Intelligent power supply monitoring method and system for airport power supply vehicle

Abstract

The present invention discloses an intelligent power supply monitoring method and system for an airport power supply vehicle, the method comprising: obtaining the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, obtaining the secondary power supply parameters of the airport power supply vehicle and the secondary charging parameters of the charging equipment; fitting the primary curve, initializing the primary threshold, and determining the difference interval; within the difference interval, calculating the information entropy of the effective local characteristics of each secondary parameter; judging the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment by the power supply consistency value, the charging consistency value and the rational model threshold; updating the primary threshold by the residual mean of the primary power supply parameters of the airport power supply vehicle and the primary power supply parameters of the charging equipment. The present invention adopts a secondary monitoring method to monitor the status of the airport power supply vehicle and the charging equipment during the power supply process, improves the monitoring accuracy, reduces the computing power loss, regularly updates the primary threshold, and further improves the intelligence level of the scheme.

Description

Technical Field

[0001] The invention relates to the technical field of power supply monitoring, and in particular to an intelligent power supply monitoring method and system for an airport power supply vehicle. Background Art

[0002] Aircraft have become an indispensable means of transportation in today's society due to their speed and convenience. As an important part of maintaining the operation and maintenance of aviation airports, airport power supply vehicles are playing an increasingly important role in power operation and maintenance, power supply, and airport power monitoring.

[0003] In order to achieve better power supply effect for airport power supply vehicles, it is necessary to monitor the power supply status of airport power supply vehicles in real time. Traditional airport power supply monitoring uses a single sensor to collect signal points, and uses differentiated information from the data to find the time when the fault occurs, or through deep learning, after a lot of training, further judgment of the data is achieved. Although the above methods can realize the function of power supply monitoring of airport power supply vehicles, on the one hand, traditional single sensor monitoring lacks local feature extraction, which leads to monitoring errors. The deep learning method requires high computing power and requires a large amount of data as support in the early stage, which is relatively complicated. Therefore, it is necessary to propose a new power supply monitoring method for airport power supply vehicles. Summary of the invention

[0004] The invention aims to solve the technical problem that the power supply monitoring efficiency of the airport power supply vehicle is low and it is difficult to find the fault time point in time.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] An intelligent power supply monitoring method for an airport power supply vehicle, comprising:

[0007] S1: Obtaining primary parameters, including primary power supply parameters of the airport power supply vehicle and primary charging parameters of the charging equipment, and obtaining secondary parameters, including secondary power supply parameters of the airport power supply vehicle and secondary charging parameters of the charging equipment;

[0008] The first-level power supply parameter is the power supply current of the airport power supply vehicle The first-level charging parameter is the charging current of the charging device. The secondary power supply parameter is the power supply voltage of the airport power supply vehicle. , Power supply and power supply operating frequency The secondary charging parameter is the charging voltage of the charging device. , Charging power and charging frequency ; Where J represents the airport power supply vehicle, S represents the charging equipment, and I represents the current. represents voltage, P represents power, and F represents frequency;

[0009] It should be noted that the present invention uses multiple parameters such as the primary power supply parameters of the airport power supply vehicle, the primary charging parameters of the charging equipment, the secondary power supply parameters of the airport power supply vehicle and the secondary charging parameters of the charging equipment to realize the intelligent power supply monitoring of the airport power supply vehicle, thereby realizing multi-dimensional monitoring of the power supply process, which can improve the accuracy of power supply monitoring;

[0010] S2: Fit the first-level curve with the first-level parameters, initialize the first-level threshold, and determine the difference interval;

[0011] S3: within the difference interval, calculate the local features of the secondary power supply parameters and the local features of the secondary charging parameters, perform secondary screening on the local features of each secondary parameter to obtain effective local features, and calculate the information entropy of the effective local features of the secondary power supply parameters and the information entropy of the effective local features of the secondary charging parameters;

[0012] The local characteristics of the secondary power supply parameters and the local characteristics of the secondary charging parameters are calculated as follows:

