Associated equipment fault processing method, system and equipment based on multi-dimensional fault data

Abstract

The invention relates to the technical field of computers, in particular to an associated equipment fault processing method, system and equipment based on multi-dimensional fault data, which can efficiently and flexibly process multi-dimensional faults. The associated equipment fault processing method based on the multi-dimensional fault data comprises the following steps: acquiring equipment information and equipment fault work order data of machine room associated equipment in real time; counting the number of professional fault equipment, calculating the total number of machine room fault equipment of each machine room, and calculating the total number of professional fault equipment according to professions; sorting the number of the fault equipment in the machine room from large to small according to specialty in all the machine rooms to obtain the inverted sorting number of the number of the fault equipment according to specialty, and sorting the total number of the fault equipment in all the machine rooms from large to small to obtain the inverted sorting number of the number of the fault equipment; calculating a comprehensive fault severity index of the machine room according to the professional equipment sorting number, the equipment total sorting number, the corresponding professional coefficient and the equipment total coefficient; and generating a priority ranking queue for each machine room according to the comprehensive fault severity index.

Description

Technical Field

[0001] One or more embodiments of the present invention relate to the field of computer technology, and more particularly to a method, system and device for handling associated equipment faults based on multidimensional fault data. Background Technology

[0002] When a single data center fails, its associated wireless devices, broadband devices, and transmission devices often generate a large number of fault tickets simultaneously. The operations and maintenance team needs to dynamically decide on processing priorities based on various ticket data.

[0003] However, current methods for handling data center failures have three major drawbacks:

[0004] 1. Problem of fragmented analysis of multi-source work orders: Fault work orders for wireless, broadband, and transmission equipment are handled independently, lacking cross-service impact analysis, thus easily overlooking system-level chain reactions (such as power outages in the data center causing wireless base station paralysis).

[0005] 2. Static rules are rigid: Static rules cannot adapt to real-time changing fault scenarios (such as a sudden surge in work orders);

[0006] 3. Inefficient human decision-making: Human judgment is highly subjective, resulting in inefficient decision-making, vague standards, and poor consistency in assessing urgency. Summary of the Invention

[0007] One or more embodiments of the present invention describe a method, system and device for handling associated equipment faults based on multidimensional fault data, which can efficiently and flexibly handle multidimensional faults.

[0008] According to an embodiment of a first aspect of the present invention, a method for handling associated equipment faults based on multidimensional fault data is provided, comprising:

[0009] The system collects equipment information and equipment fault work order data of the associated equipment from multiple data centers in real time. The associated equipment in each data center includes broadband equipment, transmission equipment, and wireless equipment according to their respective specialties.

[0010] Associate the fault work orders of each computer room with the equipment fault work orders of the associated equipment under that computer room, count the number of faulty equipment of the associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the associated equipment under each computer room according to the profession.

[0011] The number of faulty devices in each computer room is sorted by specialty from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room: broadband devices, transmission devices, and wireless devices. Furthermore, the total number of faulty devices in each computer room is sorted from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room: total number of devices.

[0012] Based on the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, and based on the preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient for the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, calculate the comprehensive fault severity index for each data center.

[0013] Each data center that has experienced a failure will be sorted into a priority queue according to the comprehensive failure severity index from high to low, with the data center having the highest comprehensive failure severity index having the highest processing priority.

[0014] Preferably, in any embodiment,

[0015] The preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient are coefficients that can be adjusted according to the actual situation.

[0016] Preferably, in any embodiment,

[0017] At least one of the broadband professional coefficient, the transmission professional coefficient, the wireless professional coefficient, and the total number of devices coefficient is dynamically adjusted based on the importance of at least one of the data center-related devices in at least one data center to the operation of the data center.

[0018] Preferably, in any embodiment,

[0019] The step of calculating the comprehensive fault severity index of each computer room includes: calculating the comprehensive fault severity index of each computer room through a normalized scoring method, wherein the broadband professional coefficient, the transmission professional coefficient, the wireless professional coefficient, and the total number of devices coefficient are: broadband professional weight value, transmission professional weight value, wireless professional weight value, and total number of devices weight value.

