Checking processing system and method for parameters of power equipment

Abstract

The invention discloses a checking processing system and method for power equipment parameters. The power equipment parameters of power equipment are collected; the outlier criticality probability of the previous parameters of each cluster is calculated according to the previous parameters and the current parameters; according to the outlier criticality probability of the previous parameters of each cluster, calculating an obstacle level of the parameters when the parameters appear; obtaining a recent beforehand announcement amount according to the barrier level of the current parameter; the obstacle level of the current parameter is obtained through calculation, and the higher the obstacle level is, the higher the probability of presenting the obstacle is, so that the assignment configuration is executed through the highest power equipment parameter of the last day, and the recent advance notification amount is obtained. The method overcomes the defect of reliability risk caused by deviation when a constant critical quantity is used for affirming an outlier due to power equipment condition change caused by a specific condition.

Description

Technical Field

[0001] The present invention belongs to the technical field of power equipment parameter verification and processing, and in particular relates to a power equipment parameter verification and processing system and method. Background Art

[0002] Power equipment parameters are crucial information in the power system, including but not limited to the voltage and current of power equipment. These parameters together describe the working conditions and performance of the power system, and are of great significance for ensuring the stable operation of the power system and efficient energy utilization.

[0003] The parameters of power equipment are very important, so they need to be stored. To store them, it is often as mentioned in the prior art solution with patent publication number "CN105678474A": the server stores the collected power equipment parameters in the table of the power equipment. However, at present, the server simply stores the power equipment parameters. For the power equipment parameters, the server can also detect the trend of power equipment function degradation through the power equipment parameters to help improve the working conditions of the power equipment. By detecting abnormal functions, immediate configuration and maintenance can be performed to ensure that the power equipment always operates under the best working conditions.

[0004] The parameters of the power equipment will also change due to the load of the current power equipment and changes in external conditions. When the parameters of the power equipment exceed the constant critical value, the power equipment will stop operating. However, due to specific conditions such as a sharp increase in load, the power equipment will also experience state changes. At this time, the use of constant critical values ​​for determination will have deviations, resulting in reliability risks. Summary of the invention

[0005] In order to solve the defects in the prior art, the present invention proposes a calibration processing system and method for power equipment parameters, which collects power equipment parameters of power equipment; calculates the outlier criticality probability of each cluster of past parameters based on the past parameters and current parameters; calculates the obstacle level of the parameters at the time of occurrence based on the outlier criticality probability of each cluster of past parameters; obtains the most recent advance notification amount based on the obstacle level of the current parameters; obtains the obstacle level of the current parameters through calculation, and since the higher the obstacle level, the higher the probability of the obstacle, the higher the probability of the obstacle, the allocation is performed through the highest power equipment parameter of the previous day to obtain the most recent advance notification amount. This overcomes the defect that the power equipment status changes caused by specific conditions, the use of a constant critical amount to identify outliers will have deviations, resulting in reliability risks.

[0006] The present invention uses the following technical solutions.

[0007] A method for checking and processing parameters of electric power equipment, comprising: Step 1, collecting power equipment parameters of the power equipment; Step 2, calculate the outlier criticality probability of each cluster's past parameters based on past parameters and current parameters; Step 3, calculating the barrier level of the parameters when they appear based on the probability of outlier criticality of the past parameters of each cluster; Step 4, obtaining the most recent advance notification amount according to the obstacle level of the current parameter.

[0008] Preferably, in Step 1, power equipment parameters of the power equipment are collected via the server, and the collected power equipment parameters of the power equipment are cut into past parameters and current parameters.

[0009] Preferably, all power equipment parameters collected on the days before the power equipment is used are defined as past parameters, and the power equipment parameters of the previous day when the equipment is used are defined as current parameters.

[0010] Preferably, the power equipment parameters of the power equipment in a single day are defined as a cluster.

[0011] Preferably, the power equipment parameter is a voltage value of the power equipment or a current value of the power equipment.

[0012] Preferably, the operation equation of the most recent advance notification amount is: The most recent advance notification amount = the current highest power equipment parameter * (1-R), in the equation, Represents the barrier level of the current parameter.

[0013] As the calculation obtains the latest power equipment parameter advance notification quantity is On the day when the power equipment is used, the power equipment parameters of the power equipment received in real time by the server are higher than When the server is notified, the server administrator is notified via the server.

[0014] Preferably, the operational equation for the barrier level of the current parameters is: ;

[0015] In the equation, Represents the obstacle level of the current parameter. The higher the value, the more likely the device will be obstructed. Representative The criticality of the cluster power equipment parameter minus the criticality of the corresponding previous cluster power equipment parameter, Representative The criticality of cluster power equipment parameters, Representative The criticality of cluster power equipment parameters, Represents the total amount of past parameters of several clusters.

[0016] Preferably, the computational equation for the criticality of each cluster's past parameters is: ; In the equation, Representative The criticality of cluster power equipment parameters, Representative The probability of outlier criticality of cluster power equipment parameters, Representative Cluster power equipment parameters and current parameters The approximate amount of .

[0017] Preferably, the calculation equation of the outlier criticality probability of each cluster's past parameters is: ; In the equation, Representative The probability of outlier criticality of cluster power equipment parameters, Representative Cluster power equipment parameters and current parameters The approximate amount of Representative Cluster power equipment parameters and current parameters The approximate amount of Represents the current parameter The standard deviation of , Respectively represent Cluster power equipment parameters, Standard deviation of cluster power equipment parameters, Representative The number of days between the collection day of cluster power equipment parameters and the collection day of current parameters, Represents the total amount of past parameters of several clusters.

[0018] A system for checking and processing parameters of electric power equipment, comprising: A parameter module, which is used to collect power equipment parameters of the power equipment; A calculation module, which is used to calculate the outlier criticality probability of each cluster's past parameters based on past parameters and current parameters; A hierarchy module, which is used to calculate the barrier hierarchy of the parameters when they appear based on the probability of the outlier criticality of the past parameters of each cluster; A notification module is used to obtain the most recent prior notification amount according to the obstacle level of the current parameter.

[0019] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include: Obtain the obstacle level of the current parameters through calculation. Since the higher the obstacle level, the higher the probability of an obstacle, the highest power equipment parameter of the previous day (current parameter) is used to perform the allocation and obtain the most recent advance notification amount. This overcomes the defect that the use of a constant critical amount to identify outliers due to changes in the power equipment status caused by specific conditions will have deviations, resulting in reliability risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of the method for checking and processing the parameters of the electric power equipment described in the present invention; Figure 2 It is a partial structural diagram of the power equipment parameter verification processing system described in the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely expressed in combination with the drawings in the embodiments of the present invention. The embodiments expressed in this application are only part of the embodiments of the present invention, not all of them. According to the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the protection scope of the present invention.

[0022] like Figure 1 As shown, a method for checking and processing parameters of electric power equipment according to the present invention is executed on a server, and includes: Step 1, collecting power equipment parameters of the power equipment; In a preferred but non-limiting embodiment of the present invention, in Step 1, power equipment parameters of the power equipment are collected via the server, and the collected power equipment parameters of the power equipment are cut into past parameters and current parameters.

[0023] In a preferred but non-limiting embodiment of the present invention, all power equipment parameters collected on the days before the power equipment is used are defined as past parameters, and the power equipment parameters of the previous day when the equipment is used are defined as current parameters.

[0024] In a preferred but non-limiting embodiment of the present invention, the power equipment parameters of the power equipment in a single day are defined as a cluster.

[0025] In a preferred but non-limiting embodiment of the present invention, the power equipment parameter is a voltage value of the power equipment or a current value of the power equipment.

[0026] Step 2, calculate the outlier criticality probability of each cluster's past parameters based on past parameters and current parameters; When the power parameters of the power equipment are collected through the server, since the power parameters will increase when outliers appear, the power parameter groups that increase successively are collected, and the power parameter groups that increase successively each day are defined as a cluster. Since the processed past parameters are timed, even if the values ​​of the power parameters of each cluster are different, the change trend of the power parameters is consistent, so the past parameters of each time period are compared with the current parameters to obtain the difference between the current parameters and the past parameters; since the increase of the power parameters of each power equipment starts with the power parameters with a small value, and there is a situation where the power equipment is degraded or its load is inconsistent, when comparing two clusters of power parameters, it is often found that the longer the use time, the higher the difference in the power parameters, and the larger the distance between the two clusters of parameter points; therefore, the approximation of each past parameter and the current parameter is calculated by the KL divergence calculation method. The smaller the approximation, the higher the difference between the power parameter queue of the current parameter and the power parameter queue of the past parameter.

[0027] The lower the approximation and the higher the distinction, the lower the availability of the two clusters of power equipment parameters, so the smaller the corresponding criticality. Therefore, the outlier criticality probability of the current parameter is obtained based on the criticality of the power equipment parameters in the inconsistent time period, and since it corresponds to the starting parameters in the past parameter queue (the queue is the parameters arranged in the order of the collection time points), that is, the past parameters at an earlier time point, the power equipment parameters that are closer to the collection time point of the current parameter are more available for reference to the current parameter. The parameters accompanied by the change in time point; therefore, according to the power equipment parameter change attributes, the corresponding distinctions of the past parameters and the current parameters are analyzed continuously with the time points to obtain the outlier criticality probability of each cluster of power equipment parameters.

[0028] Step 3, calculating the barrier level of the parameters when they appear based on the probability of outlier criticality of the past parameters of each cluster; Since the current parameters are inconsistent with the past parameters or their loads at a more distant time point, their variation amplitude is not low, while the variation of the parameters at a closer time point or with a similar load is not high, the obstacle level of the current parameters is obtained based on the difference between the current parameters and the parameters at a closer time point with a similar load and the difference with all the past parameters, and the outlier criticality probability of each inconsistent cluster of power equipment parameters obtained through the above method steps, and then the outlier changes of the power equipment parameters in the inconsistent period are configured according to the outlier criticality probability to obtain the obstacle level of the current parameters, so the obstacle level of the current parameters can be obtained according to the corresponding variability of the outlier criticality probability. The higher the obstacle level of the current parameters, the higher the probability of obstacles in the use of the power equipment, that is, the obstacle level of the parameters when the power equipment parameters are calculated based on the power equipment parameters on the previous day of use. The higher the obstacle level of the current parameters, the higher the probability of obstacles in the power equipment parameters on the day of use of the relevant power equipment.

[0029] Step 4, obtaining the most recent advance notification amount according to the obstacle level of the current parameter.

[0030] The obstacle level of the current parameters is obtained through the above method. Since the higher the obstacle level, the higher the probability of an obstacle, the higher the probability of an obstacle. Therefore, the highest power equipment parameters of the previous day (current parameters) are used to perform quantity allocation and obtain the latest pre-notified quantity. If the obstacle level of the power equipment parameters of the previous day is higher, the probability of an obstacle in the power equipment is higher, and the power equipment parameters of the day should be given more attention. In this way, the constant pre-notified quantity is replaced with the latest pre-notified quantity to prevent power equipment obstacles from occurring and not being detected in time. If the obstacle level of the power equipment parameters of the previous day is lower, the probability of an obstacle in the equipment on the day is lower, and the power equipment parameters of the day are given less attention. In this way, the constant pre-notified quantity is also replaced with the latest pre-notified quantity.

[0031] The server is used to detect the power equipment status based on the most recent pre-notification quantity. When the power equipment parameters are higher than the most recent pre-notification quantity, the server controller is notified through the server to avoid the occurrence of reliability risks.

[0032] In a preferred but non-limiting embodiment of the present invention, the operation equation of the most recent advance notification amount is: The most recent advance notification amount = the current highest power equipment parameter * (1-R), in the equation, Represents the barrier level of the current parameter.

[0033] As the calculation obtains the latest power equipment parameter advance notification quantity is On the day when the power equipment is used, the power equipment parameters of the power equipment received in real time by the server are higher than When the server is notified, the server administrator is notified via the server.

[0034] In a preferred but non-limiting embodiment of the present invention, the operational equation for the barrier level of the current parameter is: ; In the equation, Represents the obstacle level of the current parameter. The higher the value, the more likely the device will be obstructed. Representative The criticality of the power equipment parameters of a cluster minus the criticality of the power equipment parameters of the previous cluster is obtained to show the corresponding change relationship. Representative The criticality of cluster power equipment parameters, Representative The criticality of cluster power equipment parameters, Represents the total amount of several clusters of past parameters. For example, if there are ten clusters of past parameters, then That’s ten.

[0035] Here via Presenting the Cluster power equipment parameters and The corresponding differentiation of cluster power equipment parameters is used to overcome the first Cluster power equipment parameters have outliers that are not conducive to the current identification. The higher the value, the higher the outliers of the previous parameters. It presents the The fault identification amount of the cluster power equipment parameters for the current parameters is collected by integrating the fault identification amounts of all the cluster past parameters for the current parameters to obtain the fault level of the current parameters.

[0036] In a preferred but non-limiting embodiment of the present invention, the computational equation for the criticality of each cluster's past parameters is: ; In the equation, Representative The criticality of cluster power equipment parameters, Representative The probability of outlier criticality of cluster power equipment parameters, Representative Cluster power equipment parameters and current parameters The approximate amount of .

[0037] In a preferred but non-limiting embodiment of the present invention, the operation equation of the outlier criticality probability of each cluster's past parameters is: ; In the equation, Representative The probability of outlier criticality of cluster power equipment parameters, Representative Cluster power equipment parameters and current parameters The approximate amount of Representative Cluster power equipment parameters and current parameters The approximate amount of Represents the current parameter The standard deviation of , Respectively represent Cluster power equipment parameters, The standard deviation of the cluster power equipment parameters. The two minus signs represent the difference between the two cluster power equipment parameters, which shows the difference between the outliers. Representative The number of days between the collection date of cluster power equipment parameters and the collection date of current parameters. The greater the number of days, the smaller the approximation. Represents the total amount of past parameters of several clusters.

[0038] Here via Represents the approximate mean of the current parameters and the past parameters of each cluster, through It shows the deviation trend of the parameters of the cluster of power equipment.

[0039] Therefore, the present invention overcomes the defect that the use of constant critical quantity to identify outliers due to changes in power equipment status caused by specific conditions will have deviations, resulting in reliability risks. The identification standard of the outlier probability is configured through changes in operating conditions, and the allocation configuration is performed through the highest power equipment parameter of the previous day (current parameter), and the most recent advance notification quantity is obtained, thereby reducing the identification deviation of the outlier probability.

[0040] like Figure 2 As shown, a power equipment parameter verification processing system according to the present invention comprises: A parameter module, which is used to collect power equipment parameters of the power equipment; A calculation module, which is used to calculate the outlier criticality probability of each cluster's past parameters based on past parameters and current parameters; A hierarchy module, which is used to calculate the barrier hierarchy of the parameters when they appear based on the probability of the outlier criticality of the past parameters of each cluster; A notification module is used to obtain the most recent prior notification amount according to the obstacle level of the current parameter.

[0041] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include: Obtain the obstacle level of the current parameters through calculation. Since the higher the obstacle level, the higher the probability of an obstacle, the highest power equipment parameter of the previous day (current parameter) is used to perform the allocation and obtain the most recent advance notification amount. This overcomes the defect that the use of a constant critical amount to identify outliers due to changes in the power equipment status caused by specific conditions will have deviations, resulting in reliability risks.

