KR101843365B1 - Integrated Diagnostic System and Database based on rules and cases - Google Patents
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Abstract
The present invention provides a system and method for determining whether a state is normal or abnormal by receiving state data of a facility, an integrated diagnosis database for storing normal signals, abnormal signals, case data, diagnostic rules, Diagnosis based on case data or diagnosis rules of the integrated diagnosis database, and diagnosis of the state data of the facility in case of failure in the diagnosis of the state data of the facility, And a case-based integrated diagnosis system including a case-based diagnosis apparatus for receiving and diagnosing a case-based integrated diagnosis system.
Description
The present invention provides a system and method for determining whether a state is normal or abnormal by receiving state data of a facility, an integrated diagnosis database for storing normal signals, abnormal signals, case data, diagnostic rules, Diagnosis based on case data or diagnosis rules of the integrated diagnosis database, and diagnosis of the state data of the facility in case of failure in the diagnosis of the state data of the facility, And a case-based integrated diagnosis system including a case-based diagnosis apparatus for receiving and diagnosing a case-based integrated diagnosis system.
There are two methods of maintenance for on-site facilities, one is to check whether the current condition is normal while monitoring the on-site facilities, and a troubleshooting method to take measures in case of a problem in the field facility do.
Conventionally, in the case of performing the monitoring method of the on-site facilities, conventionally, the fault signal has been acquired in advance for each failure mode, and the classification is performed after the failure signal is obtained. However, there is a problem that the diagnosis of the field facility can not be performed quickly Respectively.
In addition, it is possible to generate an algorithm after acquiring a fault signal in a laboratory using a test kit, but there is a problem that the test data can not be applied as it can show a different sun from a fault signal of a product actually used .
In the case of a fault repair method that takes a direct action in the event of a problem in the field facility, conventionally, a lot of data accumulated during maintenance is measured, analyzed, and used. However, You should go directly to the site and take action or reference materials such as references.
In this case, it is essential that experts visit the field when repairing the fault of the field facility, and expert knowledge or experience on the field facility is very important factor. Also, it is necessary to refer to reference documents and past troubleshooting cases, but this requires a separate manual work, which is troublesome and there is a problem that it is not possible to perform quick action on the field facilities.
In addition, a database of various methods for maintenance of on-site facilities is implemented separately, so that various state data used for monitoring and repair methods, optimal diagnosis results, and expert diagnosis solutions are not coordinated in real time There is a problem that the efficiency of diagnosis is very low.
It is an object of the present invention to provide an integrated diagnostic database that can share an algorithm with a diagnostic rule database in using two independent procedures, namely, the regular monitoring method and the post-problem repair method, as described above.
The technical problem to be solved by the present invention is not limited to the above-mentioned technical problems, and various technical problems can be included within the scope of what is well known to a person skilled in the art from the following description.
The rule-based and case-based integrated diagnosis system of the present invention for solving the above-mentioned problems includes an integrated diagnosis database for storing a normal signal, an abnormal signal, a case data, a diagnosis rule, Based on the diagnostic data stored in the integrated diagnosis database, and classifying abnormal state data according to the diagnostic rule of the integrated diagnostic database and diagnosing the abnormality based on the diagnostic model, And a case-based diagnosis device for receiving and diagnosing the expert diagnosis data when the diagnosis of the state data of the field facility fails.
Meanwhile, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention includes an integrated diagnostic database in association with a rule-based diagnostic device or a case-based diagnostic device. The integrated diagnostic database includes a normal signal database for storing steady- A case database for storing state data of the on-site facility as case data, a diagnosis rule for storing a diagnosis rule for classifying the abnormal state of the inputted state data used in the rule-based diagnosis device or the case- A database, and an abnormal signal database for storing abnormal condition data classified according to the diagnostic rule.
In addition, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the state data of the field facility is state data measured at at least two portions of the field facility.
In addition, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the state data of the field facility is vibration state data of the rotating body.
