JP2002328914A - Device and method for detecting degree of state similarity, storage medium and computer program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve judging precision of a state similarity by making it possible to define a precise state similarity index based on two kinds of time-series readouts obtained from two evaluation subjects. SOLUTION: Similarity of a shape of a curved surface at each time of a reconfiguration attractor formed by time history of delay vector is evaluated by a distance between the two curved surfaces (norm d) and the state similarity index is defined on the basis of the evaluation, enabling evaluation of the degree of state similarity to be made on the basis of a plane. In this way the degree of similarity of the two evaluation subjects 10a and 10b can be evaluated highly precisely even in a state where recognition is impossible on the basis of a point due to great latitude allowed.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a state similarity detection device, a state similarity detection method, a recording medium, and a computer program. More particularly, the present invention relates to two types of time series measurement values obtained from two types of evaluation objects. It is suitable for creating a constituent attractor, defining a state similarity index indicating the similarity of these reconstructed attractors at each time, and detecting the similarity between the two evaluation targets.

[0002]

2. Description of the Related Art Conventionally, the state of an object to be evaluated is measured by directly measuring a physical quantity (temperature, etc.) reflecting the state from the object to be evaluated using a measuring instrument, and measuring the state of the object to be evaluated from the measured value. Was detected.

If the physical quantity reflecting the above condition cannot be directly measured from the evaluation object, the physical quantity is measured at a measurement point distant from the evaluation object, and the state of the evaluation object is estimated from the measured value. I was

[0004] For example, two thermocouples are arranged in a mold in the horizontal direction, and the values obtained from the thermocouples are compared to measure the heat flow rate. Further, the correlation degree between the two evaluation targets to be detected is detected using the correlation coefficient of the values obtained from the two thermocouples.

[0005]

In the case of directly comparing the values obtained from each of the above thermocouples, the comparison has been a point comparison. When detecting the degree of correlation between two evaluation targets,
Since this is a one-dimensional line comparison, there is a limit in improving the accuracy of performing state similarity determination.

The present invention has been made to solve the above-described problem, and an accurate state similarity index can be defined based on two types of time-series measurement values obtained from two evaluation targets. In this way, an object of the present invention is to improve the state similarity determination accuracy.

[0007]

According to the present invention, there is provided a state similarity detecting apparatus for detecting a similarity between two evaluation targets based on two types of time series measurement values obtained from the two evaluation targets. A reconstructor attractor creating means for creating two reconstructor attractors respectively corresponding to the two evaluation objects from the two types of time-series measurement values respectively obtained from the two evaluation objects; Index defining means for defining a state similarity index indicating similarity at each time of the reconstructed attractor, wherein the similarity between the two evaluation targets is detected based on the state similarity index. . According to another feature of the present invention, the index defining means sets the number of past consecutive time points to a certain time as N and the number falling within a predetermined threshold as n ^t ε. The above-mentioned state similarity index ISS
And calculated by the ISS = n ^t ε / N is characterized by defining the state similarity index. Another feature of the present invention is that the state similarity index is defined after standardizing the size of the reconstructed attractor. Another feature of the present invention is that the reconstruction attractor creating means creates the reconstruction attractor by performing an operation for obtaining signals at the two evaluation target positions by inverse problem analysis. And Another feature of the present invention is that the apparatus includes a processing unit that executes at least one of the analysis processing, the diagnosis processing, and the control processing of the phenomena in the two evaluation targets. According to another feature of the present invention, based on signals measured at measurement points separated by a predetermined distance from two evaluation targets,
A state similarity detection device for two evaluation targets that detects a similar state between the two evaluation targets, wherein the similarity state between the two evaluation targets is stored in a storage medium that stores a priori information obtained in the past. Information measuring means for measuring the signals output from the two evaluation objects and attenuated by the resistance between the two evaluation objects and the measurement points at the measurement points; and Using the signal
Calculating means for obtaining signals at two positions to be evaluated by inverse problem analysis; and performing predetermined processing on the signals at the two positions to be evaluated obtained by the calculating means to obtain signals at each time of the two reconstructed attractors. It is characterized by having index definition means for defining a state similarity index indicating similarity, and similarity detection means for detecting the similarity between the two evaluation targets based on the state similarity index.