[0020] Preferably, in any embodiment,

[0021] The comprehensive fault severity index S is calculated according to the following formula:

[0022] S=W1*(L-R1) / L+W2*(L-R2) / L+W3*(L-R3) / L+W4*(L-R4) / L,

[0023] Where W1, W2, W3, and W4 are the weight values ​​for broadband, transmission, wireless, and total number of devices, respectively; L = the total number of all computer rooms that have experienced a failure + 1;

[0024] R1, R2, and R3 are the sorted numbers of the broadband devices, transmission devices, and wireless devices that have failed in the data center, obtained by sorting them in reverse order among all data centers where failures have occurred. R4 is the total number of devices, obtained by sorting the total number of devices that have failed in the data center in reverse order among all data centers where failures have occurred.

[0025] Preferably, in any embodiment, it further includes:

[0026] Based on the real-time collected equipment information from multiple data centers and the equipment failure work order data of the data center-related equipment, the equipment failure work order data is updated in real time, and the comprehensive failure severity index of each data center is recalculated and the priority sorting queue is regenerated.

[0027] Preferably, in any embodiment, it further includes:

[0028] Based on the real-time collected equipment information from multiple data centers and the equipment failure work order data of the data center-related equipment, the equipment failure work order data is updated periodically, and the comprehensive failure severity index of each data center is recalculated and the priority sorting queue is regenerated.

[0029] Preferably, in any embodiment, it further includes:

[0030] When the comprehensive fault severity index exceeds the preset comprehensive fault severity index threshold, a severe fault warning signal is issued.

[0031] According to a second aspect of the present invention, a system for handling associated equipment faults based on multidimensional fault data is provided, which is used to implement the aforementioned method for handling associated equipment faults based on multidimensional fault data, including:

[0032] The data acquisition module is used to collect equipment information and equipment fault work order data of the associated equipment from multiple computer rooms in real time. The associated equipment of each computer room includes broadband equipment, transmission equipment and wireless equipment according to their respective specialties.

[0033] The statistical calculation module is used to associate the computer room fault work order of each computer room with the equipment fault work orders of the computer room associated equipment under that computer room, count the number of faulty equipment of the computer room associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the computer room associated equipment that has failed according to the profession.

[0034] The professional sorting module is used to sort the number of faulty devices in each computer room by professional category from most to least among all computer rooms where faults have occurred, to obtain the reverse order of the number of faulty devices in that computer room by professional category: broadband devices, transmission devices, and wireless devices. It also sorts the total number of faulty devices in each computer room from most to least among all computer rooms where faults have occurred, to obtain the reverse order of the number of faulty devices in that computer room: total number of devices.

[0035] The comprehensive fault severity index calculation module is used to calculate the comprehensive fault severity index of each computer room based on the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices, and based on the home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient preset for the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices.

[0036] The priority sorting queue generation module is used to generate priority sorting queues for each faulty computer room according to the comprehensive fault severity index from high to low, wherein the computer room with the highest comprehensive fault severity index has the highest processing priority.

[0037] According to an embodiment of a third aspect of the present invention, an associated device fault handling device based on multidimensional fault data is provided, comprising a memory and a processor, wherein executable code is stored in the memory, and when the processor executes the executable code, the associated device fault handling method based on multidimensional fault data described above is performed.

[0038] The method, system, and device for handling associated equipment faults based on multidimensional fault data provided by one or more embodiments of the present invention can efficiently and flexibly handle multidimensional faults. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating a method for handling associated equipment faults based on multidimensional fault data according to an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the structure of an associated equipment fault handling system based on multidimensional fault data according to an embodiment of the present invention. Detailed Implementation

[0042] One or more embodiments of the present invention describe a method, system and device for handling associated equipment faults based on multidimensional fault data, which can efficiently and flexibly handle multidimensional faults.

[0043] The technical solutions of various embodiments of the present invention will be clearly and completely described 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 described in the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] According to an embodiment of a first aspect of the present invention, a method for handling associated equipment faults based on multidimensional fault data is provided, comprising:

[0045] The system collects equipment information and equipment fault work order data of the associated equipment from multiple data centers in real time. The associated equipment in each data center includes broadband equipment, transmission equipment, and wireless equipment according to their respective specialties.

[0046] Associate the fault work orders of each computer room with the equipment fault work orders of the associated equipment under that computer room, count the number of faulty equipment of the associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the associated equipment under each computer room according to the profession.