Further, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the normal signal database is used for abnormal behavior detection of the rule-based diagnostic apparatus.
In addition, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the normal signal database collects and stores steady state data in real time while normal operation of the field facility is being performed.
In addition, the rule-based diagnosing database according to an embodiment of the present invention is characterized in that when the rule-based diagnosis apparatus classifies abnormal state data according to the diagnosis rule, the rule- To the device.
The rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the abnormal signal database stores abnormal state data classified by classifying the abnormal state data according to a fault type . Wherein the abnormal signal database transmits the stored abnormal condition data to the rule based diagnostic apparatus when new status data is collected.
Further, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention further includes an SVM model database storing an SVM diagnostic model used when the rule-based diagnostic apparatus diagnoses input state data .
Further, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the case database is used for state data diagnosis of the case-based diagnosis apparatus.
In addition, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention may be configured such that, when the case database diagnoses state data inputted by the case-based diagnosis apparatus, whether the case data matching the state data exists And diagnoses the abnormality.
In this case, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention may be configured such that when the diagnostic rule database detects the state data inputted on the basis of the case data by the case- And the diagnosis rule for diagnosing the state data is transmitted to the case-based diagnosis apparatus.
In addition, the rule-based and case-based integrated diagnosis database according to an embodiment of the present invention is characterized in that the case-based diagnosis apparatus receives expert diagnosis data from an expert terminal and stores the same in the diagnosis rule database.
The rule of the present invention and the case-based integrated diagnosis system and database can improve the real-time diagnosis performance by applying the diagnosis rule generated from the case collection and diagnosis procedure to the diagnosis rule in the rule / signal complex diagnosis procedure.
Further, the rules and the case-based integrated diagnosis system and database of the present invention can obtain improved diagnosis results by applying the diagnostic rules generated by the experts to the diagnostic procedures of the rule / signal complex diagnosis system in real time.
In addition, the rule and case-based integrated diagnosis system and database of the present invention are a regular monitoring method through a rule-based diagnosis device when the field facility is normally operating, And the maintenance can be carried out with quick action through.
BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a flow diagram illustrating a rule and signal based diagnostic method.
Figure 2 is an exemplary diagram illustrating a case based diagnostic system.
3 is a block diagram showing a rule-based and case-based integrated diagnosis system and database of the present invention.
Hereinafter, the 'rule and case-based integrated diagnosis system and database' according to the present invention will be described in detail with reference to the accompanying drawings. The present invention is not limited to the above-described embodiments, and various changes and modifications may be made without departing from the scope of the present invention. In addition, the matters described in the attached drawings may be different from those actually implemented by the schematic drawings to easily describe the embodiments of the present invention.
In the meantime, each constituent unit described below is only an example for implementing the present invention. Thus, in other implementations of the present invention, other components may be used without departing from the spirit and scope of the present invention.
Also, the expression " comprising " is intended to merely denote that such elements are present as an expression of " open ", and should not be understood to exclude additional elements.
Also, the expressions such as 'first, second', etc. are used only to distinguish between plural configurations, and do not limit the order or other features among the configurations.
In the description of the embodiments, it is to be understood that each layer (film), area, pattern or structure may be referred to as being "on" or "under / under" Quot; includes all that is formed directly or through another layer. The criteria for top / bottom or bottom / bottom of each layer are described with reference to the drawings.
When a part is "connected" to another part, it includes not only "directly connected" but also "indirectly connected" with another part in between. Also, when an element is referred to as "comprising ", it means that it can include other elements, not excluding other elements unless specifically stated otherwise.
BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a flow diagram illustrating a rule and signal based diagnostic method.
Referring to FIG. 1, in the case of a rule-based diagnosis system that performs a continuous monitoring method of the field facility, it is checked whether the state of the facility is faulty or not, and the type of the fault is classified according to the diagnosis rule to diagnose the diagnosis model .
