JPH05312989A - Reactor stability monitoring method and its device - Google Patents

Abstract

PURPOSE:To accurately estimate core stability. CONSTITUTION:LPRM signal 3 and APRM signal 5 from neutron detectors 2 are sampled with an A/D converter 6 and digitalized. Based on the digitalized time series data, a correlation dimension value and its variation rate are calculated using a correlation dimension calculator 8 and a memory 9. In a data base 11, a typical core status, the correlation dimension value concerning its variation and the variation rate are stored in advance. The correlation value and its variation rate calculated using the correlation dimension calculator 8 and the memory 9 are compared with the data stored in the data base 11 by a comparison calculator 10. Then, with a judger 12, the core 1 stability is estimated.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a reactor stability monitoring method and apparatus for monitoring core power stability of a boiling water reactor.

[0002]

2. Description of the Related Art A boiling water reactor (BWR) includes a boiling channel consisting of gas-liquid two-phase flow in its core, and the boiling channel is called an instability mode caused by a density difference, that is, density wave oscillation. There is an inherent flow oscillation phenomenon. This is called channel instability, but in the actual BWR core, the effect of neutron dynamics is added to this, and it appears as a phenomenon that the neutron flux level in the core, that is, the core output, oscillates, and this is called core instability. I am calling it. Normally, the core instability is an unstable event that oscillates integrally in the core according to the neutron flux fundamental mode that exists originally in the most stable manner. In addition, spatially inhomogeneous neutron flux higher-order modes are excited in the core, and a phenomenon of oscillating at different spatial phases is also observed, which is called regional instability.

As an index showing the stability of the core, a width reduction ratio which is a ratio of adjacent amplitudes of responses is used. If the width reduction ratio is less than 1, it means that the vibration is damped, and thus it is stable. On the contrary, when it exceeds 1, it means that vibration grows and is unstable. When the value is exactly 1, it indicates that the amplitude is constant and the vibration continues.

However, in reality, due to the non-linearity of the system, even if the width reduction ratio exceeds 1, the growth of the amplitude stops at a certain point, and the oscillation shifts to a constant amplitude oscillation, that is, limit cycle oscillation. Therefore, limit cycle vibration is a vibration phenomenon that is completely different from harmonic vibration in a linear system, and since the actual system has nonlinearity,
The definition of the width reduction ratio may differ from the width reduction ratio in the sense of linearity.

In response to such a situation, when monitoring the stability of the plant on-site, at present, the width reduction ratio is obtained by a statistical method assuming linear stationarity / normality of the time series data, and its transition. Are watching.

[0006]

In the above-mentioned conventional reactor stability monitoring method, since the method of obtaining the width reduction ratio and monitoring the transition thereof is adopted, during a transient event that deviates from the stationarity, or In a region close to the stability limit where non-linearity becomes remarkable, it is difficult to accurately estimate the reduction ratio, and there is a problem that the core stability cannot be estimated accurately.

The present invention has been made in consideration of the above points, and it is possible to accurately monitor the stability of the reactor core and to improve the safety and operating rate of the reactor. It aims at providing the degree monitoring method and its apparatus.

[0008]

The reactor stability monitoring method according to the present invention, as a means for achieving the above object, obtains a correlation dimension from a neutron flux detection system signal, and based on the value and the fluctuation rate, The feature is that the transition of stability is monitored.

Further, the reactor stability monitoring apparatus according to the present invention comprises, as means for achieving the above object, a sampling means for sampling a neutron flux detection system signal; a correlation dimension for obtaining a correlation dimension from sampled time series data. Calculation means; calculation means for calculating the variation rate based on the change over time of the calculated correlation dimension value; storage means for storing the correlation dimension value and variation rate relating to a typical core state and its transition; And a determination means for comparing the value of the correlation dimension and the variation rate obtained by both the calculation means with the data from the storage means to determine the core stability.

[0010]

In the reactor stability monitoring method according to the present invention, the transition of stability is monitored using the correlation dimension. This correlation dimension is closely related to the stability of the system, which depends only on the dynamical system that describes the system, not on the nonstationarity / nonlinearity of the system. For this reason,
It is possible to estimate the stability of the core more accurately than the conventional method of monitoring only the reduction ratio.

Further, in the reactor stability monitoring device according to the present invention, the neutron flux detection system signal is sampled,
The correlation dimension is obtained from the sampled time series data, and the variation rate is obtained based on the change over time of the value. These are then compared to the values and volatility of the correlation dimension for typical core states and their transitions,
The core stability is determined. Therefore, more flexible monitoring is possible, and necessary stability improvement measures can be taken easily and quickly.

