JP6789160B2 - Auxiliary arithmetic unit and arithmetic unit equipped with it - Google Patents

Description

The present invention is an auxiliary arithmetic unit provided as an auxiliary to a main arithmetic unit which has a highly reliable main database and executes a main arithmetic based on data stored in the main database, and executes an auxiliary arithmetic. And the arithmetic unit including both the auxiliary arithmetic unit and the main arithmetic unit.

Conventionally, a cogeneration system including an internal combustion engine or the like as a target, and a remote monitoring system for monitoring the measured operating state of the target from a remote location is known.
The remote monitoring system is constructed as a system in which a very high operating rate is guaranteed because it is necessary to avoid an unexpected system down due to a failure or the like. For this reason, the remote monitoring system has a problem that it is difficult to add a function after the system is constructed.

On the other hand, it is conceivable to realize the whole system by constructing an auxiliary system having the function to be added without adding the function to the remote monitoring system and communicating with the remote monitoring system.
For example, Patent Document 1 has a main computer provided with a main database for storing information related to main operations, and a sub-database for backing up data stored in the main database at appropriately set backup timings. A system with a backup computer is disclosed.

Japanese Unexamined Patent Publication No. 2001-090771

As described above, when the entire system is realized by constructing an auxiliary system having the function to be added without adding the function to the remote monitoring system and communicating with the remote monitoring system, the whole including the auxiliary system. When trying to construct the system as a system in which a high operating rate is guaranteed, in addition to the high cost of the remote monitoring system, the construction of the auxiliary system also requires a high cost, which is problematic from the viewpoint of economic efficiency.

The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to provide a device for giving an additional function to a relatively reliable main arithmetic unit, which is highly economical. However, it is an object of the present invention to provide an auxiliary arithmetic unit capable of realizing additional functions with high reliability and an arithmetic unit equipped with the auxiliary arithmetic unit.

The auxiliary arithmetic unit for achieving the above purpose is
It is an auxiliary arithmetic unit that is provided as an auxiliary to the main arithmetic unit that has a highly reliable main database and executes the main arithmetic based on the data stored in the main database and executes the auxiliary arithmetic. The feature composition is
A sub-database that can back up the data stored in the main database and is less reliable than the main database,
A backup processing unit that executes a backup process of backing up the difference data between the data stored in the main database and the data stored in the sub-database from the main database to the sub-database at specific time intervals.
Immediately after the backup time at which the backup process is executed, an auxiliary calculation execution unit that executes the auxiliary calculation based on the data stored in the sub-database after the backup process is provided.

An auxiliary arithmetic unit having the above-mentioned characteristic configuration is retrofitted to a main arithmetic unit that has a highly reliable main database and in particular, it is relatively difficult to change the system configuration after system construction from the viewpoint of cost. Therefore, it is possible to construct a system to which the auxiliary calculation function is added without changing the system configuration of the main arithmetic unit.
In particular, since the auxiliary arithmetic unit having the above-mentioned feature configuration uses a sub-database having a lower reliability than the main database, it is possible to construct a system to which the auxiliary arithmetic function is added at a relatively low cost.
However, when the above configuration is adopted, since a database with low reliability is adopted as the sub-database, there is a high possibility that the auxiliary arithmetic unit will go down.
According to the above feature configuration, the auxiliary calculation execution unit executes the auxiliary calculation immediately after the backup time when the backup is executed. Therefore, even if the auxiliary calculation device is down, the auxiliary calculation device is restarted. After that, the auxiliary calculation is executed immediately after the difference data is backed up from the main database to the sub database, so that the reliability of the auxiliary calculation can be ensured.
From the above, when adding an auxiliary arithmetic function to the main arithmetic unit, it is possible to realize an auxiliary arithmetic unit capable of executing the auxiliary arithmetic while ensuring high reliability while maintaining a relatively low cost.

Further features of the auxiliary arithmetic unit
In the backup process, the backup processing unit compares the data name of the data stored in the main database with the data name of the data stored in the sub-database for each of the plurality of stored data. Then, the first backup process of backing up the data with the data name existing in the data stored in the main database and not in the data stored in the sub-database from the main database to the sub-database is executed. There is a point to do.

According to the above feature configuration, the data to be backed up is determined by a process that compares only the data names with a relatively small amount of calculation. Therefore, for example, the data to be backed up including the differential processing of the data contents. The time required for backup can be shortened as compared with the case of determining.