The state similarity detection method according to the present invention is a method for detecting the similarity between the two evaluation targets based on two kinds of time-series measurement values respectively obtained from the two evaluation targets. Reconstruction attractor creation processing for creating two reconstructed attractors corresponding to the two evaluation objects from two types of time-series measurement values respectively obtained from the two evaluation objects, and respective times of the two reconstructed attractors And an index definition process for defining a state similarity index indicating the similarity in the above.
It is characterized in that the similarity between two evaluation targets is detected, and at least one of a diagnosis process and a control process is performed according to the detection result. Further, another feature of the present invention is that the index definition processing is performed when the number of past consecutive time points reaching a certain time is N, and the number falling within a predetermined threshold is n ^t ε. The above state similarity index ISS is
It is characterized in that the above-mentioned state similarity index is defined by calculating with SS = ^nt ε / N. Another feature of the present invention is that the state similarity index is defined after standardizing the size of the reconstructed attractor. Other features of the present invention include:
The reconstructed attractor creation process is characterized in that the reconstructed attractor is created by performing an operation for obtaining signals at the two positions to be evaluated by inverse problem analysis. Another feature of the present invention is that at least one of analysis, diagnosis, and control of the phenomena in the two evaluation targets is performed. Another feature of the present invention is that, based on signals measured at measurement points separated by a predetermined distance from the two evaluation targets, two evaluation targets for detecting a similar state between the two evaluation targets are detected. A state similarity detection method, wherein a similar state of the two evaluation targets is stored in a storage medium storing a priori information obtained in the past; A signal measurement process of measuring a signal attenuated by a resistance between two evaluation targets and a measurement point at a measurement point, and a signal measured by the signal measurement process described above, the inverse problem analysis is performed at two evaluation target positions. An arithmetic operation for obtaining a signal, and a state in which predetermined processing is performed on the signals at the two positions to be evaluated obtained by the arithmetic operation to indicate the similarity of the two reconstructed attractors at each time An index definition process for defining a similarity index and a similarity detection process for detecting the similarity between the two evaluation targets based on the state similarity index are performed, and at least one of a diagnosis process and a control process is performed according to the detection result. It is characterized in that one process is performed.

A storage medium according to the present invention is characterized in that a program for causing a computer to function as each of the above-described means is recorded. Another feature of the present invention is that a program for causing a computer to execute the processing procedure of the state similarity detection method according to any one of the above is recorded.

[0010] A computer program according to the present invention causes a computer to execute the processing procedure of the state similarity detection method described in any of the above.

According to the present invention configured as described above, the similarity of the curved surface shape at each time of the reconstructed attractor formed by the time history of the delay vector is evaluated by the distance (norm) between these two curved surfaces. Since the state similarity index is defined based on the above evaluation, it is possible to evaluate the state similarity based on the surface, and in the state where the degree of freedom is too large to be recognized in the point evaluation, Can be evaluated, and the discrimination accuracy can be significantly improved.

According to another feature of the present invention, the influence of the resistance between the evaluation target and the measurement point included in the signal measured at the measurement point at a predetermined distance from the evaluation target is removed by inverse problem analysis. Becomes possible.

According to another feature of the present invention, a signal at a position of an evaluation target is obtained by inverse problem analysis using a signal measured at a measurement point at a predetermined distance from the evaluation target, and a predetermined process is performed. Since the state of the evaluation target is detected by comparing the obtained state information with the a priori information obtained in the past, the influence of the resistance between the evaluation target and the measurement point is excluded. The state similarity of two evaluation targets can be detected.

