A fault alarm method and system for electric power equipment

Abstract

The present invention is applicable to the field of fault alarm technology, and provides a fault alarm method and system for power equipment, including the following steps: drawing a parameter dynamic curve diagram based on power parameter information, wherein a parameter dynamic curve diagram contains several parameter curves; inputting the parameter dynamic curve diagram into a fault parameter curve library for curve diagram matching to determine whether there is a potential fault, and if so, determining the fault type and predicted time; inputting the equipment number and fault type of the potential fault into the power equipment group model to determine the impact range; determining the fault alarm information according to the fault type, predicted time and impact range, and the fault alarm information includes fault maintenance information, safe transfer information, shutdown information and basic service interruption information. The present invention can determine the fault risk caused by the joint action of multiple power parameters, and determine the fault alarm information based on the fault type, predicted time and impact range, so that the fault alarm is more accurate and effective.

Description

Technical Field

[0001] The present invention relates to the technical field of fault alarm, and in particular to a fault alarm method and system for electric power equipment. Background Art

[0002] The demand for electricity in modern factories is constantly increasing, and power equipment is becoming more and more complex. The operating conditions of these equipment directly affect the factory's production efficiency and product quality. Failure of power equipment will not only lead to production interruptions, but may also cause safety accidents such as fire and electric shock, posing a serious threat to personnel and equipment. Therefore, timely detection and handling of equipment failures is an important measure to ensure the safe operation of the factory. With the rapid development of computer technology and Internet of Things technology, early warning and timely handling of faults can be achieved by real-time monitoring of the operating status of equipment. At present, the detection and judgment of each power parameter data is carried out separately, and it is difficult to warn of the fault risk caused by the joint action of various power parameters, and it is impossible to determine the time and scope of the fault risk, and thus it is impossible to obtain better alarm information. Therefore, it is necessary to provide a fault alarm method and system for power equipment to solve the above problems. Summary of the invention

[0003] In view of the deficiencies in the prior art, an object of the present invention is to provide a fault alarm method and system for electric power equipment to solve the problems existing in the above-mentioned background technology.

[0004] The present invention is implemented as follows: a fault alarm method for electric power equipment, the method comprising the following steps:

[0005] Collecting power parameter information, the power parameter information includes collection time, device number, parameter item and parameter value, the device number includes device type, installation location and function location;

[0006] Draw a parameter dynamic curve graph based on the power parameter information, wherein the horizontal axis of the parameter dynamic curve graph is the collection time, and the vertical axis is the parameter item. A parameter dynamic curve graph includes several parameter curves, and the colors of the parameter curves corresponding to different parameter items are different;

[0007] Input the parameter dynamic curve graph into the fault parameter curve library for curve graph matching to determine whether there is a potential fault. If there is a potential fault, determine the fault type and predicted time;

[0008] Input the device number and fault type with potential faults into the power equipment group model to determine the impact scope;

[0009] Fault alarm information is determined according to the fault type, predicted time and impact scope, and the fault alarm information includes one or more of fault maintenance information, safe transfer information, work stoppage information and basic service interruption information; when the fault alarm information includes safe transfer information, the area to be transferred and the transfer route are determined, the alarm at the area to be transferred performs sound and light alarm, and the transfer route is played; when the fault alarm information includes work stoppage information or basic service interruption information, remedial measures information is generated.

[0010] As a further solution of the present invention, the parameter dynamic curve graph is input into the fault parameter curve library for curve graph matching to determine whether there is a potential fault, and when there is a potential fault, the step of determining the fault type and predicted time specifically includes:

[0011] Input the parameter dynamic curve graph into the fault parameter curve library for matching. Each type of power equipment corresponds to a fault parameter curve library. The fault parameter curve library contains several fault parameter curve graphs. Each fault parameter curve graph corresponds to a fault type. The horizontal axis of the fault parameter curve graph is the time from the fault, and the vertical axis is the parameter item.

[0012] The parameter dynamic curve graph is intercepted for a preset time length, and the intercepted parameter dynamic curve graph is similarly calculated with all fault parameter curve graphs to obtain the highest similarity value and prediction time;

[0013] When the highest similarity value is greater than the preset similarity, it is determined that there is a potential fault, and the predicted time and the fault type corresponding to the highest similarity value are output; otherwise, there is no potential fault.