[0012]

Embodiments of the present invention will be described below with reference to the drawings.

First, the monitoring principle of the reactor stability monitoring method according to the present invention will be described.

In the present invention, the correlation dimension is used as an index indicating the stability, in addition to the conventionally obtained width reduction ratio.
The correlation dimension is a type of fractal dimension that reflects the fractal structure of the dynamical system of the system, and is widely used because it is relatively easy to calculate. To obtain the correlation dimension, the correlation integral shown in the following equation is first obtained.

[0015] Here, x _i is a time series data vector obtained by an operation of embedding from the observed time series data. H is a snakesite function. When it is assumed that the correlation integral thus obtained has a relationship of C (r) to r ^μ (2) with respect to the norm r between time series data, this index μ is called a correlation dimension. The correlation dimension is that the number of orbits of a dynamical system existing in a certain phase space is similar to the scale of the object when the object index (norm) used for observation is changed, that is, the spatial fractal. It is a dimension that appears when sex is extracted from time series data by an operation called embedding. The embedding is an operation of reorganizing the data vector from the time-series data at equal intervals for each arbitrary number (called an embedding dimension). The embedding operation is repeated for this embedding dimension until the correlation dimension converges. This correlation dimension is closely related to the stability of the system, which depends only on the dynamical system that describes the system purely, not on the nonstationarity / nonlinearity of the system.
That is, the relationship between the stability and the correlation dimension can be explained as follows. If the system is sufficiently stable, there will be no special dominant degrees of freedom in the time series data, and noise will dominate. Since noise is a high-degree-of-freedom system, the correlation dimension tends to take a large value when stable. On the other hand, when the system becomes unstable, it is considered that a certain orbit in the degree of freedom becomes unstable, and that orbit gradually suppresses the noise component and becomes dominant. Therefore, the degree of freedom decreases with destabilization, and the value of the correlation dimension that reflects this also decreases. From such a relationship, it is considered that there is a close relationship between the stability of the system and the correlation dimension obtained from the time series data which is the output of the system.

Therefore, by monitoring the value of this correlation dimension and its temporal transition, it becomes possible to estimate the stability of the system and its transition more accurately than in the case where only the width reduction ratio is monitored. In monitoring, the value of the correlation dimension in a typical core state and its fluctuation rate are stored in a database beforehand, and the judgment criteria are set based on that database, which enables more flexible monitoring. ..

Next, with reference to FIG. 1, an embodiment of the reactor stability monitoring apparatus according to the present invention will be described.

In FIG. 1, reference numeral 1 is a core, and a large number of neutron detectors 2 are installed in the core 1. From each of these neutron detectors 2, an LPRM signal 3 is respectively converted into an analog signal. It is supposed to be taken out. Then, the LPRM signal 3 thus taken out is collected by the adder 4 and is evenly averaged every about 20 signals.
The signal is output as the signal 5, and normally, the reduction ratio is calculated from the APRM signal 5 by statistical processing.

The LPRM signal 3 and the APRM signal 5 are
The signals are input to the A / D converter 6, and the A / D converter 6 samples both signals 3 and 5 to digitize the analog signal. Therefore, the digitized LPRM signal 3
In the preprocessor 7, noise component removal using, for example, a Hanning window or the like is performed as appropriate preprocessing.

By the way, since the noise component acts in the direction of increasing the correlation dimension, removal of the noise component is important in evaluating the correlation dimension. It doesn't change. Therefore, if the processing method is unified, including the database to be compared, there is no problem in stability evaluation.
Here, as the preprocessor 7, a general low-pass filter is used.

The correlation dimension of the time-series data which has been subjected to the preprocessing is obtained by the correlation dimension calculator 8 using the correlation integral of the above equation (1).

N in the equation (1) is the number of time-series data points, and it is necessary to have the number enough to obtain the correlation dimension with sufficient accuracy. Therefore, the correlation dimension will be obtained batchwise at a certain time interval. Although the time interval depends on the sampling interval, if the same sampling interval as that of the conventional stability detector is used, the time interval becomes about several tens. Then, all the time-series data sampled within this time interval are temporarily stored in the memory 9.

The correlation dimension can be obtained as the slope of the logarithm of the correlation integral with respect to the logarithm of Nomeul, as can be seen from the form of the equation (2). The correlation dimension obtained here is stored in the memory 9, and the variation rate is obtained from the difference from the value stored one batch before, which is also stored in the memory 9.