[0014]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment of a state similarity detection device, a state similarity detection method, a recording medium, and a computer program according to the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram showing a configuration example of a state control device to which the state detection device according to the first embodiment is applied. In FIG. 1, 30a and 30b are measuring units,
At a measurement point having a predetermined distance from the two evaluation targets 10a and 10b, the state signals output from the two evaluation targets 10a and 10b and attenuated by the resistors 20a and 20b are measured.

The state signals output from the two evaluation objects 10a and 10b are signals reflecting the state of the two evaluation objects 10a and 10b, and include heat, vibration, sound, and the like. That is, the measurement units 30a, 30ba, and 30b measure physical quantities and the like in which the states of the two evaluation targets 10a and 10b at the measurement points are reflected.

Here, the resistors 20a and 20b attenuate the state signals output from the two evaluation targets 10a and 10b. For example, if the state signal is a signal related to heat, the state signal becomes a heat transfer resistance such as a signal having a large heat capacity or a signal having a low thermal conductivity.

Numeral 40 denotes an arithmetic unit, which is the measuring unit 30a,
Based on the measurement result of the state signal in 30b (hereinafter, referred to as “measured value at measurement point”), the state of the outer surface of the evaluation target 10 or a point on the outer surface (hereinafter, referred to as “evaluation surface”). Find signals by inverse problem analysis,
A reconstructed attractor is created from the obtained state signals on the evaluation plane.

The operation unit 40 includes an inverse problem analysis unit 41, an attractor creation unit 42, an index definition unit 43, and a storage unit 4.
4 and the like.

The inverse problem analysis unit 41 performs an inverse problem analysis using the measured values at the measurement points and the physical properties of the resistors 20a and 20b, and obtains state signals on the evaluation planes of the two evaluation targets 10a and 10b. That is, the inverse problem analysis unit 41
Calculates a state signal measured when it is assumed that measurement is performed on the evaluation surfaces of the two evaluation targets 10a and 10b.

In the above inverse problem analysis, for example, two evaluation objects 10a and 10b, resistors 20a and 20b, and a measuring unit 3
A state signal at a measurement point is calculated using a predetermined equation (partial differential equation or the like) for a system including 0a and 30b and an assumed value of a state signal on the evaluation plane of the two evaluation targets 10a and 10b. .

The calculated state signal and the measuring unit 30a,
The assumption value of the state signal on the evaluation plane of the two evaluation targets 10a and 10b is corrected so that the error from the measurement value at the measurement point actually measured by 30b is smaller than a predetermined value, and the state signal at the measurement point is corrected. Is repeated. An assumed value when an error between the calculated state signal and an actually measured value at the measurement point is smaller than a predetermined value is set as a state signal on the evaluation plane of the two evaluation targets 10a and 10b.

Further, for example, based on the following equation, the state signals of the two evaluation objects 10a and 10b on the evaluation surface are calculated.

[0024]

(Equation 1)

The above equation (1) is a non-stationary equation, for example, a heat conduction equation in the case of heat conduction. Equation (1) above
By performing a predetermined operation or the like, an integral boundary equation such as equation (2) is obtained. In the equation (2), G is a solution of the conjugate equation, u is a scalar value (for example, temperature for heat conduction), and ∂u / ∂n is a scalar gradient (for example, heat flux for heat conduction). .

In equation (2), the left side is the integral with respect to the evaluation plane of the two evaluation objects 10a and 10b, and the right side is the integral with respect to a predetermined known boundary plane, for example, a plane including the measurement points. Therefore, based on the measurement value at the measurement point,
The value on the right side of Expression (2) is obtained, and from the obtained value, Expression (2) is obtained.
Scalar gradient ∂u / ∂n on the evaluation plane on the left side of is calculated. Further, the scalar gradient ∂u / ∂n on the evaluation plane obtained as described above is solved using the measurement value at the measurement point as a boundary condition to obtain the scalar value u on the evaluation plane.
Is calculated. This scalar value u is a state signal on the evaluation surface.