In the case of a diagnosis rule-based diagnosis system, which is a new system that diagnoses by using general diagnosis rules even if there is no accumulated fault signal data, the measured state data is judged as abnormal state data by the general diagnosis rule and classified. Based on the accumulation of fault signal data, it is possible to construct a signal-based database with high diagnostic rate, and there is an advantage that diagnosis can be performed based on general diagnostic rules even if failure signals are not acquired in advance.
More specifically, the diagnosis rule-based diagnosis system may be implemented as a diagnostic apparatus, and the diagnostic apparatus may include a measurement unit, a database, a detection unit, and a diagnosis unit.
The measuring unit collects the state data of the facility. At this time, the measuring unit can measure the state data which is the value of the present state of the field facility. The state data is not limited to any one numerical value but may be variously changed depending on the kind of the field facility. For example, the state data can be collected by measuring various state data such as temperature, pressure, torque, rotational state, amount of output, and number of revolutions of the field facility.
In addition, the measuring unit can measure and collect various status data of the on-site facilities, collect various parts of the status data for one on-site facility, collect and collect status data for various on-site facilities simultaneously It is possible.
Further, the measuring section can receive vibration state data of the rotating body. The rotating body is collectively referred to as a rotating device such as a motor or a turbine. In such a rotating body, unusual vibration may be generated only by rotating bodies such as unbalance, rubbing, misalignment, etc. . These abnormal vibrations not only shorten the service life of various parts such as bearings, but also can cause a large-scale accident of the equipment. Therefore, there is a need for a diagnostic method for estimating the state of the machine by measuring various state data (physical quantity) of the facility such as vibration or temperature without directly disassembling the mechanical equipment.
In particular, the failure of the equipment can be caused by changes in output, abnormal rise in temperature, and noise and vibration, so that most of the equipment malfunctions. Since this change occurs before the facility is completely shut down, it may be possible to measure the vibration condition of the facility and diagnose it without disassembling or disrupting the facility. Therefore, it is possible to manage the facility by performing the vibration diagnosis using the vibration measurement, and it is possible to generate various effects such as improvement of the operation rate, ease of parts management, and reduction of defects.
In addition, the measuring unit can collect status data using a K-mean clustering method. K-mean clustering is an algorithm that groups given data into k clusters, and operates in a way that minimizes the variance of the distance difference with each cluster.
In addition, the measuring unit can collect the steady state data in real time while storing the steady state operation of the equipment and store it in the database. In general, the facility is much longer than the period of operating in the steady state, which is longer than the period of operating in the unsteady state, so that the facility is in its normal state, You can quickly check whether or not it is.
The database stores state data. The database can efficiently collect and database status data for various problems occurring in the field facilities of the site. Furthermore, the database can store and store general diagnostic rules that distinguish the steady state or the abnormal state, and can also store and store the diagnostic model of the SVM model algorithm used for diagnosis.
When the measurement unit acquires new state data, the detection unit determines whether the new state data is in a normal state or an abnormal state based on the database. When the new state data is collected, it is determined whether there is information on state data corresponding to the new state data in the database, and then a normal state or an abnormal state is determined. The database may contain both the stored normal state data or the stored abnormal state data, and the corresponding state data may not exist.
In the case of steady-state data, the collection of normal steady-state data remains in the database because all data is collected that would normally operate the facility. However, in the case of abnormal state data, it may not be stored separately in the database. At this time, even if the abnormal state data does not exist in the database, the detection unit can determine whether the new state data is in the normal state or the abnormal state by checking the abnormal state data according to the general diagnosis rule described later.
The diagnostic unit classifies the abnormal state data according to a general diagnosis rule when the state data is abnormal state data, and stores the classified abnormal state data in the database. In this case, the general diagnosis rule refers to a rule that can be determined by the abnormal state mode.
In addition, the diagnostic unit may store the classified abnormal state data in a database according to classification, accumulate the abnormal state data, and diagnose the abnormal state data accumulated when the new state data is collected later. Therefore, it is possible to quickly determine whether a failure has occurred by checking the abnormal state data without any diagnosis by a general diagnosis rule in the database.