[0013] (1) Select the value of the secondary parameter at the i-th moment in the difference interval time in sequence , where V represents the secondary parameter category, ;

[0014] (2) Selection and The most recent h values , and by Construct a set of adjacent values ​​A;

[0015] (3) Calculation and the residual sum of each value of the adjacent value set A , where j represents an integer;

[0016] (4) Calculate the local eigenvalues ​​of each secondary parameter at the i-th moment in the difference interval time :

[0017] ;

[0018] S4: Construct a consistency monitoring method based on multi-dimensional information entropy, calculate the power supply consistency value and charging consistency value, initialize the rational model threshold, and judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment based on the power supply consistency value, charging consistency value and rational model threshold;

[0019] S5: Update the first-level threshold value by the residual mean of the first-level power supply parameters of the airport power supply vehicle and the first-level power supply parameters of the charging equipment, and publish the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment.

[0020] Furthermore, the step S2 comprises:

[0021] Assume the total charging time is n, then the primary power supply parameters of the airport power supply vehicle are The specific expression is: , primary power supply parameters of charging equipment The specific expression is: , where i is an integer;

[0022] Calculate the residual of the primary power supply parameters of the power supply vehicle and the primary charging parameters of the charging equipment at the i-th moment , the specific expression is as follows:

[0023] ;

[0024] in, Represents the residuals of the airport power supply vehicle and charging equipment;

[0025] Then calculate the residual of the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment during the total charging time ,Depend on Fitting the first-order curve;

[0026] Initialize the first level threshold , fitting the first-order threshold curve;

[0027] The difference between the first-order curve and the first-order threshold curve , fit the primary diagnostic curve, the first point greater than zero in the primary diagnostic curve is taken as the starting point of the difference interval, and the time corresponding to the starting point is the starting time of the difference interval The first point in the primary diagnostic curve that is less than or equal to zero is taken as the end point of the difference interval, and the time corresponding to the end point is the end time of the difference interval. , and then the difference interval time can be determined, where , Represents the total number of moments in the difference interval.

[0028] It should be noted that the present invention further determines the difference interval by fitting the primary diagnostic curve. By fitting the primary curve and the primary threshold curve, the difference interval can be intuitively reflected on the image. In terms of data calculation, by processing the data within the difference interval, the computing power of invalid information can be reduced, thereby improving the computing efficiency of power supply monitoring.

[0029] Furthermore, the secondary screening of the local features of each secondary parameter to obtain effective local features in step S3 includes the following steps:

[0030] Set the flag of the local features of each secondary parameter , traverse the local characteristics of each secondary parameter in the difference interval, if and , and , and If the values ​​at time i are all 0, FLAG is equal to 1, otherwise FLAG is equal to 0. The specific expression is as follows:

[0031] ;

[0032] ;

[0033] Will The local features of the secondary parameters are taken as the effective local features of the secondary parameters, and the effective local feature set of the secondary parameters in the difference interval is reconstructed, and the effective local features of the secondary parameters in the effective local feature set of the secondary parameters are reordered. It is assumed that the total number of effective local features of the secondary parameters is c.

[0034] It should be noted that in the actual calculation process, the data itself is related to the surrounding data. In the difference range, through secondary screening, the normal data can be further screened out, thereby improving the detection efficiency of abnormal data and realizing real-time monitoring of abnormal data. For this solution, the time point and approximate cause of the fault can be quickly discovered, and the intelligent monitoring of the power supply of the airport power supply vehicle can be realized without too much data reference;

[0035] Furthermore, the step S3 of calculating the information entropy of the effective local characteristics of the secondary power supply parameters and the information entropy of the effective local characteristics of the secondary charging parameters includes the following steps:

[0036] (1) Calculate the covariance matrix of the effective local features of the secondary parameters within the difference interval and mean ;

[0037] (2) Calculate the prior probability density function of the effective local characteristics of the secondary parameters , the specific expression is as follows:

[0038] ;

[0039] Where T represents the transposition operator. represents an exponential function with base e;

[0040] (3) Calculate the information entropy of the effective local features of the secondary parameters. The specific expression is as follows:

[0041] ;

[0042] in, represents the logarithmic function with base e, Express Find the integral. ∫ represents the integral operation.

