KR20150137950A - Apparatus and method for system monitoring - Google Patents
Apparatus and method for system monitoring Download PDFInfo
- Publication number
- KR20150137950A KR20150137950A KR1020140133525A KR20140133525A KR20150137950A KR 20150137950 A KR20150137950 A KR 20150137950A KR 1020140133525 A KR1020140133525 A KR 1020140133525A KR 20140133525 A KR20140133525 A KR 20140133525A KR 20150137950 A KR20150137950 A KR 20150137950A
- Authority
- KR
- South Korea
- Prior art keywords
- state
- data set
- subsystems
- time
- indicator
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 99
- 238000012544 monitoring process Methods 0.000 title claims abstract description 77
- 238000013480 data collection Methods 0.000 claims abstract description 4
- 238000012806 monitoring device Methods 0.000 claims description 35
- 230000007547 defect Effects 0.000 claims description 26
- 208000024891 symptom Diseases 0.000 claims description 20
- 230000002950 deficient Effects 0.000 claims description 19
- 230000002159 abnormal effect Effects 0.000 claims description 16
- 230000005856 abnormality Effects 0.000 claims description 7
- 230000002547 anomalous effect Effects 0.000 claims description 7
- 230000004044 response Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 8
- 230000008569 process Effects 0.000 description 8
- 230000008859 change Effects 0.000 description 6
- 238000002790 cross-validation Methods 0.000 description 5
- 238000001816 cooling Methods 0.000 description 3
- 230000032683 aging Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000014509 gene expression Effects 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
A system monitoring apparatus and method are disclosed. A system monitoring apparatus according to an exemplary embodiment includes a data collection unit configured to collect a first data set obtained in a monitored system and determined to indicate the status of the system and a second data set obtained in the system; And an output unit configured to calculate an index associated with the status of the system using the first data set and the second data set.
Description
The disclosed embodiments relate to a system monitoring apparatus and method, and more particularly to a technique for diagnosing and indexing the state of a system.
With the development of information and communication technologies, there has been an increasing demand for services that place various types of sensors in buildings and control devices in buildings based on sensor values. The state of the system providing such service may be monitored based on sensor values. Typically, such system monitoring involves determining whether the system is healthy or defective.
However, existing system monitoring techniques are not useful for detecting potential defects in the system. In general, the conventional technique only informs the user of a situation in which a fault has already occurred, and sets a protective threshold for determining that such a situation has occurred with only a slight possibility that the system is not normal. In addition, for a system with a high degree of complexity, the above-mentioned dichotomous judgment is difficult to show satisfactory performance. Therefore, there is a need for an improved technique for monitoring the above system to diagnose the system state.
The disclosed embodiments provide a system monitoring apparatus and method.
According to an exemplary embodiment, a data collection unit is configured to collect a first data set obtained in a monitored system and determined to indicate the status of the system and a second data set obtained in the system; And a calculation unit configured to calculate an indicator associated with the state of the system using the first data set and the second data set.
The first set of data may be one determined to indicate that the state of the system at the first time is a steady state or a defective state.
The indicator may comprise a basic state index value associated with the state of the system at a second time point.
The indicator may include an operational state index value associated with a state of the system over a time period from a time preceding the second time point to a second time point.
Wherein the calculating unit may be configured to calculate the operational state index value from a plurality of time-based basic state index values, each of the plurality of time-based basic state index values being associated with a state of the system at a point in time within the time period .
The system may comprise a plurality of subsystems, and the indicator may comprise a substatus index value associated with a status of one of the plurality of subsystems at the second time point.
Wherein the calculating unit may be configured to calculate the lower status indicator value from the plurality of subsystem-based basic status indicator values, wherein each of the plurality of the basic status indicator values for each of the plurality of subsystems comprises: Can be associated with one state.
The lower status indicator value may be a minimum value among the plurality of basic status indicator values for each subsystem.
The system monitoring apparatus may further include an interface unit configured to display the indicator on a user interface.
The system may include a plurality of subsystems, and the calculating unit may be further configured to calculate an index for each of the plurality of subsystems, wherein the interface unit is further configured to calculate, , Wherein each of the plurality of indicators for each subsystem may be associated with a status of a corresponding one of the plurality of subsystems.
The interface may also be configured to present at least one of the plurality of subsystems in an emphasized format.