The attractor creating unit 42 includes the inverse problem analyzing unit 4
A trajectory called an attractor is reconstructed on the basis of the state signal on the evaluation plane in the time series calculated in step (1). First, the attractor creating unit 42 calculates a delay vector v having a dimension m more than twice the target phenomenon from the state signal on the evaluation plane of the time series calculated by the inverse problem analysis unit 41.
(T) = (u (t), u (t + τ), u (t + 2τ),
.., U (t + (m−1) τ)).

Here, in the delay vector v (t), u (T) is the value of the state signal on the evaluation plane at time T. For example, when the inverse problem analysis unit 41 calculates the state signal on the evaluation plane using the above-described equations (1) and (2), u (T) is a scalar value u of the evaluation plane. Note that the scalar gradient ∂u / ∂n on the evaluation plane may be used as u (T).

Next, the attractor creating section 42 maps the created delay vector v (t) into a phase space having a predetermined dimension. The attractor is reconstructed by creating a trajectory of the mapped delay vector v (t) based on the time transition. In the following description, the reconstructed attractor is referred to as a “reconstructed attractor”.

The index definition section 43 is for defining a state similarity index indicating the similarity between the two reconstructed attractors at each time. In the present embodiment, when the number of past consecutive time points up to a certain time is N and the number falling within a predetermined threshold is n ^t ε, the state similarity index ISS is calculated as ISS = ^nt The above state similarity index is defined by calculating with ε / N.

Further, the index definition unit 43 of the present embodiment
The state similarity index is defined after standardizing the sizes of the two reconstructed attractors. There are several methods for standardizing the above two reconstructed attractors. In this embodiment, the distance d (i) between the above-mentioned N neighboring points at the same time is expressed by the following equation (3). It calculates and represents the number of neighbors that satisfies the condition of the following equation (4).

[0032]

(Equation 2)

Here, i represents an arbitrary time point of the N neighboring points, and var (v ₁ (t ₀ )) and var (v
₂ (t ₀ )) are the delay vectors v ₁ (t ₀ ) and v
₂ (t ₀ ) represents the variance of the N neighboring points.

Further, / v ₁ (t ₀ ) and / v ₂ (t ₀ ) represent an average value of N neighboring points, ε ′ represents a threshold value for performing distance determination, and a certain positive Give a real value. Note that the above “/” indicates “overbar” in the equation (3).

FIG. 2 shows the concept of defining the state similarity index ISS performed by the state similarity detection device of the present embodiment. As shown in FIG. 2, the shapes of the first reconstruction attractor 21 and the second reconstruction attractor 22 are compared.

The storage unit 44 stores data used for processing in the inverse problem analysis unit 41, attractor creation unit 42, and graph creation unit 43. The storage unit 44 stores the measured values of the state signals measured by the measurement units 30a and 30b, the state signals on the evaluation plane calculated by the inverse problem analysis unit 41, the two reconstructed attractors created by the attractor creation unit 42, and the like. Is stored.

Reference numeral 50 denotes an a priori information storage unit, and two evaluation objects 10a, 10a and 10a obtained by past experiments, experiences, and the like.
The state of b and a recurrence plot showing the behavior of that state are stored.

Reference numeral 60 denotes a processing unit, which includes a similarity detection unit 61 and converts the recurrence plot supplied from the arithmetic unit 40 and the recurrence plot stored in the prior information storage unit 50. Based on two evaluation objects 10
The states of a and 10b are detected.

The similarity detection unit 61 compares the shapes of the first reconstructed attractor 21 and the second reconstructed attractor 22 supplied from the arithmetic unit 40, and determines the state of the two evaluation objects 10a and 10b. Define similarity indicators. And
Based on the result, the similarity detection unit 61 detects the states of the two evaluation targets 10a and 10b.

For example, 2 supplied from the arithmetic unit 40
If the shapes of the two evaluation targets 21 and 22 are similar, the value of the state similarity index ISS is defined as being infinitely close to “1”, and it can be seen that the states of the two evaluation targets are stable.