[0047] The number of faulty devices in each computer room is sorted by specialty from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room: broadband devices, transmission devices, and wireless devices. Furthermore, the total number of faulty devices in each computer room is sorted from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room: total number of devices.

[0048] Based on the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, and based on the preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient for the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, calculate the comprehensive fault severity index for each data center.

[0049] Each data center that has experienced a failure will be sorted into a priority queue according to the comprehensive failure severity index from high to low, with the data center having the highest comprehensive failure severity index having the highest processing priority.

[0050] In this way, based on the real-time collected equipment information (e.g., by specialty, including broadband equipment, transmission equipment, and wireless equipment) and their equipment fault work order data from multiple data centers, the number of faulty equipment in each specialty of each data center can be counted, and the total number of faulty equipment in each data center can be calculated. Furthermore, the total number of faulty equipment in each data center can be calculated by specialty (i.e., broadband equipment + transmission equipment + wireless equipment). In all data centers where faults have occurred, the number of faulty equipment in each data center by specialty is sorted (e.g., from most to least). This yields the descending order of the number of faulty equipment in each data center by specialty, i.e., the descending order of the number of faulty equipment in each specialty, i.e., the descending order of the number of broadband equipment, the descending order of the number of wireless ... The system first ranks the number of faulty transmission devices and wireless devices, and then sorts the total number of faulty devices in each equipment room from most to least among all the equipment rooms that experienced faults, thus obtaining the reverse sorted number of the number of faulty devices in that equipment room, i.e., the total number of devices. Then, based on the sorted numbers of each specialized equipment (i.e., the number of broadband devices, the number of transmission devices, and the number of wireless devices) and the total number of devices, and according to the corresponding preset specialized coefficients (i.e., broadband specialized coefficient, transmission specialized coefficient, and wireless specialized coefficient) and the total number of devices coefficient, it calculates the comprehensive fault severity index for each equipment room. Based on the comprehensive fault severity index from high to low, a priority sorting queue is generated for each faulty equipment room (where the equipment room with the highest comprehensive fault severity index has the highest processing priority).

[0051] In this way, high-priority (i.e., those with higher overall fault severity indices) data centers can be prioritized for processing based on the priority queue, avoiding misjudgments of priority due to subjective human decision-making and preventing severe system-wide chain reactions caused by failing to address the most urgent data center faults in a timely manner. It should be emphasized that when calculating the overall fault severity index for each data center, not only the total number of faulty devices within it is considered, but also the potential chain reactions caused by the professional types of related equipment (i.e., broadband, transmission, and wireless). Therefore, the most urgent data center faults can be prioritized overall, significantly improving the efficiency of resolving multi-dimensional fault problems.

[0052] By integrating the number of fault tickets for broadband, transmission, and wireless devices within the data center, a multi-dimensional correlation model is established, solving the problem of priority misjudgment caused by single-source fault analysis in traditional operations and maintenance. Compared with existing technologies, the correlation device fault handling method based on multi-dimensional fault data provided by this invention can more comprehensively reflect the overall health status of the data center, making the allocation of operations and maintenance resources more accurate and significantly improving processing efficiency.

[0053] Therefore, the associated equipment fault handling method based on multidimensional fault data provided in the embodiments of the present invention can efficiently and flexibly handle multidimensional faults.

[0054] Preferably, in any embodiment,

[0055] The preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient are coefficients that can be adjusted according to the actual situation.

[0056] Preferably, in any embodiment,

[0057] At least one of the broadband professional coefficient, the transmission professional coefficient, the wireless professional coefficient, and the total number of devices coefficient is dynamically adjusted based on the importance of at least one of the data center-related devices in at least one data center to the operation of the data center.

[0058] Preferably, in any embodiment,

[0059] The step of calculating the comprehensive fault severity index of each computer room includes: calculating the comprehensive fault severity index of each computer room through a normalized scoring method, wherein the broadband professional coefficient, the transmission professional coefficient, the wireless professional coefficient, and the total number of devices coefficient are: broadband professional weight value, transmission professional weight value, wireless professional weight value, and total number of devices weight value.