FIG. 2 shows an example of the relationship between the correlation dimension and the core stability. As the stability deteriorates (the width reduction ratio increases), the correlation dimension decreases and the oscillation point (width reduction ratio) increases. It can be seen that the rate of decrease in the correlation dimension increases as the value approaches 1 or more). Regarding the oscillation mode, since the LPRM and the APRM response are almost the same during the core integrated vibration, the difference in the correlation dimension does not appear so much, but during the region vibration, the APRM is more complicated than the LPRM. Because of the response, the former correlation dimension is significantly larger than that of the latter. Therefore, the vibration mode can be determined by comparing the correlation dimensions of the two.

As shown in FIG. 1, these determinations are performed using a database 11 and a comparison calculator 10, and the database includes values of correlation dimensions in typical core states (stability) and their values. The fluctuation rate, the value of the correlation dimension of APRM / LPRM at the time of core integrated vibration and at the time of region vibration are stored.

Since the correlation dimension depends on the dynamic system that describes the system, it hardly depends on the plant type. Therefore, these databases can be created from the results obtained in many stability tests that have already been performed.

In the comparison calculator 10, the value of the correlation dimension obtained for each batch interval and its variation rate are compared with those in the database 11 to obtain the stability and the conventional method at the same batch interval. The obtained stability (width reduction ratio) is compared with the stability obtained in the correlation dimension.

FIG. 3 shows an embodiment of the monitoring method according to the present invention.

Here, time series data observed in an actual plant is used. If the instability level L shown in FIG. 3 is set using actual machine data, and if the correlation dimension is reduced by this, and a vibration state occurs, the first region of the figure is a stable region and the vibration is It is determined not to occur. Furthermore, by setting a finer level higher than this level, it becomes possible to evaluate the margin of stability up to vibration. Further, in the middle region of time, the correlation dimension measured from the APRM signal is at a stable level, but that of LPRM belongs to an unstable level, and it can be seen that this is a vibration phenomenon that cannot be observed by APRM.

Therefore, it is possible to set the difference G between the correlation dimension values of the two and to judge that the region vibration mode is set when the difference exceeds the gap. Further, the correlation dimension of LPRM gradually increases, the difference from APRM becomes G or less, and the value of the correlation dimension of LPRM itself also exits the instability level L, and it can be determined that the core is stabilized.

FIG. 4 is a flow chart showing the above determination path.

As shown in FIG. 1, the above judgment is carried out by the judgment device 12, and the judgment signal 13 obtained by the judgment.
Is input to the stabilizing measure determiner 14, and the stabilizing measure signal 15 is output from the stabilizing measure determiner 14.

In this way, the observation signal is sampled,
The correlation dimension is calculated from the sampled time series data, the value is stored in the memory, the fluctuation rate is calculated based on this, the core stability is judged by comparing them with the database, and the necessary stability improvement measures are based on the result. Therefore, the stability of the system and its transition can be estimated more accurately than in the case where only the reduction ratio is monitored.

[0034]

As described above, since the reactor stability monitoring method according to the present invention monitors the transition of stability using the correlation dimension, the conventional method for monitoring only the width reduction ratio is used. The stability of the core can be estimated more accurately than

Further, in the reactor stability monitoring apparatus according to the present invention, the value of the correlation dimension and the variation rate relating to the typical core state and its transition are stored in the storage means in advance,
Since the core stability is determined by comparing the obtained correlation dimension value and the fluctuation rate with the data from the storage means, more flexible monitoring is possible, and necessary stability improvement measures can be performed easily and easily. Can be taken quickly.

[Brief description of drawings]

FIG. 1 is a configuration diagram showing an example of a reactor stability monitoring device according to the present invention.

FIG. 2 is a graph showing the relationship between correlation dimension and stability.

FIG. 3 is a graph showing an example of the present invention, in which a horizontal axis represents a time transition and a vertical axis represents a correlation dimension.

FIG. 4 is a flowchart showing a determination processing procedure in a determiner.

[Explanation of symbols]

 1 core 2 neutron detector 3 LPRM signal 5 APRM signal 6 A / D converter 7 preprocessor 8 correlation dimension calculator 9 memory 10 comparison calculator 11 database 12 determiner

Claims (2)

[Claims] 1. A correlation dimension is obtained from a neutron flux detection system signal,
A reactor stability monitoring method characterized by monitoring the transition of core stability based on the value and the fluctuation rate. 2. A sampling means for sampling a neutron flux detection system signal; a correlation dimension calculation means for obtaining a correlation dimension from sampled time series data; and a variation rate based on a temporal change of the calculated correlation dimension value. A calculation means for calculating a variation rate; a storage means for storing a value and a variation rate of a correlation dimension relating to a typical core state and its transition; a value and a variation rate of the correlation dimension obtained by both the calculation means And a determining means for determining core stability by comparing the data with the data of 1.