This will be specifically described with reference to FIG. As shown in FIG. 2, the first reconstruction attractor 2
When comparing the shapes of the first and second reconstruction attractors 22, the state similarity index ISS is evaluated by evaluating the distance (norm d) between the two curved surfaces at each time of the two reconstruction attractors.
Is defined.

In the example shown in FIG. 2, each time on the first reconstructed attractor surface 21a is represented by white circles i, i-1, i-2, i.
-3,..., The second reconstructed attractor surface 22a
Are the times i, i-1, i-2, i-3,.
・ Indicated by Further, the distance between the two reconstructed attractors at time i is indicated by l ₀ , and the distance between the two reconstructed attractors at time i-1 is indicated by l ₁ . Similarly, it indicates the distance between two reconstructed attractor at time i-2 at l _2, represents the distance between two reconstructed attractor at time i-3 at l _3.

It is determined whether or not the distance between the two reconstructed attractors at the same time satisfies the condition of the above-mentioned equation (4), and the number which falls within the threshold value is detected. Then, a state similarity index is defined by an expression for calculating the above-mentioned state similarity index ISS, that is, ISS = ^nt ε / N.

FIG. 3 is a flowchart showing an operation example of the state similarity detection device of the present embodiment. In FIG. 3, the calculation unit 40 takes in the measurement values supplied from the measurement units 30a and 30b (step S1). Next, in step S2, the measured values from the two two evaluation targets 10a and 10b captured in step S1 are converted into the inverse problem analysis unit 4.
Feed to 1. The inverse problem analysis unit 41 performs an inverse problem analysis for obtaining the temperature or the heat flux at the two evaluation targets 10a and 10b on the operating surface of the cast slab in the mold using the supplied measured values.

Here, it is assumed that inverse problem analysis is performed using the above-described equations (1) and (2). That is, the inverse problem analysis unit 41 first evaluates two points on the operating surface of the cast slab in the mold based on the temperature measured by the thermocouple measuring the evaluation target 10a and the temperature measured by the thermocouple measuring the evaluation target 10b. Target 10
a, heat flux at 10b ({u / ∂ on the left side of equation (2))
n). Then, the temperatures at the two evaluation targets 10a and 10b on the operating surface of the cast slab in the mold are obtained from the obtained heat flux and the temperatures measured by the thermocouples.

Next, at step S3, the attractor creating section 4
No. 2 reconstructs the attractor from the heat flux values of the two evaluation targets 10a and 10b on the operating surface of the cast slab in the mold calculated in step S2. That is, the attractor creating unit 42 creates an m-dimensional delay vector v (t) based on the heat flux value calculated by the inverse problem analysis unit 41. Then, the delay vector is represented by (x (t),
By plotting x (t + 7τ) and x (t + (m−1) τ) as coordinates, an attractor showing the time transition of the delay vector is reconstructed. Here, m is a number that is twice or more the dimension obtained by the correlation dimension analysis.

Next, in step S4, as described above,
The index definition unit 43 performs a comparison process between the first reconstructed attractor 21 and the second reconstructed attractor 22 reconstructed in step S3. Next, in step S5, the state definition index ISS is defined by the index definition unit 43.

Next, in step S6, the processing section 60 performs a predetermined process according to the state detected by the similarity detection section 61. For example, when the cooling is not performed uniformly in the width direction of the mold, when a vertical crack or the like occurs in the in-mold slab, the cooling method is improved so as to eliminate the non-uniform cooling. .

As described above, according to the present embodiment, the calculating unit is operated based on the temperatures output from the two evaluation targets 10a and 10b and measured by the measuring units 30a and 30b via the resistors 20a and 20b. In the inverse problem analysis unit 41 in the 40, two evaluation objects 1 on the working surface of the in-mould slab 201
An inverse problem analysis for obtaining the temperature and the heat flux at 0a and 10b is performed.