Further features of the auxiliary arithmetic unit
The sub-database stores data compressed so that the ratio of the data stored in the main database to the data stored in the sub-database becomes a reference compression ratio.
In the backup process, the backup processing unit uses the data stored in the main database and the sub-database associated with the data stored in the main database for each of the plurality of stored data. Judgment compression ratio calculation processing that calculates the compression ratio with the stored data as the judgment compression ratio,
The point is that the second backup process of backing up from the main database to the sub-database is executed by using the data whose determination compression ratio calculated by the determination compression ratio calculation process is different from the reference compression ratio as the difference data. ..

When there is a defect in the data as in the above characteristic configuration, the determination compression ratio calculated by the determination compression ratio calculation process is a value different from the reference compression ratio.
According to the above feature configuration, data having a determination compression ratio different from the reference compression ratio is determined to be missing data and backed up as difference data. As a result, missing data can be backed up to a sub-database without omission.
Further, according to the above feature configuration, the presence or absence of data loss can be determined without comparing the data contents of the main database and the data contents of the sub-database, so that the amount of calculation is larger than that of comparing the data contents. Can be reduced and the calculation time can be shortened.

Further features of the auxiliary arithmetic unit
The data stored in the main database is time series data.
The auxiliary calculation execution unit determines the abnormal state of the target based on the time series data as the auxiliary calculation.
Among the time-series data determined by the auxiliary calculation execution unit to be in an abnormal state, the time-series data related to the time zone related to the determination of the abnormal state is graphed and transmitted to the management unit. At the point.

According to the above feature configuration, the management unit can satisfactorily determine whether or not the determination target is in an abnormal state based on the visualized graph.

In addition, in the present application, even the arithmetic unit composed of the auxiliary arithmetic unit and the main arithmetic unit described above can satisfactorily perform the effects described above.

Schematic configuration diagram of the arithmetic unit including the abnormal state determination notification device according to the embodiment Graph diagram to explain the derivation of the degree of anomaly Graph diagram to explain the derivation of the degree of anomaly Conceptual diagram showing the concept when determining an abnormal state from multiple abnormalities Control flow diagram of abnormal state judgment processing and its notification processing

The abnormality state determination notification device 100 (an example of an auxiliary arithmetic unit) according to the embodiment of the present invention provides an additional function to the relatively highly reliable failure prediction device 200 (an example of a main arithmetic unit). The present invention relates to a device for this purpose, which is highly economical and can realize additional functions with high reliability.
Hereinafter, description will be given based on the drawings.

As shown in FIG. 1, the failure prediction device 200 (an example of the main calculation device) that predicts the failure of the cogeneration system C (an example of the main calculation) is a main database DBm that guarantees a high operating rate and has high reliability. , Prediction of failure of the communication unit M1 that connects the plurality of cogeneration systems C and the management unit K that manages the plurality of cogeneration systems C in a communicable state via the network line N, and the cogeneration system C. It is provided with a failure prediction unit M2 for performing the above. The failure prediction result of the failure prediction unit M2 can be transmitted by the communication unit M1 to the management unit K that manages the cogeneration system C via the network line N.

In the embodiment, the cogeneration system C is mainly composed of an engine 30 that supplies heat and electric power together and a control device Cc including an ECU of the engine 30.
The engine 30 uses a gaseous fuel such as city gas (13A) as fuel, and operates the spark plug at a desired time by reciprocating the piston in the cylinder and opening and closing the intake valve and the exhaust valve. By doing so, in the combustion chamber Co (illustrated in FIG. 4: Co is a concept including any one or all of Co1 to Co20), each stroke of intake stroke, compression stroke, expansion stroke, and exhaust stroke is sequentially executed. .. As a result, the reciprocating motion of the piston is output as the rotational motion of the crankshaft via the connecting rod. The configuration is the same as that of a normal 4-stroke internal combustion engine.
Further, the engine 30 is composed of a multi-cylinder gas engine provided with a plurality of combustion chambers Co, and a temperature sensor S1 for separately measuring the exhaust temperature from each combustion chamber Co in the exhaust passage, and each of them. It includes a knock sensor S2 that detects the knocking strength in the combustion chamber Co, and a rotation speed sensor S3 that measures the rotation speed of the engine in the form of measuring the crank angle of the crankshaft.
The control device Cc includes a control unit (not shown) that controls the operation of the engine 30, a data acquisition unit Cc1 that acquires measurement data of the temperature sensor S1, the knock sensor S2, and the rotation speed sensor S3, and a data acquisition unit. It includes a storage unit DBc that stores the measurement data acquired by Cc1 and a communication unit Cc2 that executes data transmission / reception to and from the outside. In particular, the communication unit Cc2 is configured to be able to transmit the measurement data stored in the storage unit DBc to the failure prediction device 200 via the network line N.