Wherein the calculating unit may be further configured to calculate a degree of similarity between the first data set and the second data set, and the system monitoring apparatus is further configured to determine, based on the threshold and the similarity associated with the first data set, And a determination unit configured to determine whether the set indicates an abnormal symptom state of the system, the normal state, or the defect state.
The calculating unit may be further configured to calculate the index from the similarity.
Wherein the first data set may comprise a plurality of first sensor values measured through a plurality of sensors installed in association with the system and the second data set comprises a plurality of second sensors Value. ≪ / RTI >
The calculating unit may be further configured to calculate the contribution of each of the plurality of sensors to the similarity if it is determined that the second data set represents the defect state or the abnormal symptom state.
The determination unit may be further configured to select one of the plurality of sensors as a sensor to be inspected based on the calculated contribution.
The similarity may indicate a distance between the first data set and the second data set according to a predetermined distance metric.
The second data set may be determined to indicate the steady state if the distance is less than the threshold and the first data set is determined to represent the steady state and the distance is less than the threshold and the first data The second data set may be determined to indicate the fault state if the set is determined to represent the fault condition and the second data set may be determined to indicate the abnormal symptom condition if the distance is greater than the threshold value have.
The calculating unit may be further configured to calculate a basic state index value associated with a state of the system at a second time point from the distance, and the basic state index value is determined when the first data set indicates the normal state And the basic state index value may be calculated based on an increasing function for the distance when it is determined that the first data set represents the fault state.
According to another exemplary embodiment, there is provided a system monitoring method implemented by a computing device, the method comprising: collecting a first data set obtained in a monitored system and determined to indicate the status of the system and a second data set obtained in the system step; And calculating an indicator associated with the status of the system using the first data set and the second data set.
The first set of data may be one determined to indicate that the state of the system at the first time is a steady state or a defective state.
The indicator may comprise a basic state index value associated with the state of the system at a second time point.
The indicator may include an operational state index value associated with a state of the system over a time period from a time preceding the second time point to a second time point.
Wherein the calculating step may include calculating the operational state index value from a plurality of time-based basic state index values, wherein each of the plurality of time-based basic state indexes is calculated based on the time- Lt; / RTI >
The system may comprise a plurality of subsystems, and the indicator may comprise a substatus index value associated with a status of one of the plurality of subsystems at the second time point.
Wherein the calculating step may include calculating the lower status indicator value from the basic status indicator value for each of the plurality of subsystems, wherein each of the plurality of basic status indicator values for each of the plurality of subsystems includes the plurality RTI ID = 0.0 > of, < / RTI >
The lower status indicator value may be a minimum value among the plurality of basic status indicator values for each subsystem.
The system monitoring method may further include the step of presenting the indicator to the user interface.
The system may include a plurality of subsystems, the method comprising: calculating an indicator for each of the plurality of subsystems; And presenting at least some of the plurality of subsystem-specific indicators in the user interface in response to receiving user input, wherein each of the plurality of subsystem-specific indicators is associated with a corresponding one of the plurality of subsystems Lt; RTI ID = 0.0 > and / or < / RTI >
And displaying at least one of the plurality of subsystems in an emphasized format.
The system monitoring method comprising: calculating a degree of similarity between the first data set and the second data set; And determining based on the threshold and the similarity associated with the first data set whether the second data set represents an anomalous state of the system, the steady state, or the fault state.
The system monitoring method may further include calculating the indicator from the similarity.
Wherein the first data set may comprise a plurality of first sensor values measured through a plurality of sensors installed in association with the system and the second data set comprises a plurality of second sensors Value. ≪ / RTI >
The system monitoring method may further include calculating the contribution of each of the plurality of sensors to the similarity when it is determined that the second data set represents the defect state or the abnormal symptom state.
The system monitoring method may further include selecting one of the plurality of sensors as a sensor to be inspected based on the calculated contribution.
The similarity may indicate a distance between the first data set and the second data set according to a predetermined distance metric.
The second data set may be determined to indicate the steady state if the distance is less than the threshold and the first data set is determined to represent the steady state and the distance is less than the threshold and the first data The second data set may be determined to indicate the fault state if the set is determined to represent the fault condition and the second data set may be determined to indicate the abnormal symptom condition if the distance is greater than the threshold value have.
The system monitoring method may further comprise calculating a basic state index value associated with a state of the system at a second time point from the distance and wherein the basic state index value indicates that the first data set is in the steady state And the basic state index value can be calculated based on an increasing function for the distance when it is determined that the first data set represents the fault state have.