As a result, the two evaluation objects 10a, 10a
b and the measuring units 30a and 30b are separated from each other, and even if the temperature output from the slab in the mold cannot be directly measured, the influence of the resistors 20a and 20b between them can be removed by inverse problem analysis. It is possible to accurately calculate the temperature and the heat flux when it is assumed that the measurement is performed on the two evaluation objects 10a and 10b on the working surface of the cast slab in the mold.

Next, a specific example will be described with reference to FIGS. In FIG. 4, 41 is a continuous casting mold, 42 is a molten metal surface position, 43 is a first central thermocouple, 44 is a second central thermocouple, 45 is a first end surface thermocouple, and 46 is a second end surface thermocouple. Each pair is shown.

In the case of this example, the average molten metal position 42 to 10
A time series observation value comprising an average value of the first central thermocouple 43 and the second central thermocouple 44 disposed about 0 mm below;
The similarity with the time series observation value composed of the average value of the first end face thermocouple 45 and the second end face thermocouple 46 is determined by the state similarity index IS.
S is evaluated.

FIG. 5 shows an example of the case where the similarity of the time series observation values is evaluated by the state similarity index ISS. In FIG. 5, a vertical crack occurs in a region indicated by an arrow 50. It can be seen that such a region is remarkably generated when the state similarity index ISS falls below a certain value.

The vertical cracks are said to occur when the cooling in the width direction in the mold becomes non-uniform, and the similarity evaluation of the thermocouple measurement values of the center and the end face is based on the evaluation of the cooling uniformity in the width direction in the mold. It is a quantification index. The region in which the state similarity index in FIG. 2 is reduced means that the uniformity of cooling in the mold width direction is reduced. The occurrence of vertical cracks in this region indicates the validity of the method of the present embodiment. ing.

FIG. 6 is a block diagram showing an example of the internal configuration of a computer system which can constitute the state similarity detection device of the present embodiment. 6, reference numeral 600 denotes a computer PC. The PC 600 includes a CPU 601.
Stored in the ROM 602 or the hard disk (HD) 611 or a flexible disk drive (F
D) The device control software supplied from the 612 is executed to comprehensively control each device connected to the system bus 604.

The CPU 601 and the ROM 6 of the PC 600
02 or the program stored in the hard disk (HD) 611 constitutes each functional unit of the present embodiment.

Reference numeral 603 denotes a RAM, which functions as a main memory, a work area, and the like for the CPU 601. Reference numeral 607 denotes a disk controller (DKC), which is a hard disk that stores a boot program (a boot program: a program for starting execution (operation) of a hardware or software of a personal computer), a plurality of applications, an edit file, a user file, a network management program, and the like. HD) 611 and flexible disk (FD) 612.

Reference numeral 608 denotes a network interface card (NIC) for bidirectional data exchange with a network printer, another network device, or another PC via a LAN 620.

(Other Embodiments of the Present Invention) The measuring device and the state detecting device of the present embodiment described above are constituted by a CPU or MPU of a computer, a RAM, a ROM, and the like. It can be realized by operating a program stored in the ROM. Therefore, the present invention can be realized by recording a program that causes a computer to perform the above function on a recording medium such as a CD-ROM and reading the program into the computer. As a recording medium for recording the program, a flexible disk, a hard disk, a magnetic tape, a magneto-optical disk, a nonvolatile memory card, and the like can be used in addition to the CD-ROM.

Further, the functions of the above-described embodiments are not only realized by the computer executing the supplied program, but also the OS (operating system) or other application software running the program on the computer. When the functions of the above-described embodiment are realized in cooperation with the computer, or when all or a part of the processing of the supplied program is performed by a function expansion board or a function expansion unit of a computer, the functions of the above-described embodiment are realized. Such a program is also included in the embodiment of the present invention.