Figure 2 is an exemplary diagram illustrating a case based diagnostic system.
Referring to FIG. 2, in the case of the case-based diagnosis system in which a problem occurs in the field facility, the diagnosis is made based on accumulated case data. If the diagnosis fails, It is made into a database so that it can be used continuously.
In case of a case-based diagnosis system, which is a new system to diagnose through technical support of a remote expert, it is determined based on the cases accumulated in the case database that the state of the current facility is in a fault state, Proceed with troubleshooting by requesting diagnostic data. It is able to cope with abnormal situations by directly updating cases collection through expert technical support without disturbing geographical restrictions. It is also possible to replicate, accumulate and accumulate knowledge by normalizing the solution through expert knowledge, There is an advantage that it can be improved.
More specifically, the case-based diagnostic system and server may include a field terminal, a case-based diagnostic server, and an expert terminal.
The field terminal measures the state data of the field facility and sends it to the case-based diagnosis server. At this time, the state data refers to the value of the present state of the field facility, and is not limited to any one of the numerical values, but may be variously changed according to the type of the field facility. For example, the state data can be collected by measuring various state data such as temperature, pressure, torque, rotational state, amount of output, and number of revolutions of the field facility.
At this time, the field terminal can measure various state data of the field facility, measure several pieces of state data for one field facility, and simultaneously measure state data for various field facilities.
The case-based diagnosis server diagnoses the state data based on the data stored in the database, transmits diagnostic data to the field terminal when the diagnosis is successful, and transmits the state data to the expert terminal if the diagnosis fails. At this time, the case-based diagnosis server may include an input unit, a database, a diagnostic unit, and a control unit.
The input can receive the measured state data of the field facility from the field terminal. At this time, the input unit can receive the measured state data at at least two or more parts of the field facility as described above, or receive the vibration state data of the field facility.
The database stores case data and diagnostic data. The database efficiently collects and databases the state data for various problems occurring in the field facilities of the field, stores the diagnostic data corresponding to the state data, and extracts the diagnosis results when necessary. Therefore, the diagnostic data corresponding to the status data can be confirmed through the database. At this time, the database may include a case database in which previously stored state data are stored as case data, and a diagnosis database in which diagnostic data corresponding to the case data is stored.
The diagnosis unit diagnoses the state data based on the case data, and judges whether the diagnosis succeeded or failed. At this time, the diagnosis unit can diagnose using the case data stored in the database.
The diagnosis unit may judge whether or not case data matching the status data exists and diagnose it, and if the identical case data exists, the diagnosis unit may determine that the diagnosis is successful. In addition, the diagnosis unit may judge whether or not there is case data consistent with the state data and diagnose it, and may determine that the diagnosis fails if there is no matching case data.
The control unit transmits the diagnostic data corresponding to the status data to the field terminal when the diagnostic unit succeeds in diagnosis. When the diagnostic unit fails the diagnosis, the controller requests the expert terminal to perform the expert diagnosis, receives the expert diagnosis data, Lt; / RTI >
If the diagnostic unit succeeds in diagnosis, the control unit can extract the diagnostic data corresponding to the case data and transmit the diagnostic data to the field terminal. If the diagnostic unit fails the diagnosis, the control unit requests the expert terminal to receive the expert diagnosis data and receive the expert diagnosis data. Further, the control unit may receive additional state data of the field facility from the field terminal and transmit the additional state data to the expert terminal. Since there is a possibility that an abnormal condition which is difficult to be judged by only the current state data exists, it is possible to transmit all the state data of the current field facility for accurate diagnosis by the expert.
When the expert diagnostic data by the expert terminal is input, the control unit transmits the expert diagnostic data to the field terminal. The field terminal takes the expert diagnosis data as priority and proceeds to repair the fault of the field facility.