The above-mentioned failure prediction device 200 acquires the measurement data stored in the storage unit DBc of the cogeneration system C via the network line N in the communication unit M1 and stores it in the main database DBm, and stores it in the failure prediction unit M2. Then, based on the measurement data stored in the main database DBm, the failure of the cogeneration system C is predicted by a prediction method for predicting the failure by setting a threshold or the like.
Nowadays, with the progress of technology, various technologies for determining the abnormal state of the cogeneration system C based on a statistical method or the like have been developed. However, it is difficult to change the specifications of the failure prediction device 200, which is guaranteed to have a high operating rate and has high reliability, from the viewpoint of cost and the like, and new functions such as determination of an abnormal state are added. Difficult to do.

Therefore, in the embodiment, the data acquisition unit A7 that acquires data from the main database DBm and the measurement data (data acquired by the data acquisition unit A7) stored in the main database DBm can be backed up, and the main database can be backed up. Abnormal state determination notification device 100 (an example of an auxiliary computing device) including sub-database DBs having lower reliability than DBm and a communication unit A1 that connects to the management unit K in a communicable state via a network line N. It has.
By the way, the abnormal state determination notification device 100 employs sub-database DBs whose reliability is lower than that of the main database DBm in order to obtain economic merit, but the reliability of the abnormal state determination is lowered by this. In order to avoid doing this, it is configured as follows.
That is, the abnormal state determination notification device 100 uses the difference data between the measurement data (data acquired by the data acquisition unit A7) stored in the main database DBm and the data stored in the sub-database DBs as the main database. Based on the backup processing unit A8 that executes the backup process that backs up from the DBm to the sub-database DBs at specific time intervals, and the data stored in the sub-database DBs after the backup process immediately after the backup process is executed. It is provided with an auxiliary calculation execution unit A10 that executes a determination of an abnormal state (an example of an auxiliary calculation).
With this configuration, the auxiliary calculation execution unit A10 executes the determination of the abnormal state immediately after the backup time when the backup is executed. Therefore, when the abnormal state determination notification device 100 goes down or the sub-database DBs crash. However, after restarting the abnormal state determination notification device 100, immediately after backing up the difference data from the main database DBm to the sub-database DBs, the abnormal state determination is executed, so that the data has data loss or the like. It is possible to prevent the auxiliary calculation from being executed based on the basis, and the reliability of the auxiliary calculation can be ensured.

Further, the backup processing unit A8 determines the data to be backed up by the processing with a small amount of calculation, and in order to improve the reliability while shortening the time required for the backup, in the above-mentioned backup processing, the main database DBm and For each of the plurality of data stored in the sub-database DBs, the data name of the data stored in the main database DBm is compared with the data name of the data stored in the sub-database DBs, and the data is stored in the main database DBm. The first backup process of backing up the data (an example of the difference data) existing in the stored data and not in the data stored in the sub-database DBs from the main database DBm to the sub-database DBs is executed.

The sub-database DBs according to the embodiment store data compressed so that the ratio of the data stored in the main database DBm to the data stored in the sub-database DBs becomes the reference compression ratio. Is.
The backup processing unit A8 determines whether or not the data stored in the sub-database DBs has data loss with respect to the data stored in the main database DBm, and sets the data having data loss as the data without loss. In the above-mentioned backup process, in order to execute the replacement process with a small amount of calculation, the data stored in the main database DBm and the main data are stored in the main database DBm and the sub-database DBs, respectively. Calculated by the judgment compression ratio calculation process and the judgment compression ratio calculation process, which calculates the compression ratio with the data stored in the sub-database DBs associated with the data stored in the database DBm as the judgment compression ratio. The second backup process of backing up from the main database DBm to the sub-database DBs is executed by using the data whose determination compression ratio is different from the reference compression ratio as the difference data.
As a result, even if data loss or the like occurs in the data stored in the sub-database DBs due to a crash of the sub-database DBs having relatively low reliability, the loss can be appropriately detected with a small amount of calculation. By substituting with appropriate data, the reliability of the accuracy of subsequent determination of the abnormal state of the abnormal state determination notification device 100 is improved.