[0060] Preferably, in any embodiment,

[0061] The comprehensive fault severity index S is calculated according to the following formula:

[0062] S=W1*(L-R1) / L+W2*(L-R2) / L+W3*(L-R3) / L+W4*(L-R4) / L,

[0063] Where W1, W2, W3, and W4 are the weight values ​​for broadband, transmission, wireless, and total number of devices, respectively; L = the total number of all computer rooms that have experienced a failure + 1;

[0064] R1, R2, and R3 are the sorted numbers of the broadband devices, transmission devices, and wireless devices that have failed in the data center, obtained by sorting them in reverse order among all data centers where failures have occurred. R4 is the total number of devices, obtained by sorting the total number of devices that have failed in the data center in reverse order among all data centers where failures have occurred.

[0065] Preferably, in any embodiment, it further includes:

[0066] Based on the real-time collected equipment information from multiple data centers and the equipment failure work order data of the data center-related equipment, the equipment failure work order data is updated in real time, and the comprehensive failure severity index of each data center is recalculated and the priority sorting queue is regenerated.

[0067] Preferably, in any embodiment, it further includes:

[0068] Based on the real-time collected equipment information from multiple data centers and the equipment failure work order data of the data center-related equipment, the equipment failure work order data is updated periodically, and the comprehensive failure severity index of each data center is recalculated and the priority sorting queue is regenerated.

[0069] Preferably, in any embodiment, it further includes:

[0070] When the comprehensive fault severity index exceeds the preset comprehensive fault severity index threshold, a severe fault warning signal is issued.

[0071] Optionally, in any embodiment, the associated device fault handling method based on multidimensional fault data is used in fault scheduling scenarios of distributed network infrastructure.

[0072] In a preferred embodiment of the present invention, a method for handling associated equipment faults based on multidimensional fault data is provided, comprising:

[0073] The system collects equipment information and equipment fault work order data of the associated equipment from multiple computer rooms in real time. The associated equipment in each computer room is classified into home broadband equipment (home broadband specialty), transmission equipment (transmission specialty), and wireless equipment (wireless specialty).

[0074] Associate the fault work orders of each computer room with the equipment fault work orders of the associated equipment under that computer room, count the number of faulty equipment of the associated equipment under each computer room according to the profession (number of faulty broadband equipment, number of faulty transmission equipment, number of faulty wireless equipment), calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the associated equipment under each computer room according to the profession.

[0075] The number of faulty devices in each computer room is sorted by specialty from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room (R1 for broadband devices, R2 for transmission devices, and R3 for wireless devices). Furthermore, the total number of faulty devices in each computer room is sorted from most to least among all computer rooms that experienced faults, resulting in a descending order of the total number of faulty devices in that computer room (number of faulty broadband devices + number of faulty transmission devices + number of faulty wireless devices) (R4 for total number of devices) (where the highest number is ranked 1).

[0076] Based on the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, and according to the preset home broadband professional weight, transmission professional weight, wireless professional weight, and total number of devices weight for the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, the comprehensive fault severity index S for each data center is calculated as follows: S = W1*(L-R1) / L + W2*(L-R2) / L + W3*(L-R3) / L + W4*(L-R4) / L.

[0077] Where W1, W2, W3, and W4 are the weight values ​​for broadband, transmission, wireless, and total number of devices, respectively; L = the total number of all computer rooms that have experienced a failure + 1;

[0078] R1, R2, and R3 are the sorted numbers of the broadband devices, transmission devices, and wireless devices that have failed in the data center, obtained by reversing the order of their numbers in all data centers where failures have occurred. R4 is the total number of devices, obtained by reversing the order of their numbers in all data centers where failures have occurred.

[0079] Each data center that has experienced a failure will be sorted into a priority queue according to the comprehensive failure severity index from high to low, with the data center having the highest comprehensive failure severity index having the highest processing priority.

[0080] In an exemplary embodiment of the present invention, a summary list of the comprehensive fault severity indices of each computer room that has experienced a fault is provided as follows:

[0081]

[0082] As shown in the table above, among the 13 computer rooms that experienced failures, although computer room 2 had the most failure devices (96), considering all factors, computer room 7 (which had the most failure devices (95)) had a higher comprehensive failure severity index score (2.92307693), indicating that it was more urgent and therefore had the highest priority in the failure handling priority ranking queue, and should therefore be handled with the highest priority.

[0083] Figure 1 This is a flowchart illustrating a method for handling associated equipment faults based on multidimensional fault data according to an embodiment of the present invention.