According to yet another exemplary embodiment, there is provided a method of monitoring a system, comprising a basic state indicator value associated with a point-in-time condition of a monitored system and including an operating state indicator value associated with a time- A status indicator configured to obtain a system status indicator further comprising at least one of a status indicator value; And an interface unit configured to display the system status indicator in a user interface.
The basic state index value may indicate a state of the system at a specific point in time and the operation state index value may indicate a state of the system over a time period from a point preceding the point in time to the point in time, The lower status indicator value may indicate the status of the particular subsystem at the particular point in time.
Wherein the calculating unit may be configured to obtain the operational state index value using a plurality of time-based basic state indexes, and each of the plurality of time-based basic state indexes may include a state of the system at a point within the time period Lt; / RTI >
The calculating unit may be configured to obtain the lower state index value using a plurality of subsystem-specific basic state index values, and the system may include a plurality of subsystems, System, and each of the plurality of subsystem-specific basic status indicator values may be associated with a status of one of the plurality of subsystems at the specific time.
The lower status indicator value may be a minimum value among the plurality of basic status indicator values for each subsystem.
The system may include a plurality of subsystems, the plurality of subsystems may include the particular subsystem, and the calculating unit may be further configured to obtain a plurality of subsystem-specific system state indicators, Each of the plurality of subsystem-specific system status indicators may be associated with a status of a corresponding one of the plurality of subsystems, and the interface unit may also display at least some of the plurality of subsystem-specific system status indicators on the user interface .
The interface may also be configured to present at least one of the plurality of subsystems in a highlighted format on the user interface.
According to yet another exemplary embodiment, there is provided a method of monitoring a system, comprising a basic state indicator value associated with a point-in-time condition of a monitored system and including an operating state indicator value associated with a time- Obtaining a system status indicator that further includes at least one of a lower status indicator value; And presenting the system state indicator to a user interface.
The basic state index value may indicate a state of the system at a specific point in time and the operation state index value may indicate a state of the system over a time period from a point preceding the point in time to the point in time, The lower status indicator value may indicate the status of the particular subsystem at the particular point in time.
Wherein the acquiring may include acquiring the operational state index value using a plurality of time-based basic state indexes, and each of the plurality of time-based basic state indexes may include a time- May be associated with the state of the system.
The acquiring may comprise acquiring the substatus index value using a plurality of subsystem-specific basic status indicator values, the system may comprise a plurality of subsystems, May comprise the particular subsystem and each of the plurality of subsystem-specific basic status indicator values may be associated with a status of one of the plurality of subsystems at the particular time.
The lower status indicator value may be a minimum value among the plurality of basic status indicator values for each subsystem.
The system may include a plurality of subsystems, the plurality of subsystems may include the particular subsystem, and the system monitoring method further comprises obtaining a plurality of subsystem-specific system status indicators And wherein each of the plurality of subsystem-specific system status indicators may be associated with a status of a corresponding one of the plurality of subsystems, and wherein the system monitoring method is adapted to detect at least some of the plurality of subsystem- To the user interface.
The system monitoring method may further include presenting at least one of the plurality of subsystems to the user interface in an emphasized format.
According to an exemplary embodiment, a computer readable storage medium having stored thereon a computer program for executing any one of the methods is provided.
According to certain embodiments, techniques are provided that not only can determine that the monitored system is healthy or defective, but can also determine that a potential defect or anomalous indication has occurred in the system.
According to some embodiments, even though the data indicative of the fault condition of the monitored system and the fault occurrence situation associated therewith are not defined (e.g., by an expert with detailed knowledge of the system) The state of the system can be determined as an abnormal symptom state only by the data indicating that the monitoring target system can be operated economically and conveniently.
According to some embodiments, the status of the monitored system can be efficiently presented, and anomalous indications of the system or elements that cause defects can be easily recognized.