[0043] It should be noted that the traditional method directly calculates the power supply parameters. In this solution, by extracting effective local features, the power supply parameters can be screened again, thereby further locking in the data with differences and improving the accuracy of power supply monitoring.

[0044] Furthermore, the step S4 comprises:

[0045] Construct a consistency monitoring method of multi-dimensional information entropy and initialize the multi-dimensional threshold Q, where , is the threshold coefficient;

[0046] Calculate the power supply consistency value ,in , It represents the i-th power supply consistency value within the difference interval. The specific expression is as follows:

[0047] ;

[0048] Calculate the charging consistency value ,in , It represents the i-th charging consistency value within the difference interval. The specific expression is as follows:

[0049] ;

[0050] Initialize rational model threshold ;

[0051] Sort the power supply consistency values ​​in ascending order ;

[0052] Sort the charging consistency values ​​in ascending order ;

[0053] The power supply consistency value, charging consistency value and rational model threshold are used to judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment, as follows:

[0054] (1) If Greater than or equal to and Greater than or equal to , indicating that there is a fault in the interface between the airport power supply vehicle and the charging equipment, and it is necessary to check the interface between the airport power supply vehicle and the charging equipment at the i-th moment in the difference interval;

[0055] (2) If Greater than or equal to , indicating that there is a fault in the airport power supply vehicle, and it is necessary to check the airport power supply vehicle at the i-th moment in the difference interval;

[0056] (3) If Greater than or equal to , indicating that there is a fault in the charging equipment, and it is necessary to check the charging equipment at the i-th moment in the difference interval;

[0057] (4) If Less than , indicating that the airport power supply vehicle is in good condition;

[0058] (5) If Less than , indicating that the charging device is charging healthily.

[0059] It should be noted that this solution can determine the different power supply states of the airport power supply vehicle by calculating the power supply consistency value and the charging consistency value, which is convenient for engineers to maintain and service the airport power supply vehicle or charging equipment.

[0060] Furthermore, the step S5 comprises:

[0061] Initialize the update period L of the first-level threshold;

[0062] After the update cycle of the first-level threshold, the residual mean of the first-level power supply parameters of the power supply vehicle and the first-level power supply parameters of the charging equipment is calculated. ;

[0063] Update the first level threshold ,in ;

[0064] Publish the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment.

[0065] It should be noted that in this scheme, by regularly updating the first-level threshold, dynamic changes of the first-level threshold can be achieved, which is more in line with the actual conditions of on-site operation of the airport power supply vehicle, avoids monitoring and judgment errors caused by fixed thresholds, and thus improves the accuracy of this scheme.

[0066] The present invention also provides an intelligent power supply monitoring system for an airport power supply vehicle, comprising the following modules:

[0067] Information acquisition module: obtains the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, obtains the secondary power supply parameters of the airport power supply vehicle and the secondary charging parameters of the charging equipment;

[0068] Local feature calculation module: fit the primary curve with the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, initialize the primary threshold, and determine the difference interval; within the difference interval, calculate the local features of the secondary power supply parameters and the local features of the secondary charging parameters, perform secondary screening on the local features of each secondary parameter to obtain effective local features, and calculate the information entropy of the effective local features of the secondary power supply parameters and the information entropy of the effective local features of the secondary charging parameters;

[0069] Health judgment module: Construct a consistency monitoring method of multi-dimensional information entropy, calculate the power supply consistency value and charging consistency value, initialize the rational model threshold, and judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment based on the power supply consistency value, charging consistency value and rational model threshold;

[0070] Threshold update module: The first-level threshold is updated by the residual mean of the first-level power supply parameters of the airport power supply vehicle and the first-level power supply parameters of the charging equipment, and the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment are released.