Next, a description will be added about a specific configuration and a determination method for realizing the determination of the abnormal state with high accuracy.

The abnormality state determination notification device 100 according to the embodiment has the determination accuracy adjusting unit A2, the selection unit A3, the abnormality degree derivation unit A4, and the abnormality determination unit, which will be described below, as the auxiliary calculation execution unit A10 for executing the abnormality state determination. It is provided with A5 and a sensitivity adjusting unit A6. Hereinafter, they will be described in order.
The abnormal state determination notification device 100 sets the temperature of the exhaust gas measured in a plurality of combustion chambers Co (an example of a plurality of objects) provided in the cogeneration system C (specifically, in each combustion chamber Co by the temperature sensor S1). Time-series data of temperature measured in the corresponding exhaust passage (an example of parameters) is stored in the sub-database DBs, and based on the time-series data stored in the sub-database DBs, there are abnormalities in a plurality of combustion chambers Co. The abnormality determination unit A5 for executing the determination is provided.

Adding an explanation, the abnormality state determination notification device 100 selects one combustion chamber Co, which is an abnormality determination target, from a plurality of combustion chambers Co, and in a predetermined derivation period, other than the abnormality determination target from the plurality of combustion chambers Co. The selection unit A3 that selects the combustion chamber Co that is the non-abnormality determination target, the time series data corresponding to the combustion chamber Co that is the abnormality determination target selected by the selection unit A3, and the non-abnormality determination target. From the pair of time series data with the time series data corresponding to the combustion chamber Co, the Mahalanobis distance at each time point of the time series data is calculated, the normal region of the calculated Mahalanobis distance is calculated, and the Mahalanobis distance and the normal region are calculated. An abnormality degree deriving unit A4 for deriving the abnormality degree E of the abnormality determination target based on the above is provided.
The above-mentioned predetermined derivation period is preferably 30 minutes or more, and 3 or 4 hours at the longest, for example, when the measurement cycle of the sensor value (value at each time point of the time series data) is 1 second interval. The score of the sensor value needs to be at least 1,000 to 2,000 from the viewpoint of statistics. Therefore, when the number of data points is recorded at 1-second intervals, it is desirable to derive the data in a period of 30 minutes or more in which 30 × 60 points = 1,800 points are guaranteed. Moreover, since the sensor value is affected by the outside air temperature, it is desirable to set a period in which the outside air temperature is constant as much as possible as the derivation period. Therefore, it is better to set the derivation period to 3 or 4 hours at the longest.

First, the abnormality degree derivation unit A4 will be described.
Regarding the derivation of the abnormality degree E by the abnormality degree derivation unit A4, the time series data corresponding to the combustion chamber Co which is one abnormality determination target is set to χ _1, and the time series corresponding to the combustion chamber Co which is one non-abnormality determination target. When the data is χ ₂ , the Mahalanobis distance is represented by the following [Equation 1].

The time-series data χ ₁ and χ _{2 correspond} to the exhaust gas temperature of the combustion chamber Co belonging to one engine 30 and the exhaust gas temperature of the combustion chamber Co which is the non-abnormality determination target, respectively. , Both have a high correlation with each other as shown in FIG.
On the other hand, Mahalanobis distance, as shown in the equation (1), chi ₁ of dispersion, for chi ₂ of dispersion is obtained by considering the covariance between chi ₁ and chi _2, the boundary of the normal region, FIG. 2 in two time series data chi _1, rather than the circle from the center of gravity represented equidistant by average vector of chi ₂ mu, the two time series data chi _1, correlation chi ₂ is reflected elliptically (for example, FIG. It will be indicated by the ellipse indicated by E in 2. Here, the inside of the ellipse is the normal region and the outside of the ellipse is the abnormal region.

Hereinafter, data showing a state in which the temperatures of the combustion chamber Co subject to abnormality determination and the combustion chamber Co subject to non-abnormality determination have risen when a high load operation is executed (data to be determined to be normal: FIG. 2). , Variable vector at time a indicated by χ (a)) and the combustion chamber Co that is the target of abnormality determination, and the combustion chamber Co that is the target of non-abnormality determination indicates that normal operation is being executed. Further explanation will be added using data (data to be determined to be abnormal: variable vector at time b represented by χ (b) in FIG. 2). Here, as shown in FIG. 2, χ (a) and χ (b) are equidistant from the center of gravity represented by the average vector μ of the _two time series data χ ₁ and χ ₂ (La = Lb in FIG. 2). ).
Incidentally, FIG. 2 also illustrates a plurality of data for a time different from the times a and b.
According to the anomaly degree derivation unit A4 according to the embodiment, since the anomaly degree E is derived in consideration of the correlation between the two time series data using the Mahalanobis distance, χ (a) located at the same distance from the center of gravity μ. , Χ (b), the data χ (a) that should be determined to be normal is the data within the normal region (inside the ellipse E in FIG. With (b) as the data in the anomaly region (outside the ellipse E in FIG. 2), the derivation of the anomaly degree E can be executed in a state according to the substance.