In addition, the control unit can update the database with the diagnosis-failed data in correspondence with the diagnostic data. Since the failed state data is data that does not exist in the conventional database, the database is updated by associating the failed diagnosis state data with the expert diagnosis data. If the same status data as that of the failed diagnostic status data is received from the field terminal of the field facility in the future, it is possible to transmit the already stored expert diagnostic data to the field terminal for further troubleshooting without any additional expert diagnosis. Therefore, the diagnostic performance of the case-based diagnosis system and the case-based diagnosis server can be efficiently improved.
The expert terminal generates the expert diagnosis data according to the state data, transmits it to the case based diagnosis server, and updates the database. Expert terminal can be used when requesting help from external experts for diagnosis of field facility in case case of diagnosis failure of case-based diagnosis server. Expert can check status data And then generate the expert diagnosis data.
The diagnosis rule-based diagnosis system and the case-based diagnosis system of FIGS. 1 and 2 can be used through independent diagnosis procedures. However, even if an abnormal condition occurs in the field facility, It is necessary to implement a system and a database that are updated and used. Therefore, it is possible to organically link the rule-based and signal-based complex diagnosis procedure with the vibration case collection and diagnosis procedure, and to construct a concrete implementation method of integrated diagnosis system and database based on rule-based and case-based upload and download of each data.
Therefore, the rule-based diagnosis system and the case-based diagnosis system can be implemented by separately building each database and allowing the two to independently perform diagnostic procedures. However, if integrated diagnosis of on-site facilities and integrated diagnosis database are established, there is an advantage that the combined rules and signal-based complex diagnosis procedures and vibration case collection and diagnosis procedures are organically linked and the mutual data can be used flexibly, Based diagnosis apparatus and the case-based diagnosis apparatus can be integrated into a single diagnosis system by sharing rule data and algorithms with each other. A detailed description thereof will be given with reference to FIG.
3 is a block diagram showing a rule-based and case-based integrated diagnosis system and database of the present invention.
Referring to FIG. 3, the rules and the case-based integrated diagnosis system of the present invention may include a rule-based
In particular, in the integrated diagnostic system of the present invention, the state data of the field facility may be state data measured at at least two parts of the field facility. If the field facility is a sufficiently complex machine, it may be difficult to diagnose sufficiently by the state data measured in one part. Therefore, the accuracy of the diagnosis can be improved by diagnosing based on the state data measured in various parts.
In addition, it is possible to measure various state data of an on-site facility, measure several pieces of state data for one on-site facility, and simultaneously measure status data for various on-site facilities.
For example, it is possible to divide the compressor (part A), the combustor (part B), and the turbine (part C) of the gas turbine and measure the status data for each part. Various state data such as the current rotational state of the compressor and the amount of output, the temperature and pressure state of the combustor, the number of revolutions of the turbine, and the torque value can all be collected and transmitted to the diagnosis system. In addition, state data of various on-site facilities such as the first gas turbine, the second gas turbine, the first motor, the second motor, and the like can be measured and transmitted to the diagnosis system at once.
The state data of the field facility may be vibration state data of the rotating body. The failure of the equipment can be caused by a change in output, an abnormal temperature rise, and noise and vibration, so that the abnormality of the equipment is mostly caused by vibration. Since this change occurs before the facility is completely shut down, it may be possible to measure the vibration condition of the facility and diagnose it without disassembling or disrupting the facility. Therefore, it is possible to manage the facility by performing the vibration diagnosis using the vibration measurement, and it is possible to generate various effects such as improvement of the operation rate, ease of parts management, and reduction of defects.
For example, vibration caused by unbalance caused by the eccentricity of the rotating body, unbalance caused by scattering of the rotating body, rubbing caused by changing the equilibrium and dynamic stiffness by physical contact between the rotating part and the fixing part , Unstable vibration due to fluid vibration due to self-excited vibrations such as oil wheels, vibrations due to cracks due to improper placement of stress concentration elements in design, alignment caused by poor alignment of turbine, generator and exciter It is possible to receive various vibration state data such as vibration caused by defects.