1 illustrates an operating environment in which a system monitoring device according to an exemplary embodiment is deployed,
Figure 2 illustrates a graphical representation of a system state indicator in accordance with an illustrative embodiment;
Figure 3 illustrates a user interface according to an exemplary embodiment;
4 is a diagram for explaining a similarity degree calculation and system state determination according to an exemplary embodiment;
Figure 5 illustrates a user interface according to an exemplary embodiment;
6 is a diagram illustrating a system monitoring process according to an exemplary embodiment;
FIG. 7 illustrates a system monitoring process according to an exemplary embodiment;
Figures 8-10 each illustrate graphical representations representing different system status indicators in accordance with an exemplary embodiment;
Hereinafter, specific embodiments of the present invention will be described with reference to the drawings. The following detailed description is provided to provide a comprehensive understanding of the methods, apparatus, and / or systems described herein. However, this is merely an example and the present invention is not limited thereto.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. The following terms are defined in consideration of the functions of the present invention, and may be changed according to the intention or custom of the user, the operator, and the like. Therefore, the definition should be based on the contents throughout this specification. The terms used in the detailed description are intended only to describe embodiments of the invention and should in no way be limiting. Unless specifically stated otherwise, the singular forms of the expressions include plural forms of meanings. In this description, the expressions "comprising" or "comprising" are intended to indicate certain features, numbers, steps, operations, elements, parts or combinations thereof, Should not be construed to preclude the presence or possibility of other features, numbers, steps, operations, elements, portions or combinations thereof.
Figure 1 illustrates an operating environment in which a system monitoring device according to an exemplary embodiment is deployed.
The
The monitored
The
The
- steady state: the monitored
- Defect Status: The monitored
- Abnormal Indication Status: The monitored
For the sake of convenience, hereinafter, a data set indicating a normal state of the system such as the
The
The
In addition, the
Default State Indicator Value
The system state indicator may include an indicator value, which may also be referred to as a "basic state indicator value ". The basic state index values may be associated with the state of the monitored
Operational State Indicator Value
The system status indicator may further include other indicator values, which may also be referred to as "operational status indicator values. &Quot; The operational state index values may be associated with the state of the monitored
Indicator values associated with the state of the parent system containing the subsystems
In some embodiments, the operating
The
For example, the
The
Accordingly, even if the user does not have sufficient expertise in the
As an example, the
As another example, the
As another example, the
3 illustrates a user interface according to an exemplary embodiment.
The
An exemplary implementation of the
The
The
The
For a specific example, assume that two sets of data Y 1 and Y 2 are collected from
Furthermore, the calculating
If it is determined that data set Y represents a steady state of the monitored
Here, assuming that P data sets Y i are collected from the
If the data set Y is determined to indicate a fault condition of the monitored
As described above, the basic state index value can be calculated so that the closer the data set X is to normal data, the closer to 1 and closer to the defect data, the closer to 0. Therefore, the basic state index value may indicate that the state of the
For the sake of concrete example, it is assumed in FIG. 4 that data points 410 and 420 represent normal data and defect data, respectively. If the
According to some embodiments, data set Y may be clustered data. Whether the data set (for example, the data set Y) stored in the
The determining
If the distance r is less than the threshold and the data set Y is determined to be normal data, then the data set X is determined to represent the steady state of the monitored
If the distance r is less than the threshold and the data set Y is determined to be defective data, then the data set X is determined to indicate the defective state of the monitored
If the distance r is greater than the threshold, then the data set X is determined to indicate the anomalous state of the monitored
4 is a threshold R 1 associated with data set Y 1 (normal data) represented by
In view of the above, when the data set X is included in the valid range of the data set Y, it can be determined that the data set X represents the state represented by the data set Y as it is. Otherwise, the data set X may be determined to represent an abnormal symptom state. As a result, the threshold associated with data set Y may also be referred to as the effective range of data set Y. [ This validity range may be established using various statistical methods (e.g., by applying an n-fold cross validation technique based on the history of the defects of the monitored system 120). The greater the effective range, the higher the possibility that the state of the
In addition, when it is determined that the data set X represents a defect status or abnormality symptom state of the monitored
On the other hand, as mentioned above, the basic state index value may not sufficiently represent a gradual change in the state of the monitored
The
For example, the
Assume that the P data sets Y i constructed in the
- the number of days in which the occurrence frequency of events in which the data set X is out of the range mentioned above exceeds a certain value (for example, b% b) over time in the monitoring period (for example, u is 14 days) If the number is smaller than u (e.g., 9 days) that is smaller than u, it is likely that the operation of the monitored
- If the number of days in which the data set X that is statistically unlikely to occur over time in the monitoring period (for example, u is 14 days) has occurred even once, It is highly likely that the operation of the
If two or more of the above conditions are satisfied, the operational state indicator value may be calculated as a weighted average of the basic state indicator values at a plurality of time points, with a weight p (where 0 <p <1). Here, p can be chosen to minimize RSS using an n-fold cross validation technique. For example, if the above weighted average is 0.9 and p is 0.5 and two or more of the above conditions are satisfied, then the final operating state indicator value can be calculated as 0.9 * 0.5 = 0.45 (i.e., 45%).