On the other hand, under the same conditions, when the Euclidean distance that does not consider the correlation between the two is used as the statistical distance, the boundary of the normal region is a perfect circle (the circle indicated by P in FIG. 3) as shown in FIG. Therefore, in some cases, as shown in FIG. 3, the data χ (b) that should be determined to be abnormal becomes the data in the normal region (inside the circle P in FIG. 3), and the abnormality degree E Derivation cannot be executed in a state that conforms to the substance. In the present invention, the inventors comprehensively consider these points and adopt the Mahalanobis distance as the statistical distance.

As described above, the anomaly degree derivation unit A4 according to the present invention is particularly effective when the correlation coefficient of the two time series data has a high correlation of 0.7 or more and 1 or less. ..

Further, in the abnormality degree deriving unit A4 according to the embodiment, the number of data whose Mahalanobis distance is outside the normal region exceeds the statistical threshold value for abnormality determination (for example, a value of 5) statistically determined in the Mahalanobis distance. In this case, it is derived that the abnormality degree E is high, and when the number of data whose Mahalanobis distance is outside the normal region is equal to or less than the statistical threshold, it is derived that the abnormality degree E is low.

More preferably, the abnormality degree deriving unit A4 adopts the normalized Mahalanobis distance as the Mahalanobis distance, and derives the abnormality degree E with a statistical threshold value of 3 or more and 5 or less.
When, for example, 3 is adopted as the statistical threshold value, in the example shown in FIG. 2, since the number of data existing in the abnormal region is 5, the abnormality degree derivation unit A4 determines that the abnormality degree E is high.

Further, in the abnormality state determination notification device 100, the selection unit A3 selects a plurality of combustion chambers Co, which are non-abnormality determination targets, with respect to the combustion chamber Co, which is one abnormality determination target. A4 derives the abnormality degree E with respect to each of the combustion chamber Co which is one abnormality determination target and the combustion chamber Co which is a plurality of non-abnormality determination targets selected by the selection unit A3. The unit A5 determines whether or not the combustion chamber Co, which is the object of the abnormality determination, is in the abnormal state based on the plurality of abnormality degrees E derived by the abnormality degree deriving unit A4.

A specific description will be given with reference to FIG.
For example, when the engine 30 is a 20-cylinder multi-cylinder engine and the abnormal state of the combustion chamber Co1 to be determined for one abnormality is determined, the selection unit A3 is non-abnormal from the remaining 19 combustion chambers. A plurality of combustion chambers Co to be determined (19 from combustion chamber Co2 to combustion chamber Co20 in FIG. 4) are selected.
The abnormality degree deriving unit A4 derives the abnormality degree E between each of the combustion chamber Co1 of one abnormality determination target and the combustion chambers Co2 and Co20 of other non-abnormality determination targets.
The abnormality determination unit A5 determines whether or not the abnormality determination target is in an abnormal state based on the ratio at which the abnormality degree E is determined to be high among the plurality of abnormality degrees E derived by the abnormality degree derivation unit A4. .. More specifically, the abnormality determination unit A5 is abnormal when the ratio of the plurality of abnormality degrees E derived by the abnormality degree derivation unit A4 to be determined to have a high abnormality degree E is equal to or more than the abnormality state determination ratio. It is determined that the combustion chamber Co to be determined is in an abnormal state, and when it is less than the abnormal state determination ratio, it is determined that the combustion chamber Co to be determined to be abnormal is not in an abnormal state.
The abnormal state determination ratio depends on the determination target, but is preferably, for example, 50% or more, and more preferably 50%.