The rule-based
In the case of rule-based diagnosis, it is possible to diagnose by the general diagnosis rule even if there is no accumulated fault signal, and it is possible to build a signal-based database with high diagnosis rate as the fault signal data accumulates. In particular, the rule-based diagnostics gathers state data of the field facility while monitoring in real-time whether the field facility is operating normally. Therefore, the rule-based diagnosis device extracts various functions such as rms value, pressure or temperature value after measuring the signal of the field facility, detects abnormal behavior of the present field facility, and stores it in the normal signal database if it is determined as normal signal data.
In addition, rule based diagnostics can classify abnormal signal data by diagnostic rule based diagnosis. In this case, the diagnosis rule is a general diagnosis rule, and it is a rule that can be discriminated according to the abnormal state mode. For example, in the case of a rotating body, it can be discriminated by the abnormal state mode based on the amplitude and phase of the harmonic component of the number of revolutions. Through these rules, diagnosis is possible even in the absence of abnormal state data.
In addition, the rule-based diagnostic apparatus can collect various abnormal signals through K-mean clustering, classify them into fault types according to general diagnosis rules, and store them in the abnormal signal database. For example, the rule-based diagnostics can be used to determine whether the gas turbine on-site is in the A failure mode when the gas turbine has a value, B failure mode when the b value is present, or C failure mode when the gas turbine has the c value. . Therefore, if the rule-based diagnostic apparatus has a value of b as a measurement for the gas turbine, data for confirming the B failure mode is extracted from the abnormal signal database.
In addition, the rule-based diagnostic device can be analyzed by a specialist. Even if there are several failure modes, if an unknown failure mode occurs, the expert can check the cause of the failure.
In addition, rule based diagnostics can be diagnosed based on the SVM model. If multiple values are clustered and A, B, and C fault modes are broken down, and new values for field installations not located in the respective boundaries appear, Mode.
The case-based
A signal is measured from the field facility, and facility state information including all of the various conditions can be collected by the case-based diagnostic device as case data. The case-based diagnostic apparatus confirms whether the case data is present in the case database, and if there is existing case data, it is determined that the diagnosis is successful and the diagnosis is performed.
If the state data currently entered in the case database does not exist, it is determined that the diagnosis of the corresponding state data has failed and the diagnosis is made according to the general diagnosis rule. In this case, the general diagnosis rule is the same as the diagnostic rule of the rule-based diagnostic apparatus described above, and refers to a rule that can be determined for each abnormal state mode. Through these rules, it is possible to diagnose abnormal state data even in the absence of case data.
In addition, the case-based diagnostic device can transmit the status data and case data of the current field facility to the expert terminal, and receive the expert diagnostic data from the expert. The expert can analyze the cause of the on-site facility in the abnormal state, and generate the diagnostic rule as a solution to the problem. When an expert diagnostic rule is received, the case based diagnostic device stores the expert diagnostic rule in the diagnostic rule database and updates it for future use.
The
In particular, the integrated diagnosis database of the present invention is divided into various databases storing various data, so that the rule-based diagnosis device and the case-based diagnosis device can simultaneously upload or download data, and if necessary, can do.
First, the integrated diagnostic database can be used for diagnostic methods using real-time monitoring of rule-based diagnostic devices.
The steady
In addition, the normal signal database can collect and store the steady state data in real time while the normal operation of the field facility is proceeded. In general, the facility is much longer than the period of operating in the steady state, which is longer than the period of operating in the unsteady state, so that the facility is in its normal state, You can quickly check whether or not it is.
The diagnostic rule database 430 stores diagnostic rules for classifying the abnormal state of input state data used in the rule-based diagnostic apparatus. As described above, it is possible to classify abnormal status data as abnormal status through a general diagnosis rule.
At this time, the diagnostic rule database can transmit the diagnostic rule to the rule-based diagnostic device when the rule-based diagnostic device classifies the abnormal status data according to the diagnostic rule. Therefore, since the rule-based diagnostic apparatus can be uploaded or downloaded in real time with the diagnosis rule database, the updated expert diagnosis rule can be immediately applied by the case-based diagnosis apparatus.
