Patent Application
20090248179
1. Field of the Invention
The present invention relates to a plant operation data monitoring apparatus for detecting an error by monitoring plant data.
2. Related Art
In order to detect a plant error in a power plant, a point (sensor value) to be monitored is specified in advance and the presence or absence of a plant error is determined by comparing a specified fixed upper/lower limit and most recent plant data to see whether the limit is exceeded (see Japanese Patent Laid-Open No. 05-120582). Further, a technique has been introduced, which the limit is calculated by using an average value, a standard deviation and the like of historical plant data in a monitoring point to improve the accuracy of detecting a plant error (see Japanese Patent Application No. 2004-346716).
Unfortunately, according to the aforementioned prior art, when a plant operating state (activating, loading up, terminating, or the like) is changed, a value at a monitoring point may exceed the upper/lower limit to be used to detect a plant error in spite of a normal operation state, and an operator may be informed of a false alarm.
Therefore, there is a problem in that it takes knowledge of a skilled plant operator to determine an optimum upper/lower limit, or it takes time and efforts such as repeating a plant test operation and changing limit values many times.
In view of the above problems, the present invention has been made and an object of the present invention is to provide a plant operation data monitoring apparatus capable of monitoring a plant error with a high accuracy without requiring a skilled operator.
In order to achieve the above object, the present invention provides a plant operation data monitoring apparatus including:
plant-data inputting means for fetching plant data from each sensor installed in a plant facility;
a plant-data most-recent-value table for temporarily storing a most recent value of said plant data;
plant-data recording means for retrieving said most recent value from said plant-data most-recent-value table and storing long-term time-series plant data in a plant-data history table;
monitoring point editing means for registering one or more monitoring points used to monitor an error of said plant facility in response to an operator request;
a monitoring-point registering table for storing a result registered by said monitoring-point editing means;
data-correlation determining means for selecting one or more main variable points having a strong correlation from said plant-data history table using said monitoring point as a key;
a main-variable-point registering table for registering a main variable point selected by said data-correlation determining means;
limit-value calculating means for defining a statistical upper/lower limit value function of said plant-data history table on the basis of time-series plant data of said monitoring point and said main variable point;
a limit-value function table for storing a limit-value function defined by said limit-value calculating means;
limit-value determining means which refers to table information in said limit-value function table and periodically matches content of said plant-data most-recent-value table; and if the most recent value is outside the limit value range, deviation information is stored in a determination result table;
plant-error monitoring/outputting means for outputting an error signal and content of said determination result table if a new plant error occurs; and
a display device for displaying an output from said plant-error monitoring/outputting means.
As described above, according to the present invention, a statistical technique is used to automatically select a monitoring point for monitoring the amount of variation of plant data subject to plant monitoring and a main variable point which has a strong correlation to the monitoring point and which is appropriate for monitoring a plant error. These monitoring points are incorporated in a plant monitoring conditions. Accordingly, the present invention can provide a monitoring apparatus capable of monitoring a plant error with a high accuracy without requiring a skilled operator.
Hereinafter, embodiments of the plant operation data monitoring apparatus in accordance with the present invention will be described with reference to accompanying drawings.
The configuration of an Embodiment 1 in accordance with the present invention will be described with reference to
The monitoring apparatus is provided with plant-data inputting means A2 which periodically fetches plant data from each sensor installed in a power facility of a power plant A1. Time information and an instantaneous value are written from the plant-data inputting means A2 to a plant-data most-recent-value table A3 (
Further, a plant-data recording means A4 periodically reads the content of the plant-data most-recent-value table A3 and writes long-term time-series plant data into a plant history data table A5 (
A monitoring-point editing means A7 resisters operator-specified one or more plant-error monitoring points in a monitoring-point registering table A8 (
As a result, a data-correlation determining means A6 uses a statistical process to automatically extract one or more main variable points having a strong correlation (1.0≦correlation factor R<0.9) as shown in
A limit-value calculating means A10 reads historical plant data about a monitoring point and a main variable point from the plant history data table A5 by referring to the main-variable-point registering table A9. Then the limit-value calculating means A10 calculates a statistical upper/lower limit of the monitoring point as a function (y=aX2+bX+c) of the main variable point and stores in a limit-value function table A11 (
A limit-value determining means A12 periodically reads the most recent value data in a monitoring point and a main variable point from the plant-data most-recent-value table A3 and determines whether the most recent value is within a range of a statistical upper/lower limit function stored in the limit-value function table A11.
