A relay life management method and system based on cloud edge collaboration

Abstract

The application discloses a relay life management method and system based on cloud-edge cooperation, which comprises a cloud end and a plurality of edge layers in communication connection with the cloud end, the edge layers comprising a test reference unit and a data acquisition unit, and the cloud end comprising a weighted processing unit. The application obtains safety test data of the effective opening and closing times of different models of relays under standard temperature and humidity, and standardizes the test data to obtain life standardized weight data of the corresponding models of relays. Real-time operation parameters of the relays are acquired, the relays are identified based on the data, fitting information between adjacent two actions is recorded, the fitting information is divided into standard time periods, a standard gradient is determined to obtain a weighted reference number, weighted weight calculation is performed based on the standard gradient and the weighted reference number, the life weight of the relay is updated according to the optimized weight, the remaining effective opening and closing times of the relay are calculated by using the updated life weight, and the life management of the relay is realized.

Description

Technical Field

[0001] This invention relates to the technical field of relays, and in particular to a relay lifespan management method and system based on cloud-edge collaboration. Background Technology

[0002] A relay is an electrical control device that, when the input quantity reaches a specified value, causes a predetermined step change in the controlled quantity or changes the on / off state of the controlled circuit. Relays are generally composed of electromagnets, springs, electrical contacts, etc., and are used in electrical appliances in protection devices, automatic control systems, and communication equipment. They are usually used to transmit signals and control multiple circuits simultaneously, and can also be used directly to control small-capacity motors or other electrical actuators.

[0003] Existing methods for improving relay reliability and ensuring the stable and effective operation of related electronic systems are of great significance. However, relay life prediction mainly focuses on analyzing individual characteristic parameters, while the analysis of the overall failure mechanism is not in-depth enough. This results in an inability to accurately reflect the relay life and a lack of effective prediction of relay life, especially in complex operating environments such as those with varying temperatures, humidity, and load intensities. The lack of effective assessment of the remaining effective switching counts leads to an inability to accurately evaluate the remaining effective service life of the relay. Therefore, this paper proposes a cloud-edge collaborative relay life management system and method that considers the impact of complex environments on the effective switching counts of relays, enabling the assessment of the remaining effective switching counts of relays. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a relay life management method and system based on cloud-edge collaboration to solve the problem of lacking an effective assessment of the remaining effective opening and closing counts of relays under different environments with varying temperatures, humidity, and load intensities.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0008] In a first aspect, embodiments of the present invention provide a relay life management method based on cloud-edge collaboration, including: acquiring safety test data on the effective opening and closing times of relays of different models under standard temperature and humidity, and standardizing the test data to obtain life standardized weight data of the corresponding relay models;

[0009] Collect real-time operating parameters of the relay, identify relay actions based on the data, record fitting information between two adjacent actions, divide the fitting information into standard time periods, determine the standard gradient, and obtain the weighted reference number.

[0010] The weighted weights are calculated based on the standard gradient and the weighted reference number. The lifetime weight of the relay is updated according to the optimized weights. The remaining effective opening and closing times of the relay are calculated using the updated lifetime weights.

[0011] As a preferred embodiment of the relay life management method based on cloud-edge collaboration described in this invention, the safety test data for the effective opening and closing counts of different relay models under standard temperature and humidity includes: the effective opening and closing counts under standard temperature and humidity, as mechanical reference counts; the effective opening and closing counts under different temperature gradients at standard humidity, the temperature reference counts; the effective opening and closing counts under different humidity gradients at standard temperature, as humidity reference counts; and the effective opening and closing counts under different load gradients at standard temperature and humidity, as load reference counts.

[0012] As a preferred embodiment of the cloud-edge collaborative relay lifespan management method described in this invention, the standardization processing of the test data to obtain the lifespan standardized weight data of the corresponding relay model includes: obtaining the lifespan standardized weight data of the corresponding relay model as follows:

[0013] A:B k :C s :D t =W A :W B :W C :W D

[0014] In the formula, A represents the number of mechanical references, and W... A For mechanical reference weights, B k Let W be the temperature reference number under the k-th temperature gradient. B C represents the temperature reference weight under the k-th temperature gradient. s Let W be the humidity reference number under the s-th humidity gradient. C Let D be the humidity reference weight under the s-th humidity gradient. t Let W be the load reference number under the t-th load gradient. DThe load reference weight.

