or 10, wherein the information related to the process state is information of at least one of a process state value, a target value, and a process manipulated variable. 12. The monitoring target of the abnormality monitoring means according to claim 4, wherein at least one of an upper and lower limit abnormality of the process state value, a deviation abnormality and a change rate abnormality is included.
Process information display system.