If the most recent value exceeds the upper/lower limit range, the limit-value determining means A12 stores the time of exceeding the upper/lower limit range and the detected value of that time in a determination result table A13 (
First, the operator uses the display device A15 to register an error monitoring point of the power plant through the monitoring-point editing means A7. Then, the data-correlation determining means A6 uses the time-series plant data in the plant history data table A5 to automatically select a main variable point having a strong correlation.
Then, the limit-value calculating means A10 calculates a statistical upper/lower limit of a monitoring point as a function of a main variable point and the limit-value determining means A12 compares the periodical most recent plant data to detect a plant error. This enables monitoring of a dynamically varying plant.
As described above, according to the Embodiment 1, even if the operator is not a skilled plant operation technician, the operator can set a statistical upper/lower limit optimum for a plant operation state to a plant error monitoring point. Accordingly, it is possible to increase the plant monitoring accuracy without dependence on the operator's skill.
The configuration of an Embodiment 2 in accordance with the present invention will be described with reference to
As shown in
With reference to
As shown in
As described above, according to the Embodiment 2, when the statistical upper/lower limit of monitoring points and main variable points is calculated, an optimum upper/lower limit range can be obtained as shown in
The configuration of an Embodiment 3 in accordance with the present invention will be described with reference to
As shown in
According to the Embodiment 3 shown in
The limit-value calculating means A10 extracts the historical data satisfying the condition, and calculates the statistical upper/lower limit based on less varying data. Further, the limit-value determining means A12 refers to the condition and performs monitoring check only if the condition is satisfied.
As described above, according to the Embodiment 3, it is possible to increase the accuracy of calculating the statistical upper/lower limit of monitoring points and main variable points and to perform plant monitoring by preventing a false alarm from occurring due to varying data.
The configuration of an Embodiment 4 in accordance with the present invention will be described with reference to
The Embodiment 4 of the present invention adds group-determination-condition editing means A19 and a group-determination-condition table A20, as shown in
As shown in
When the operator sets a condition to distinguish the plurality of statistical upper/lower limit values (e.g., selects group 1 if the ambient temperature is equal to or higher than 10° C., and selects group 2 if the ambient temperature is lower than 10° C.), the set condition is stored in the group-determination-condition table A20.
During the periodical monitoring checking, the limit-value determining means A12 matches the condition with the most recent plant data value to find a statistical upper/lower limit value satisfying the condition for checking. Therefore, according to the Embodiment 4, if a two-dimensional distribution of monitoring points and main variable points is combined into a single group, the statistical upper/lower limit range contains a large error.
According to the Embodiment 4, the distribution is divided into a plurality of groups each having a different distribution depending on the plant operation condition, and a selection condition is added for each group. This allows an appropriate statistical upper/lower limit value to be selected depending on the plant operation state, thereby increasing the accuracy of monitoring the plant.
Hereinafter, the Embodiment 5 of the present invention will be described. It should be noted that the description is omitted since the configuration of the Embodiment 5 is the same as that of the Embodiment 3 except the structure of the limit-value function table A11.
The data processing of the Embodiment 5 will be described with reference to
Therefore, according to the Embodiment 5, further to the Embodiment 4, an optimum group selection condition is automatically calculated on the basis of the tendency of the history data without requiring an operator's decision. This can not only reduce the burden of the operator, but also can select an accurate statistical upper/lower limit value according to the plant state, and increase the plant monitoring accuracy.
The configuration of an Embodiment 6 in accordance with the present invention will be described with reference to
As shown in
When the operator sets a plurality of plant states (1) to (n) to one of the monitoring points stored in the monitoring-point registering table A8 through the display device A15 in
The data-correlation determining means A6 automatically extracts one or more main variable points having a strong correlation to a monitoring point in this plant state and stores them in the main-variable-point registering table A9 (1) to (n) for each plant state.
As shown in
The limit-value determining means A12 periodically checks for the most recent value for the plant state and the plant data in the plant-state tables A22 (1) to (n). When the set plant state is established, the limit-value determining means A12 reads the limit-value function table A11 related to the plant state and performs monitoring by the statistical upper/lower limit.
As described above, according to the Embodiment 6, when the operator specifies noteworthy several plant states, an appropriate main variable point corresponding to a monitoring point is automatically extracted according to the plant state to calculate the statistical upper/lower limit values, thereby enabling plant monitoring more adapted to a change of the plant operation.
Hereinafter, the Embodiment 7 of the present invention will be described. It should be noted that the description is omitted since the configuration of the Embodiment 7 is the same as that of the Embodiment 6.