[0014] As a further solution of the present invention: the step of calculating the similarity between the intercepted parameter dynamic curve graph and all fault parameter curve graphs to obtain the highest similarity value and prediction time specifically includes:

[0015] Extracting and processing the fault parameter curve according to the preset time length and the cut-off interval time to obtain a plurality of fault parameter sub-curves, wherein the span of each fault parameter sub-curve is the preset time length, and the interval between the initial points of two adjacent fault parameter sub-curves is the cut-off interval time;

[0016] Calculate the similarity between the intercepted parameter dynamic curve and all fault parameter sub-curves to obtain the highest similarity value;

[0017] The distance to failure time of the fault parameter sub-curve corresponding to the highest similarity value is determined, and the prediction time is determined according to the distance to failure time.

[0018] As a further solution of the present invention: the step of inputting the device number and fault type with potential fault into the power equipment group model to determine the impact range specifically includes:

[0019] The equipment numbers with potential faults are input into the power equipment group model, and some power equipment in the power equipment group model are marked in red;

[0020] Retrieving the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number, and determining whether the functional relationship is interrupted according to the fault type. When the functional relationship is interrupted, the corresponding power equipment is affected;

[0021] Output the equipment numbers of all affected power equipment and determine the impact range based on the location of the equipment numbers.

[0022] As a further solution of the present invention: the step of determining the area to be transferred and the transfer route specifically includes:

[0023] Determine the installation location of the equipment number corresponding to the safe transfer information, and determine the area to be transferred based on the installation location;

[0024] The installation location and the area to be evacuated are input into the factory emergency map, the transfer route is output, and the evacuation level is determined based on the predicted time.

[0025] As a further solution of the present invention: the step of generating remedial measures information specifically includes:

[0026] Retrieve the impact range of the equipment number corresponding to the shutdown information and basic service interruption information, and determine the production line number and basic area based on the impact range;

[0027] Determine the estimated maintenance time based on the equipment number and fault type, input the production line number, forecast time and estimated maintenance time into the production scheduling information, obtain the affected product model and product quantity, and determine the expedited production line information based on the product model and product quantity;

[0028] Determine the remedial equipment and remedial quantity according to the fault type and basic area, and generate remedial action information according to the expedited production line information, remedial equipment and remedial quantity.

[0029] Another object of the present invention is to provide a fault alarm system for electric power equipment, the system comprising:

[0030] The power parameter collection module is used to collect power parameter information, wherein the power parameter information includes collection time, device number, parameter item and parameter value, wherein the device number includes device type, installation location and function location;

[0031] A parameter dynamic curve module is used to draw a parameter dynamic curve diagram based on power parameter information. The horizontal axis of the parameter dynamic curve diagram is the acquisition time, and the vertical axis is the parameter item. A parameter dynamic curve diagram contains several parameter curves, and the colors of parameter curves corresponding to different parameter items are different;

[0032] A potential fault determination module is used to input the parameter dynamic curve graph into the fault parameter curve library for curve matching to determine whether there is a potential fault, and if so, determine the fault type and predicted time;

[0033] An impact range determination module is used to input the device number and fault type with potential faults into the power equipment group model to determine the impact range;

[0034] The comprehensive fault alarm module is used to determine the fault alarm information according to the fault type, predicted time and impact scope, and the fault alarm information includes one or more of fault maintenance information, safe transfer information, work stoppage information and basic service interruption information; when the fault alarm information includes safe transfer information, the area to be transferred and the transfer route are determined, the alarm at the area to be transferred performs sound and light alarm, and the transfer route is played; when the fault alarm information includes work stoppage information or basic service interruption information, remedial measures information is generated.

[0035] As a further solution of the present invention: the potential fault determination module includes:

[0036] A dynamic curve input unit is used to input the parameter dynamic curve graph into the fault parameter curve library for matching. Each type of power equipment corresponds to a fault parameter curve library. The fault parameter curve library contains several fault parameter curve graphs. Each fault parameter curve graph corresponds to a fault type. The horizontal axis of the fault parameter curve graph is the time from the fault, and the vertical axis is the parameter item.

[0037] A similarity calculation unit is used to intercept the parameter dynamic curve graph for a preset time length, and perform similarity calculation between the intercepted parameter dynamic curve graph and all fault parameter curve graphs to obtain the highest similarity value and prediction time;

[0038] The potential fault determination unit is used to determine the existence of a potential fault when the highest similarity value is greater than a preset similarity, and output the predicted time and the fault type corresponding to the highest similarity value; otherwise, there is no potential fault.

[0039] As a further solution of the present invention: the similarity calculation unit includes:

[0040] The extraction processing subunit is used to extract and process the fault parameter curve according to the preset time length and the cut-off interval time to obtain a plurality of fault parameter sub-curves, wherein the span of each fault parameter sub-curve is the preset time length, and the interval between the initial points of two adjacent fault parameter sub-curves is the cut-off interval time;

[0041] A similarity calculation subunit is used to perform similarity calculation on the intercepted parameter dynamic curve diagram and all fault parameter sub-curves to obtain the highest similarity value;

[0042] The prediction time subunit is used to determine the distance to failure time of the fault parameter subcurve corresponding to the highest similarity value, and determine the prediction time according to the distance to failure time.

[0043] As a further solution of the present invention: the impact range determination module includes:

[0044] The device number input unit is used to input the device number with potential fault into the power device group model, and some power devices in the power device group model are marked in red;

[0045] A functional relationship determination unit, used to retrieve the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number, and determine whether the functional relationship is interrupted according to the fault type. When the functional relationship is interrupted, the corresponding power equipment is affected;

[0046] The impact range determination unit is used to output the equipment numbers of all affected power equipment and determine the impact range according to the action positions of the equipment numbers.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention draws a parameter dynamic curve graph based on power parameter information. A parameter dynamic curve graph contains several parameter curves. Then the parameter dynamic curve graph is input into the fault parameter curve library for curve graph matching to determine whether there is a potential fault. If there is, the fault type and predicted time will be determined; the device number and fault type of the potential fault are input into the power equipment group model to determine the impact range; the fault alarm information is determined according to the fault type, predicted time and impact range. In this way, the present invention can determine the fault risk caused by the joint action of multiple power parameters, and determine the fault alarm information based on the fault type, predicted time and impact range, so that the fault alarm is more accurate and effective.

[0049] In addition, when the fault alarm information contains safe transfer information, the area and route to be transferred will be determined, the alarm in the area to be transferred will sound an audible and visual alarm, and the transfer route will be played to facilitate the workers to evacuate quickly and avoid panic; when the fault alarm information contains work stoppage information or basic service interruption information, remedial measures information will be automatically generated to reduce industrial losses caused by equipment failure and ensure that workers can live a normal life. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flowchart of a fault alarm method for electric power equipment;

[0051] Figure 2 A flow chart for determining fault type and prediction time in a fault alarm method for electric power equipment;

[0052] Figure 3 A flowchart for obtaining the highest similarity value and prediction time in a fault alarm method for electric power equipment;

[0053] Figure 4 A flow chart for determining an impact range in a fault alarm method for electric power equipment;

[0054] Figure 5 A flow chart for determining a transfer area and a transfer route in a fault alarm method for electric power equipment;

[0055] Figure 6 A flow chart for generating remedial action information in a fault alarm method for electric power equipment;

[0056] Figure 7 The present invention is a structural schematic diagram of a fault alarm system for electric power equipment. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0058] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0059] like Figure 1 As shown, an embodiment of the present invention provides a fault alarm method for electric power equipment, the method comprising the following steps:

[0060] S100, collecting power parameter information, the power parameter information including collection time, device number, parameter item and parameter value, the device number including device type, installation location and function location;

[0061] S200, drawing a parameter dynamic curve graph based on the power parameter information, wherein the horizontal axis of the parameter dynamic curve graph is the collection time, and the vertical axis is the parameter item. A parameter dynamic curve graph includes a plurality of parameter curves, and the colors of the parameter curves corresponding to different parameter items are all different;

[0062] S300, inputting the parameter dynamic curve graph into the fault parameter curve library for curve graph matching to determine whether there is a potential fault, and if so, determining the fault type and predicted time;

[0063] S400, inputting the device number and fault type with potential fault into the power equipment group model to determine the impact scope;

[0064] S500, determine the fault alarm information according to the fault type, predicted time and impact scope, the fault alarm information includes one or more of fault maintenance information, safe transfer information, work stoppage information and basic service interruption information; when the fault alarm information includes safe transfer information, determine the area to be transferred and the transfer route, the alarm at the area to be transferred will give out sound and light alarm, and play the transfer route; when the fault alarm information includes work stoppage information or basic service interruption information, generate remedial measures information.

[0065] It should be noted that, at present, the detection and judgment of each power parameter data is carried out separately, and it is difficult to warn of the fault risk caused by the combined effect of various power parameters, and it is impossible to determine the time of arrival and impact scope of the fault risk, and thus it is impossible to obtain better alarm information. The embodiments of the present invention aim to solve the above problems.

[0066] In an embodiment of the present invention, firstly, power parameter information of power equipment in a factory is collected through Internet of Things technology, wherein the power parameter information includes collection time, equipment number, parameter item and parameter value, wherein the equipment number can reflect the equipment type, installation location and action location, and the action location refers to the area affected by the power equipment, and then a parameter dynamic curve diagram is automatically drawn according to the power parameter information, wherein the horizontal axis of the parameter dynamic curve diagram is the collection time, and the vertical axis is the parameter item, and a parameter dynamic curve diagram contains several parameter curves, and the colors of the parameter curves corresponding to different parameter items are all different, so as to facilitate the subsequent accurate graphic similarity calculation. Next, the parameter dynamic curve graph is input into the fault parameter curve library for curve graph matching. When there is a potential fault, the fault type and predicted time are automatically determined, and the equipment number and fault type of the potential fault are input into the power equipment group model to determine the impact range. In this way, the embodiment of the present invention will determine the fault alarm information according to the fault type, predicted time and impact range. The fault alarm information includes one or more of fault maintenance information, safe transfer information, shutdown information and basic service interruption information. Each fault type is pre-marked with fault maintenance, safe transfer, shutdown or basic service interruption. In this way, fault alarm information can be automatically generated according to the fault type. The basic service interruption refers to the inability to supply electricity and gas, resulting in the inability of workers to live a normal life. In addition, when the fault alarm information includes safe transfer information, the transfer area and transfer route will be determined, and the alarm at the transfer area will sound and light alarm, and play the transfer route to facilitate the workers to evacuate quickly and avoid panic; when the fault alarm information includes shutdown information or basic service interruption information, remedial measures information is generated to reduce the losses caused by equipment failure and ensure that workers can live a normal life.

[0067] like Figure 2 As shown, as a preferred embodiment of the present invention, the parameter dynamic curve graph is input into the fault parameter curve library for curve graph matching to determine whether there is a potential fault. If there is a potential fault, the steps of determining the fault type and predicted time specifically include:

[0068] S301, inputting the parameter dynamic curve graph into a fault parameter curve library for matching, each type of power equipment corresponds to a fault parameter curve library, the fault parameter curve library contains a plurality of fault parameter curve graphs, each fault parameter curve graph corresponds to a fault type, the horizontal axis of the fault parameter curve graph is the time from fault, and the vertical axis is the parameter item;

[0069] S302, intercepting the parameter dynamic curve graph for a preset time length, calculating the similarity between the intercepted parameter dynamic curve graph and all fault parameter curve graphs, and obtaining the highest similarity value and prediction time;

[0070] S303, when the highest similarity value is greater than a preset similarity, it is determined that there is a potential fault, and the predicted time and the fault type corresponding to the highest similarity value are output; otherwise, there is no potential fault.

[0071] In the embodiment of the present invention, a fault parameter curve library is established in advance, each type of power equipment corresponds to a fault parameter curve library, and the fault parameter curve library contains several fault parameter curve graphs, each fault parameter curve graph corresponds to a fault type, and the horizontal axis of the fault parameter curve graph is the time from the fault, and the vertical axis is the parameter item. The fault parameter curve graph reflects the trend of each parameter of the equipment before the fault occurs. The parameter dynamic curve graph is input into the fault parameter curve library for matching, and the parameter dynamic curve graph is intercepted for a preset time length. The preset time length is a predetermined value, for example, the preset time length is 20s, and the parameter dynamic curve graph is 25s, then the last 20s part of the parameter dynamic curve graph will be intercepted, and the intercepted parameter dynamic curve graph will be similarity calculated with all fault parameter curve graphs, and the highest similarity value and predicted time will be obtained. When the highest similarity value is greater than the preset similarity, it will automatically determine that there is a potential fault, and output the predicted time and the fault type of the fault parameter curve graph corresponding to the highest similarity value.

[0072] like Figure 3 As shown, as a preferred embodiment of the present invention, the step of calculating the similarity between the intercepted parameter dynamic curve graph and all fault parameter curve graphs to obtain the highest similarity value and prediction time specifically includes:

[0073] S3021, extracting and processing the fault parameter curve according to the preset time length and the cut-off interval time to obtain a plurality of fault parameter sub-curves, wherein the span of each fault parameter sub-curve is the preset time length, and the interval between the initial points of two adjacent fault parameter sub-curves is the cut-off interval time;

[0074] S3022, performing similarity calculation on the intercepted parameter dynamic curve graph and all fault parameter sub-curves to obtain the highest similarity value;

[0075] S3023, determining the distance to failure time of the fault parameter sub-curve corresponding to the highest similarity value, and determining the prediction time according to the distance to failure time.

[0076] In the embodiment of the present invention, in order to determine the highest similarity value and the predicted time, it is first necessary to extract and process the fault parameter curve according to the preset time length and the cut-off interval time to obtain several fault parameter sub-curves. The cut-off interval time is also a fixed value set in advance, such as 5s. For example, if the total duration of a fault parameter curve is 60s, 9 fault parameter sub-curves with a duration of 20s will be obtained. Then, the intercepted parameter dynamic curve is calculated with all the fault parameter sub-curves for graphic similarity, and several similarity values ​​are obtained. The highest similarity value is taken, and the distance to fault time of the fault parameter sub-curve corresponding to the highest similarity value is determined. For example, if the distance to fault time is 20s, the predicted time is 20s, indicating that the corresponding fault is likely to occur after 20s.

[0077] like Figure 4 As shown, as a preferred embodiment of the present invention, the step of inputting the device number and fault type with potential fault into the power equipment group model to determine the impact scope specifically includes:

[0078] S401, inputting the device number with potential fault into the power device group model, and some power devices in the power device group model are marked in red;

[0079] S402, retrieving the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number, and determining whether the functional relationship is interrupted according to the fault type. When the functional relationship is interrupted, the corresponding power equipment is affected;

[0080] S403, outputting the equipment numbers of all affected power equipment, and determining the impact range according to the action positions of the equipment numbers.

[0081] In an embodiment of the present invention, a power equipment group model is established in advance, and the power equipment group model includes all the power equipment in the factory, and the connection relationship and functional relationship between the power equipment are indicated in the power equipment group model. The equipment number with potential faults is input into the power equipment group model, and some of the power equipment in the power equipment group model is marked in red. There is an electrical connection between the power equipment marked in red and the equipment corresponding to the equipment number. Then, the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number is retrieved, and it is determined whether the functional relationship is interrupted according to the fault type. When interrupted, the corresponding power equipment is affected, and which functional relationships will be affected by each fault type needs to be determined in advance. Finally, the equipment numbers of all affected power equipment will be integrated and output, and the scope of influence will be determined according to the position of the equipment number.

[0082] like Figure 5 As shown, as a preferred embodiment of the present invention, the step of determining the area to be transferred and the transfer route specifically includes:

[0083] S501, determining the installation location of the device number corresponding to the security transfer information, and determining the area to be transferred according to the installation location;

[0084] S502, input the installation location and the area to be transferred into the factory emergency map, output the transfer route, and determine the evacuation level according to the predicted time.

[0085] In an embodiment of the present invention, when the fault alarm information includes safe transfer information, it indicates that a highly dangerous fault such as fire or explosion will occur. At this time, the installation location of the equipment number corresponding to the safe transfer information will be determined, and the area where the installation location is located is the area to be transferred. The installation location and the area to be transferred are input into the factory emergency map, the transfer route is output, and the evacuation level is determined based on the predicted time. It is easy to understand that the shorter the predicted time, the higher the evacuation level.

[0086] like Figure 6 As shown, as a preferred embodiment of the present invention, the step of generating remedial measures information specifically includes:

[0087] S503, retrieve the impact range of the equipment number corresponding to the shutdown information and the basic service interruption information, and determine the production line number and the basic area according to the impact range;

[0088] S504, determining the estimated maintenance time according to the equipment number and the fault type, inputting the production line number, the predicted time and the estimated maintenance time into the production scheduling information, obtaining the affected product model and product quantity, and determining the expedited production line information based on the product model and product quantity;

[0089] S505, determining remedial equipment and remedial quantity according to the fault type and the basic area, and generating remedial measure information according to the expedited production line information, remedial equipment and remedial quantity.

[0090] In an embodiment of the present invention, when the fault alarm information includes shutdown information or basic service interruption information, the impact range of the equipment number corresponding to the shutdown information and the basic service interruption information will be automatically retrieved, and the production line number and the basic area will be determined according to the impact range. The shutdown information corresponds to the production line number, and the basic service interruption information corresponds to the basic area. Then, the estimated maintenance time is determined according to the equipment number and the fault type, and the production line number, predicted time and estimated maintenance time are input into the production scheduling information, and the affected product model and product quantity will be obtained. The expedited production line information is determined based on the product model and product quantity, and the impact of the shutdown is reduced by increasing the scheduling of other production lines. In addition, the remedial equipment and remedial quantity will be determined according to the fault type and the basic area. The larger the basic area, the greater the remedial quantity.

[0091] like Figure 7As shown, an embodiment of the present invention further provides a fault alarm system for electric power equipment, the system comprising:

[0092] The power parameter collection module 100 is used to collect power parameter information, wherein the power parameter information includes collection time, device number, parameter item and parameter value, wherein the device number includes device type, installation location and function location;

[0093] The parameter dynamic curve module 200 is used to draw a parameter dynamic curve diagram based on the power parameter information. The horizontal axis of the parameter dynamic curve diagram is the acquisition time, and the vertical axis is the parameter item. A parameter dynamic curve diagram contains several parameter curves, and the colors of the parameter curves corresponding to different parameter items are different;

[0094] The potential fault determination module 300 is used to input the parameter dynamic curve graph into the fault parameter curve library for curve graph matching to determine whether there is a potential fault, and if so, determine the fault type and predicted time;

[0095] The impact range determination module 400 is used to input the device number and fault type with potential fault into the power equipment group model to determine the impact range;

[0096] The comprehensive fault alarm module 500 is used to determine the fault alarm information according to the fault type, predicted time and impact scope, and the fault alarm information includes one or more of fault maintenance information, safe transfer information, shutdown information and basic service interruption information; when the fault alarm information includes safe transfer information, the transfer area and transfer route are determined, the alarm at the transfer area makes an audible and visual alarm, and plays the transfer route; when the fault alarm information includes shutdown information or basic service interruption information, remedial measures information is generated.

[0097] As a preferred embodiment of the present invention, the potential fault determination module 300 includes:

[0098] A dynamic curve input unit is used to input the parameter dynamic curve graph into the fault parameter curve library for matching. Each type of power equipment corresponds to a fault parameter curve library. The fault parameter curve library contains several fault parameter curve graphs. Each fault parameter curve graph corresponds to a fault type. The horizontal axis of the fault parameter curve graph is the time from the fault, and the vertical axis is the parameter item.

[0099] A similarity calculation unit is used to intercept the parameter dynamic curve graph for a preset time length, and perform similarity calculation between the intercepted parameter dynamic curve graph and all fault parameter curve graphs to obtain the highest similarity value and prediction time;

[0100] The potential fault determination unit is used to determine the existence of a potential fault when the highest similarity value is greater than a preset similarity, and output the predicted time and the fault type corresponding to the highest similarity value; otherwise, there is no potential fault.

[0101] As a preferred embodiment of the present invention, the similarity calculation unit includes:

[0102] The extraction processing subunit is used to extract and process the fault parameter curve according to the preset time length and the cut-off interval time to obtain a plurality of fault parameter sub-curves, wherein the span of each fault parameter sub-curve is the preset time length, and the interval between the initial points of two adjacent fault parameter sub-curves is the cut-off interval time;

[0103] A similarity calculation subunit is used to perform similarity calculation on the intercepted parameter dynamic curve diagram and all fault parameter sub-curves to obtain the highest similarity value;

[0104] The prediction time subunit is used to determine the distance to failure time of the fault parameter subcurve corresponding to the highest similarity value, and determine the prediction time according to the distance to failure time.

