CN116599217B - Intelligent diagnosis system for power distribution network based on big data driving - Google Patents
Intelligent diagnosis system for power distribution network based on big data driving Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract
The invention relates to the field of power distribution network fault diagnosis, in particular to a power distribution network intelligent diagnosis system based on big data driving, which comprises an information acquisition unit, a power supply monitoring module and a power supply monitoring module, wherein the information acquisition unit comprises a field monitoring module for detecting equipment information of power utilization ends, and the power supply monitoring module is used for detecting the production number of current on-line target pieces in a production area of each power utilization end; the cloud platform is used for storing protection grade labels and maintenance auxiliary information of all the power utilization terminals; the analysis management unit is respectively connected with the information acquisition unit and the cloud platform, and is used for judging whether each power utilization end normally operates according to the power utilization load of each power utilization end in operation and analyzing and processing the power utilization ends in overload operation when the power utilization ends in overload operation exist; the invention combines the actual power failure condition of the power utilization end and the actual condition of the production process of the factory within the allowable range, thereby avoiding the production progress delay caused by stopping the factory production when the power failure does not influence.
Description
Technical Field
The invention relates to the field of power distribution network fault diagnosis, in particular to a power distribution network intelligent diagnosis system based on big data driving.
Background
The distribution network can be classified into an urban distribution network, a rural distribution network, a factory distribution network and the like according to the functions of a power supply area, wherein aiming at the factory distribution network, due to the progress of power electronic technology, the power utilization burden of a factory is increased increasingly due to the fact that electric equipment in the factory is increased increasingly, therefore, power supply faults in the factory need to be processed in time to ensure electric safety and normal production operation, and usually, after the electric faults happen in the factory, the faults need to be positioned and subjected to power-off inspection maintenance, but how to position the faults and how to select proper power-off inspection means according to the influence degree and production progress of the faults are the problems to be solved currently.
Chinese patent publication No. CN111864904B discloses a power distribution monitoring terminal, which includes an acquisition module, a control module and an execution module; the acquisition module is connected with the control module and is used for acquiring the transmission electric quantity of the distribution line and the consumption electric quantity of electric equipment in a factory and sending the transmission electric quantity and the consumption electric quantity to the control module; the control module is connected with the execution module and is used for inputting the transmitted electric quantity and the consumed electric quantity into the calculation model, obtaining the electric quantity relation between the transmitted electric quantity and the consumed electric quantity, judging whether the electric quantity relation meets the threshold relation range, and if not, sending a first control signal to the execution module; and the execution module is used for executing corresponding operation according to the first control signal, and the power distribution quantity and the power consumption quantity detected by the power distribution monitoring terminal are convenient for a user to know the power consumption condition. It can be seen from this that the following problems exist in the power distribution monitoring terminal: according to the electric consumption of the electric equipment in the factory, the reliability is poor, and a feasible electric fault processing scheme is generated by combining the influence degree of the electric faults and the actual working progress in the factory.
Disclosure of Invention
Therefore, the invention provides a power distribution network intelligent diagnosis system based on big data driving, which is used for overcoming the defects that in the prior art, the delay of the factory production progress and the potential safety hazard of equipment caused by the power failure processing scheme cannot be adaptively selected according to the influence degree of the electric faults of a power utilization end and the factory production progress.
In order to achieve the above object, the present invention provides an intelligent diagnosis system for a power distribution network based on big data driving, which is applied to a factory power distribution network provided with a power distribution end and a plurality of power utilization ends, wherein the power distribution end comprises a power supply bus and a standby power supply, and each power utilization end comprises a plurality of electric equipment, and the intelligent diagnosis system comprises:
the information acquisition unit is used for detecting the information of the power distribution network of the factory and comprises a field monitoring module and a power supply monitoring module,
the power supply monitoring module is connected with the power utilization end and is used for detecting equipment information of the power utilization end, and comprises actual running current of a power supply bus of the power utilization end, the number of electric equipment with the current temperature being greater than a preset temperature threshold value in the power utilization end and actual running power of the power utilization end;
the field monitoring module is arranged in a factory production area and is used for detecting the production number of the current on-line target parts in the production area of each power utilization end;
The cloud platform is connected with the information acquisition unit and used for storing protection grade labels and maintenance auxiliary information of all the power utilization terminals;
the analysis management unit is respectively connected with the information acquisition unit and the cloud platform, and is used for judging whether each power utilization end normally operates according to the power utilization load of each power utilization end in operation and analyzing and processing the power utilization ends in overload operation when the power utilization ends in overload operation exist;
the analysis management unit judges a diagnosis mode adopted for the electricity utilization end according to a comparison result of the overload time of the electricity utilization end in overload operation and the preset overload time, wherein the diagnosis mode comprises a first diagnosis mode and a second diagnosis mode;
when a first diagnosis mode is selected, the analysis management unit judges whether to power off the equipment of the power utilization end for fault detection according to the equipment operation dangerous degree of the power utilization end calculated by the information acquisition unit;
when the second diagnosis mode is selected, the analysis management unit judges the power-off waiting time of the power utilization end according to the comparison result of the current on-line target piece production number of the power utilization end and the preset rated piece number, and judges whether the preset rated piece number is regulated according to the protection grade label corresponding to the power utilization end which is in overload operation in the cloud platform;
When the power failure of the power utilization end is completed, the analysis management unit detects the comparison result of the actual running power of the current power utilization end and the preset comparison power, judges the access waiting time of the standby power supply after the power failure, and judges whether the standby power supply is accessed in a grading manner according to the duty ratio of the current power utilization end;
the maintenance auxiliary information is the dangerous degree of the electricity consumption end calculated according to the actual running current of the electricity consumption end power supply bus, the number of electric equipment with the current temperature greater than a preset temperature threshold value in the electricity consumption end and the working time of the electricity consumption end.
Further, the information acquisition unit continuously acquires the power load of each power utilization end in the power distribution network of the factory under the operation monitoring condition, and the analysis management unit judges whether the power utilization end operates normally according to the power load of each power utilization end;
if the electricity load of the electricity utilization end is in the first electricity load state, the analysis management unit judges that the electricity utilization end is normally operated;
if the electricity load of the electricity end is in the second electricity load state, the analysis management unit judges that the electricity end is normally operated;
the operation monitoring condition is that the power distribution network of the factory starts to work, and the power load of the power utilization end in the first power load state is smaller than that of the power utilization end in the second power load state.