[0084] exist Figure 1 The illustrated embodiment shows a method for handling associated equipment faults based on multidimensional fault data, including the following steps:

[0085] 110: Real-time collection of equipment information and equipment fault work order data of equipment associated with multiple computer rooms. The equipment associated with each computer room includes broadband equipment, transmission equipment, and wireless equipment according to their respective specialties.

[0086] 120: Associate the computer room fault work order of each computer room with the equipment fault work orders of the computer room associated equipment under that computer room, count the number of faulty equipment of the computer room associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the computer room associated equipment that has failed according to the profession.

[0087] 130: Sort the number of faulty devices in each computer room by specialty from the largest to the smallest among all computer rooms that experienced faults, to obtain the reverse order of the number of faulty devices in that computer room by specialty: broadband devices, transmission devices, and wireless devices. Also, sort the total number of faulty devices in each computer room from the largest to the smallest among all computer rooms that experienced faults, to obtain the reverse order of the number of faulty devices in that computer room: total number of devices.

[0088] 140: Calculate the comprehensive fault severity index for each computer room based on the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the sorted number of total devices, and based on the preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total device coefficient for the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the sorted number of total devices.

[0089] 150: Generate a priority sorting queue for each computer room that has experienced a failure, based on the comprehensive failure severity index from high to low, wherein the computer room with the highest comprehensive failure severity index has the highest processing priority.

[0090] According to a second aspect of the present invention, a system for handling associated equipment faults based on multidimensional fault data is provided, which is used to implement the aforementioned method for handling associated equipment faults based on multidimensional fault data, including:

[0091] The data acquisition module is used to collect equipment information and equipment fault work order data of the associated equipment from multiple computer rooms in real time. The associated equipment of each computer room includes broadband equipment, transmission equipment and wireless equipment according to their respective specialties.

[0092] The statistical calculation module is used to associate the computer room fault work order of each computer room with the equipment fault work orders of the computer room associated equipment under that computer room, count the number of faulty equipment of the computer room associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the computer room associated equipment that has failed according to the profession.

[0093] The professional sorting module is used to sort the number of faulty devices in each computer room by professional category from most to least among all computer rooms where faults have occurred, to obtain the reverse order of the number of faulty devices in that computer room by professional category: broadband devices, transmission devices, and wireless devices. It also sorts the total number of faulty devices in each computer room from most to least among all computer rooms where faults have occurred, to obtain the reverse order of the number of faulty devices in that computer room: total number of devices.

[0094] The comprehensive fault severity index calculation module is used to calculate the comprehensive fault severity index of each computer room based on the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices, and based on the home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient preset for the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices.

[0095] The priority sorting queue generation module is used to generate priority sorting queues for each faulty computer room according to the comprehensive fault severity index from high to low, wherein the computer room with the highest comprehensive fault severity index has the highest processing priority.

[0096] By integrating the number of fault tickets for broadband, transmission, and wireless devices within the data center, a multi-dimensional correlation model is established, solving the problem of priority misjudgment caused by single-source fault analysis in traditional operations and maintenance. Compared with existing technologies, the correlation device fault handling method based on multi-dimensional fault data provided by this invention can more comprehensively reflect the overall health status of the data center, making the allocation of operations and maintenance resources more accurate and significantly improving processing efficiency.

[0097] Therefore, the associated equipment fault handling system based on multidimensional fault data provided in the embodiments of the present invention can efficiently and flexibly handle multidimensional faults.

[0098] Figure 2 This is a schematic diagram of the structure of an associated equipment fault handling system based on multidimensional fault data according to an embodiment of the present invention.

[0099] exist Figure 2 The illustrated embodiment shows an associated equipment fault handling system based on multidimensional fault data, comprising:

[0100] The data acquisition module 201 is used to collect in real time the equipment information of the equipment associated with multiple computer rooms and the equipment fault work order data of the equipment associated with the computer rooms. The equipment associated with the computer rooms in each computer room includes broadband equipment, transmission equipment and wireless equipment according to their respective specialties.

[0101] The statistical calculation module 202 is used to associate the computer room fault work order of each computer room with the equipment fault work orders of the computer room associated equipment under that computer room, count the number of faulty equipment of the computer room associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the computer room associated equipment according to the profession.

[0102] The professional sorting module 203 is used to sort the number of faulty devices in each computer room according to their professional category from the largest to the smallest among all computer rooms where faults have occurred, to obtain the reverse sorted number of the number of faulty devices in that computer room by professional category: broadband devices, transmission devices, and wireless devices. It also sorts the total number of faulty devices in each computer room from the largest to the smallest among all computer rooms where faults have occurred, to obtain the reverse sorted number of the number of faulty devices in that computer room: total number of devices.

[0103] The comprehensive fault severity index calculation module 204 is used to calculate the comprehensive fault severity index of each computer room based on the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices, and based on the home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient preset for the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices.

[0104] The priority sorting queue generation module 205 is used to generate a priority sorting queue for each computer room that has experienced a failure, from high to low according to the comprehensive failure severity index, wherein the computer room with the highest comprehensive failure severity index has the highest processing priority.

[0105] According to an embodiment of a third aspect of the present invention, an associated device fault handling device based on multidimensional fault data is provided, comprising a memory and a processor, wherein executable code is stored in the memory, and when the processor executes the executable code, the associated device fault handling method based on multidimensional fault data described above is performed.

[0106] One embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform a data center associated equipment fault handling method based on multi-dimensional fault data according to any embodiment of the specification.

[0107] According to one or more embodiments of the present invention, the associated equipment fault handling method, system and equipment based on multi-dimensional fault data adopts a comprehensive data center fault handling priority ranking algorithm. Through the collaborative calculation of three-dimensional work order quantities of broadband equipment, transmission equipment and wireless equipment, dynamic optimal scheduling of data center fault handling is realized. It can solve a number of existing technical problems such as fragmented analysis of multi-source work orders, inefficiency of manual decision-making and rigidity of static rules. Experiments show that its fault location efficiency is significantly improved.

[0108] According to one or more embodiments of the present invention, a method, system, and device for handling associated equipment faults based on multidimensional fault data are provided. By establishing a cross-device work order fusion mechanism, the method integrates three types of heterogeneous fault work order data—broadband equipment, transmission equipment, and wireless equipment—and constructs a unified quantitative model, thereby effectively eliminating data silos. Based on a preset weight strategy and real-time changes in work order volume, the method can automatically calculate the comprehensive fault severity index score for each data center, thereby dynamically generating a fault handling priority ranking queue, which can replace the traditional manual experience-based ranking with poor objectivity. The method can intelligently allocate operation and maintenance resources according to the dynamic fault handling priority ranking queue to ensure that data center faults with higher severity are handled first, thereby optimizing resource scheduling response and shortening service interruption time.

[0109] In summary, the method, system, and device for handling associated equipment faults based on multidimensional fault data provided by one or more embodiments of the present invention can efficiently and flexibly handle multidimensional faults.

[0110] It should be noted that the terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0111] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0112] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the apparatus of the embodiments of the present invention. In other embodiments of the specification, the above-described apparatus may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0113] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0114] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using hardware, software, widgets, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium.

[0115] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for handling associated equipment faults based on multidimensional fault data, characterized in that, include: The system collects equipment information and equipment fault work order data of the associated equipment from multiple data centers in real time. The associated equipment in each data center includes broadband equipment, transmission equipment, and wireless equipment according to their respective specialties. Associate the fault work orders of each computer room with the equipment fault work orders of the associated equipment under that computer room, count the number of faulty equipment of the associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the associated equipment under each computer room according to the profession. The number of faulty devices in each computer room is sorted by specialty from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room: broadband devices, transmission devices, and wireless devices. Furthermore, the total number of faulty devices in each computer room is sorted from most to least among all computer rooms that experienced faults, resulting in a descending order of the number of faulty devices in that computer room: total number of devices. Based on the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, and based on the preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient for the sorted number of home broadband devices, the sorted number of transmission devices, the sorted number of wireless devices, and the total number of devices, calculate the comprehensive fault severity index for each data center. Each data center that has experienced a failure will be sorted into a priority queue according to the comprehensive failure severity index from high to low, with the data center having the highest comprehensive failure severity index having the highest processing priority.

2. The method for handling associated equipment faults based on multidimensional fault data as described in claim 1, characterized in that, The preset home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient are coefficients that can be adjusted according to the actual situation.