In order to use the present invention in a network environment, all or some of the programs may be executed by another computer. For example, the screen input processing may be performed by a remote terminal computer, and various determinations and log recording may be performed by another center computer or the like.

[0062]

As described above, according to the present invention,
The similarity of the curved surface shape at each time of the reconstructed attractor formed by the time history of the delay vector is evaluated by the distance (norm) between these two curved surfaces, and the state similarity index is defined based on the evaluation. Therefore, it is possible to evaluate the state similarity based on the surface, and it is possible to evaluate the similarity with high accuracy even in a state where the degree of freedom is too large to be recognized in the point evaluation. Thus, the discrimination accuracy can be significantly improved.

According to another characteristic of the present invention,
It is possible to remove the influence of the resistance between the evaluation target and the measurement point included in the signal measured at the measurement point at a predetermined distance from the two evaluation targets by the inverse problem analysis.

According to another feature of the present invention, a signal output from an object to be measured whose physical quantity cannot be directly measured and attenuated by a resistance between the object to be evaluated and a measurement point is converted into a predetermined signal from the object to be evaluated. Measured at a measurement point that is only a distance away, and the signal at the position of the evaluation target is obtained by inverse problem analysis using the signal measured above. The influence can be removed by inverse problem analysis, and the signal at the position to be evaluated can be accurately obtained to define the state similarity index.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration example of a state control device to which a state detection device according to a first embodiment is applied.

FIG. 2 is a diagram illustrating a procedure for defining a state similarity index.

FIG. 3 is a flowchart illustrating an operation example of the state similarity detection device according to the embodiment;

FIG. 4 is a diagram showing an example in which the state similarity detection device of the embodiment is applied to a continuous casting mold.

FIG. 5 is a diagram illustrating an example in which the similarity of time-series observation values measured by a thermocouple is evaluated using a state similarity index.

FIG. 6 is a block diagram illustrating an example of a computer system that can configure the state similarity detection device according to the embodiment;

[Explanation of symbols]

10a First evaluation target 10b Second evaluation target 20a First resistance 20b Second resistance 30a First measurement unit 30b Second measurement unit 40 Operation unit 41 Inverse problem analysis unit 42 Attractor creation unit 43 Index definition unit 44 storage unit 50 a priori information storage unit 60 processing unit 61 similarity detection unit 600 PC (computer) 601 CPU (central processing unit) 602 ROM (read only memory) 603 RAM (random access memory) 604 system bus 605 KBC ( Keyboard controller) 606 CRTC (controller for controlling access to CRT) 607 DKC (disk controller) 608 NIC (network interface card) 609 KB (keyboard) 610 CRT (display) 611 HD (hard disk) 612 D (flexible disk) 620 LAN (Local Area Network)

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Junichi Hayashi 20-1 Shintomi, Futtsu City Nippon Steel Corporation Technology Development Division (72) Inventor Kazuyuki Aihara 4-8-8-208 Yatsu, Narashino-shi, Chiba F term (reference) 2F076 BA01 BE04 BE06 BE08 5B056 BB23 HH00 5D015 HH02

Claims (15)