Further, the information acquisition unit continuously monitors the overload time of the power utilization end of the overload operation under the overload monitoring condition, and the analysis management unit judges the diagnosis mode adopted for the power utilization end according to the overload time of the power utilization end;
if the overload time of the power utilization terminal is in the first overload time state, the analysis management unit judges that the diagnosis of the electric equipment of the power utilization terminal is not needed;
if the overload time of the power utilization terminal is in the second overload time state, the analysis management unit judges that a first diagnosis mode is adopted, and equipment information acquisition is carried out on electric equipment of the power utilization terminal;
if the overload time of the electricity utilization terminal is in a third overload time state, the analysis management unit judges that a second diagnosis mode is adopted, and detects the working progress information of the electricity utilization terminal;
the overload monitoring condition is that the analysis management unit judges that an overload operation power utilization end exists, the overload time of the power utilization end in the first overload time state is greater than 0 and smaller than that of the power utilization end in the second overload time state, and the overload time of the power utilization end in the second overload time state is smaller than that of the power utilization end in the third overload time state.
Further, the information acquisition unit calculates the equipment operation risk degree S of the power utilization end of overload operation under the equipment information acquisition condition, and a calculation formula of the equipment operation risk degree is as follows:
wherein, L is the actual running current of the power supply bus of the power utilization end, L0 is the preset rated current of the power utilization end, N is the number of electric equipment with the current temperature being greater than the preset working temperature in the power utilization end, N0 is the total number of the electric equipment of the power utilization end, tc is the working time of the power utilization end, tc0 is the preset healthy working time of the power utilization end, alpha 1 is a first danger degree weight coefficient, alpha 2 is a second danger degree weight coefficient, alpha 3 is a third danger degree weight coefficient, wherein, 0 is less than L0,0 is less than N0,0 is less than Q0,0 is less than alpha 1 is less than alpha 2 is less than alpha 3;
the equipment information acquisition condition is that the analysis management unit judges that equipment information acquisition of electric equipment at the power utilization end is completed by adopting a first diagnosis mode.
Further, the analysis management unit judges whether to conduct fault investigation on the equipment of the electricity utilization end according to the equipment operation risk degree of the electricity utilization end which is in overload operation under the first equipment analysis condition;
if the equipment operation dangerous level of the overload operation power utilization end is in a first dangerous level state, the analysis management unit judges that the operation of the power utilization end does not need to be stopped, and counts the dangerous level and the overload time of the power utilization end as maintenance auxiliary information; the user can obtain maintenance auxiliary information corresponding to the power utilization terminal through the cloud platform
If the equipment operation risk degree of the overload operation power utilization end is in a second risk degree state, the analysis management unit controls the power utilization end to stop operation after the detection waiting time Tg and reminds a user to carry out fault detection on the electric equipment of the power utilization end, and the risk degree of the power utilization end and the overload time are used as maintenance auxiliary information to be transmitted to the user, wherein the value of Tg is related to the difference value of the equipment operation risk degree of the overload operation power utilization end and a preset risk degree threshold value, the difference value is obtained by subtracting the equipment operation risk degree of the overload operation power utilization end from the preset risk degree threshold value, and the magnitude relation between Tg and the difference value is a linear relation;
the first equipment analysis condition is that equipment operation dangerous degree calculation of the information acquisition unit on the overload operation power utilization end is completed, equipment operation dangerous degree of the overload operation power utilization end in the first dangerous degree state is smaller than equipment operation dangerous degree of the overload operation power utilization end in the second dangerous degree state, the analysis management unit is provided with a preset minimum investigation waiting time Tgmin, if Tg is smaller than Tgmin, the analysis management unit sets the value of Tg to Tgmin, wherein Tg is smaller than Tgmin.
Further, the information acquisition unit detects the production number of the target piece on the current line of the electricity utilization end under the detection condition of the working progress information, and the analysis management unit judges the power-off waiting time of the electricity utilization end according to the production number of the target piece on the current line of the electricity utilization end;
if the production number of the target parts is in the first rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is first power-off waiting time;
if the production number of the target parts is in the second rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is the second power-off waiting time;
if the production number of the target parts is in a third rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is third power-off waiting time;
the work progress information detection condition is that the analysis management unit judges that a second diagnosis mode is adopted for an overload operation power utilization end, the production number of target pieces in a first rated piece number state is smaller than that in a second rated piece number state, the production number of target pieces in the second rated piece number state is smaller than that in a third rated piece number state, the first power-off waiting time is smaller than the second power-off waiting time, and the second power-off waiting time is smaller than the third power-off waiting time.
Further, the analysis management unit extracts a protection grade label corresponding to the overload operation power utilization end in the cloud platform under the standard regulation condition and judges whether to regulate the threshold standard of the rated number state according to the grade label of the power utilization end;
if the grade label of the electricity utilization end is a primary protection grade label, the analysis management unit judges that the preset rated number is not required to be adjusted;
if the grade label of the electricity utilization end is a secondary protection grade label, the analysis management unit judges that a first adjustment mode is used for adjusting the threshold standard of the rated number state;
if the grade label of the electricity utilization end is a three-grade protection grade label, the analysis management unit judges that a second adjustment mode is used for adjusting the threshold standard of the rated number state;
the standard adjusting condition is that when the analysis management unit judges that the power-off waiting time of the power utilization end starts according to the production number of the target parts on the current line of the power utilization end, wherein the threshold standard of the rated number state after the adjustment of the first adjusting mode is smaller than that of the rated number state after the adjustment of the second adjusting mode.
Further, the analysis management unit detects the access waiting time of the standby power supply after power failure according to the actual running power of the current power utilization terminal under the second power failure analysis condition;
If the actual running power of the current power utilization terminal is in a first running power state, the analysis management unit judges that the access waiting time length of the standby power supply is a first waiting time length;
if the actual running power of the current power utilization terminal is in the second running power state, the analysis management unit judges that the access waiting time length of the standby power supply is the second waiting time length;
if the actual running power of the current power utilization terminal is in a third running power state, the analysis management unit judges that the access waiting time length of the standby power supply is third waiting time length;
the second outage analysis condition is that the outage of the electricity consumption end is completed, the actual operation power in the first operation power state is smaller than the actual operation power in the second operation power state, the actual operation power in the second operation power state is smaller than the actual operation power in the third operation power state, the first waiting time length is smaller than the second waiting time length, and the second waiting time length is smaller than the third waiting time length.