[0015] As a preferred embodiment of the relay life management method based on cloud-edge collaboration described in this invention, the following steps are included: collecting real-time operating parameters of the relay, identifying relay actions based on the data, and recording fitting information between two adjacent actions: the real-time operating parameters of the relay include opening and closing time, load electrical quantity, ambient temperature, and ambient humidity.

[0016] The number of times the relay opens and closes is determined based on the opening and closing time, and each opening and closing is considered as one action. The load electrical quantity, ambient temperature and ambient humidity data between two adjacent actions are selected as fitting information before the next action occurs.

[0017] As a preferred embodiment of the relay lifespan management method based on cloud-edge collaboration described in this invention, the following steps are taken: dividing the fitted information into standard time periods and determining the weighted reference number of standard gradients include: dividing the fitted information into standard time periods and obtaining the gradient information corresponding to the fitted information under different standard time periods; counting the number of times the same gradient appears in all gradient information in the fitted information; determining the gradient with the highest number of times the same gradient appears as the standard gradient of the fitted information; and using the number of times the gradient information appears higher than the standard gradient as the weighted reference number.

[0018] The weighted reference times are used to calculate the weighted weights, which is expressed as follows:

[0019]

[0020] Among them, W Bn W is the weighted average of the temperature reference weights under the standard gradient. B1 W is the weighted reference number when the standard gradient is the corresponding temperature gradient. Cn W is the weighted average of the humidity reference weights under the standard gradient. C1 W is the weighted reference number when the standard gradient is the corresponding humidity gradient. Dn W is the weighted average of the load reference weights under the standard gradient. D1 β is the weighted reference number when the standard gradient is the corresponding load gradient, and β is the weight adjustment factor.

[0021] As a preferred embodiment of the cloud-edge collaborative relay lifespan management method described in this invention, the method for updating the relay lifespan weight according to the optimized weight includes: the calculation method for updating the relay lifespan weight is as follows:

[0022] A P :B kP :C sP :D tP

[0023] =(W A-W Bn -W Cn -W Dn ):(W BP +W Bn ):(W CP +W Cn ):(W DP +W Dn )

[0024] Among them, A P For the updated mechanical reference weights, B kP For the updated temperature reference weights, C sP For the updated humidity reference weights, D tP The updated load reference weights;

[0025] The remaining effective number of opening and closing cycles is calculated as follows:

[0026]

[0027] Where Z represents the remaining effective number of times the relay can be switched on and off, and B represents the number of times the relay can be switched on and off. kn C is the temperature reference number corresponding to the standard gradient. sn D is the number of humidity references corresponding to the standard gradient. tn This is the load reference number corresponding to the standard gradient.

[0028] Secondly, the present invention provides a relay life management system based on cloud-edge collaboration, comprising: a cloud, and several edge layers communicating with the cloud; the cloud includes a weighted processing unit, which is used to evaluate and calculate the remaining effective opening and closing counts of the relay based on a standard gradient and a weighted reference count;

[0029] The edge layer includes a test reference unit and a data acquisition unit; the test reference unit is used to perform safety tests on different models of relays, acquire test data, and acquire life-standardized weight data of the corresponding model of relay.

[0030] The data acquisition unit is used to acquire relay operating parameters near the relay side and to perform statistics on standard gradient and weighted reference times.

[0031] As a preferred embodiment of the cloud-edge collaborative relay life management system described in this invention, the test reference unit further includes a test recording module and a standardization processing module, wherein the test recording module is connected to the standardization processing module.

[0032] The test recording module is used to perform safety tests on different models of relays and acquire test data. The test data includes the effective opening and closing times under standard temperature and standard humidity, which are used as mechanical reference times; the effective opening and closing times under different temperature gradients under standard humidity, which are used as temperature reference times; the effective opening and closing times under different humidity gradients under standard temperature, which are used as humidity reference times; and the effective opening and closing times under different load gradients under standard temperature and standard humidity, which are used as load reference times.

[0033] The standardization processing module is used to standardize the test data and obtain the lifespan standardized weight data for the corresponding relay model:

[0034] A:B k :C s :D t =W A :W B :W C :W D

[0035] Where A is the number of mechanical references, W A For mechanical reference weights, B k Let W be the temperature reference number under the k-th temperature gradient. B C represents the temperature reference weight under the k-th temperature gradient. s Let W be the humidity reference number under the s-th humidity gradient. C Let D be the humidity reference weight under the s-th humidity gradient. t Let W be the load reference number under the t-th load gradient. D The load reference weight.