[Claims] 1. A method according to claim 1, wherein each of the two evaluation targets is obtained from two evaluation targets.
An apparatus for detecting a degree of similarity between the two evaluation targets based on the types of time-series measurement values, wherein the two types of time-series measurement values obtained from the two evaluation targets are used to determine the similarity of the two evaluation targets. A reconstructing attractor creating means for creating two reconstructing attractors corresponding thereto, and an index defining means for defining a state similarity index indicating the similarity of each of the two reconstructing attractors at each time; A state similarity detection device characterized in that the similarity between the two evaluation targets is detected based on the following. 2. The state similarity index ISS is defined as N, where N is the number of consecutive time points in the past leading to a certain time, and n ^t ε is a number falling within a predetermined threshold.
2. The state similarity detection device according to claim 1, wherein the state similarity index is defined by calculating ISS = n ^t ε / N. 3. The state similarity detection apparatus according to claim 1, wherein the state similarity index is defined after standardizing the size of the reconstruction attractor. 4. The reconstructed attractor according to claim 1, wherein the reconstructed attractor creating means creates the reconstructed attractor by performing an operation for obtaining signals at the two evaluation target positions by inverse problem analysis. The state similarity detection device according to claim 1. 5. The apparatus according to claim 1, further comprising a processing unit that executes at least one of an analysis process, a diagnosis process, and a control process of the phenomena in the two evaluation targets. The state similarity detection device according to the paragraph. 6. A state similarity detection device for two evaluation targets, which detects a similar state between the two evaluation targets based on a signal measured at a measurement point separated by a predetermined distance from the two evaluation targets. Information storage means for storing a priori information obtained in the past with respect to the similar state of the two evaluation objects, and an information storage means, A signal measuring means for measuring a signal attenuated by a resistance between the measuring points at a measuring point; a calculating means for obtaining signals at two evaluation target positions by inverse problem analysis using the signal measured by the signal measuring means; An index definition for performing a predetermined process on the signals at the two positions to be evaluated obtained by the arithmetic means and defining a state similarity index representing the similarity of the two reconstructed attractors at each time. Stage and state similarity detecting apparatus characterized by having a similarity detecting means for detecting the two evaluated similarity based on the state similarity index. 7. Each of two obtained from two evaluation targets
A method for detecting a similarity between the two evaluation targets based on the type of time-series measurement values, wherein the two types of time-series measurement values obtained from the two evaluation targets are used to determine the similarity between the two evaluation targets. Performing a reconstructed attractor creating process for creating two reconstructed attractors corresponding to each of the two, and an index defining process for defining a state similarity indicator representing the similarity of the two reconstructed attractors at each time, Detecting a similarity between the two evaluation objects based on the detection result, and performing at least one of a diagnosis process and a control process in accordance with a detection result. 8. The index defining process is defined as follows: when the number of past consecutive time points up to a certain time is N and the number falling within a predetermined threshold is n ^t ε, the state similarity index ISS
Is calculated by ISS = ^nt ε / N to define the state similarity index. 9. The state similarity detection method according to claim 7, wherein the state similarity index is defined after standardizing the size of the reconstructed attractor. 10. The reconstructed attractor according to claim 7, wherein the reconstructed attractor creating process performs an operation for obtaining signals at the two evaluation target positions by inverse problem analysis to create the reconstructed attractor. A method for detecting a state similarity according to any one of the preceding claims. 11. The state according to claim 7, wherein at least one of an analysis process, a diagnosis process, and a control process of the phenomena in the two evaluation targets is performed. Similarity detection method. 12. A method for detecting a state similarity between two evaluation objects, wherein the similarity between the two evaluation objects is detected based on a signal measured at a measurement point separated by a predetermined distance from the two evaluation objects. An information storage process of storing a priori information obtained in the past with respect to the similar state of the two evaluation objects, and an information storage process of the two evaluation objects and the measurement points output from the two evaluation objects. A signal measurement process of measuring a signal attenuated by a resistance between the measurement points at a measurement point; an arithmetic process of obtaining signals at two evaluation target positions by inverse problem analysis using the signal measured by the signal measurement process; A predetermined process is performed on the signals at the two evaluation target positions obtained by the arithmetic processing to define a state similarity index indicating the similarity between the two reconstructed attractors at each time. Performing a similarity detection process of detecting the similarity between the two evaluation targets based on the state similarity index, and performing at least one of a diagnosis process and a control process according to the detection result. Characteristic state similarity detection method. 13. A computer-readable recording medium on which a program for causing a computer to function as each of the means according to claim 1 is recorded. 14. A computer-readable recording medium on which is recorded a program for causing a computer to execute the processing procedure of the state similarity detection method according to claim 7. Description: 15. A computer program for causing a computer to execute the processing procedure of the state similarity detection method according to claim 7. Description: