CN116880395A - Monitoring method, device, equipment and medium based on DCS system - Google Patents
Monitoring method, device, equipment and medium based on DCS system Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41845—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by system universality, reconfigurability, modularity
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
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Abstract
The application relates to a monitoring method, a device, equipment and a medium based on a DCS (distributed control system), which are applied to the technical field of DCS monitoring, and the method comprises the following steps: acquiring operation data of each region in the DCS, wherein the operation data comprise data received by a sub-control module of a wind turbine generator; performing data association based on the operation data of all the areas to obtain an association result; performing front monitoring on the DCS based on the association result to obtain a front monitoring result; judging whether the DCS system has faults or not based on the front monitoring result; and if the DCS system fails, controlling the DCS system to perform early warning. The method has the effects of monitoring the DCS of the wind power plant in real time and ensuring the stable control and operation of the wind turbine generator.
Description
Technical Field
The application relates to the technical field of DCS system monitoring, in particular to a monitoring method, device, equipment and medium based on a DCS system.
Background
The DCS system is an English abbreviation of a distributed control system, is a multi-stage computer system which is composed of a process control stage and a process monitoring stage and takes a communication network as a tie, and adopts a design principle of decentralized control functions, centralized display operation, balance of division, autonomy and comprehensive coordination on the basis of a microprocessor. The DCS system is widely applied to various industries such as electric power, metallurgy, petrochemical industry and the like.
At present, in the actual operation process, the DCS system of the wind power plant is limited by computing power, the alarm value of the system or equipment parameter adopts a given value which is used for explaining the specification or operation experience, the alarm can be given only after exceeding the limit value, the parameter deviates from the normal parameter but cannot be judged when the limit alarm is not reached in the operation process of the equipment and the system, the alarm is given only when the parameter report reaches the limit, and when some alarms appear, the system or equipment can run in a sick state for a long time, so that the system or equipment is damaged.
In the actual production process, accidents such as controller damage, fan tripping, fan stall, unit tripping and the like occur in the running process of the wind turbine, manual adjustment is greatly relied on by operators, but once the accident occurs in the wind turbine, the wind turbine can be stopped to run, and loss is caused to the wind power plant, so that a monitoring method based on a DCS system is needed to monitor the controller of the wind turbine.
Disclosure of Invention
In order to monitor a DCS (distributed control system) of a wind power plant in real time and ensure stable control and operation of a wind turbine generator, the application provides a monitoring method, a device, equipment and a medium based on the DCS.
In a first aspect, the present application provides a monitoring method based on a DCS system, which adopts the following technical scheme:
a monitoring method based on a DCS system comprises the following steps:
acquiring operation data of each region in the DCS, wherein the operation data comprise data received by a sub-control module of a wind turbine generator;
performing data association based on the operation data of all the areas to obtain an association result;
performing front monitoring on the DCS based on the association result to obtain a front monitoring result;
judging whether the DCS system has faults or not based on the front monitoring result;
and if the DCS system fails, controlling the DCS system to perform early warning.
Through adopting above-mentioned technical scheme, through obtaining the operation data of each region in the DCS system, then carry out the correlation to every DCS system according to operation data, then judge the data condition in other regions through the operation data of an region respectively, carry out the front monitor to other regions, obtain the front monitor result, when judging the trouble of DCS system through the front monitor result, can early warn in advance to realize the real-time supervision to the DCS system, and then guarantee the steady operation of wind turbine generator system.
Optionally, before the acquiring the operation data of each region in the DCS system, the method further includes:
acquiring regional distribution information of a wind power plant;
dividing the area of the wind power plant based on the area distribution information to obtain a plurality of monitoring areas;
carrying out importance level division on the monitoring area to obtain a division result;
acquiring logic functions of sub-control modules of the DCS of each monitoring area based on the dividing result;
and carrying out area packing on the monitoring area based on the logic function of the sub-control module to obtain a packing area.