[0036] As a preferred embodiment of the cloud-edge collaborative relay life management system described in this invention, the data acquisition unit further includes: a data acquisition classification module, an integrated fitting module, a limit comparison module, and a counting module. The data acquisition classification module is connected to the integrated fitting module, the integrated fitting module is connected to the limit comparison module, and the limit comparison module is connected to the counting module.

[0037] The data acquisition and classification module is used to collect the operating parameters of the relay;

[0038] The integrated fitting module is used to determine the number of times the relay opens and closes based on the opening and closing time, and to treat one opening and closing as one action. It also filters the load electrical quantity, ambient temperature and ambient humidity collected between two adjacent actions as fitting information before the next action occurs.

[0039] The limit comparison module is used to divide the fitted information into standard time periods and obtain the gradient information corresponding to the fitted information under different standard time periods. It also performs a statistical analysis of the number of times the same gradient appears in all gradient information in the fitted information and determines the gradient with the highest number of times the same gradient appears as the standard gradient of the fitted information.

[0040] The counting module is used to count the number of times gradient information above the standard gradient occurs, which is used as a weighted reference number.

[0041] As a preferred embodiment of the cloud-edge collaborative relay life management system described in this invention, the weighted processing unit includes: a data analysis module, a weighted statistics module, and a life scoring module. The data analysis module is connected to the weighted statistics module, and the weighted statistics module is connected to the life scoring module.

[0042] The data analysis module is used to use the weights corresponding to the standard gradient as the basic calculation weights and to calculate the weighted weights based on the weighted reference times; the weighted statistics module is used to update the relay's lifespan weights based on the weight optimization ratio; and the lifespan scoring module is used to evaluate the remaining effective opening and closing times of the relay based on the updated lifespan weights.

[0043] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention conducts safety tests on relays under different environments to obtain the effective opening and closing counts of the relays under different environments, and determines weights for different environments. By treating each opening and closing of the relay as one action, and by collecting data on the load electrical quantity, ambient temperature, and ambient humidity between adjacent actions, the weights are updated. While comprehensively considering multiple influencing factors, this provides reliable data support for evaluating the remaining effective opening and closing counts of the relay, thereby achieving relay lifespan management. Furthermore, by dividing the fitted information, the frequency of occurrence of all gradient information in the fitted information is statistically analyzed. The gradient with the highest frequency of occurrence of the same gradient is determined as the standard gradient of the fitted information, providing a valid reference for the weighting analysis of the fitted information. By using the frequency of occurrence of gradient information higher than the standard gradient as the weighting reference frequency, data support is provided for subsequent weighting, providing more accurate data assurance for evaluating the remaining effective opening and closing counts of the relay. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0045] Figure 1This is a schematic diagram of the method flow of a relay life management method and system based on cloud-edge collaboration according to an embodiment of the present invention;

[0046] Figure 2 This is a system principle block diagram of a relay life management method and system based on cloud-edge collaboration according to an embodiment of the present invention;

[0047] Figure 3 This is a system principle block diagram of a test reference unit for a relay life management method and system based on cloud-edge collaboration, as described in one embodiment of the present invention.

[0048] Figure 4 This is a system principle block diagram of the data acquisition unit of a relay life management method and system based on cloud-edge collaboration according to an embodiment of the present invention;

[0049] Figure 5 This is a system principle block diagram of a weighted processing unit of a relay life management method and system based on cloud-edge collaboration, as described in one embodiment of the present invention. Detailed Implementation

[0050] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0051] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0052] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0053] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0054] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0055] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0056] Example 1

[0057] Reference Figure 1 As one embodiment of the present invention, this embodiment provides a relay lifetime management method based on cloud-edge collaboration, including:

[0058] S1: Obtain safety test data on the effective opening and closing times of different relay models under standard temperature and humidity, and standardize the test data to obtain the life standardized weight data of the corresponding relay models.

[0059] S2: Collect real-time operating parameters of the relay, identify relay actions based on the data, record the fitting information between two adjacent actions, divide the fitting information into standard time periods, determine the standard gradient, and obtain the weighted reference number.

[0060] S3: Calculate the weighted weights based on the standard gradient and the weighted reference number, update the relay's lifetime weights according to the optimized weights, and calculate the remaining effective opening and closing counts of the relay using the updated lifetime weights.