The
At this time, the abnormal signal database may classify the abnormal state data according to the fault type, and store the classified abnormal state data. The abnormal vibration that can be generated in the diagnostic equipment (rotating body) may cause various abnormal vibrations such as unbalance, rubbing, misalignment, and the like. To be stored in the abnormal signal database.
The
More specifically, when a new value of the field facility not located within each boundary appears when a plurality of values are clustered and divided into A failure mode, B failure mode, and C failure mode, respectively, Through the diagnostic model, it can be determined which fault mode this value is located in. The SVM model can be used as the most efficient model among these diagnostic models.
On the other hand, the integrated diagnostic database can be used for diagnostic methods using trouble shooting of case-based diagnostic devices.
The
In addition, when the case-based diagnosis apparatus diagnoses input state data, the case database determines whether or not case data matching the state data exists and diagnoses. For example, if received status data indicates that the status data is present in the case database when the temperature of the gas turbine has risen to 1100 ° C and the compressor operating power receives 40% of the turbine generation output. If the case database contains diagnostic data for the gas turbine temperature and the output relative to the output, the case-based diagnostics determines that the diagnostic is successful for that state data.
At this time, after the case-based diagnosis apparatus diagnoses the inputted state data based on the case data, if the diagnosis fails, the diagnosis rule for diagnosing the state data can be transmitted to the case-based diagnosis apparatus. This can be determined by judging whether or not the case data matching the state data exists and diagnosing the case where there is no case data that matches.
The abnormal condition data determined to have failed diagnosis can be diagnosed by the general diagnosis rule. In this case, if the abnormal condition data can be diagnosed by the general diagnosis rule, the case based diagnosis device takes action by the diagnosis, but if it is impossible to diagnose by the general diagnosis rule, analysis by the expert is required.
The case-based device requests the expert terminal to receive the expert diagnosis data, receives the additional state data of the field facility, and transmits it to the expert terminal. Since the expert terminal receives the on-site status data directly from the case-based diagnostic device or the on-site terminal, there is a possibility that an abnormal condition which is difficult to be judged by only the present status data exists. Therefore, Data can be transmitted.
Then, when the case-based diagnosis apparatus receives the expert diagnosis data from the expert terminal, it can be stored in the diagnosis rule database. When a diagnostic rule is created, which is a solution created by a specialist, it can be stored in the integrated diagnostic database so that it can be used not only in the case-based diagnostic device but also in the rule-based diagnostic device.
Therefore, the rules and the case-based integrated diagnosis system of the present invention can use the integrated diagnosis database together with the rule-based diagnosis device and the case-based diagnosis device. In particular, the integrated diagnosis database stores various kinds of data, and uploads data updated in real time by a rule-based diagnosis device or a case-based diagnosis device, thereby enabling quick response even in an unexpected situation.
Meanwhile, the rule-based diagnosis device, the case-based diagnosis device, and the integrated diagnosis database of the present invention may be implemented as one hardware device or as separate independent hardware devices. The normal signal database, the case database, the diagnostic rule database, and the abnormal signal database constituting the integrated diagnosis database may be implemented as one hardware device or a separate independent hardware device.
The embodiments of the present invention described above are disclosed for the purpose of illustration, and the present invention is not limited thereto. It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the invention.