For example, as in the example shown in FIG. 4, it is derived that the degree of abnormality E between the combustion chamber Co1 and the combustion chamber Co2 is high, and the abnormality between the combustion chamber Co1 and the combustion chamber Co3 to the combustion chamber Co20 is high. Consider the case where it is derived that the degree E is low, that is, the ratio of the derived abnormality degrees E where the abnormality degree E is determined to be high is 5%. In this case, for example, when the abnormality determination unit A5 sets the abnormality state determination rate to 50%, the rate (5%) at which the above-mentioned abnormality degree E is determined to be high is the abnormality state determination rate (50). %), Therefore, it is determined that the combustion chamber Co1 as an abnormality determination target is not in an abnormal state.
As a result, it is possible to suppress erroneous determination of the abnormal state as compared with the case where the determination of the abnormal state is performed only by a single abnormality degree E.

The abnormality determination unit A5 is configured to be able to execute the determination of the abnormal state by changing the combustion chamber Co as the abnormality determination target, and sets all the targets as the abnormality determination targets and whether or not they are in the abnormal state. It is configured so that it can be determined.

The abnormal state determination notification device 100 according to the embodiment includes a determination accuracy adjusting unit A2 that adjusts the accuracy of determining whether or not the combustion chamber Co as an abnormality determination target is in the abnormal state.
The determination accuracy adjusting unit A2 increases the number of combustion chambers Co as the non-abnormality determination target selected by the selection unit A3 as the determination accuracy is adjusted to be high.
For example, the abnormal state determination notification device 100 includes an operation unit (not shown) capable of adjusting the possibility of erroneous determination by an operation by the operator, and the determination accuracy adjustment unit A2 is based on the set value of the operation unit. And adjust the accuracy of the judgment.

Further, the abnormal state determination notification device 100 includes a sensitivity adjusting unit A6 for adjusting the sensitivity of whether or not the combustion chamber Co as an abnormality determination target is in an abnormal state.
The sensitivity adjustment unit A6 adjusts the sensitivity to a high value, and sets the statistical threshold value as a statistical threshold value for abnormal determination statistically determined in the Mahalanobis distance (for example, 3 or more and 5 or less). Reduce.

By using the abnormality state determination notification device 100 described so far, the following abnormality determination method can be executed.
That is, in the abnormality determination method, the combustion chamber Co as one abnormality determination target is selected from the plurality of combustion chambers Co of one engine 30, and the abnormality determination is made from the plurality of combustion chambers Co of one engine 30. The exhaust gas temperature (measured by the temperature sensor S1) corresponding to the selection step of selecting the combustion chamber Co as one non-abnormality determination target other than the target and the combustion chamber Co as the abnormality determination target selected in the selection step. Temperature: an example of time-series data) and the exhaust gas temperature corresponding to the combustion chamber Co as a non-abnormality determination target (temperature measured by the temperature sensor S1: an example of time-series data) correspond to each of the exhaust gas temperatures. The selection process includes an abnormality degree derivation step of calculating the maharanobis distance to be performed, calculating the normal region of the calculated maharanobis distance, and deriving the abnormality degree E of the abnormality determination target based on the maharanobis distance and the normal region. A plurality of combustion chambers Co as non-abnormality determination targets are selected for the combustion chamber Co as one abnormality determination target, and the abnormality degree derivation step is selected from the combustion chamber Co as one abnormality determination target. The abnormality degree E is derived from each of the plurality of combustion chamber Cos selected in the process as non-abnormality determination targets, and the abnormality determination step is a plurality of abnormality degrees derived in the abnormality degree derivation step. Based on E, it is determined whether or not the combustion chamber Co as an abnormality determination target is in an abnormal state.

[Control flow of backup processing and abnormal status notification processing]
Next, the control of the backup process and the abnormal state notification process in the abnormal state determination notification device 100 according to the embodiment will be described based on the control flow of FIG.

The data acquisition unit A7 of the abnormality state determination notification device 100 acquires the data stored in the main database DBm of the failure prediction device 200 so far.
If the data acquisition unit A7 has not acquired the reference compression ratio for compressing the data so far, the data acquisition unit A7 acquires the reference compression ratio from a setting unit (not shown). The backup processing unit A8 compresses the data acquired by the data acquisition unit A7 at the reference compression ratio, and stores the data in which the data name is set in the sub-database DBs as a unit (# 01).