Meanwhile, as mentioned above, the operating
Furthermore, the higher indicator may further include at least one of an operating state indicator value and a lower state indicator value (e.g., a minimum state indicator value) of the host system. For example, the calculating
The
For example, the
The
Similarly, the
6 illustrates a system monitoring process according to an exemplary embodiment. For example, an
After the start operation, the
Such normal data or defect data may be stored in a database such as the
Sensor values of existing data sets may be normalized per sensor. For example, if the mean and standard deviation of the ambient temperature sensor values of the existing data sets are s and t, respectively, the ambient temperature sensor value of the data set presented in Table 2 above can be normalized to (-1.94485 - s) / t have. The normalized sensor value may be limited to a specific interval (e.g., -1.0 to 1.0). In addition, the upper section may be divided into a plurality of sub-sections, and a representative value (e.g., a median value or an average value of the sensor values in the sub-section) may be given to each sub-section.
In operation S610, a new data set (hereinafter also referred to as the "current data set") to be used to determine the current state of the "air conditioner 3" device is collected from the "air conditioner 3" device. For example, the current data set may be given as the data set presented in the following table.
The sensor values of the current data set can be normalized per sensor. For example, the ambient temperature sensor value of the data set presented in Table 3 above can be normalized to (-12.9682-s) / t.
In operation S615, the similarity between each of the existing data sets and the current data set is calculated. As noted above, the similarity may be Euclidean distance between two data points. As another example, the similarity may be a Manhattan distance between two data points. Through this calculation of similarity, an existing data set that is most similar to the current data set among the existing data sets can be determined. For convenience of explanation, it is assumed that the existing data set presented in Table 2 is the closest to the current data set presented in Table 3.
In operation S620, it is determined whether the similarity between the current data set and the existing data set most similar to the most similar existing data set effective range is large. If the similarity is greater than or equal to the effective range, it is determined that the current data set represents the abnormality symptom state of the "air conditioner 3" device (S625). Further, the history of such a determination may be recorded (e.g., in a database), and the user may be notified of the anomalous state of the anomaly. If the above degree of similarity is smaller than the effective range, it is determined whether the most similar existing data set is defective data (S630). If it is determined that the most similar existing data set is defective data, it is determined that the current data set represents the defective state of the "air conditioner 3" device (S635). The history of such a determination can be recorded (e. G., In a database) and the user can be notified of the defect status. Subsequently, the
On the other hand, if it is determined that the current data set represents an abnormality symptom state of the "air conditioner 3" device, a sensor that has the greatest influence on such determination can be identified. For this, the contribution of each sensor to the similarity between the most similar existing data set and the current data set can be calculated (S640). The contribution of the Kth sensor among the N sensors can be given by the following equation.
Subsequently, the
In operation S645, an indicator associated with the state of the "air conditioner 3" device is calculated. Such an indicator may include a basic status indicator value that is calculated as described above, and may additionally include an operational status indicator value. On the other hand, operations (S610) to (S645) may be repeated for each in-building apparatus, and an index related to the state of the building, which is an upper system, can be calculated. Such an indicator may include a basic status indicator value calculated as described above, and may additionally include an operational status indicator value and / or a minimum status indicator value.
7 illustrates a system monitoring process according to an exemplary embodiment. For example, an
After the start operation, the
According to some embodiments, the system monitoring device 110 (the computing portion 114) may obtain such system state indicators through the same or similar operations as those previously mentioned. For example, when a monitored system includes a plurality of subsystems, a plurality of subsystem-specific system state indicators (each associated with a status of a corresponding one of the subsystems of the monitored system 120) A higher indicator (i. E., A system state indicator of the monitored system 120) may be obtained.
Specifically, the basic state index value may indicate the state the monitored system has at a particular point in time. For example, the calculating
In operation S720, the obtained system state index is represented in the user interface. According to some embodiments, the
Then, if another system state indicator is obtained, the
On the other hand, exemplary embodiments may include a computer-readable storage medium including a program for performing the procedures described herein on a computer. Such computer-readable storage media may include program instructions, local data files, local data structures, etc., alone or in combination. The computer-readable storage medium may be those specially designed and constructed for the present invention. Examples of computer-readable storage media include magnetic media such as hard disks, floppy disks and magnetic tape, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floppy disks, and ROMs, And hardware devices specifically configured to store and execute the same program instructions. Examples of program instructions may include machine language code such as those generated by a compiler, as well as high-level language code that may be executed by a computer using an interpreter or the like.