3. The method for handling associated equipment faults based on multidimensional fault data as described in claim 2, characterized in that, At least one of the broadband professional coefficient, the transmission professional coefficient, the wireless professional coefficient, and the total number of devices coefficient is dynamically adjusted based on the importance of at least one of the data center-related devices in at least one data center to the operation of the data center.

4. The method for handling associated equipment faults based on multidimensional fault data as described in claim 1, characterized in that, The step of calculating the comprehensive fault severity index of each computer room includes: calculating the comprehensive fault severity index of each computer room through a normalized scoring method, wherein the broadband professional coefficient, the transmission professional coefficient, the wireless professional coefficient, and the total number of devices coefficient are: broadband professional weight value, transmission professional weight value, wireless professional weight value, and total number of devices weight value.

5. The method for handling associated equipment faults based on multidimensional fault data as described in claim 4, characterized in that, The comprehensive fault severity index S is calculated according to the following formula: S=W1*(L-R1) / L+W2*(L-R2) / L+W3*(L-R3) / L+W4*(L-R4) / L, Where W1, W2, W3, and W4 are the weight values ​​for the home broadband, transmission, and wireless equipment, respectively, and the total number of devices; L = the total number of all equipment rooms where faults occurred + 1; R1, R2, and R3 are the sorted numbers of the home broadband, transmission, and wireless equipment in the equipment rooms, obtained by sorting the number of faulty devices in the equipment rooms in reverse order among all equipment rooms where faults occurred; R4 is the total number of devices obtained by sorting the total number of faulty devices in the equipment rooms in reverse order among all equipment rooms where faults occurred.

6. The method for handling associated equipment faults based on multidimensional fault data as described in claim 1, characterized in that, Further includes: Based on the real-time collected equipment information from multiple data centers and the equipment failure work order data of the data center-related equipment, the equipment failure work order data is updated in real time, and the comprehensive failure severity index of each data center is recalculated and the priority sorting queue is regenerated.

7. The method for handling associated equipment faults based on multidimensional fault data as described in claim 1, characterized in that, Further includes: Based on the real-time collected equipment information from multiple data centers and the equipment failure work order data of the data center-related equipment, the equipment failure work order data is updated periodically, and the comprehensive failure severity index of each data center is recalculated and the priority sorting queue is regenerated.

8. The method for handling associated equipment faults based on multidimensional fault data as described in claim 1, characterized in that, Further includes: When the comprehensive fault severity index exceeds the preset comprehensive fault severity index threshold, a severe fault warning signal is issued.

9. A fault handling system for associated equipment based on multidimensional fault data, characterized in that, The method for handling associated equipment faults based on multidimensional fault data according to any one of claims 1-8 includes: The data acquisition module is used to collect equipment information and equipment fault work order data of the associated equipment from multiple computer rooms in real time. The associated equipment of each computer room includes broadband equipment, transmission equipment and wireless equipment according to their respective specialties. The statistical calculation module is used to associate the computer room fault work order of each computer room with the equipment fault work orders of the computer room associated equipment under that computer room, count the number of faulty equipment of the computer room associated equipment under each computer room according to the profession, calculate the total number of faulty equipment in each computer room, and calculate the total number of faulty equipment of the computer room associated equipment that has failed according to the profession. The professional sorting module is used to sort the number of faulty devices in each computer room by professional category from most to least among all computer rooms where faults have occurred, to obtain the reverse order of the number of faulty devices in that computer room by professional category: broadband devices, transmission devices, and wireless devices. It also sorts the total number of faulty devices in each computer room from most to least among all computer rooms where faults have occurred, to obtain the reverse order of the number of faulty devices in that computer room: total number of devices. The comprehensive fault severity index calculation module is used to calculate the comprehensive fault severity index of each computer room based on the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices, and based on the home broadband professional coefficient, transmission professional coefficient, wireless professional coefficient, and total number of devices coefficient preset for the number of home broadband devices, the number of transmission devices, the number of wireless devices, and the total number of devices. The priority sorting queue generation module is used to generate priority sorting queues for each faulty computer room according to the comprehensive fault severity index from high to low, wherein the computer room with the highest comprehensive fault severity index has the highest processing priority.

10. A fault handling device for associated equipment based on multidimensional fault data, characterized in that, It includes a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements the associated equipment fault handling method based on multidimensional fault data according to any one of claims 1-8.

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