[0105] As a preferred embodiment of the present invention, the impact range determination module 400 includes:

[0106] The device number input unit is used to input the device number with potential fault into the power device group model, and some power devices in the power device group model are marked in red;

[0107] A functional relationship determination unit, used to retrieve the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number, and determine whether the functional relationship is interrupted according to the fault type. When the functional relationship is interrupted, the corresponding power equipment is affected;

[0108] The impact range determination unit is used to output the equipment numbers of all affected power equipment and determine the impact range according to the action positions of the equipment numbers.

[0109] The above only describes in detail the preferred embodiments of the present invention, which is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0110] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0111] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0112] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A fault alarm method for electric power equipment, characterized in that: The method comprises the following steps: Collecting power parameter information, the power parameter information includes collection time, device number, parameter item and parameter value, the device number includes device type, installation location and function location; Draw a parameter dynamic curve graph based on the power parameter information, wherein the horizontal axis of the parameter dynamic curve graph is the collection time, and the vertical axis is the parameter item. A parameter dynamic curve graph includes several parameter curves, and the colors of the parameter curves corresponding to different parameter items are different; Input the parameter dynamic curve graph into the fault parameter curve library for curve graph matching to determine whether there is a potential fault. If there is a potential fault, determine the fault type and predicted time; Input the device number and fault type with potential faults into the power equipment group model to determine the impact scope; Determine the fault alarm information according to the fault type, predicted time and impact scope, wherein the fault alarm information includes one or more of fault maintenance information, safe transfer information, work stoppage information and basic service interruption information; when the fault alarm information includes safe transfer information, determine the area to be transferred and the transfer route, the alarm at the area to be transferred will sound and light alarm, and play the transfer route; when the fault alarm information includes work stoppage information or basic service interruption information, generate remedial measures information; Among them, the parameter dynamic curve graph is input into the fault parameter curve library for curve graph matching to determine whether there is a potential fault. When there is a potential fault, the fault type and prediction time are determined. Specifically, the steps include: inputting the parameter dynamic curve graph into the fault parameter curve library for matching, each type of power equipment corresponds to a fault parameter curve library, the fault parameter curve library contains a number of fault parameter curve graphs, each fault parameter curve graph corresponds to a fault type, the horizontal axis of the fault parameter curve graph is the time from the fault, and the vertical axis is the parameter item; the parameter dynamic curve graph is intercepted for a preset time length, and the intercepted parameter dynamic curve graph is calculated for similarity with all fault parameter curve graphs to obtain the highest similarity value and prediction time; when the highest similarity value is greater than the preset similarity, it is determined that there is a potential fault, and the prediction time and the fault type corresponding to the highest similarity value are output; otherwise, there is no potential fault; Among them, the step of calculating the similarity between the intercepted parameter dynamic curve graph and all the fault parameter curve graphs to obtain the highest similarity value and the predicted time specifically includes: extracting and processing the fault parameter curve graph according to the preset time length and the cut-off interval time to obtain a plurality of fault parameter sub-curves, each fault parameter sub-curve has a span of the preset time length, and the interval between the initial points of two adjacent fault parameter sub-curves is the cut-off interval time; calculating the similarity between the intercepted parameter dynamic curve graph and all the fault parameter sub-curves to obtain the highest similarity value; determining the distance to fault time of the fault parameter sub-curve corresponding to the highest similarity value, and determining the predicted time according to the distance to fault time.

2. The fault alarm method of electric power equipment according to claim 1, characterized in that: The step of inputting the device number and fault type with potential fault into the power equipment group model to determine the impact scope specifically includes: The equipment numbers with potential faults are input into the power equipment group model, and some power equipment in the power equipment group model are marked in red; Retrieving the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number, and determining whether the functional relationship is interrupted according to the fault type. When the functional relationship is interrupted, the corresponding power equipment is affected; Output the equipment numbers of all affected power equipment and determine the impact range based on the location of the equipment numbers.