When the backup processing unit A8 has already stored the data in the sub-database DBs, the data acquisition unit A7 backs up only the difference data stored in the main database DBm and not stored in the sub-database DBs.
Specifically, the backup processing unit A8 stores each of the plurality of data stored in the main database DBm and the sub-database DBs in the data name of the data stored in the main database DBm and the sub-database DBs. Compare with the data name of the existing data (# 02).
When the backup processing unit A8 has data (an example of difference data) that exists in the data stored in the main database DBm and does not exist in the data stored in the sub-database DBs (# 03), the backup processing unit A8 starts from the main database DBm. The first backup process of backing up to the sub-database DBs is executed (# 04).
On the other hand, the backup processing unit A8 performs processing when there is no data (an example of difference data) that exists in the data stored in the main database DBm and does not exist in the data stored in the sub-database DBs (# 03). Do not execute (to # 05).

The backup processing unit A8 associates each of the plurality of data stored in the main database DBm and the sub-database DBs with the data stored in the main database DBm and the data stored in the main database DBm. The determination compression ratio calculation process for calculating the compression ratio with the data stored in the sub-database DBs is executed as the determination compression ratio (# 05).
The backup processing unit A8 determines whether or not there is data in which the determination compression ratio calculated by the determination compression ratio calculation process is different from the reference compression ratio (# 06), and if it exists, the data is differentiated. As data, a second backup process of backing up from the main database DBm to the sub-database DBs is executed (# 07).
On the other hand, the backup processing unit A8 does not execute the process (to # 08) when there is no data in which the determination compression ratio calculated by the determination compression ratio calculation process is different from the reference compression ratio.

The abnormality degree derivation unit A4 as the auxiliary calculation execution unit A10 derives the abnormality degree of the determination target (for example, the combustion chamber Co of the engine) corresponding to the data based on the data stored in the sub-database DBs (#). 08). The process (# 08) is executed immediately after the backup processes (# 01) to (# 07) described above are executed.

The abnormality determination unit A5 as the auxiliary calculation execution unit A10 determines the abnormal state based on the derived abnormality degree (# 09), and when it is determined that the abnormality state is present, the communication unit A1 is in the abnormal state. The data (time series data) is graphed and transmitted to the management unit K to be determined (# 10).
On the other hand, when the abnormality determination unit A5 as the auxiliary calculation execution unit A10 determines that there is no abnormal state, the communication unit A1 does not execute the process (control flow: to end).

The above processes (# 01) to (# 10) are executed for each backup process.

[Another Embodiment]
(1) In the present invention, an arithmetic unit including both a failure prediction device 200 (an example of a main arithmetic unit) and an abnormal state determination notification device 100 (an example of an auxiliary arithmetic unit) is also included in the scope of rights. ..

(2) In the above embodiment, the backup processing unit A8 extracts the difference data by comparing the data names in the first backup processing shown in (# 02) to (# 04), and executes the backup processing.
However, in the first backup process, a configuration may be adopted in which the difference data is extracted in the form of collating up to the specific contents of the data associated with the main database DBm and the sub-database DBs.

(3) In the above embodiment, the first backup process shown in (# 02) to (# 04) and the second backup process shown in (# 05) to (# 07) are stored in the sub-database DBs. This is a process to improve the reliability of data.
For example, when processing speed is prioritized over reliability, both the first backup process and the second backup process may not be executed, or only one of them may be executed.

(4) In the above embodiment, the abnormality determination is executed with all of the plurality of objects as determination targets. However, the determination target may be at least one or more of the plurality of targets.

(5) In the above embodiment, the failure prediction device 200 is configured to execute the abnormality determination based on the measurement data acquired from the cogeneration system C via the network line N. Indicated.
However, the failure prediction device 200 is provided side by side with each of the cogeneration system C, for example, and is configured to acquire measurement data from a plurality of targets and execute abnormality determination without going through a network line N. May be adopted.
Further, the failure prediction device 200 may adopt a configuration provided as a control device Cc of the cogeneration system C.

(6) In the above embodiment, the Mahalanobis distance used by the abnormality degree deriving unit in deriving the abnormality degree E is preferably a normalized Mahalanobis distance.
However, the Mahalanobis distance used to derive the degree of anomaly does not have to be the normalized Mahalanobis distance.

(7) The abnormality state determination notification device 100 may adopt, for example, a configuration including a steady state determination unit that determines whether or not the target is in the steady state from time series data, and the abnormality degree derivation unit A4 may adopt. The abnormality degree E of the abnormality determination target may be derived based on the time-series data determined by the steady state determination unit to be in the steady state.

(8) In the above embodiment, the configuration including the determination accuracy adjusting unit A2 and the sensitivity adjusting unit A6 is shown, but the object of the present invention can be satisfactorily achieved even if the configuration does not include these. ..