Optionally, the classifying the importance level of the monitoring area, and obtaining the classification result includes:
acquiring a corresponding functional area in the monitoring area, wherein the functional area comprises a power generation area, a power transformation area, a storage area and a transmission area;
obtaining the influence degree of each preset influence factor on the functional area, wherein the influence degree comprises the influenced coefficient of each preset influence factor on the functional area;
determining an importance level of each functional area based on the influence degree;
and dividing the functional area according to the importance level to obtain a division result.
Optionally, the performing data association based on the operation data of all the respective areas, and obtaining an association result includes:
performing area association on the monitoring areas based on the logic functions of the sub-control modules to obtain association areas, wherein the association areas comprise monitoring areas with the logic functions of the sub-control modules mutually affected;
acquiring basic information of all sub-control modules in the association area;
and carrying out data association on the operation data based on the basic information and the association area to obtain an association result.
Optionally, the performing the pre-monitoring on the DCS system based on the association result, and obtaining the pre-monitoring result includes:
judging whether the operation data is consistent with preset operation data or not based on the association result;
if the operation data are inconsistent with the preset operation data, determining abnormal information based on the operation data;
determining an affected proportion of all the areas based on the anomaly information and the correlation result;
sequencing the affected proportion according to a preset rule to obtain a sequencing result;
determining future anomaly data for the region based on the ranking result and the anomaly information;
and taking the future abnormal data as a front monitoring result.
Optionally, the judging whether the DCS system has a fault based on the pre-monitoring result includes:
setting a preset association threshold according to the association result;
calculating a current association value based on the pre-monitoring result;
judging whether the current association value is larger than a preset association threshold value or not;
and if the current association value is larger than a preset association threshold value, judging that the DCS system fails.
Optionally, after the judging whether the DCS system has a fault based on the pre-monitoring result, the method further includes:
acquiring all first fault information of the DCS based on big data;
establishing a fault information database based on the first fault information;
if the DCS system is judged to have faults based on the front monitoring result, the second fault information is obtained;
judging whether first fault information corresponding to the second fault information exists in the fault information database;
if the first fault information corresponding to the second fault information does not exist in the fault information database; and adding the second fault information into the fault information database to obtain a new fault information database.
In a second aspect, the present application provides a monitoring device based on a DCS system, which adopts the following technical scheme:
a DCS system-based monitoring device comprising:
the acquisition module is used for acquiring operation data of each region in the DCS, wherein the operation data comprise data received by a sub-control module of the wind turbine generator;
the association module is used for carrying out data association based on the operation data of all the areas to obtain an association result;
the prepositive monitoring module is used for carrying out prepositive monitoring on the DCS based on the association result to obtain a prepositive monitoring result;
the judging module is used for judging whether the DCS system has faults or not based on the front monitoring result; and if the DCS system fails, controlling the DCS system to perform early warning.
Through adopting above-mentioned technical scheme, through obtaining the operation data of each region in the DCS system, then carry out the correlation to every DCS system according to operation data, then judge the data condition in other regions through the operation data of an region respectively, carry out the front monitor to other regions, obtain the front monitor result, when judging the trouble of DCS system through the front monitor result, can early warn in advance to realize the real-time supervision to the DCS system, and then guarantee the steady operation of wind turbine generator system.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
an electronic device comprising a processor coupled with a memory;
the memory stores a computer program that can be loaded by a processor and that executes the DCS system-based monitoring method of any one of the first aspects.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer-readable storage medium storing a computer program capable of being loaded by a processor and executing the DCS system-based monitoring method of any one of the first aspects.
Drawings
Fig. 1 is a schematic flow chart of a monitoring method based on a DCS system according to an embodiment of the present application.
Fig. 2 is a block diagram of a monitoring device based on a DCS system according to an embodiment of the present application.
Fig. 3 is a block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the accompanying drawings.
The embodiment of the application provides a monitoring method based on a DCS (distributed control system), which can be executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be, but is not limited to, a smart phone, a tablet computer, a desktop computer, etc.
As shown in fig. 1, a monitoring method based on a DCS system is described as follows (steps S101 to S105):
step S101, operation data of each area in the DCS are obtained, wherein the operation data comprise data received by a sub-control module of the wind turbine generator.
In this embodiment, during the operation of the wind power plant, distributed control of the wind turbine is generally achieved through a sub-control module in the DCS system, and then operation data of a region corresponding to the wind turbine is obtained through the sub-control module, where the operation data is data collected by the sub-control module through the collecting device, and the operation data includes wind speed, rotational speed of the blade, and power generation current and motor temperature of the wind turbine.
Further, before acquiring the operation data of each region in the DCS system, the method further includes: acquiring regional distribution information of a wind power plant; dividing the area of the wind power plant based on the area distribution information to obtain a plurality of monitoring areas; carrying out importance level division on the monitoring area to obtain a division result; acquiring logic functions of sub-control modules of the DCS of each monitoring area based on the dividing result; and carrying out area packing on the monitoring area based on the logic function of the sub-control module to obtain a packing area.
In this embodiment, before the operation data of each region in the DCS system is obtained, each region of the wind power plant needs to be divided, different regions are packed and sorted, so as to obtain a plurality of packed regions, that is, the plurality of regions are combined, and the sub-control modules of the DCS system are monitored through the packed regions.
In a wind power plant, different functional areas such as a transmission area, a power generation area, a storage area and a power transformation area are present, wherein the areas are set as monitoring areas, each monitoring area comprises a plurality of sub-control modules of a DCS system, and logic functions of the plurality of sub-control modules of each monitoring area have a certain logic relationship; taking a power generation area as an example, the power generation area comprises control of a wind turbine generator, control of current conversion, control of a power supply, collection of a current signal and control of power generation capacity; because a plurality of sub-control modules are needed to be matched in each functional area to realize final logic control, the packaging area can be set to be a monitoring area according to the logic functions of the sub-control modules, the monitoring of all the sub-control modules in the packaging area can be realized conveniently by monitoring the logic functions of one sub-control module, so that the waste of monitoring resources is reduced, and the DCS can be monitored more conveniently.
Further, performing importance level division on the monitoring area, and obtaining a division result includes: acquiring a corresponding functional area in a monitoring area, wherein the functional area comprises a power generation area, a power transformation area, a storage area and a transmission area; acquiring the influence degree of each preset influence factor on the functional area, wherein the influence degree comprises the influenced coefficient of each preset influence factor on the functional area; determining an importance level of each functional area based on the influence degree; and dividing the functional areas according to the importance level to obtain a division result.
In this embodiment, when dividing the importance level of the monitoring area, when setting the influence factor, the importance level of each functional area needs to be determined according to the influence degree received by each functional area, for example, the influence factor includes temperature, weather, operation time, wind speed, and the like, and the influence of temperature on the storage unit and the transmission unit is large because the influence of temperature on the current and the electronic activity is large, where the influence of too low temperature on the storage unit is large and the influence of too high temperature on the transmission unit is large, and at this time, the importance level may be defined according to the time when the detected temperature value is not within the preset threshold range.
For example, in north China, the annual high-temperature weather is june to october, and the annual low-temperature weather is october to january, so that the importance level of the transmission area is highest, the importance level of the storage area is second, the importance level of the other functional areas is third, with respect to the influence factor of temperature.
In this embodiment, according to the change degree of each influence factor, the influence degree of each influence factor on the functional area is different, and a large amount of data needs to be collected at this time to establish an influence factor database, so that the importance level of each functional area is more conveniently determined.
For each influencing factor, determining the importance level of each functional area, then after determining all the importance levels according to the influence degree, integrating to finally determine the final importance level of the functional area, and taking the final importance level as a division result.
For example, the temperature is determined as the first importance level of the transmission area, but the importance level of the transmission area is the third importance level among the remaining influence factors, so the final importance level of the transmission area is the third importance level.