While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, . Therefore, the scope of the present invention should not be limited to the above-described embodiments, but should be determined by equivalents to the appended claims, as well as the appended claims.
110: System monitoring device
112: Data collecting unit
114:
116:
118:
120: Systems to be monitored
140: Database
160: User device
Claims (53)
And an output unit configured to calculate an index associated with the status of the system using the first data set and the second data set
System monitoring device.
Wherein the first data set is determined to indicate that the state of the system at a first time is a steady state or a fault state.
Wherein the indicator comprises a basic state index value associated with a state of the system at a second point in time.
Wherein the indicator comprises an operational state indicator value associated with a state of the system over a time period from a time preceding the second time point to a second time point.
Wherein the calculating unit is configured to calculate the operational state index value from a plurality of time-based basic state index values, each of the plurality of time-based basic state index values being associated with a state of the system at a time point within the time period, Monitoring device.
Wherein the system comprises a plurality of subsystems, and wherein the indicator comprises a substatus index value associated with a status of one of the plurality of subsystems at the second time point.
Wherein the calculating unit is configured to calculate the lower state index value from a plurality of subsystem-based base state index values, and each of the plurality of base system-specific base state index values is configured to calculate one of the plurality of subsystems at the second time point System monitoring device.
Wherein the lower status indicator value is a minimum value among the plurality of subsystem-specific basic status indicator values.
Further comprising an interface configured to present the indicator to a user interface.
Wherein the system further comprises a plurality of subsystems and wherein the calculating unit is further configured to calculate an index for each of the plurality of subsystems in response to receiving the user input, Wherein each of the plurality of subsystem-specific indicators is associated with a status of a corresponding one of the plurality of subsystems.
Wherein the interface is further configured to render at least one of the plurality of subsystems in a highlighted format.
Wherein the calculating unit is further configured to calculate a degree of similarity between the first data set and the second data set,
Wherein the system monitoring device is configured to determine, based on the threshold associated with the first data set and the similarity, whether the second data set represents an anomalous state of the system, the steady state, or the defective state Further comprising a system monitoring device.
And wherein the calculating unit is further configured to calculate the indicator from the similarity.
Wherein the first data set includes a plurality of first sensor values measured through a plurality of sensors installed in association with the system and the second data set includes a plurality of second sensor values measured through the plurality of sensors System monitoring device.
Wherein the calculating unit is further configured to calculate a contribution of each of the plurality of sensors to the similarity if it is determined that the second set of data represents the defect state or the abnormal symptom state.
Wherein the determination unit is further configured to select one of the plurality of sensors as a sensor to be inspected based on the calculated contribution.
Wherein the similarity indicates a distance between the first data set and the second data set according to a predetermined distance metric.
The second data set is determined to represent the steady state if the distance is less than the threshold and the first data set is determined to represent the steady state and the distance is less than the threshold and the first data set The second data set is determined to indicate the fault state when it is determined that the fault condition is indicated, and the second data set is determined to indicate the abnormality symptom condition if the distance is greater than the threshold value.
Wherein the calculating unit is further configured to calculate a basic state index value associated with a state of the system at a second time point from the distance, wherein the basic state index value is calculated based on the distance Wherein the basic state index value is calculated based on an increasing function for the distance when it is determined that the first data set represents the fault state.
Collecting a first data set obtained in the monitored system and determined to indicate the status of the system and a second data set obtained in the system; And
Using the first data set and the second data set to calculate an indicator associated with the state of the system
How to monitor the system.
Wherein the first data set is determined to indicate that the state of the system at a first time is a steady state or a fault state.
Wherein the indicator comprises a basic state index value associated with the state of the system at a second point in time.
Wherein the indicator comprises an operational state indicator value associated with a state of the system over a time period from a time preceding the second time point to a second time point.
Wherein the calculating step includes calculating the operating state index value from a plurality of viewpoint-based basic state index values, wherein each of the plurality of viewpoint-based basic state index values indicates a state of the system at a point within the time period Wherein the system monitoring method comprises:
Wherein the system comprises a plurality of subsystems, and wherein the indicator comprises a substatus index value associated with a status of one of the plurality of subsystems at the second time point.