(9) In the above embodiment, an example is shown in which a plurality of combustion chambers Co of one engine 30 are targeted, and the temperature (exhaust gas temperature) in each of the combustion chambers Co is used as a parameter.
However, the knocking strength detected by the knock sensor S2 described above may be used as a parameter.

(10) Each of the engines 30 of the plurality of cogeneration systems C connected to the abnormal state determination notification device 100 via the network line N is in a steady state by, for example, the steady state determination unit shown in the above another embodiment. If it is determined, the number of rotations may have a high correlation.
Therefore, the rotation speed sensor S3 that measures the rotation speed of the engine 30 by adopting each of the engines 30 of the plurality of cogeneration systems C connected to the abnormality state determination notification device 100 via the network line N as a plurality of targets. The measurement result of may be adopted as a parameter.

(11) As a plurality of targets, a plurality of servers that constantly communicate with each other can be adopted, and in this case, the data communication amount of each server is adopted as a parameter.
Further, as a plurality of objects, a plurality of bearings supporting one power generation shaft of one power generation facility can be adopted, and in this case, the vibration frequency of each bearing is adopted as a parameter.
Further, as a plurality of targets, the weather conditions of a plurality of adjacent areas can be adopted, and in this case, the temperature and humidity of each of the plurality of areas are adopted as parameters. In this case, a tornado or the like that suddenly occurs is assumed as the abnormal state.

It should be noted that the configuration disclosed in the above embodiment (including another embodiment, the same shall apply hereinafter) can be applied in combination with the configuration disclosed in other embodiments as long as there is no contradiction. The embodiments disclosed in the present specification are examples, and the embodiments of the present invention are not limited thereto, and can be appropriately modified without departing from the object of the present invention.

The auxiliary arithmetic unit of the present invention and the arithmetic unit provided with the auxiliary arithmetic unit are highly economical with respect to an apparatus for giving an additional function to a relatively reliable main arithmetic unit. It can be effectively used as an auxiliary arithmetic unit capable of realizing additional functions with high reliability and an arithmetic unit equipped with the auxiliary arithmetic unit.

100: Abnormal state determination notification device 200: Failure prediction device A1: Communication unit A2: Judgment accuracy adjustment unit A3: Selection unit A4: Abnormality derivation unit A5: Abnormality determination unit A6: Sensitivity adjustment unit A7: Data acquisition unit A8: Backup Processing unit DBm: Main database DBs: Subdatabase K: Management unit N: Network line χ1: Time series data

Claims (5)

It is an auxiliary arithmetic unit that is provided as an auxiliary to the main arithmetic unit that has a highly reliable main database and executes the main arithmetic based on the data stored in the main database, and executes the auxiliary arithmetic.
A sub-database that can back up the data stored in the main database and is less reliable than the main database,
A backup processing unit that executes a backup process of backing up the difference data between the data stored in the main database and the data stored in the sub-database from the main database to the sub-database at specific time intervals.
An auxiliary calculation device including an auxiliary calculation execution unit that executes the auxiliary calculation based on the data stored in the sub-database after the backup process immediately after the backup time when the backup process is executed. In the backup process, the backup processing unit compares the data name of the data stored in the main database with the data name of the data stored in the sub-database for each of the plurality of stored data. Then, the first backup process of backing up the data with the data name existing in the data stored in the main database and not in the data stored in the sub-database from the main database to the sub-database is executed. The auxiliary computing device according to claim 1. The sub-database stores data compressed so that the ratio of the data stored in the main database to the data stored in the sub-database becomes a reference compression ratio.
In the backup process, the backup processing unit uses the data stored in the main database and the sub-database associated with the data stored in the main database for each of the plurality of stored data. Judgment compression ratio calculation processing that calculates the compression ratio with the stored data as the judgment compression ratio,
Claim 1 to execute a second backup process of backing up from the main database to the sub-database using data whose determination compression ratio calculated by the determination compression ratio calculation process is different from the reference compression ratio as the difference data. Or the auxiliary computing device according to 2. The data stored in the main database is time series data.
The auxiliary calculation execution unit determines the abnormal state of the target based on the time series data as the auxiliary calculation.
Among the time-series data determined by the auxiliary calculation execution unit to be in an abnormal state, the time-series data related to the time zone related to the determination of the abnormal state is graphed and transmitted to the management unit. The auxiliary arithmetic unit according to any one of claims 1 to 3. An arithmetic unit composed of the auxiliary arithmetic unit according to any one of claims 1 to 4 and the main arithmetic unit.

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