That is, the final importance level is determined as the importance level ratio of the functional area in each influence factor, and in particular, when the importance level of one functional area after the four influence factors are respectively judged is respectively the second importance level, the third importance level and the third importance level, the final importance level of the current functional area is judged to be the second importance level at this time.
Step S102, data association is carried out based on the operation data of all the areas, and an association result is obtained.
Specifically, performing data association based on the operation data of all the areas, and obtaining association results includes: performing area association on the monitoring area based on the logic function of the sub-control module to obtain an association area, wherein the association area comprises monitoring areas with the logic functions of the sub-control module mutually affected; basic information of all sub-control modules in the associated area is acquired; and carrying out data association on the operation data based on the basic information and the association area to obtain an association result.
In this embodiment, after the monitoring areas are divided, the areas are associated with each other to obtain associated areas, for example, a power generation area, a transmission area and a storage area, and the three areas are mutually associated areas, so that data association is required according to operation data of the associated areas at this time to obtain corresponding association results, and operation data corresponding to all sub-control modules in the associated areas can be obtained through operation data of one sub-control module by using the association results, so that monitoring of all control modules of the DCS system is more convenient.
And step S103, performing front-end monitoring on the DCS based on the association result to obtain a front-end monitoring result.
Specifically, performing front-end monitoring on the DCS based on the association result, and obtaining the front-end monitoring result includes: judging whether the operation data is consistent with preset operation data or not based on the association result; if the operation data is inconsistent with the preset operation data, determining abnormal information based on the operation data; determining the affected proportion of all areas based on the abnormal information and the association result; sequencing the affected proportion according to a preset rule to obtain a sequencing result; determining future abnormal data of the area based on the sorting result and the abnormal information; and taking the future abnormal data as a front monitoring result.
In this embodiment, after each region is associated to obtain an association result, each sub-control module of the DCS system is monitored according to the association result, when the operation data detected by one sub-control module in the associated region is inconsistent with the preset operation data, the abnormal information is determined according to the operation data, the affected proportion of the corresponding region is determined according to the abnormal information and the association result, then the future abnormal data of the associated region is determined according to the affected proportion, and when the future abnormal data occurs, the future abnormal data is used as the pre-monitor result.
For example, in a wind power generation field, the generated current at the moment is determined according to the acquired wind speed, but the generated current at the moment has an error with the preset generated current, and when the generated current is abnormal, the generated current has the most serious influence on a power transformation area, so that the power transformation area is most seriously influenced, and the influenced proportion is the largest; the influence of the generated current on the transmission region is minimal, and the affected ratio is minimal because the transmission region can be transmitted without exceeding the upper limit value regardless of the generated current.
After determining the affected proportion of the abnormal information to the association result, sequencing the affected proportion according to a preset rule, wherein the preset rule can be from big to small or from small to big; after the sequencing result is obtained, future abnormal data of each associated area are calculated according to the sequencing result and the abnormal information, so that front monitoring of the DCS is realized.
Step S104, judging whether the DCS system fails or not based on the front-end monitoring result, and if so, turning to step S105.
Specifically, judging whether the DCS system fails based on the front-end monitoring result includes: setting a preset association threshold according to the association result; calculating a current association value based on the pre-monitoring result; judging whether the current association value is larger than a preset association threshold value or not; if the current association value is larger than the preset association threshold value, judging that the DCS system fails.
In this embodiment, when it is required to determine whether a fault occurs according to the pre-monitoring result, a current association value needs to be calculated according to the pre-monitoring result, for example, when the pre-monitoring result includes that the abnormal information is abnormal in the generated current and the temperature of the transmission area is abnormal, the current association value is calculated through the affected proportion, that is, the affected proportion is arranged from large to small to be 5, 3 and 1, different affected proportions are determined through different abnormal information calculations, then the affected proportions are subjected to addition calculation to obtain a final affected proportion, that is, the current association value, then whether the current association value is greater than the preset association value is determined, when the current association value is greater than the preset association value, the fault in the association area can be determined, and then the DCS system at the moment is determined to have the fault; when the current association value is not greater than the preset association threshold, the abnormal information does not affect other association areas or does not appear, and the DCS system operates normally.