[0071] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0072] 1. The present invention adopts a secondary monitoring method to monitor the status of the airport power supply vehicle and the charging equipment during the power supply process. First, by monitoring the primary power supply parameters and the primary charging parameters, the difference interval is quickly determined, and the primary screening of the monitoring data is completed to reduce the amount of data monitored in the later stage. Then, by extracting the local characteristics of the secondary power supply parameters and the secondary charging parameters, the information entropy of the secondary power supply parameters and the secondary charging parameters is calculated, and the secondary screening of the monitoring data is completed. Finally, by designing a consistency monitoring algorithm of multi-dimensional information entropy, the health status of the airport power supply vehicle and the charging equipment is obtained, and the primary threshold is updated regularly. Compared with the traditional power supply monitoring method of the airport power supply vehicle, the present method can realize the rapid locking of the difference interval. Through secondary screening, the computing power loss of the monitoring task is further reduced, the computing efficiency of the method is improved, and the hardware cost is reduced. The accuracy of power supply monitoring can be improved through secondary monitoring.

[0073] 2. The present invention quickly determines the difference interval by monitoring the first-level power supply parameters and the first-level charging parameters, and further performs a second data monitoring and calculation in the difference interval. Compared with the traditional scheme, the calculation efficiency of this scheme is higher. By setting the update cycle of the first-level threshold, the first-level threshold is updated regularly. Compared with the fixed threshold scheme, this scheme has stronger adaptability and higher intelligence level, while avoiding the risk of inaccurate judgment due to the fixed threshold, further improving the monitoring accuracy.

[0074] 3. After the first monitoring, further conduct secondary monitoring on the difference interval, and complete the screening of the effective local characteristics of the secondary power supply parameters of the airport power supply vehicle and the effective local characteristics of the secondary charging parameters of the charging equipment, further reduce the number of data that need to be calculated, design a consistency monitoring algorithm for multi-dimensional information entropy, and realize the joint monitoring of multi-dimensional information entropy. Compared with the existing methods, the scheme can reduce the calculation of unnecessary data through secondary data screening, reduce the interference of redundant information, improve the real-time and accuracy of the method, and thus improve the intelligence level of this scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0076] Figure 1 This is a flow chart of an intelligent power supply monitoring method for an airport power supply vehicle provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0077] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0078] Example 1

[0079] This embodiment will be described in more detail with reference to the accompanying drawings. Figure 1 As shown, an intelligent power supply monitoring method for an airport power supply vehicle comprises the following steps:

[0080] Step S1: obtaining primary parameters, including primary power supply parameters of the airport power supply vehicle and primary charging parameters of the charging equipment, and obtaining secondary parameters, including secondary power supply parameters of the airport power supply vehicle and secondary charging parameters of the charging equipment; including:

[0081] The primary power supply parameter of the airport power supply vehicle is the power supply current of the airport power supply vehicle during the power supply process. , where I represents current and J represents the airport power supply vehicle;

[0082] The primary charging parameter of the charging device is the charging current of the charging device during the charging process. , where S represents the charging device;

[0083] The secondary power supply parameter of the airport power supply vehicle is the power supply voltage of the airport power supply vehicle during the power supply process. , Power supply and power supply operating frequency , where U represents voltage, P represents power, and F represents frequency;

[0084] The secondary charging parameter of the charging device is the charging voltage of the charging device during the charging process. , Charging power and charging frequency ;

[0085] The acquired primary and secondary parameters are uploaded to the monitoring center in real time.

[0086] It should be noted that the present invention adopts multiple parameters such as the first-level power supply parameters of the airport power supply vehicle, the first-level charging parameters of the charging equipment, the second-level power supply parameters of the airport power supply vehicle and the second-level charging parameters of the charging equipment to realize intelligent power supply monitoring of the airport power supply vehicle, and then realize multi-dimensional monitoring of the power supply process, which can improve the accuracy of power supply monitoring.

[0087] Step S2: fitting a primary curve based on the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, initializing the primary threshold, and determining the difference interval; including:

[0088] Assume the total charging time is n, then the primary power supply parameters of the airport power supply vehicle are The specific expression is: , primary power supply parameters of charging equipment The specific expression is: , where i is an integer;

[0089] Calculate the residual of the primary power supply parameters of the power supply vehicle and the primary charging parameters of the charging equipment at the i-th moment , the specific expression is as follows:

[0090] ;

[0091] in, Represents the residuals of the airport power supply vehicle and charging equipment;

[0092] Then calculate the residual of the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment during the total charging time ,Depend on Fitting the first-order curve;

[0093] Initialize the first level threshold , fitting the first-order threshold curve;

[0094] It should be noted that the first-level threshold in this scheme According to historical experience, in actual operation, the threshold can be set according to the actual condition of the airport power supply vehicle. If the airport power supply vehicle has many faults, the first-level threshold can be set smaller than the historical experience. If the airport power supply vehicle has few faults, the first-level threshold can be set larger than the historical experience.

[0095] The difference between the first-order curve and the first-order threshold curve , fit the primary diagnostic curve, the first point greater than zero in the primary diagnostic curve is taken as the starting point of the difference interval, and the time corresponding to the starting point is the starting time of the difference interval The first point in the primary diagnostic curve that is less than or equal to zero is taken as the end point of the difference interval, and the time corresponding to the end point is the end time of the difference interval. , and then the difference interval time can be determined, where , Represents the total number of moments in the difference interval.

[0096] Step S3: within the difference interval, calculating the local features of the secondary power supply parameters of the power supply vehicle of the power supply vehicle, calculating the local features of the secondary charging parameters of the charging equipment, performing secondary screening on the local features of each secondary parameter to obtain the effective local features of each secondary parameter, calculating the information entropy of the effective local features of the secondary power supply parameters of the power supply vehicle of the power supply vehicle, and calculating the information entropy of the effective local features of the secondary charging parameters of the charging equipment; including:

[0097] Calculate the local characteristics of each secondary parameter:

[0098] (1) Select the value of the secondary parameter at the i-th moment in the difference interval time in sequence , where V represents the secondary parameter category, ;

[0099] (2) Selection and The most recent h values , and by Construct a set of adjacent values ​​A;

[0100] (3) Calculation and the residual sum of each value of the adjacent value set A ;

[0101] (4) Calculate the local characteristics of each secondary parameter at the i-th moment in the difference interval time , the specific expression is as follows:

[0102] ;

[0103] Among them, j is an integer, h is an integer, and The number of recent values;

[0104] Secondary screening of the local features of each secondary parameter is performed to obtain effective local features:

[0105] Set the flag of the local features of each secondary parameter , traverse the local characteristics of each secondary parameter in the difference interval time, if and , and , and If the values ​​at time i are all 0, FLAG is equal to 1, otherwise FLAG is equal to 0. The specific expression is as follows:

[0106] ;

[0107] ;

[0108] in, Indicates other situations;

[0109] Will The local features of the secondary parameters are taken as the effective local features of the secondary parameters, and the effective local feature set of the secondary parameters in the difference interval time is reconstructed, and the effective local features of the secondary parameters in the effective local feature set of the secondary parameters are reordered. Let the total number of effective local features of the secondary parameters be c;

[0110] Calculate the information entropy of the effective local features of each secondary parameter:

[0111] (1) Calculate the covariance matrix of the effective local features of the secondary parameters within the difference interval time and mean ;

[0112] (2) Calculate the prior probability density function of the effective local characteristics of the secondary parameters , the specific expression is as follows:

[0113] ;

[0114] Where T represents the transposition operator. represents an exponential function with base e;

[0115] (3) Calculate the information entropy of the effective local features of the secondary parameters. The specific expression is as follows:

[0116] ;

[0117] in, represents the logarithmic function with base e, Express Find the integral. ∫ represents the integral operation.

[0118] It should be noted that, in this solution, by screening and calculating effective local features, invalid information can be further screened out, thereby improving the calculation efficiency of this solution.

[0119] Step S4: construct a consistency monitoring method of multi-dimensional information entropy, calculate the power supply consistency value and the charging consistency value, initialize the rational model threshold, and judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment by the power supply consistency value, the charging consistency value and the rational model threshold; including:

[0120] Construct a consistency monitoring method of multi-dimensional information entropy and initialize the multi-dimensional threshold Q, where , is the threshold coefficient;

[0121] Calculate the power supply consistency value ,in , It represents the i-th power supply consistency value within the difference interval time. The specific expression is as follows:

[0122] ;

[0123] Calculate the charging consistency value ,in , It represents the i-th charging consistency value within the difference interval time. The specific expression is as follows:

[0124] ;

[0125] Initialize rational model threshold ;

[0126] Sort the power supply consistency values ​​in ascending order ;

[0127] Sort the charging consistency values ​​in ascending order ;

[0128] The power supply consistency value, charging consistency value and rational model threshold are used to judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment, as follows:

[0129] (1) If Greater than or equal to and Greater than or equal to , indicating that there is a fault in the interface between the airport power supply vehicle and the charging device, and it is necessary to check the interface between the airport power supply vehicle and the charging device at the i-th moment in the difference interval time;

[0130] (2) If Greater than or equal to , indicating that there is a fault in the airport power supply vehicle, and it is necessary to check the airport power supply vehicle at the i-th moment in the difference interval time;

[0131] (3) If Greater than or equal to , indicating that there is a fault in the charging equipment, and it is necessary to check the charging equipment at the i-th moment in the difference interval time;

[0132] (4) If Less than , indicating that the airport power supply vehicle is supplying healthy power;

[0133] (5) If Less than , indicating that the charging device is charging healthily.

[0134] Step S5: updating the primary threshold value by the residual mean of the primary power supply parameters of the airport power supply vehicle and the primary power supply parameters of the charging equipment, and publishing the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment; including:

[0135] Initialize the update period L of the first-level threshold;

[0136] After the update cycle of the first-level threshold, the residual mean of the first-level power supply parameters of the power supply vehicle and the first-level power supply parameters of the charging equipment is calculated. ;

[0137] Update the first level threshold ,in ;

[0138] Publish the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment.

[0139] It should be noted that the update of the first-level threshold in this scheme means updating the first-level threshold once after each update cycle of the first-level threshold. Compared with the fixed threshold scheme, this scheme can be adjusted according to the real-time power supply of the airport power supply vehicle, thereby improving the intelligence level of this scheme.

[0140] Example 2

[0141] This embodiment also provides an intelligent power supply monitoring system for an airport power supply vehicle, including:

[0142] Information acquisition module: obtains the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, obtains the secondary power supply parameters of the airport power supply vehicle and the secondary charging parameters of the charging equipment;

[0143] Local feature calculation module: fit the primary curve with the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, initialize the primary threshold, and determine the difference interval; within the difference interval, calculate the local features of the secondary power supply parameters and the local features of the secondary charging parameters, perform secondary screening on the local features of each secondary parameter to obtain effective local features, and calculate the information entropy of the effective local features of the secondary power supply parameters and the information entropy of the effective local features of the secondary charging parameters;

[0144] Health judgment module: Construct a consistency monitoring method of multi-dimensional information entropy, calculate the power supply consistency value and charging consistency value, initialize the rational model threshold, and judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment based on the power supply consistency value, charging consistency value and rational model threshold;

[0145] Threshold update module: The first-level threshold is updated by the residual mean of the first-level power supply parameters of the airport power supply vehicle and the first-level power supply parameters of the charging equipment, and the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment are released.

[0146] The intelligent power supply monitoring system for an airport power supply vehicle of the present embodiment corresponds to the intelligent power supply monitoring method for an airport power supply vehicle of the above embodiment; wherein, the functions implemented by each functional module in the intelligent power supply monitoring system for an airport power supply vehicle of the present embodiment correspond one-to-one to each process step in the intelligent power supply monitoring method for an airport power supply vehicle of the above embodiment; therefore, they will not be repeated here.

[0147] It should be noted that the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. And the terms "including", "comprising" or any other variants thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0148] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0149] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An intelligent power supply monitoring method for an airport power supply vehicle, characterized in that: The following steps are involved: S1: Obtaining primary parameters, including primary power supply parameters of the airport power supply vehicle and primary charging parameters of the charging equipment, and obtaining secondary parameters, including secondary power supply parameters of the airport power supply vehicle and secondary charging parameters of the charging equipment; The first-level power supply parameter is the power supply current of the airport power supply vehicle The first-level charging parameter is the charging current of the charging device. The secondary power supply parameter is the power supply voltage of the airport power supply vehicle. , Power supply and power supply operating frequency The secondary charging parameter is the charging voltage of the charging device. , Charging power and charging frequency ; Where J represents the airport power supply vehicle, S represents the charging equipment, and I represents the current. represents voltage, P represents power, and F represents frequency; S2: Fit the first-level curve with the first-level parameters, initialize the first-level threshold, and determine the difference interval; S3: within the difference interval, calculate the local features of the secondary power supply parameters and the local features of the secondary charging parameters, perform secondary screening on the local features of each secondary parameter to obtain effective local features, and calculate the information entropy of the effective local features of the secondary power supply parameters and the information entropy of the effective local features of the secondary charging parameters; The calculating of the local characteristics of the secondary power supply parameters and the local characteristics of the secondary charging parameters comprises the following steps: (1) Select the value of the secondary parameter at the i-th moment in the difference interval in sequence , where V represents the secondary parameter category, ; (2) Selection and The most recent h values , and by Construct a set of adjacent values ​​A; (3) Calculation and the residual sum of each value of the adjacent value set A , where j represents an integer; (4) Calculate the local eigenvalues ​​of each secondary parameter at the i-th moment within the difference interval : ； The total number of effective local features obtained by secondary screening of the local features of each secondary parameter is c; The calculating of the information entropy of the effective local characteristics of the secondary power supply parameters and the information entropy of the effective local characteristics of the secondary charging parameters comprises the following steps: (1) Calculate the covariance matrix of the effective local features of the secondary parameters within the difference interval time and mean ; (2) Calculate the prior probability density function of the effective local characteristics of the secondary parameters , the specific expression is as follows: ； Where T represents the transposition operator. represents an exponential function with base e; (3) Calculate the information entropy of the effective local features of the secondary parameters. The specific expression is as follows: ； in, represents the logarithmic function with base e, Express Find the integral, ∫ represents the integral operation; S4: Construct a consistency monitoring method of multi-dimensional information entropy, calculate the power supply consistency value and the charging consistency value, initialize the rational model threshold, and judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment by the power supply consistency value, the charging consistency value and the rational model threshold; including the following steps: Construct a consistency monitoring method of multi-dimensional information entropy and initialize the multi-dimensional threshold Q, where , is the threshold coefficient; Calculate the power supply consistency value ,in , It represents the i-th power supply consistency value within the difference interval. The specific expression is as follows: ； Calculate the charging consistency value ,in , It represents the i-th charging consistency value within the difference interval. The specific expression is as follows: ； Initialize rational model threshold ; Sort the power supply consistency values ​​in ascending order ; Sort the charging consistency values ​​in ascending order ; The power supply consistency value, charging consistency value and rational model threshold are used to judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment, as follows: (1) If Greater than or equal to and Greater than or equal to , indicating that there is a fault in the interface between the airport power supply vehicle and the charging equipment, and it is necessary to check the interface between the airport power supply vehicle and the charging equipment at the i-th moment in the difference interval; (2) If Greater than or equal to , indicating that there is a fault in the airport power supply vehicle, and it is necessary to check the airport power supply vehicle at the i-th moment in the difference interval; (3) If Greater than or equal to , indicating that there is a fault in the charging equipment, and it is necessary to check the charging equipment at the i-th moment in the difference interval; (4) If Less than , indicating that the airport power supply vehicle is supplying healthy power; (5) If Less than , indicating that the charging device is charging healthily; S5: Update the first-level threshold value by the residual mean of the first-level power supply parameters of the airport power supply vehicle and the first-level power supply parameters of the charging equipment, and publish the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment.

2. The intelligent power supply monitoring method for an airport power supply vehicle according to claim 1 is characterized in that: The step S2 comprises: Assume the total charging time is n, then the primary power supply parameters of the airport power supply vehicle are The specific expression is: , primary power supply parameters of charging equipment The specific expression is: , where i is an integer; Calculate the residual of the primary power supply parameters of the power supply vehicle and the primary charging parameters of the charging equipment at the i-th moment , the specific expression is as follows: ； in, Represents the residuals of the airport power supply vehicle and charging equipment; Then calculate the residual of the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment during the total charging time ,Depend on Fitting the first-order curve; Initialize the first level threshold , fitting the first-order threshold curve; The difference between the first-order curve and the first-order threshold curve , fit the primary diagnostic curve, the first point greater than zero in the primary diagnostic curve is taken as the starting point of the difference interval, and the time corresponding to the starting point is the starting time of the difference interval The first point in the primary diagnostic curve that is less than or equal to zero is taken as the end point of the difference interval, and the time corresponding to the end point is the end time of the difference interval. , and then the difference interval time can be determined, where , Represents the total number of moments in the difference interval.

3. According to the intelligent power supply monitoring method of the airport power supply vehicle of claim 1, the secondary screening of the local features of each secondary parameter to obtain effective local features in step S3 comprises the following steps: Set the flag of the local features of each secondary parameter , traverse the local characteristics of each secondary parameter in the difference interval time, if and , and , and If the values ​​at time i are all 0, FLAG is equal to 1, otherwise FLAG is equal to 0. The specific expression is as follows: ； ； Will The local features of the secondary parameters are taken as the effective local features of the secondary parameters, and the effective local feature set of the secondary parameters in the difference interval time is reconstructed, and the effective local features of the secondary parameters in the effective local feature set of the secondary parameters are reordered. It is assumed that the total number of effective local features of the secondary parameters is c.

4. The intelligent power supply monitoring method for an airport power supply vehicle according to claim 1, characterized in that: The step S5 comprises: Initialize the update period L of the first-level threshold; After the update cycle of the first-level threshold, the residual mean of the first-level power supply parameters of the power supply vehicle and the first-level power supply parameters of the charging equipment is calculated. ; Update the first level threshold ,in ; Publish the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment.

5. An intelligent power supply monitoring system for an airport power supply vehicle, characterized in that: include: Information acquisition module: obtains the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, obtains the secondary power supply parameters of the airport power supply vehicle and the secondary charging parameters of the charging equipment; Local feature calculation module: fit the primary curve with the primary power supply parameters of the airport power supply vehicle and the primary charging parameters of the charging equipment, initialize the primary threshold, and determine the difference interval; within the difference interval, calculate the local features of the secondary power supply parameters and the local features of the secondary charging parameters, perform secondary screening on the local features of each secondary parameter to obtain effective local features, and calculate the information entropy of the effective local features of the secondary power supply parameters and the information entropy of the effective local features of the secondary charging parameters; Health judgment module: Construct a consistency monitoring method of multi-dimensional information entropy, calculate the power supply consistency value and charging consistency value, initialize the rational model threshold, and judge the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment based on the power supply consistency value, charging consistency value and rational model threshold; Threshold update module: updates the primary threshold value by the residual mean of the primary power supply parameters of the airport power supply vehicle and the primary power supply parameters of the charging equipment, and publishes the power supply health status of the airport power supply vehicle and the charging health status of the charging equipment; To realize the intelligent power supply monitoring method of the airport power supply vehicle as described in any one of claims 1-4.

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