Further, the analysis management unit judges whether the standby power supply is connected in a grading manner according to the current power-off power utilization end duty ratio P under a third power-off analysis condition, and sets P=Nu/Nu 0, wherein Nu is the current power-off power utilization end number, nu0 is the total number of power utilization ends, and 0 is less than Nu0;
If the current power-off power utilization end duty ratio is in a first duty ratio state, the analysis management unit judges that the standby power supply does not need to be accessed in a grading manner, and simultaneously supplies power to all power-off power utilization ends;
if the current power-off power utilization end duty ratio is in the second duty ratio state, the analysis management unit judges that the standby power supply is connected in a grading manner, namely the analysis management unit sequentially detects the current on-line target piece production number of each power utilization end and sequentially supplies power to the corresponding power utilization ends in a sequence from large to small;
the third power-off analysis condition is that power-off of each power-on end needing power-off is completed, the power-off duration reaches the access waiting duration, and the power-on end duty ratio of the current power-off in the first duty ratio state is smaller than the power-on end duty ratio of the current power-off in the second duty ratio state.
Further, the analysis management unit controls the standby power supply to supply power to the power utilization end under the secondary detection condition, detects the equipment operation dangerous degree S of the power utilization end when the operation time of the power utilization end reaches the preset secondary detection time, and compares the S with the preset secondary detection dangerous degree S0 to judge whether the power utilization end is in fault, wherein 0 is less than S0;
if S is less than or equal to S0, the analysis management unit judges that the power utilization end is not faulty and sends out reminding information for checking the power distribution end to a user;
If S0 is less than S, the analysis management unit judges the fault of the power utilization end;
when S0 is less than S, the analysis management unit stops the power supply of the power utilization end when the current production number of the on-line target parts of the power utilization end is 0.
Compared with the prior art, the method has the advantages that the diagnosis mode of the power utilization end aiming at overload operation is judged according to the overload operation time of the power utilization end, because the actual working environment of a factory is considered, when the power utilization end is overloaded for a short time, the power utilization end is not processed in real time to avoid influencing factory production, the analysis management unit judges that the operation of the power utilization end is not needed to be stopped when the equipment operation dangerous degree of the power utilization end is smaller than a preset threshold value, the dangerous degree and the overload time of the power utilization end are recorded as maintenance auxiliary information, and the analysis management unit judges the power failure waiting time of the power utilization end according to the current on-line target piece production number of the power utilization end, so that the method is more suitable for large-scale factory application, avoids influencing the factory operation in the allowable range of the power utilization end.
Further, the invention has the beneficial effects that the analysis management unit controls the electricity utilization terminal to stop running after the checking waiting time and reminds a user to perform fault checking on the electric equipment of the electricity utilization terminal, wherein the checking waiting time is related to the running dangerous degree of the equipment, the actual power failure condition of the equipment is combined with the factory production, and the delay of the production progress caused by stopping the production halfway is reduced.
Further, the invention has the beneficial effects that the analysis management unit judges the power-off waiting time of the power-on end according to the current production number of the target piece on the line of the power-on end, and the power-off waiting time is set to avoid the delay of the production progress caused by the power-off waiting time because the electric equipment is checked by power-off, but the scrapping phenomenon exists after the production of the workpiece in some production processes is stopped.
Further, the method has the beneficial effects that the analysis management unit extracts the protection grade label corresponding to the power utilization end of overload operation in the cloud platform under the standard regulation condition, judges whether to regulate the preset rated number according to the grade label of the power utilization end, and sets different protection grade labels aiming at the power utilization ends with different responsibilities or different production capacities in consideration of the influence of the production progress and the power failure, so that the preset standard is more in accordance with the actual application, and the applicability of the method is improved.
Further, the invention has the beneficial effects that the analysis management unit judges the access waiting time length of the standby power supply after the power is off according to the actual running power of the current power utilization end under the second power-off analysis condition, and the access waiting time length is set to avoid secondary faults of the equipment because the original current is easy to exist in the equipment after the equipment is off.
Further, the invention has the beneficial effects that the analysis management unit controls the standby power supply to supply power to the power utilization end under the secondary detection condition, detects the equipment operation dangerous degree S of the power utilization end when the operation time of the power utilization end reaches the preset secondary detection time, compares the S with the preset secondary detection dangerous degree S0 to judge whether the power utilization end is in fault, and can reflect whether the power utilization end still has a problem through secondary detection due to the fact that the staff may have a detection loophole during power failure detection.
Drawings
FIG. 1 is a connection relation diagram of a distribution network intelligent diagnosis system based on big data driving according to an embodiment of the invention;
fig. 2 is a schematic diagram of a power distribution network according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1 to 2, the invention provides an intelligent diagnosis system for a power distribution network based on big data driving, which is applied to a factory power distribution network provided with a power distribution end and a plurality of power utilization ends, wherein the power distribution end comprises a power supply bus and a standby power supply, and each power utilization end comprises a plurality of electric equipment, and the intelligent diagnosis system comprises:
the information acquisition unit is used for detecting the information of the power distribution network of the factory and comprises a field monitoring module and a power supply monitoring module,
the power supply monitoring module is connected with the power utilization end and is used for detecting equipment information of the power utilization end, and comprises actual running current of a power supply bus of the power utilization end, the number of electric equipment with the current temperature being greater than a preset temperature threshold value in the power utilization end and actual running power of the power utilization end;
the field monitoring module is arranged in a factory production area and is used for detecting the production number of the current on-line target parts in the production area of each power utilization end;
the cloud platform is connected with the information acquisition unit and used for storing protection grade labels and maintenance auxiliary information of all the power utilization terminals;
the analysis management unit is respectively connected with the information acquisition unit and the cloud platform, and is used for judging whether each power utilization end normally operates according to the power utilization load of each power utilization end in operation and analyzing and processing the power utilization ends in overload operation when the power utilization ends in overload operation exist;
The analysis management unit judges a diagnosis mode adopted for the electricity utilization end according to a comparison result of the overload time of the electricity utilization end in overload operation and the preset overload time, wherein the diagnosis mode comprises a first diagnosis mode and a second diagnosis mode;
when a first diagnosis mode is selected, the analysis management unit judges whether to power off the equipment of the power utilization end for fault detection according to the equipment operation dangerous degree of the power utilization end calculated by the information acquisition unit;
when the second diagnosis mode is selected, the analysis management unit judges the power-off waiting time of the power utilization end according to the comparison result of the current on-line target piece production number of the power utilization end and the preset rated piece number, and judges whether the preset rated piece number is regulated according to the protection grade label corresponding to the power utilization end which is in overload operation in the cloud platform;
when the power failure of the power utilization end is completed, the analysis management unit detects the comparison result of the actual running power of the current power utilization end and the preset comparison power, judges the access waiting time of the standby power supply after the power failure, and judges whether the standby power supply is accessed in a grading manner according to the duty ratio of the current power utilization end;
the maintenance auxiliary information is the dangerous degree of the electricity consumption end calculated according to the actual running current of the electricity consumption end power supply bus, the number of electric equipment with the current temperature greater than a preset temperature threshold value in the electricity consumption end and the working time of the electricity consumption end.
Specifically, the information acquisition unit continuously acquires the power load of each power utilization end in the power distribution network of the factory under the operation monitoring condition, and the analysis management unit judges whether the power utilization end operates normally according to the power load of each power utilization end;
if the electricity load of the electricity utilization end is in the first electricity load state, the analysis management unit judges that the electricity utilization end is normally operated;
if the electricity load of the electricity end is in the second electricity load state, the analysis management unit judges that the electricity end is normally operated;
the operation monitoring condition is that the power distribution network of the factory starts to work, and the power load of the power utilization end in the first power load state is smaller than that of the power utilization end in the second power load state.
As an implementation manner, the above determination process may be converted into: the information acquisition unit continuously acquires the power utilization load of each power utilization end in the power distribution network of the factory under the operation monitoring condition, the analysis management unit respectively compares the power utilization load Wi of the ith power utilization end with the corresponding preset power utilization load standard of the ith power utilization end to judge whether the ith power utilization end operates normally or not, the analysis management unit is provided with the preset power utilization load standard W0i of the ith power utilization end, W0i is less than 0i, i=1, 2,3, … … and n, wherein n is the total number of the power utilization ends, and n is less than n;
If Wi is less than or equal to W0i, the analysis management unit judges that the ith power utilization end is normally operated;
if Wi is larger than W0i, the analysis management unit judges that the ith power utilization terminal is in overload operation and monitors overload time.
The preset power load standard is related to the scale of a factory powered by an actual power distribution network and specific rated working parameters of electric equipment, and a worker can determine the value range of the power load which does not affect the stable power supply by combining the experience of the worker with the specific rated working parameters of each electric equipment, and select the value of the preset power load standard in the value range according to the requirement on the power supply safety.
Specifically, the information acquisition unit continuously monitors the overload time of the power utilization end of the overload operation under the overload monitoring condition, and the analysis management unit judges the diagnosis mode adopted for the power utilization end according to the overload time of the power utilization end;
if the overload time of the power utilization terminal is in the first overload time state, the analysis management unit judges that the diagnosis of the electric equipment of the power utilization terminal is not needed;
if the overload time of the power utilization terminal is in the second overload time state, the analysis management unit judges that a first diagnosis mode is adopted, and equipment information acquisition is carried out on electric equipment of the power utilization terminal;
If the overload time of the electricity utilization terminal is in a third overload time state, the analysis management unit judges that a second diagnosis mode is adopted, and detects the working progress information of the electricity utilization terminal;
the overload monitoring condition is that the analysis management unit judges that an overload operation power utilization end exists, the overload time of the power utilization end in the first overload time state is greater than 0 and smaller than that of the power utilization end in the second overload time state, and the overload time of the power utilization end in the second overload time state is smaller than that of the power utilization end in the third overload time state.
As an implementation manner, the above determination process may be converted into: the information acquisition unit continuously monitors the overload time T of the power utilization end of overload operation under the overload monitoring condition, the analysis management unit compares the T with the preset overload time to judge the diagnosis mode adopted for the power utilization end, and the analysis management unit is provided with a first preset overload time T1 and a second preset overload time T2, wherein, 0 is more than T1 and less than T2;
if T is less than or equal to T1, the analysis management unit judges that information acquisition is not required to be carried out on the electric equipment at the power utilization end;
if T1 is more than T and less than or equal to T2, the analysis management unit judges that a first diagnosis mode is adopted, and equipment information acquisition is carried out on electric equipment of the power utilization end;
If T2 is less than T, the analysis management unit judges that a second diagnosis mode is adopted, and the work progress information of the power utilization terminal is detected;
the preset overload time is related to the maintenance times and the service life of the electric equipment at the electric end, the electric equipment can not be influenced by short-time overload operation for the electric equipment with shorter operation time in a factory, and the possibility of causing power failure for the electric equipment with longer operation time in the factory is higher, so that a user can determine the preset overload time according to the maintenance times of the electric equipment at the electric end and the operation time in the factory and the working experience of the user.
Specifically, the information acquisition unit calculates the equipment operation risk degree S of the overload operation power utilization terminal under the equipment information acquisition condition, and a calculation formula of the equipment operation risk degree is as follows:
wherein, L is the actual running current of the power supply bus of the power utilization end, L0 is the preset rated current of the power utilization end, N is the number of electric equipment with the current temperature being greater than the preset working temperature in the power utilization end, N0 is the total number of the electric equipment of the power utilization end, tc is the working time of the power utilization end, tc0 is the preset healthy working time of the power utilization end, alpha 1 is a first danger degree weight coefficient, alpha 2 is a second danger degree weight coefficient, alpha 3 is a third danger degree weight coefficient, wherein, 0 is less than L0,0 is less than N0,0 is less than Q0,0 is less than alpha 1 is less than alpha 2 is less than alpha 3;
As an embodiment, a value of the risk level weight coefficient is provided, α1=0.2, α2=0.3, α3=0.5, and it is noted that the user can determine the value of the risk level weight coefficient according to the actual plant working condition and the service life of the equipment.
The equipment information acquisition condition is that the analysis management unit judges that equipment information acquisition of electric equipment at the power utilization end is completed by adopting a first diagnosis mode.
The analysis management unit judges whether to conduct fault investigation on the equipment of the electricity utilization end according to the equipment operation risk degree of the electricity utilization end which is in overload operation under the first equipment analysis condition;
if the equipment operation dangerous level of the overload operation power utilization end is in a first dangerous level state, the analysis management unit judges that the operation of the power utilization end does not need to be stopped, and counts the dangerous level and the overload time of the power utilization end as maintenance auxiliary information; the user can obtain maintenance auxiliary information corresponding to the power utilization terminal through the cloud platform
If the equipment operation risk degree of the overload operation power utilization end is in a second risk degree state, the analysis management unit controls the power utilization end to stop operation after the detection waiting time Tg and reminds a user to carry out fault detection on the electric equipment of the power utilization end, and the risk degree of the power utilization end and the overload time are used as maintenance auxiliary information to be transmitted to the user, wherein the value of Tg is related to the difference value of the equipment operation risk degree of the overload operation power utilization end and a preset risk degree threshold value, the difference value is obtained by subtracting the equipment operation risk degree of the overload operation power utilization end from the preset risk degree threshold value, and the magnitude relation between Tg and the difference value is a linear relation;
The first equipment analysis condition is that equipment operation dangerous degree calculation of the information acquisition unit on the overload operation power utilization end is completed, equipment operation dangerous degree of the overload operation power utilization end in the first dangerous degree state is smaller than equipment operation dangerous degree of the overload operation power utilization end in the second dangerous degree state, the analysis management unit is provided with a preset minimum investigation waiting time Tgmin, if Tg is smaller than Tgmin, the analysis management unit sets the value of Tg to Tgmin, wherein Tg is smaller than Tgmin.