Wherein the calculating step includes calculating the lower state index value from a plurality of basic system state index values for each subsystem, wherein each of the plurality of base state index values for each of the plurality of subsystems includes a plurality of sub- A method of monitoring a system, the method being associated with a state of one of the systems.
Wherein the lower status indicator value is a minimum one of the plurality of basic status indicator values for each of the plurality of subsystems.
And presenting the indicator to a user interface.
The system includes a plurality of subsystems,
Calculating an index for each of the plurality of subsystems; And
Further comprising presenting at least a portion of the plurality of subsystem-specific indicators in the user interface in response to receiving user input, wherein each of the plurality of subsystem-specific indicators is associated with a corresponding one of the plurality of subsystems The method comprising:
Further comprising presenting at least one of the plurality of subsystems in an emphasized format.
Calculating a degree of similarity between the first data set and the second data set; And
Further comprising determining based on the threshold and the similarity associated with the first data set whether the second data set represents an anomalous state of the system, the steady state, or the fault state.
And calculating said indicator from said degree of similarity.
Wherein the first data set includes a plurality of first sensor values measured through a plurality of sensors installed in association with the system and the second data set includes a plurality of second sensor values measured through the plurality of sensors And a method for monitoring the system.
Further comprising calculating the contribution of each of the plurality of sensors to the similarity if it is determined that the second set of data represents the defect state or the abnormal symptom state.
And selecting one of the plurality of sensors as a sensor to be inspected based on the calculated contribution.
Wherein the similarity indicates a distance between the first data set and the second data set according to a predetermined distance metric.
The second data set is determined to represent the steady state if the distance is less than the threshold and the first data set is determined to represent the steady state and the distance is less than the threshold and the first data set The second data set is determined to indicate the fault state when it is determined to indicate the fault condition and the second data set is determined to indicate the abnormal symptom condition if the distance is greater than the threshold value.
Further comprising calculating from the distance a basic state index value associated with a state of the system at a second time point, wherein the basic state index value is calculated based on the distance to the first state when the first data set is determined to represent the steady state Wherein the basic state index value is calculated based on an increasing function for the distance when it is determined that the first data set represents the fault state.
And an interface unit configured to display the system status indicator in a user interface.
Wherein the basic state index value indicates a state of the system at a specific point in time, the operational state index value indicates a state of the system over a time period from a point preceding the specific point in time to the point in time, Value indicates the status of the particular subsystem at the particular time.
Wherein the calculating unit is configured to obtain the operational state index value using a plurality of time-based basic state index values, and each of the plurality of time-based basic state index values is associated with a state of the system at a time point within the time period , System monitoring device.
Wherein the calculating unit is configured to obtain the substatus indicator value using a plurality of subsystem-specific basic status indicator values, the system comprising a plurality of subsystems, the plurality of subsystems comprising the specific subsystem Wherein each of the plurality of subsystem-specific basic status indicator values is associated with a status of one of the plurality of subsystems at the specific time.
Wherein the lower status indicator value is a minimum value among the plurality of subsystem-specific basic status indicator values.
Wherein the system comprises a plurality of subsystems, wherein the plurality of subsystems comprises the specific subsystem, and wherein the calculator is further configured to obtain a plurality of subsystem-specific system status indicators, wherein the plurality of subsystem- Wherein each of the status indicators is associated with a status of a corresponding one of the plurality of subsystems, and wherein the interface is further configured to present at least a portion of the plurality of subsystem-specific system status indicators to the user interface.
Wherein the interface is further configured to render at least one of the plurality of subsystems in a highlighted format on the user interface.
And presenting the system state indicator to a user interface.
Wherein the basic state index value indicates a state of the system at a specific point in time, the operational state index value indicates a state of the system over a time period from a point preceding the specific point in time to the point in time, Value represents the status of the particular subsystem at the particular point in time.
Wherein the acquiring includes acquiring the operational state index value using a plurality of time-based basic state index values, wherein each of the plurality of time- The method comprising:
Wherein the acquiring includes obtaining the substatus indicator value using a plurality of subsystem-specific basic status indicator values, the system comprising a plurality of subsystems, Wherein each of the plurality of subsystem-specific basic status indicator values is associated with a status of one of the plurality of subsystems at the specific time.
Wherein the lower status indicator value is a minimum one of the plurality of basic status indicator values for each of the plurality of subsystems.