Further, after judging whether the DCS system has a fault based on the pre-monitoring result, the method further comprises: acquiring all first fault information of the DCS based on the big data; establishing a fault information database based on the first fault information; if the DCS system is judged to have faults based on the front monitoring result, second fault information is obtained; judging whether first fault information corresponding to the second fault information exists in the fault information database; if the first fault information corresponding to the second fault information does not exist in the fault information database; and adding the second fault information into the fault information database to obtain a new fault information database.
In this embodiment, after determining that a DCS system fails, it is necessary to search all first failure information of the DCS system using big data, then establish a failure information database according to the first failure information, then obtain second failure information through a failure of the current DCS system, search from the failure information database, determine whether there is first failure information identical to the second failure information in the failure information database, and when there is no first failure information identical to the second failure information in the failure information database, supplement the second failure information to the failure information database to obtain a new failure information database; when first fault information which is the same as second fault information exists in the fault information database, the first fault information is pushed to staff according to a preset processing strategy stored in the fault information database, and then the staff overhauls, so that the method is more convenient.
And step S105, controlling the DCS system to perform early warning.
In the embodiment, when the related area in the DCS system fails, the DCS system is controlled to send out alarm information, so that a worker can monitor the DCS system in time, the DCS system is protected and maintained rapidly, and the influence of the DCS system on the wind power plant is reduced.
Fig. 2 is a block diagram of a monitoring device 200 based on a DCS system according to an embodiment of the present application.
As shown in fig. 2, a DCS system-based monitoring device 200 mainly includes:
the acquisition module 201 is configured to acquire operation data of each region in the DCS system, where the operation data includes data received by the sub-control module of the wind turbine generator;
the association module 202 is configured to perform data association based on the operation data of all the areas, so as to obtain an association result;
the front monitor module 203 is configured to perform front monitor on the DCS system based on the association result, to obtain a front monitor result;
the judging module 204 is used for judging whether the DCS system has a fault or not based on the front monitoring result; and if the DCS system fails, controlling the DCS system to perform early warning.
As an optional implementation manner of this embodiment, the obtaining module 201 is further specifically configured to, before obtaining the operation data of each area in the DCS system, the method further includes: acquiring regional distribution information of a wind power plant; dividing the area of the wind power plant based on the area distribution information to obtain a plurality of monitoring areas; carrying out importance level division on the monitoring area to obtain a division result; acquiring logic functions of sub-control modules of the DCS of each monitoring area based on the dividing result; and carrying out area packing on the monitoring area based on the logic function of the sub-control module to obtain a packing area.
As an optional implementation manner of this embodiment, the obtaining module 201 is further specifically configured to perform importance level classification on the monitored area, where obtaining the classification result includes: acquiring a corresponding functional area in a monitoring area, wherein the functional area comprises a power generation area, a power transformation area, a storage area and a transmission area; acquiring the influence degree of each preset influence factor on the functional area, wherein the influence degree comprises the influenced coefficient of each preset influence factor on the functional area; determining an importance level of each functional area based on the influence degree; and dividing the functional areas according to the importance level to obtain a division result.
As an optional implementation manner of this embodiment, the obtaining module 201 is further specifically configured to perform data association based on operation data of all the respective areas, and the obtaining an association result includes: performing area association on the monitoring area based on the logic function of the sub-control module to obtain an association area, wherein the association area comprises monitoring areas with the logic functions of the sub-control module mutually affected; basic information of all sub-control modules in the associated area is acquired; and carrying out data association on the operation data based on the basic information and the association area to obtain an association result.
As an optional implementation manner of this embodiment, the pre-monitoring module 203 is further specifically configured to perform pre-monitoring on the DCS system based on the association result, where obtaining the pre-monitoring result includes: judging whether the operation data is consistent with preset operation data or not based on the association result; if the operation data is inconsistent with the preset operation data, determining abnormal information based on the operation data; determining the affected proportion of all areas based on the abnormal information and the association result; sequencing the affected proportion according to a preset rule to obtain a sequencing result; determining future abnormal data of the area based on the sorting result and the abnormal information; and taking the future abnormal data as a front monitoring result.