[0061] It should be noted that this application conducts safety tests on relays under different environments to obtain the effective opening and closing counts of the relays under different conditions. Weights are then determined for different environments. By defining each relay opening and closing as one action, and by collecting data on load electrical quantities, ambient temperature, and ambient humidity between adjacent actions, the weights are updated. This comprehensive consideration of multiple influencing factors provides reliable data support for assessing the remaining effective opening and closing counts of the relays, thereby enabling relay lifespan management. Through the division of the fitted information, the frequency of occurrence of the same gradient information in all gradient information is statistically analyzed. The gradient with the highest frequency of occurrence of the same gradient is determined as the standard gradient of the fitted information, providing a valid reference for the weighting analysis of the fitted information. Furthermore, the frequency of occurrence of gradient information higher than the standard gradient is used as the weighting reference frequency, providing data support for subsequent weighting and ensuring more accurate data for assessing the remaining effective opening and closing counts of the relays.

[0062] In this embodiment of the application, the safety test data for the effective opening and closing times of different relay models under standard temperature and humidity includes: the effective opening and closing times under standard temperature and humidity, as mechanical reference times; the effective opening and closing times under different temperature gradients under standard humidity, as temperature reference times; the effective opening and closing times under different humidity gradients under standard temperature, as humidity reference times; and the effective opening and closing times under different load gradients under standard temperature and humidity, as load reference times.

[0063] In this embodiment of the application, standardizing the test data to obtain the lifespan standardized weight data of the corresponding relay model includes: obtaining the lifespan standardized weight data of the corresponding relay model as follows:

[0064] A:B k :C s :D t =W A :W B :W C :W D

[0065] In the formula, A represents the number of mechanical references, and W... A For mechanical reference weights, B k Let W be the temperature reference number under the k-th temperature gradient. B C represents the temperature reference weight under the k-th temperature gradient. s Let W be the humidity reference number under the s-th humidity gradient. C Let D be the humidity reference weight under the s-th humidity gradient. t Let W be the load reference number under the t-th load gradient. D The load reference weight.

[0066] In this embodiment of the application, the real-time operating parameters of the relay are collected, the relay action is identified based on the data, and the fitting information between two adjacent actions is recorded. The real-time operating parameters of the relay include opening and closing time, load electrical quantity, ambient temperature and ambient humidity.

[0067] The number of times the relay opens and closes is determined based on the opening and closing time, and each opening and closing is considered as one action. The load electrical quantity, ambient temperature and ambient humidity data between two adjacent actions are selected as fitting information before the next action occurs.

[0068] In this embodiment of the application, dividing the fitted information into standard time periods and determining the weighted reference number of standard gradients includes: dividing the fitted information into standard time periods and obtaining the gradient information corresponding to the fitted information under different standard time periods; counting the number of times the same gradient appears in all gradient information in the fitted information; determining the gradient with the highest number of times the same gradient appears as the standard gradient of the fitted information; and using the number of times the gradient information appears higher than the standard gradient as the weighted reference number.

[0069] The weighted weight calculation based on the number of references is expressed as follows:

[0070]

[0071] Among them, W Bn W is the weighted average of the temperature reference weights under the standard gradient. B1 W is the weighted reference number when the standard gradient is the corresponding temperature gradient. Cn W is the weighted average of the humidity reference weights under the standard gradient. C1 W is the weighted reference number when the standard gradient is the corresponding humidity gradient. Dn W is the weighted average of the load reference weights under the standard gradient. D1 β is the weighted reference number when the standard gradient is the corresponding load gradient, and β is the weight adjustment factor.

[0072] In this embodiment of the application, updating the relay lifetime weight according to the optimized weight includes: the calculation method for updating the relay lifetime weight is as follows:

[0073] A P :B kP :C sP :D tP

[0074] =(W A -W Bn -W Cn -W Dn ):(W BP +W Bn ):(W CP +W Cn ):(WDP +W Dn )

[0075] Among them, A P For the updated mechanical reference weights, B kP For the updated temperature reference weights, C sP For the updated humidity reference weights, D tP The updated load reference weights;

[0076] The remaining effective number of opening and closing cycles is calculated as follows:

[0077]

[0078] Where Z represents the remaining effective number of times the relay can be switched on and off, and B represents the number of times the relay can be switched on and off. kn C is the temperature reference number corresponding to the standard gradient. sn D is the number of humidity references corresponding to the standard gradient. tn This is the load reference number corresponding to the standard gradient.

[0079] Example 2

[0080] Reference Figures 2-5 This is one embodiment of the present invention, which differs from the first embodiment in that it provides a relay lifespan management system based on cloud-edge collaboration, such as... Figure 2 The diagram includes: a cloud 100, and several edge layers 200 that are communicatively connected to the cloud 100; the cloud 100 includes a weighted processing unit 500, which is used to evaluate and calculate the remaining effective opening and closing times of the relay based on the standard gradient and the weighted reference number;

[0081] The edge layer 200 includes a test reference unit 300 and a data acquisition unit 400; the test reference unit 300 is used to perform safety tests on different types of relays, acquire test data, and acquire life-standardized weight data of the corresponding type of relay.

[0082] The data acquisition unit 400 is used to acquire relay operating parameters near the relay side and perform statistics on standard gradient and weighted reference times.

[0083] In this embodiment of the application, the test reference unit 300 further includes: a test recording module 301 and a standardization processing module 302, wherein the test recording module 301 is connected to the standardization processing module 302;

[0084] The test recording module 301 is used to perform safety tests on different models of relays and acquire test data. The test data includes the effective opening and closing times under standard temperature and standard humidity, which are used as mechanical reference times; the effective opening and closing times under different temperature gradients under standard humidity, which are used as temperature reference times; the effective opening and closing times under different humidity gradients under standard temperature, which are used as humidity reference times; and the effective opening and closing times under different load gradients under standard temperature and standard humidity, which are used as load reference times.

[0085] The standardization processing module 302 is used to standardize the test data and obtain the lifespan standardized weight data for the corresponding relay model:

[0086] A:B k :C s :D t =W A :W B :W C :W D

[0087] Where A is the number of mechanical references, W A For mechanical reference weights, B k Let W be the temperature reference number under the k-th temperature gradient. B C represents the temperature reference weight under the k-th temperature gradient. s Let W be the humidity reference number under the s-th humidity gradient. C Let D be the humidity reference weight under the s-th humidity gradient. t Let W be the load reference number under the t-th load gradient. D The load reference weight.

[0088] In this embodiment of the application, the data acquisition unit 400 further includes: a data acquisition classification module 401, an integrated fitting module 402, a limit comparison module 403, and a counting module 404. The data acquisition classification module 401 is connected to the integrated fitting module 402, the integrated fitting module 402 is connected to the limit comparison module 403, and the limit comparison module 403 is connected to the counting module 404.

[0089] The data acquisition and classification module 401 is used to collect the operating parameters of the relay;

[0090] Specifically, the operating parameters include opening and closing time, load electrical quantity, ambient temperature, and ambient humidity;

[0091] The integrated fitting module 402 is used to determine the number of times the relay opens and closes based on the opening and closing time, and to take one opening and closing as one action, and to filter the load electrical quantity, ambient temperature and ambient humidity collected between two adjacent actions as fitting information before the next action occurs.

[0092] The limit comparison module 403 is used to divide the fitted information into standard time periods and obtain the gradient information corresponding to the fitted information under different standard time periods. It performs a statistical analysis of the number of times the same gradient appears in all gradient information in the fitted information and determines the gradient with the highest number of times the same gradient appears as the standard gradient of the fitted information.

[0093] The counting module 404 is used to count the number of times gradient information above the standard gradient occurs, which is used as a weighted reference number.

[0094] In this embodiment of the application, the weighted processing unit 500 includes: a data analysis module 501, a weighted statistics module 502, and a lifespan scoring module 503. The data analysis module 501 is connected to the weighted statistics module 502, and the weighted statistics module 502 is connected to the lifespan scoring module 503.

[0095] The data analysis module 501 is used to use the weights corresponding to the standard gradient as the basic calculation weights and to calculate the weighted weights based on the weighted reference times; the weighted statistics module 502 is used to update the relay's life weights based on the weight optimization ratio; and the life scoring module 503 is used to evaluate and calculate the remaining effective opening and closing times of the relay based on the updated life weights of the relay.

[0096] Specifically, the data analysis module 501 uses the weights corresponding to the standard gradient as the basic calculation weights, represented as follows:

[0097]

[0098] Among them, W Bn W is the weighted average of the temperature reference weights under the standard gradient. B1 W is the weighted reference number when the standard gradient is the corresponding temperature gradient. Cn W is the weighted average of the humidity reference weights under the standard gradient. C1 W is the weighted reference number when the standard gradient is the corresponding humidity gradient. Dn W is the weighted average of the load reference weights under the standard gradient. D1 β is the weighted reference number when the standard gradient is the corresponding load gradient, and β is the weight adjustment factor.