With reference to
For example,
Plant state (1) . . . main variable point R
Plant state (2) . . . main variable point S
Plant state (3) . . . main variable point R
If a different main variable point having a strong correlation in a plant state is automatically extracted as shown above, main variable point S in plant state (2) is replaced with main variable point R so that the main variable point should be the same in every plant state, and then calculates the statistical upper/lower limit.
As described above, according to the Embodiment 7, the same main variable point in a plurality of plant states is selected from among a plurality of main variable points having a strong correlation to a monitoring point. Although the number of main variable points to be selected tends to be large up to a maximum number of n, but the main variable point having priority can be used, thereby facilitating monitoring a plant tendency.
With reference to
As shown in
As described above, according to the Embodiment 8, a main variable point can be manually set to a monitoring point. The operator can consciously set a combination of a monitoring point and a main variable point to calculate the statistical upper/lower limit for plant monitoring.
Hereinafter, the Embodiment 9 of the present invention will be described. It should be noted that the description is omitted since the configuration of the Embodiment 9 is the same as that of the Embodiment 6.
The data processing will be described with reference to
As described above, according to the Embodiment 9, a plurality of monitoring points can be registered, and thus, facility sensors at a plurality of locations can be simultaneously monitored, thereby increasing the sensitivity of multilateral plant monitoring.
The Embodiment 10 of the present invention will be described with reference to
With reference to
The limit-value calculating means A10 uses the plant condition to calculate the statistical upper/lower limit with respect to a main variable point only by history data in the range of an individual plant condition for each monitoring point. If the condition is established, the limit-value determining means A12 performs monitoring checking.
In other words, there is a need of performing plant monitoring using only plant data under an individual plant condition by a monitoring point, and this plant condition differs depending the monitoring point.
As described above, according to Embodiment 10, an individual plant condition can be set for each monitoring point. Therefore, it is possible to perform plant monitoring under a condition specified by the operator. It is also possible to remove missing data which may be a statistical outlier depending on the condition and data during test operation. Accordingly, it is possible to increase the accuracy of a statistical upper/lower limit and suppress an unnecessary false alarm.
The configuration of Embodiment 11 in accordance with the present invention will be described with reference to
With reference to
The limit-value matching means A26 reads from the limit-value function table A11 the statistical upper/lower limit values of monitoring points and main variable points calculated by the limit-value calculating means A10 on the basis of the conditions stored in the monitoring-point-condition table A25 and the plant-state tables A22 in
It should be noted that the graph display screen has means for displaying a history data search period when the statistical upper/lower limit is calculated and has means for calling a plant state about the monitoring point and an individual condition for each monitoring point. In addition, it has means for increasing visibility by changing a plot color about data outside the upper/lower limit.
As described above, according to Embodiment 11, the upper/lower limit values calculated by statistic processing on the basis of specified conditions and data used for calculation are displayed on the same graph and at the same time, the plant data count within the upper/lower limit and the data count outside the upper/lower limit are displayed. Accordingly, it is possible to quantitatively confirm the accuracy of the calculated statistical upper/lower limit.
Hereinafter, the Embodiment 12 of the present invention will be described. It should be noted that the description is omitted since the configuration of the Embodiment 12 is the same as that of the Embodiment 11.
As described above in the Embodiment 11 with reference to
The statistical upper/lower limit functions (factors) for the monitoring points are displayed on the graph screen. The operator manually changes a factor in the functional expression through the display device A15 to reset a statistical upper/lower limit value the operator assumes appropriate.
As described above, according to the Embodiment 12, statistical upper/lower limit values for monitoring points are automatically calculated on the basis of history data. If appropriate history data is not available, the operator changes a factor in the functional expression, and then the result is reflected on the statistical upper/lower limit values at monitoring checking. In other words, it is easy to edit statistical upper/lower limit values at plant monitoring.
The configuration of Embodiment 13 in accordance with the present invention will be described with reference to
The plant-state editing means A21 in
With reference to
If a plurality of upper/lower limit values and plant data are overlay-displayed depending on a plant state, the numerical values indicating supplemental information inside the graph are displayed shifted without an overlay.
As described above, according to the Embodiment 13, it is possible to display on the same graph the statistical upper/lower limit values between monitoring points and main variable points in a plurality of plant states and the plant data used for the calculation; to provide identification information such as a color and a marker; and confirm data distribution in a plant monitoring area changing depending on a plant state.
Hereinafter, the Embodiment 14 of the present invention will be described. It should be noted that the description is omitted since the configuration of the Embodiment 14 is the same as that of the Embodiment 13.
With reference to
As described above, according to the Embodiment 14, means is provided of not displaying the graph of the statistical upper/lower limit values and the plant data used for calculation for each plant state and thus it is possible to display only the graph in the plant state to be focused.