As an implementation manner, the above determination process may be converted into: the analysis management unit compares the equipment operation risk degree S of the overload operation power utilization end with a preset risk degree standard under a first equipment analysis condition to judge whether to perform fault investigation on the equipment of the power utilization end, wherein the analysis management unit is provided with the preset operation risk degree S1, and the operation risk degree S is more than 0 and less than S1;
if S is less than or equal to S1, the analysis management unit judges that the operation of the electricity utilization end does not need to be stopped, and counts the dangerous degree and overload time of the electricity utilization end as maintenance auxiliary information; the user can acquire maintenance auxiliary information corresponding to the power utilization end through the cloud platform;
If S1 is less than S, the analysis management unit controls the power utilization terminal to stop running after the checking waiting time Tg and reminds a user to perform fault checking on electric equipment of the power utilization terminal, and transmits the dangerous degree and overload time of the power utilization terminal as maintenance auxiliary information to the user, and tg=tg 0- (S-S1) x ζ is set, wherein ζ is a checking time conversion coefficient, and 0 < ζ;
the first equipment analysis condition is that the information acquisition unit calculates the equipment operation risk degree of the overload operation power utilization end, tg0 is preset checking waiting time, tg0 is smaller than Tg0, the analysis management unit is provided with preset minimum checking waiting time Tgmin, and if Tg is smaller than Tgmin, the analysis management unit sets the value of Tg to Tgmin, wherein Tg is larger than 0 and smaller than Tg0.
The preset dangerous degree standard is related to actual running current of a power supply bus of the power utilization end in a safe running state, the number of electric equipment with the temperature higher than a preset working temperature in the power utilization end and the working time of the power utilization end, and a user can record previous work and master equipment parameters to determine the value of the preset dangerous degree standard in the safe running state, wherein the electric equipment under the maximum value of the preset dangerous degree standard cannot meet the electric running standard.
Specifically, the information acquisition unit detects the production number of target pieces on the current line of the electricity utilization end under the detection condition of the working progress information, and the analysis management unit judges the power-off waiting time of the electricity utilization end according to the production number of the target pieces on the current line of the electricity utilization end;
if the production number of the target parts is in the first rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is first power-off waiting time;
if the production number of the target parts is in the second rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is the second power-off waiting time;
if the production number of the target parts is in a third rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is third power-off waiting time;
the work progress information detection condition is that the analysis management unit judges that a second diagnosis mode is adopted for an overload operation power utilization end, the production number of target pieces in a first rated piece number state is smaller than that in a second rated piece number state, the production number of target pieces in the second rated piece number state is smaller than that in a third rated piece number state, the first power-off waiting time is smaller than the second power-off waiting time, and the second power-off waiting time is smaller than the third power-off waiting time.
As an implementation manner, the above determination process may be converted into: the information acquisition unit detects the production number M of target parts on the current line of the electricity utilization end under the detection condition of the working progress information, the analysis management unit compares the M with the preset rated number to judge the power-off waiting time of the electricity utilization end, and the analysis management unit is provided with a first preset rated number M1, a second preset rated number M2, a preset power-off waiting time reference value Td0, a first preset time adjustment coefficient gamma 1 and a second preset time adjustment coefficient gamma 2, wherein M1 is more than 0 and less than M2, td0 is more than 0 and less than Tgmin, and gamma 1 is more than 0 and less than 1 and less than gamma 2;
if M is less than or equal to M1, the analysis management unit determines that the power-off waiting time of the power utilization terminal is Td, and sets td=td0×γ1;
if M1 is greater than M and less than or equal to M2, the analysis management unit determines that the power-off waiting time of the power utilization terminal is Td, and sets td=td0;
if M2 is less than M, the analysis management unit determines that the power-off waiting time of the power end is Td, and sets td=td0×γ2;
the value of the preset rated number is related to the factory scale of power supply of the power distribution network, and a worker can set the value of the preset rated number according to the production scale corresponding to each power utilization end, wherein the first preset rated number is the number of workpieces in the production process on the power utilization end line under the normal working condition.
Specifically, the analysis management unit extracts a protection grade label corresponding to an overload operation power utilization end in the cloud platform under a standard regulation condition and judges whether to regulate a threshold standard of a rated number state according to the grade label of the power utilization end;
if the grade label of the electricity utilization end is a primary protection grade label, the analysis management unit judges that the preset rated number is not required to be adjusted;
if the grade label of the electricity utilization end is a secondary protection grade label, the analysis management unit judges that a first adjustment mode is used for adjusting the threshold standard of the rated number state;
if the grade label of the electricity utilization end is a three-grade protection grade label, the analysis management unit judges that a second adjustment mode is used for adjusting the threshold standard of the rated number state;
the standard adjusting condition is that when the analysis management unit judges that the power-off waiting time of the power utilization end starts according to the production number of the target parts on the current line of the power utilization end, wherein the threshold standard of the rated number state after the adjustment of the first adjusting mode is smaller than that of the rated number state after the adjustment of the second adjusting mode.
As an implementation manner, the above determination process may be converted into: the analysis management unit extracts a protection grade label corresponding to an overload operation power utilization end in the cloud platform under standard adjustment conditions, judges whether the preset rated number is adjusted according to the grade label of the power utilization end, and is provided with a first preset standard adjustment coefficient beta 1 and a second preset standard adjustment coefficient beta 2, wherein 0 < beta 2 < beta 1 < 1;
If the grade label of the electricity utilization end is a primary protection grade label, the analysis management unit judges that the preset rated number is not required to be adjusted;
if the grade label of the electricity end is a secondary protection grade label, the analysis management unit judges that the preset rated number is regulated, and the regulated first preset rated number is set to be M1 'and the regulated second preset rated number is set to be M2', wherein M1 '=M1×β1, and M2' =M2×β1;
if the grade label of the electricity end is a three-grade protection grade label, the analysis management unit judges that the preset rated number is regulated, and the regulated first preset rated number is set to be M1 'and the regulated second preset rated number is set to be M2', wherein M1 '=M1×β2, and M2' =M2×β2;
wherein M1 'and M2' are integers rounded up.
The protection grade label represents the importance degree of the corresponding electricity utilization end, namely, a user can determine the protection grade label according to the economical efficiency of production pieces of all the electricity utilization ends, the production scale of the electricity utilization ends and the number of electric equipment of the electricity utilization ends, wherein the importance degree of the primary protection grade label is smaller than that of the secondary protection grade label, and the importance degree of the secondary protection grade label is smaller than that of the three protection grade labels.
Specifically, the analysis management unit detects the access waiting time of the standby power supply after power failure according to the actual running power of the current power utilization terminal under the second power failure analysis condition;
if the actual running power of the current power utilization terminal is in a first running power state, the analysis management unit judges that the access waiting time length of the standby power supply is a first waiting time length;
if the actual running power of the current power utilization terminal is in the second running power state, the analysis management unit judges that the access waiting time length of the standby power supply is the second waiting time length;
if the actual running power of the current power utilization terminal is in a third running power state, the analysis management unit judges that the access waiting time length of the standby power supply is third waiting time length;
the power load is a working parameter of a power supply bus of the power utilization terminal, the actual running power of the current power utilization terminal is an average value of running power of each electric equipment of the current power utilization terminal, and it is worth noting that a worker can exclude the electric equipment with non-production functions from a monitoring range according to the actual condition of the electric equipment.
The second outage analysis condition is that the outage of the electricity consumption end is completed, the actual operation power in the first operation power state is smaller than the actual operation power in the second operation power state, the actual operation power in the second operation power state is smaller than the actual operation power in the third operation power state, the first waiting time length is smaller than the second waiting time length, and the second waiting time length is smaller than the third waiting time length.
As an implementation manner, the above determination process may be converted into: the analysis management unit detects the comparison result of the actual running power Q of the current power utilization terminal and the preset comparison power under the second power-off analysis condition, judges the access waiting time length of the standby power supply after power off, the analysis management unit is provided with a first preset comparison power Q1, a second preset comparison power Q2, a preset access waiting time length reference value Tb0, a first access time length adjustment coefficient epsilon 1 and a second access time length adjustment coefficient epsilon 2,
if Q is less than or equal to Q1, the analysis management unit determines that the access waiting time of the standby power supply is Tb, and sets tb=tb0×epsilon 1;
if Q1 is smaller than Q and smaller than or equal to Q2, the analysis management unit determines that the access waiting time of the standby power supply is Tb, and tb=tb0 is set;
if Q2 is less than Q, the analysis management unit determines that the access waiting time of the standby power supply is Tb, and sets tb=tb0×epsilon 2;
and the preset comparison power and the preset access waiting time reference value are related to the average value of the power of the electric equipment in the electric end, and the user determines the preset access waiting time reference value according to the average value and the past working experience.
Specifically, the analysis management unit determines whether the standby power supply is connected in a classified manner according to the current power-off power utilization end duty ratio P under a third power-off analysis condition, and sets P=Nu/Nu 0, wherein Nu is the current power-off power utilization end number, nu0 is the total number of power utilization ends, and 0 is less than Nu0;
If the current power-off power utilization end duty ratio is in a first duty ratio state, the analysis management unit judges that the standby power supply does not need to be accessed in a grading manner, and simultaneously supplies power to all power-off power utilization ends;
if the current power-off power utilization end duty ratio is in the second duty ratio state, the analysis management unit judges that the standby power supply is connected in a grading manner, namely the analysis management unit sequentially detects the current on-line target piece production number of each power utilization end and sequentially supplies power to the corresponding power utilization ends in a sequence from large to small;
the third power-off analysis condition is that power-off of each power-on end needing power-off is completed, the power-off duration reaches the access waiting duration, and the power-on end duty ratio of the current power-off in the first duty ratio state is smaller than the power-on end duty ratio of the current power-off in the second duty ratio state.
As an implementation manner, the above determination process may be converted into: the analysis management unit detects the current power-off power utilization end duty ratio P under a third power-off analysis condition, compares the P with a preset power-off duty ratio to judge whether the standby power supply is accessed in a grading manner, and sets P=Nu/Nu 0, wherein Nu is the current power-off power utilization end number, nu0 is the total number of power utilization ends, 0 is less than Nu0, and the analysis management unit is provided with a first preset power-off duty ratio P1,0 is less than P1;
If P is less than or equal to P1, the analysis management unit judges that the standby power supply does not need to be connected in a grading manner, and simultaneously supplies power to all power utilization ends which are powered off;
if P1 is less than P, the analysis management unit judges that the standby power supply is connected in a grading manner, namely the analysis management unit sequentially detects the current on-line target piece production number of each power utilization end and sequentially supplies power to the corresponding power utilization ends in a sequence from large to small;
the value of the preset power-off duty ratio is related to the total number of the power-on terminals, that is, the larger the total number of the power-on terminals is, the value of the preset power-off duty ratio can be relatively reduced, the smaller the total number of the power-on terminals is, the value of the preset power-off duty ratio can be relatively increased, but it is worth noting that the purpose of setting the preset power-off duty ratio is to reasonably allocate the standby power supply when the power-off scale is larger, so that in practice, the staff can set the value of the preset power-off duty ratio according to the actual condition of a factory.
Specifically, the analysis management unit controls the standby power supply to supply power to the power utilization end under the secondary detection condition, detects the equipment operation dangerous degree S of the power utilization end when the operation time of the power utilization end reaches the preset secondary detection time, and compares the S with the preset secondary detection dangerous degree S0 to judge whether the power utilization end is in fault, wherein 0 is less than S0;
If S is less than or equal to S0, the analysis management unit judges that the power utilization end is not faulty and sends out reminding information for checking the power distribution end to a user;
if S0 is less than S, the analysis management unit judges the fault of the power utilization end;
when S0 is less than S, the analysis management unit stops the power supply of the power utilization end when the current production number of the on-line target parts of the power utilization end is 0.