As an optional implementation manner of this embodiment, the determining module 204 is further specifically configured to determine, based on the pre-monitoring result, whether the DCS system fails, including: setting a preset association threshold according to the association result; calculating a current association value based on the pre-monitoring result; judging whether the current association value is larger than a preset association threshold value or not; if the current association value is larger than the preset association threshold value, judging that the DCS system fails.
As an optional implementation manner of this embodiment, the determining module 204 is further specifically configured to, after determining whether the DCS system fails based on the pre-monitoring result, further include: acquiring all first fault information of the DCS based on the big data; establishing a fault information database based on the first fault information; if the DCS system is judged to have faults based on the front monitoring result, second fault information is obtained; judging whether first fault information corresponding to the second fault information exists in the fault information database; if the first fault information corresponding to the second fault information does not exist in the fault information database; and adding the second fault information into the fault information database to obtain a new fault information database.
In one example, a module in any of the above apparatuses may be one or more integrated circuits configured to implement the above methods, for example: one or more application specific integrated circuits (application specific integratedcircuit, ASIC), or one or more digital signal processors (digital signal processor, DSP), or one or more field programmable gate arrays (field programmable gate array, FPGA), or a combination of at least two of these integrated circuit forms.
For another example, when a module in an apparatus may be implemented in the form of a scheduler of processing elements, the processing elements may be general-purpose processors, such as a central processing unit (central processing unit, CPU) or other processor that may invoke a program. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the apparatus and modules described above may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein.
Fig. 3 is a block diagram of an electronic device 300 according to an embodiment of the present application.
As shown in FIG. 3, electronic device 300 includes a processor 301 and memory 302, and may further include an information input/information output (I/O) interface 303, one or more of a communication component 304, and a communication bus 305.
The processor 301 is configured to control the overall operation of the electronic device 300, so as to complete all or part of the steps of the DCS system-based monitoring method described above; the memory 302 is used to store various types of data to support operation at the electronic device 300, which may include, for example, instructions for any application or method operating on the electronic device 300, as well as application-related data. The Memory 302 may be implemented by any type or combination of volatile or non-volatile Memory devices, such as one or more of static random access Memory (Static Random Access Memory, SRAM), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
The I/O interface 303 provides an interface between the processor 301 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 304 is used for wired or wireless communication between the electronic device 300 and other devices. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near Field Communication, NFC for short), 2G, 3G, or 4G, or a combination of one or more thereof, and accordingly the communication component 304 can include: wi-Fi part, bluetooth part, NFC part.
The electronic device 300 may be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), digital signal processors (Digital Signal Processor, abbreviated as DSP), digital signal processing devices (Digital Signal Processing Device, abbreviated as DSPD), programmable logic devices (Programmable Logic Device, abbreviated as PLD), field programmable gate arrays (Field Programmable Gate Array, abbreviated as FPGA), controllers, microcontrollers, microprocessors, or other electronic components for performing the DCS system-based monitoring methods set forth in the above embodiments.
Communication bus 305 may include a pathway to transfer information between the aforementioned components. The communication bus 305 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture ) bus, or the like. The communication bus 305 may be divided into an address bus, a data bus, a control bus, and the like.
The electronic device 300 may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), car terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like, and may also be a server, and the like.
The application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the monitoring method based on the DCS system when being executed by a processor.
The computer readable storage medium may include: a U-disk, a removable hard disk, a read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application is not limited to the specific combinations of the features described above, but also covers other embodiments which may be formed by any combination of the features described above or their equivalents without departing from the spirit of the application. Such as the above-mentioned features and the technical features having similar functions (but not limited to) applied for in the present application are replaced with each other.