[0099] Specifically, the weighted statistics module 502 updates the relay lifespan weight based on the weight optimization ratio, as shown in the following calculation:

[0100] A P :B kP :C sP :D tP

[0101] =(W A -W Bn -WCn -W Dn ):(W BP +W Bn ):(W CP +W Cn ):(W DP +W Dn )

[0102] Among them, A P For the updated mechanical reference weights, B kP For the updated temperature reference weights, C sP For the updated humidity reference weights, D tP The updated load reference weight.

[0103] Specifically, the lifespan scoring module 503 evaluates and calculates the remaining effective opening and closing counts of the relay based on the updated lifespan weights of the relay, as shown in the following expression:

[0104]

[0105] Where Z represents the remaining effective number of times the relay can be switched on and off, and B represents the number of times the relay can be switched on and off. kn C is the temperature reference number corresponding to the standard gradient. sn D is the number of humidity references corresponding to the standard gradient. tn This is the load reference number corresponding to the standard gradient.

[0106] This embodiment also provides a computing device applicable to a relay lifetime management method based on cloud-edge collaboration, including:

[0107] The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement the cloud-edge collaborative relay life management method proposed in the above embodiments.

[0108] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements the relay life management method based on cloud-edge collaboration as proposed in the above embodiments.

[0109] The storage medium proposed in this embodiment and the relay life management method based on cloud-edge collaboration proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0110] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0111] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A relay lifespan management method based on cloud-edge collaboration, characterized in that, include: Obtain safety test data on the effective opening and closing counts of different relay models under standard temperature and humidity conditions, and standardize the test data to obtain the lifespan standardized weight data for the corresponding relay models. Specifically, this includes obtaining the lifespan standardized weight data for the corresponding relay models, represented as follows: ； in, For mechanical reference times, For mechanical reference weights, For the first Temperature reference number under various temperature gradients, For the first Temperature reference weights under various temperature gradients For the first Humidity reference number under various humidity gradients For the first Humidity reference weights under various humidity gradients For the first The load reference number under various load gradients As a reference weight for the load; The process involves collecting real-time operating parameters of the relay, identifying relay actions based on these parameters, recording fitting information between two adjacent actions, dividing the fitting information into standard time periods, determining the standard gradient, and obtaining the weighted reference number of times. Specifically, this includes dividing the fitting information into standard time periods, obtaining the gradient information corresponding to the fitting information under different standard time periods, counting the number of times all gradient information in the fitting information has the same gradient, determining the gradient with the highest number of times the same gradient occurs as the standard gradient of the fitting information, and using the number of times gradient information occurs that is higher than the standard gradient as the weighted reference number. The weighted reference times are used to calculate the weighted weights, which is expressed as follows: ； ； ； in, The weighted average of the temperature reference weights under the standard gradient is used. This represents the weighted reference number when the standard gradient corresponds to the temperature gradient. The weighted average of the humidity reference weights under the standard gradient is used. This represents the weighted reference number when the standard gradient corresponds to the humidity gradient. The weighted average of the load reference weights under the standard gradient is used. This represents the weighted reference number when the standard gradient corresponds to the load gradient. This is the weighting adjustment factor; Weighted weights are calculated based on the standard gradient and weighted reference counts to obtain optimized weights. These optimized weights include weighted weights for temperature references under the standard gradient, humidity references under the standard gradient, and load references under the standard gradient. The relay's lifetime weight is updated based on the optimized weights, and the remaining effective opening and closing counts of the relay are calculated using the updated lifetime weights. Specifically, the update calculation method for the relay's lifetime weight is as follows: ； ； in, For the updated mechanical reference weights, For the updated temperature reference weights, For the updated humidity reference weights, The updated load reference weights; The remaining effective number of opening and closing operations is calculated as follows: ； in, This represents the remaining effective number of times the relay can be switched on and off. For the temperature reference number corresponding to the standard gradient, For the humidity reference number corresponding to the standard gradient, This is the load reference number corresponding to the standard gradient.

2. The relay lifespan management method based on cloud-edge collaboration as described in claim 1, characterized in that, The safety test data for the effective opening and closing counts of different relay models under standard temperature and humidity includes: the effective opening and closing counts under standard temperature and humidity as mechanical reference counts; the effective opening and closing counts under different temperature gradients under standard humidity as temperature reference counts; the effective opening and closing counts under different humidity gradients under standard temperature as humidity reference counts; and the effective opening and closing counts under different load gradients under standard temperature and humidity as load reference counts.

3. The relay lifespan management method based on cloud-edge collaboration as described in claim 2, characterized in that, The real-time operating parameters of the relay are collected, the relay action is identified based on the data, and the fitting information between two adjacent actions is recorded. The real-time operating parameters of the relay include opening and closing time, load electrical quantity, ambient temperature and ambient humidity. The number of times the relay opens and closes is determined based on the opening and closing time, and each opening and closing is considered as one action. The load electrical quantity, ambient temperature and ambient humidity data between two adjacent actions are selected as fitting information before the next action occurs.

4. A relay life management system based on cloud-edge collaboration, applied to the method described in any one of claims 1-3, characterized in that, include: The cloud (100) and several edge layers (200) communicating with the cloud (100); the cloud (100) includes a weighted processing unit (500), which is used to evaluate and calculate the remaining effective opening and closing times of the relay based on the standard gradient and the weighted reference number; the weighted processing unit (500) includes: a data analysis module (501), a weighted statistics module (502) and a lifespan scoring module (503), the data analysis module (501) is connected to the weighted statistics module (502), and the weighted statistics module (502) is connected to the lifespan scoring module (503); the data analysis module (501) is used to use the weight corresponding to the standard gradient as the basic calculation weight, and to calculate the weighted weight based on the weighted reference number to obtain the weight optimization ratio; the weighted statistics module (502) is used to update and calculate the lifespan weight of the relay based on the weight optimization ratio; the lifespan scoring module (503) is used to evaluate and calculate the remaining effective opening and closing times of the relay based on the update result of the lifespan weight of the relay. The edge layer (200) includes a test reference unit (300) and a data acquisition unit (400); the test reference unit (300) is used to perform safety tests on different types of relays, acquire test data, and acquire life-standardized weight data of the corresponding type of relay. The data acquisition unit (400) is used to acquire relay operating parameters near the relay side and perform statistics on standard gradient and weighted reference times.

5. The relay life management system based on cloud-edge collaboration as described in claim 4, characterized in that, The test reference unit (300) further includes a test recording module (301) and a standardization processing module (302), wherein the test recording module (301) is connected to the standardization processing module (302); The test recording module (301) is used to perform safety tests on different models of relays and obtain test data. The test data includes the effective opening and closing times under standard temperature and standard humidity, which are used as mechanical reference times; the effective opening and closing times under different temperature gradients under standard humidity, which are used as temperature reference times; the effective opening and closing times under different humidity gradients under standard temperature, which are used as humidity reference times; and the effective opening and closing times under different load gradients under standard temperature and standard humidity, which are used as load reference times. The standardization processing module (302) is used to standardize the test data and obtain the lifespan standardized weight data of the corresponding relay model: ； in, For mechanical reference times, For mechanical reference weights, For the first Temperature reference number under various temperature gradients, For the first Temperature reference weights under various temperature gradients For the first Humidity reference number under various humidity gradients For the first Humidity reference weights under various humidity gradients For the first The load reference number under various load gradients The load reference weight.

6. The relay life management system based on cloud-edge collaboration as described in claim 5, characterized in that, The data acquisition unit (400) further includes: a data acquisition classification module (401), an integrated fitting module (402), a limit comparison module (403), and a counting module (404). The data acquisition classification module (401) is connected to the integrated fitting module (402), the integrated fitting module (402) is connected to the limit comparison module (403), and the limit comparison module (403) is connected to the counting module (404). The data acquisition and classification module (401) is used to acquire the operating parameters of the relay; The integrated fitting module (402) is used to determine the number of times the relay opens and closes based on the opening and closing time, and to treat one opening and closing as one action, and to filter the load electrical quantity, ambient temperature and ambient humidity collected between two adjacent actions as fitting information before the next action occurs. The limit comparison module (403) is used to divide the fitting information into standard time periods and obtain the gradient information corresponding to the fitting information under different standard time periods. It performs a statistical analysis of the number of times the same gradient appears in all gradient information in the fitting information and determines the gradient with the highest number of times the same gradient appears as the standard gradient of the fitting information. The counting module (404) is used to count the number of times gradient information above the standard gradient occurs, as a weighted reference number.

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