Wherein the system comprises a plurality of subsystems, wherein the plurality of subsystems comprises the specific subsystem, and wherein the system monitoring method further comprises obtaining a plurality of subsystem-specific system status indicators, Wherein each of the subsystem-specific system status indicators is associated with a status of a corresponding one of the plurality of subsystems, and wherein the system monitoring method comprises: representing at least a portion of the plurality of subsystem-specific system status indicators in the user interface ≪ / RTI >
And presenting at least one of the plurality of subsystems in a highlighted format to the user interface.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/KR2014/010250 WO2015182831A1 (en) | 2014-05-30 | 2014-10-29 | Apparatus and method for monitoring system |
| CN201510063712.2A CN105278494A (en) | 2014-05-30 | 2015-02-06 | System monitoring apparatus and method |
| US14/616,131 US20150347213A1 (en) | 2014-05-30 | 2015-02-06 | Apparatus and method for system monitoring |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR20140066494 | 2014-05-30 | ||
| KR1020140066494 | 2014-05-30 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| KR20150137950A true KR20150137950A (en) | 2015-12-09 |
Family
ID=54873815
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020140133525A KR20150137950A (en) | 2014-05-30 | 2014-10-02 | Apparatus and method for system monitoring |
Country Status (2)
| Country | Link |
|---|---|
| KR (1) | KR20150137950A (en) |
| CN (1) | CN105278494A (en) |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6834256B2 (en) * | 2002-08-30 | 2004-12-21 | General Electric Company | Method and system for determining motor reliability |
| US8731724B2 (en) * | 2009-06-22 | 2014-05-20 | Johnson Controls Technology Company | Automated fault detection and diagnostics in a building management system |
| JP5284433B2 (en) * | 2011-09-14 | 2013-09-11 | 株式会社東芝 | Process monitoring / diagnosis / support equipment |
-
2014
- 2014-10-02 KR KR1020140133525A patent/KR20150137950A/en not_active Application Discontinuation
-
2015
- 2015-02-06 CN CN201510063712.2A patent/CN105278494A/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| CN105278494A (en) | 2016-01-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR102011620B1 (en) | Importance determination device of abnormal data and importance determination method of abnormal data | |
| JP6394726B2 (en) | Operation management apparatus, operation management method, and program | |
| US20160033946A1 (en) | Building management system analysis | |
| US20160378583A1 (en) | Management computer and method for evaluating performance threshold value | |
| US20090216393A1 (en) | Data-driven anomaly detection to anticipate flight deck effects | |
| RU2601669C2 (en) | Turbojet engine measuring circuit monitoring system | |
| CN108268689B (en) | Method for diagnosing and evaluating state of heating element and application thereof | |
| JP6521096B2 (en) | Display method, display device, and program | |
| JP6304767B2 (en) | SENSOR MONITORING DEVICE, SENSOR MONITORING METHOD, AND SENSOR MONITORING PROGRAM | |
| CN103502951B (en) | Operation management system, operation management method and program thereof | |
| JP6482743B1 (en) | Risk assessment device, risk assessment system, risk assessment method, and risk assessment program | |
| US20180234746A1 (en) | Maintenance device, presentation system, and program | |
| JP2016128973A (en) | Sign diagnosis system and sign diagnosis method | |
| CN112199258A (en) | Method and device for monitoring magnetic disk, electronic equipment and medium | |
| US20190265088A1 (en) | System analysis method, system analysis apparatus, and program | |
| JP5771317B1 (en) | Abnormality diagnosis apparatus and abnormality diagnosis method | |
| US20190369165A1 (en) | Management device, management method, and non-transitory storage medium | |
| JP6574533B2 (en) | Risk assessment device, risk assessment system, risk assessment method, and risk assessment program | |
| JP5918661B2 (en) | Equipment diagnostic device and setting change reminding method | |
| JP6875199B2 (en) | Equipment diagnostic system | |
| KR20150137950A (en) | Apparatus and method for system monitoring | |
| US20150347213A1 (en) | Apparatus and method for system monitoring | |
| JP7347953B2 (en) | Equipment early warning monitoring device and equipment early warning monitoring method | |
| JP5771318B1 (en) | Abnormality diagnosis apparatus and abnormality diagnosis method | |
| JP7170564B2 (en) | Motor deterioration trend monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| WITN | Withdrawal due to no request for examination |