Claims (10)
1. The monitoring method based on the DCS system is characterized by comprising the following steps of:
acquiring operation data of each region in the DCS, wherein the operation data comprise data received by a sub-control module of a wind turbine generator;
performing data association based on the operation data of all the areas to obtain an association result;
performing front monitoring on the DCS based on the association result to obtain a front monitoring result;
judging whether the DCS system has faults or not based on the front monitoring result;
and if the DCS system fails, controlling the DCS system to perform early warning.
2. The method of claim 1, wherein prior to the acquiring the operational data for each region in the DCS system, the method further comprises:
acquiring regional distribution information of a wind power plant;
dividing the area of the wind power plant based on the area distribution information to obtain a plurality of monitoring areas;
carrying out importance level division on the monitoring area to obtain a division result;
acquiring logic functions of sub-control modules of the DCS of each monitoring area based on the dividing result;
and carrying out area packing on the monitoring area based on the logic function of the sub-control module to obtain a packing area.
3. The method of claim 2, wherein the classifying the importance level of the monitored area includes:
acquiring a corresponding functional area in the monitoring area, wherein the functional area comprises a power generation area, a power transformation area, a storage area and a transmission area;
obtaining the influence degree of each preset influence factor on the functional area, wherein the influence degree comprises the influenced coefficient of each preset influence factor on the functional area;
determining an importance level of each functional area based on the influence degree;
and dividing the functional area according to the importance level to obtain a division result.
4. The method according to claim 2, wherein the performing data association based on the operation data of all the respective areas, and obtaining the association result includes:
performing area association on the monitoring areas based on the logic functions of the sub-control modules to obtain association areas, wherein the association areas comprise monitoring areas with the logic functions of the sub-control modules mutually affected;
acquiring basic information of all sub-control modules in the association area;
and carrying out data association on the operation data based on the basic information and the association area to obtain an association result.
5. The method of claim 1, wherein the pre-monitoring the DCS system based on the correlation result comprises:
judging whether the operation data is consistent with preset operation data or not based on the association result;
if the operation data are inconsistent with the preset operation data, determining abnormal information based on the operation data;
determining an affected proportion of all the areas based on the anomaly information and the correlation result;
sequencing the affected proportion according to a preset rule to obtain a sequencing result;
determining future anomaly data for the region based on the ranking result and the anomaly information;
and taking the future abnormal data as a front monitoring result.
6. The method of claim 1, wherein the determining whether the DCS system has failed based on the pre-monitor results comprises:
setting a preset association threshold according to the association result;
calculating a current association value based on the pre-monitoring result;
judging whether the current association value is larger than a preset association threshold value or not;
and if the current association value is larger than a preset association threshold value, judging that the DCS system fails.
7. The method of claim 1, wherein after said determining whether the DCS system has failed based on the pre-monitor results, the method further comprises:
acquiring all first fault information of the DCS based on big data;
establishing a fault information database based on the first fault information;
if the DCS system is judged to have faults based on the front monitoring result, the second fault information is obtained;
judging whether first fault information corresponding to the second fault information exists in the fault information database;
if the first fault information corresponding to the second fault information does not exist in the fault information database; and adding the second fault information into the fault information database to obtain a new fault information database.
8. Monitoring device based on DCS system, characterized by comprising:
the acquisition module is used for acquiring operation data of each region in the DCS, wherein the operation data comprise data received by a sub-control module of the wind turbine generator;
the association module is used for carrying out data association based on the operation data of all the areas to obtain an association result;
the prepositive monitoring module is used for carrying out prepositive monitoring on the DCS based on the association result to obtain a prepositive monitoring result;
the judging module is used for judging whether the DCS system has faults or not based on the front monitoring result; and if the DCS system fails, controlling the DCS system to perform early warning.
9. An electronic device comprising a processor coupled to a memory;
the processor is configured to execute a computer program stored in the memory to cause the electronic device to perform the method of any one of claims 1 to 7.
10. A computer readable storage medium comprising a computer program or instructions which, when run on a computer, cause the computer to perform the method of any of claims 1 to 7.
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