In this embodiment, the power distribution network power supply plant is a machine part manufacturing plant;
the method comprises the steps that an information acquisition unit continuously acquires electricity loads of all electricity utilization ends in a power distribution network of a factory under an operation monitoring condition, wherein the electricity utilization load W1=70 kW of a 1 st electricity utilization end is preset, the electricity utilization load standard W01=60 kW of the 1 st electricity utilization end is preset, at the moment, W1 is larger than W01, and an analysis management unit judges that the 1 st electricity utilization end is in overload operation and monitors overload time;
the overload time T=3min of the 1 st electricity utilization end, the first preset overload time T1=1min and the second preset overload time T2=2min, at this time, T2 is smaller than T, the analysis management unit judges that a second diagnosis mode is adopted, and the second diagnosis mode is adopted for the electricity utilization end;
the grade label of the electricity utilization end is a primary protection grade label, and the analysis management unit judges that the preset rated number is not required to be adjusted;
The information acquisition unit detects that the number of target parts on the current line of the 1 st power utilization end is M=10, the number of first preset rated parts M1=10 corresponding to the power utilization end, a preset power-off waiting time reference value Td0=30s, a first preset time adjustment coefficient γ1=0.8, at the moment M=M1, the analysis management unit judges that the power-off waiting time of the power utilization end is Td, and Td=30x0.8=24s;
the analysis management unit detects that the actual running power Q=55 kW of the current power utilization end, the second preset comparison power Q2=55 kW, the preset access waiting time reference value Tb0=1.5 min, at this time, Q=Q2, the analysis management unit judges that the access waiting time of the standby power supply is Tb, and Tb=1.5 min is set;
the current power-off power utilization end accounts for P=10%, the first preset power-off duty ratio accounts for P1=30%, at the moment, P is smaller than P1, the analysis management unit judges that the standby power supply does not need to be connected in a grading manner, and simultaneously, power is supplied to each power-off power utilization end;
and when the operation time of the 1 st power utilization end reaches 5min, detecting that the equipment operation dangerous degree of the power utilization end is smaller than the preset secondary detection dangerous degree, judging that the power utilization end is not failed by the analysis management unit, and sending out reminding information for checking the power distribution end to a user, wherein 5min is the preset secondary detection time.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. Big data drive-based intelligent diagnosis system of power distribution network is applied to be provided with in the mill's power distribution network of distribution end and a plurality of power consumption end, and the distribution end includes power supply bus and stand-by power supply, and each power consumption end includes a plurality of consumers, its characterized in that includes:
the information acquisition unit is used for detecting the information of the power distribution network of the factory and comprises a field monitoring module and a power supply monitoring module,
The power supply monitoring module is connected with the power utilization end and is used for detecting equipment information of the power utilization end, and comprises actual running current of a power supply bus of the power utilization end, the number of electric equipment with the current temperature being greater than a preset temperature threshold value in the power utilization end and actual running power of the power utilization end;
the field monitoring module is arranged in a factory production area and is used for detecting the production number of the current on-line target parts in the production area of each power utilization end;
the cloud platform is connected with the information acquisition unit and used for storing protection grade labels and maintenance auxiliary information of all the power utilization terminals;
the analysis management unit is respectively connected with the information acquisition unit and the cloud platform, and is used for judging whether each power utilization end normally operates according to the power utilization load of each power utilization end in operation and analyzing and processing the power utilization ends in overload operation when the power utilization ends in overload operation exist;
the analysis management unit judges a diagnosis mode adopted for the electricity utilization end according to a comparison result of the overload time of the electricity utilization end in overload operation and the preset overload time, wherein the diagnosis mode comprises a first diagnosis mode and a second diagnosis mode;
when a first diagnosis mode is selected, the analysis management unit judges whether to power off the equipment of the power utilization end for fault detection according to the equipment operation dangerous degree of the power utilization end calculated by the information acquisition unit;
When the second diagnosis mode is selected, the analysis management unit judges the power-off waiting time of the power utilization end according to the comparison result of the current on-line target piece production number of the power utilization end and the preset rated piece number, and judges whether the preset rated piece number is regulated according to the protection grade label corresponding to the power utilization end which is in overload operation in the cloud platform;
when the power failure of the power utilization end is completed, the analysis management unit detects the comparison result of the actual running power of the current power utilization end and the preset comparison power, judges the access waiting time of the standby power supply after the power failure, and judges whether the standby power supply is accessed in a grading manner according to the duty ratio of the current power utilization end;
the maintenance auxiliary information is the dangerous degree of the electricity consumption end calculated according to the actual running current of the electricity consumption end power supply bus, the number of electric equipment with the current temperature greater than a preset temperature threshold value in the electricity consumption end and the working time of the electricity consumption end.
2. The intelligent diagnosis system of the power distribution network based on big data driving according to claim 1, wherein the information acquisition unit continuously acquires the power load of each power utilization end in the power distribution network of the factory under the operation monitoring condition, and the analysis management unit judges whether the power utilization end operates normally according to the power load of each power utilization end;
If the electricity load of the electricity utilization end is in the first electricity load state, the analysis management unit judges that the electricity utilization end is normally operated;
if the electricity load of the electricity end is in the second electricity load state, the analysis management unit judges that the electricity end is normally operated;
the operation monitoring condition is that the power distribution network of the factory starts to work, and the power load of the power utilization end in the first power load state is smaller than that of the power utilization end in the second power load state.
3. The intelligent diagnosis system of the power distribution network based on big data driving according to claim 2, wherein the information acquisition unit continuously monitors the overload time of the power utilization end of the overload operation under the overload monitoring condition, and the analysis management unit judges the diagnosis mode adopted for the power utilization end according to the overload time of the power utilization end;
if the overload time of the power utilization terminal is in the first overload time state, the analysis management unit judges that the diagnosis of the electric equipment of the power utilization terminal is not needed;
if the overload time of the power utilization terminal is in the second overload time state, the analysis management unit judges that a first diagnosis mode is adopted, and equipment information acquisition is carried out on electric equipment of the power utilization terminal;
If the overload time of the electricity utilization terminal is in a third overload time state, the analysis management unit judges that a second diagnosis mode is adopted, and detects the working progress information of the electricity utilization terminal;
the overload monitoring condition is that the analysis management unit judges that an overload operation power utilization end exists, the overload time of the power utilization end in the first overload time state is greater than 0 and smaller than that of the power utilization end in the second overload time state, and the overload time of the power utilization end in the second overload time state is smaller than that of the power utilization end in the third overload time state.
4. The intelligent diagnosis system for a power distribution network based on big data driving according to claim 3, wherein the information acquisition unit calculates the equipment operation risk degree S of the power utilization terminal of overload operation under the equipment information acquisition condition, and a calculation formula of the equipment operation risk degree is as follows:
wherein, L is the actual running current of the power supply bus of the power utilization end, L0 is the preset rated current of the power utilization end, N is the number of electric equipment with the current temperature being greater than the preset working temperature in the power utilization end, N0 is the total number of the electric equipment of the power utilization end, tc is the working time of the power utilization end, tc0 is the preset healthy working time of the power utilization end, alpha 1 is a first danger degree weight coefficient, alpha 2 is a second danger degree weight coefficient, alpha 3 is a third danger degree weight coefficient, wherein, 0 is less than L0,0 is less than N0,0 is less than Q0,0 is less than alpha 1 is less than alpha 2 is less than alpha 3;
The equipment information acquisition condition is that the analysis management unit judges that equipment information acquisition of electric equipment at the power utilization end is completed by adopting a first diagnosis mode.