3. The fault alarm method of electric power equipment according to claim 1, characterized in that: The step of determining the area to be transferred and the transfer route specifically includes: Determine the installation location of the equipment number corresponding to the safe transfer information, and determine the area to be transferred based on the installation location; The installation location and the area to be evacuated are input into the factory emergency map, the transfer route is output, and the evacuation level is determined based on the predicted time.

4. The fault alarm method of electric power equipment according to claim 1, characterized in that: The step of generating remedial measures information specifically includes: Retrieve the impact range of the equipment number corresponding to the shutdown information and basic service interruption information, and determine the production line number and basic area based on the impact range; Determine the estimated maintenance time based on the equipment number and fault type, input the production line number, forecast time and estimated maintenance time into the production scheduling information, obtain the affected product model and product quantity, and determine the expedited production line information based on the product model and product quantity; Determine the remedial equipment and remedial quantity according to the fault type and basic area, and generate remedial action information according to the expedited production line information, remedial equipment and remedial quantity.

5. A fault alarm system for electric power equipment, characterized in that: The system comprises: The power parameter collection module is used to collect power parameter information, wherein the power parameter information includes collection time, device number, parameter item and parameter value, wherein the device number includes device type, installation location and function location; A parameter dynamic curve module is used to draw a parameter dynamic curve diagram based on power parameter information. The horizontal axis of the parameter dynamic curve diagram is the acquisition time, and the vertical axis is the parameter item. A parameter dynamic curve diagram contains several parameter curves, and the colors of parameter curves corresponding to different parameter items are different; A potential fault determination module is used to input the parameter dynamic curve graph into the fault parameter curve library for curve matching to determine whether there is a potential fault, and if so, determine the fault type and predicted time; An impact range determination module is used to input the device number and fault type with potential faults into the power equipment group model to determine the impact range; A comprehensive fault alarm module is used to determine fault alarm information according to the fault type, predicted time and impact range, wherein the fault alarm information includes one or more of fault maintenance information, safe transfer information, shutdown information and basic service interruption information; when the fault alarm information includes safe transfer information, the required transfer area and transfer route are determined, the alarm at the required transfer area performs sound and light alarm, and the transfer route is played; when the fault alarm information includes shutdown information or basic service interruption information, remedial measures information is generated; Wherein, the potential fault determination module includes: a dynamic curve input unit, which is used to input the parameter dynamic curve graph into the fault parameter curve library for matching, each type of power equipment corresponds to a fault parameter curve library, the fault parameter curve library contains several fault parameter curve graphs, each fault parameter curve graph corresponds to a fault type, the horizontal axis of the fault parameter curve graph is the time from the fault, and the vertical axis is the parameter item; a similarity calculation unit, which is used to intercept the parameter dynamic curve graph for a preset time length, and perform similarity calculation on the intercepted parameter dynamic curve graph and all fault parameter curve graphs to obtain the highest similarity value and predicted time; a potential fault determination unit, which is used to determine the existence of a potential fault when the highest similarity value is greater than the preset similarity, and output the predicted time and the fault type corresponding to the highest similarity value; otherwise, there is no potential fault; Among them, the similarity calculation unit includes: an extraction processing subunit, which is used to extract and process the fault parameter curve diagram according to a preset time length and a cut-off interval time to obtain a plurality of fault parameter sub-curves, the span of each fault parameter sub-curve is the preset time length, and the interval between the initial points of two adjacent fault parameter sub-curves is the cut-off interval time; a similarity calculation subunit, which is used to perform similarity calculation on the intercepted parameter dynamic curve diagram and all fault parameter sub-curves to obtain the highest similarity value; a prediction time subunit, which is used to determine the distance to fault time of the fault parameter sub-curve corresponding to the highest similarity value, and determine the prediction time according to the distance to fault time.

6. The fault alarm system for electric power equipment according to claim 5, characterized in that: The impact range determination module includes: The device number input unit is used to input the device number with potential fault into the power device group model, and some power devices in the power device group model are marked in red; A functional relationship determination unit, used to retrieve the functional relationship between the power equipment marked in red and the power equipment corresponding to the equipment number, and determine whether the functional relationship is interrupted according to the fault type. When the functional relationship is interrupted, the corresponding power equipment is affected; The impact range determination unit is used to output the equipment numbers of all affected power equipment and determine the impact range according to the action positions of the equipment numbers.

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