110: On-site facilities
120: Field terminal
130: Case-based diagnostics
131: Case based diagnostic report
140: Conventional expert terminal
200: rule based diagnostics
210: Signal measurement
220: Function extraction
230: Abnormal behavior detection
240: Diagnostic rule-based diagnostics
250: K-mean clustering
260: Expert Analysis
270: SVM model-based diagnostics
300: Case-based diagnostics
310: Signal measurement
320: Enter equipment status information
330: Judge case data
340: Diagnostic rule-based diagnostics
350: Expert Analysis
360: Create Diagnostic Rule
400: Integrated Diagnostic Database
410: normal signal database
420: Case database
430: diagnostic rule database
440: abnormal signal database
450: SVM model database
Claims (14)
Based on the status data of the field facility in real time and judging whether it is in a normal state or an abnormal state and storing the data in the integrated diagnosis database and classifying the abnormal state data according to the diagnosis rule of the integrated diagnosis database, Device; And
Based diagnosis device for diagnosing based on case data or diagnosis rules of the integrated diagnosis database and receiving and diagnosing the expert diagnosis data when the diagnosis of the state data of the field facility fails,
Wherein the rule-based diagnostic apparatus comprises: an SVM diagnostic model of an SVM model algorithm and storing the SVM diagnostic model in the integrated diagnostic database; diagnosing the state data using the SVM diagnostic model;
Wherein the expert diagnostic data is generated as a new diagnostic rule and stored in the integrated diagnostic database for use in the rule based diagnostic device,
Here, the integrated diagnosis database may include:
A steady state signal database for storing steady state data of the field facility;
A case database for storing state data of the on-site facility as case data;
A diagnostic rule database used for the rule-based diagnostic device or the case-based diagnostic device to store diagnostic rules for classifying the abnormal state of input state data; And
An abnormality signal database for storing abnormal condition data classified according to the diagnosis rule;
And a case-based integrated diagnostic system.
The state data of the on-
And the state data measured at at least two or more parts of the field facility.
The state data of the on-
And the vibration state data of the rotating body.
The normal signal database comprises:
Based diagnostic system is used for detecting an abnormal behavior of the rule-based diagnostic apparatus.
The normal signal database comprises:
And the normal state data is collected and stored in real time while the normal operation of the field facility is being performed.
The diagnostic rule database includes:
Wherein the rule-based diagnostic device transmits the diagnostic rule to the rule-based diagnostic device when the rule-based diagnostic device classifies the abnormal condition data according to the diagnostic rule.
Wherein the abnormal signal database comprises:
Wherein the abnormal state data is classified according to a fault type and the classified abnormal state data is stored.
Wherein the abnormal signal database comprises:
And transmits the stored abnormality status data to the rule-based diagnostic apparatus when new status data is collected.
An SVM model database storing an SVM diagnostic model used when the rule-based diagnostic apparatus diagnoses input state data;
And a case-based integrated diagnostic system.
In the case database,
Wherein the diagnostic information is used for diagnosing status data of the case based diagnostic device.
In the case database,
Wherein the case-based diagnostic apparatus diagnoses inputted state data by determining whether or not there is case data consistent with the state data.
The diagnostic rule database includes:
Wherein the case-based diagnostic device diagnoses inputted state data based on the case data and then transmits a diagnosis rule for diagnosing the state data to the case-based diagnosis device when the diagnosis fails. Based integrated diagnosis system.
Wherein the case based diagnostic device receives expert diagnostic data from an expert terminal and the expert diagnostic data is generated as a new diagnostic rule and stored in the diagnostic rule database.
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| US11585732B2 (en) | 2020-01-02 | 2023-02-21 | Doosan Enerbnity Co., Ltd. | Apparatus and method for diagnosing failure of plant |
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| KR101989267B1 (en) * | 2018-01-09 | 2019-06-13 | 한국산업기술대학교산학협력단 | Method of detecting abnormal of a machine and apparatuses performing the same |
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| KR102108975B1 (en) * | 2019-10-21 | 2020-05-13 | (주) 리얼웹 | Apparatus and method for condition based maintenance support of naval ship equipment |
| US11585732B2 (en) | 2020-01-02 | 2023-02-21 | Doosan Enerbnity Co., Ltd. | Apparatus and method for diagnosing failure of plant |
| KR102296059B1 (en) * | 2020-05-21 | 2021-08-31 | (주)주인정보시스템 | Noise anomaly detection system of elevator using small data amplification algorithm |
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