5. The intelligent diagnosis system of the distribution network based on big data driving according to claim 4, wherein the analysis management unit judges whether to perform fault investigation on the equipment of the electricity utilization end according to the equipment operation risk degree of the overload operation electricity utilization end under the first equipment analysis condition;
if the equipment operation dangerous level of the overload operation power utilization end is in a first dangerous level state, the analysis management unit judges that the operation of the power utilization end does not need to be stopped, and counts the dangerous level and the overload time of the power utilization end as maintenance auxiliary information; the user can obtain maintenance auxiliary information corresponding to the power utilization terminal through the cloud platform
If the equipment operation risk degree of the overload operation power utilization end is in a second risk degree state, the analysis management unit controls the power utilization end to stop operation after the detection waiting time Tg and reminds a user to carry out fault detection on the electric equipment of the power utilization end, and the risk degree of the power utilization end and the overload time are used as maintenance auxiliary information to be transmitted to the user, wherein the value of Tg is related to the difference value of the equipment operation risk degree of the overload operation power utilization end and a preset risk degree threshold value, the difference value is obtained by subtracting the equipment operation risk degree of the overload operation power utilization end from the preset risk degree threshold value, and the magnitude relation between Tg and the difference value is a linear relation;
The first equipment analysis condition is that equipment operation dangerous degree calculation of the information acquisition unit on the overload operation power utilization end is completed, equipment operation dangerous degree of the overload operation power utilization end in the first dangerous degree state is smaller than equipment operation dangerous degree of the overload operation power utilization end in the second dangerous degree state, the analysis management unit is provided with a preset minimum investigation waiting time Tgmin, if Tg is smaller than Tgmin, the analysis management unit sets the value of Tg to Tgmin, wherein Tg is smaller than Tgmin.
6. The intelligent diagnosis system of the power distribution network based on big data driving according to claim 5, wherein the information acquisition unit detects the current on-line target part production number of the power utilization terminal under the detection condition of the working progress information, and the analysis management unit judges the power-off waiting time of the power utilization terminal according to the current on-line target part production number of the power utilization terminal;
if the production number of the target parts is in the first rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is first power-off waiting time;
if the production number of the target parts is in the second rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is the second power-off waiting time;
If the production number of the target parts is in a third rated number state, the analysis management unit judges that the power-off waiting time of the power utilization end is third power-off waiting time;
the work progress information detection condition is that the analysis management unit judges that a second diagnosis mode is adopted for an overload operation power utilization end, the production number of target pieces in a first rated piece number state is smaller than that in a second rated piece number state, the production number of target pieces in the second rated piece number state is smaller than that in a third rated piece number state, the first power-off waiting time is smaller than the second power-off waiting time, and the second power-off waiting time is smaller than the third power-off waiting time.
7. The intelligent diagnosis system of the distribution network based on big data driving according to claim 6, wherein the analysis management unit extracts a protection grade label corresponding to an overload operation power utilization end in the cloud platform under standard adjustment conditions and judges whether to adjust a threshold standard of a rated number state according to the grade label of the power utilization end;
if the grade label of the electricity utilization end is a primary protection grade label, the analysis management unit judges that the preset rated number is not required to be adjusted;
If the grade label of the electricity utilization end is a secondary protection grade label, the analysis management unit judges that a first adjustment mode is used for adjusting the threshold standard of the rated number state;
if the grade label of the electricity utilization end is a three-grade protection grade label, the analysis management unit judges that a second adjustment mode is used for adjusting the threshold standard of the rated number state;
the standard adjusting condition is that when the analysis management unit judges that the power-off waiting time of the power utilization end starts according to the production number of the target parts on the current line of the power utilization end, wherein the threshold standard of the rated number state after the adjustment of the first adjusting mode is smaller than that of the rated number state after the adjustment of the second adjusting mode.
8. The intelligent diagnosis system of the distribution network based on big data driving according to claim 7, wherein the analysis management unit detects the access waiting time of the standby power supply after power failure according to the actual running power of the current power utilization terminal under the second power failure analysis condition;
if the actual running power of the current power utilization terminal is in a first running power state, the analysis management unit judges that the access waiting time length of the standby power supply is a first waiting time length;
If the actual running power of the current power utilization terminal is in the second running power state, the analysis management unit judges that the access waiting time length of the standby power supply is the second waiting time length;
if the actual running power of the current power utilization terminal is in a third running power state, the analysis management unit judges that the access waiting time length of the standby power supply is third waiting time length;
the second outage analysis condition is that the outage of the electricity consumption end is completed, the actual operation power in the first operation power state is smaller than the actual operation power in the second operation power state, the actual operation power in the second operation power state is smaller than the actual operation power in the third operation power state, the first waiting time length is smaller than the second waiting time length, and the second waiting time length is smaller than the third waiting time length.
9. The intelligent diagnosis system of the distribution network based on big data driving according to claim 8, wherein the analysis management unit determines whether the standby power is connected in a classified manner according to the current power-off power utilization end duty ratio P under the third power-off analysis condition, and sets p=nu/Nu 0, wherein Nu is the current power-off power utilization end number, nu0 is the total number of power utilization ends, and 0 < Nu0;
If the current power-off power utilization end duty ratio is in a first duty ratio state, the analysis management unit judges that the standby power supply does not need to be accessed in a grading manner, and simultaneously supplies power to all power-off power utilization ends;
if the current power-off power utilization end duty ratio is in the second duty ratio state, the analysis management unit judges that the standby power supply is connected in a grading manner, namely the analysis management unit sequentially detects the current on-line target piece production number of each power utilization end and sequentially supplies power to the corresponding power utilization ends in a sequence from large to small;
the third power-off analysis condition is that power-off of each power-on end needing power-off is completed, the power-off duration reaches the access waiting duration, and the power-on end duty ratio of the current power-off in the first duty ratio state is smaller than the power-on end duty ratio of the current power-off in the second duty ratio state.
10. The intelligent diagnosis system of the power distribution network based on big data driving according to claim 9, wherein the analysis management unit controls the standby power supply to supply power to the power utilization terminal under the secondary detection condition, detects the equipment operation dangerous degree S of the power utilization terminal when the operation time of the power utilization terminal reaches the preset secondary detection time, and compares S with the preset secondary detection dangerous degree S0 to determine whether the power utilization terminal is faulty, wherein 0 < S0;
If S is less than or equal to S0, the analysis management unit judges that the power utilization end is not faulty and sends out reminding information for checking the power distribution end to a user;
if S0 is less than S, the analysis management unit judges the fault of the power utilization end;
when S0 is less than S, the analysis management unit stops the power supply of the power utilization end when the current production number of the on-line target parts of the power utilization end is 0.
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