[0042] The present disclosure can be a system, method and / or computer program product. The computer program product can include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0043] A computer-readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the above. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (such as, a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0044] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0045] The computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as "C" language or similar programming languages. Computer-readable program instructions can be executed entirely on the controller computer, partially on the controller computer, as a separate software package, partially on the controller computer, partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the controller computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (just as using an Internet service provider to connect through the Internet). In some embodiments, various aspects of the present disclosure are implemented by utilizing state information of computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), which can execute computer-readable program instructions.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for checking and processing parameters of electric power equipment, characterized in that: include: Step 1, collecting power equipment parameters of the power equipment; Step 2, calculate the outlier criticality probability of each cluster's past parameters based on past parameters and current parameters; Step 3, calculating the barrier level of the parameters when they appear based on the probability of outlier criticality of the past parameters of each cluster; Step 4, obtaining the most recent advance notification amount according to the obstacle level of the current parameter.

2. The method for checking and processing electric power equipment parameters according to claim 1, characterized in that: In Step 1, power equipment parameters of the power equipment are received through the server, and the received power equipment parameters of the power equipment are divided into past parameters and current parameters.

3. The method for checking and processing electric power equipment parameters according to claim 2, characterized in that: The overall power equipment parameters collected on the days before the power equipment was used are defined as past parameters, and the power equipment parameters on the previous day when the equipment was used are defined as current parameters.

4. The method for checking and processing electric power equipment parameters according to claim 3, characterized in that: The power equipment parameters of a single day of the power equipment are defined as a cluster.

5. The method for checking and processing parameters of electric power equipment according to claim 4, characterized in that: The power equipment parameter is a voltage value of the power equipment or a current value of the power equipment.

6. The method for checking and processing electric power equipment parameters according to claim 5, characterized in that: The calculation equation for the latest advance notification volume is: The most recent advance notification amount = the current highest power equipment parameter * (1-R), in the equation, Represents the barrier level of the current parameter.

7. The method for checking and processing electric power equipment parameters according to claim 6, characterized in that: The operational equation for the barrier level of the current parameters is: ； In the equation, Represents the obstacle level of the current parameter. The higher the value, the more likely the device will be obstructed. Representative The criticality of the cluster power equipment parameter minus the criticality of the corresponding previous cluster power equipment parameter, Representative The criticality of cluster power equipment parameters, Representative The criticality of cluster power equipment parameters, Represents the total amount of past parameters of several clusters.

8. The method for checking and processing electric power equipment parameters according to claim 7, characterized in that: The calculation equation of the criticality of each cluster's past parameters is: ； In the equation, Representative The criticality of cluster power equipment parameters, Representative The probability of outlier criticality of cluster power equipment parameters, Representative Cluster power equipment parameters and current parameters The approximate amount of .

9. The method for checking and processing electric power equipment parameters according to claim 8, characterized in that: The calculation equation of the outlier criticality probability of each cluster's past parameters is: ； In the equation, Representative The probability of outlier criticality of cluster power equipment parameters, Representative Cluster power equipment parameters and current parameters The approximate amount of Representative Cluster power equipment parameters and current parameters The approximate amount of Represents the current parameter The standard deviation of , Respectively represent Cluster power equipment parameters, Standard deviation of cluster power equipment parameters, Representative The number of days between the collection day of cluster power equipment parameters and the collection day of current parameters, Represents the total amount of past parameters of several clusters.

10. A power equipment parameter verification processing system, characterized in that: include: A parameter module, which is used to collect power equipment parameters of the power equipment; A calculation module, which is used to calculate the outlier criticality probability of each cluster's past parameters based on past parameters and current parameters; A hierarchy module, which is used to calculate the barrier hierarchy of the parameters when they appear based on the probability of the outlier criticality of the past parameters of each cluster; A notification module is used to obtain the most recent prior notification amount according to the obstacle level of the current parameter.

Images