Alarm information fusion and processing method, system, equipment and medium in operation and maintenance of intelligent machine room

Abstract

The invention relates to an alarm information fusion and processing method, system, equipment and medium in operation and maintenance of an intelligent machine room, and the method comprises the following steps: carrying out the data collection and preprocessing, and obtaining a real-time data set; performing aggregation and correlation analysis on the real-time data set to obtain an alarm data set; and performing alarm processing on the alarm data set, and visualizing an alarm processing result. According to the invention, big data analysis and machine learning technologies are comprehensively applied to process equipment states and environment parameter information collected by various sensors deployed in a machine room, a clustering algorithm in machine learning is adopted to classify and cluster alarm information, and meanwhile, a composite alarm event is identified through association analysis, so that repeated alarms are reduced, and the alarm efficiency is improved. The accuracy and efficiency of alarm processing are improved, and the reliability and safety of machine room operation are guaranteed. Therefore, the method can be widely applied to the field of machine room intelligent operation and maintenance management.

Description

Technical Field

[0001] The present invention relates to a method, system, equipment and medium for merging and processing alarm information in intelligent computer room operation and maintenance, and belongs to the field of intelligent computer room operation and maintenance management. Background Art

[0002] The intelligent operation and maintenance management system of the communication room is a new model that strengthens the construction, management and maintenance of the room by comprehensively applying modern science and technology, integrating information resources, and coordinating business application systems. It is a brand-new operation and maintenance management system for the room. The platform software integrates technologies such as intelligent perception, big data, artificial intelligence, and three-dimensional digital twins to form a set of intelligent operation and maintenance management systems for communication rooms with diverse business forms and efficient user interaction modes. The system provides real-time collection, processing, and big data analysis of equipment information, and provides intelligent processing solutions for the operation and maintenance of the room, realizing unattended operation, precise maintenance, and efficient operation and maintenance of the room. Through the operation and maintenance management platform software, users can intuitively view the layout environment of the room, the location information of cabinets and equipment, the environmental data of the room, etc., to assist users in quickly locating faults and taking timely processing measures, thereby ensuring the reliability and safety of the operation of the room.

[0003] The communication room plays a key role in modern data centers and network systems, ensuring the stable operation of network services. With the continuous expansion of data centers and the rapid development of technology, the types and quantity of equipment in the communication room are numerous, and the alarm information generated is also increasing. At present, the monitoring of communication rooms mainly relies on a series of sensors, cameras and other equipment, and processes alarm information through traditional alarm processing methods such as manual screening and simple rule matching. However, these alarm information processing methods are unable to cope with massive alarm data, and there are the following problems: 1. The high duplication rate of alarm information makes it difficult for security administrators to focus on handling truly important alarm events; 2. Lack of effective alarm fusion mechanism makes alarm processing inefficient; 3. It is impossible to perform intelligent analysis based on the correlation of alarm information, resulting in a high false alarm rate. Summary of the invention

[0004] In response to the above problems, the purpose of the present invention is to provide a method, system, equipment and medium for fusion and processing of alarm information in the operation and maintenance of intelligent computer rooms. By comprehensively analyzing various types of alarm information, it can reduce duplicate alarms, improve the accuracy and efficiency of alarm processing, and ensure the reliability and safety of computer room operation.

[0005] To achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for merging and processing alarm information in intelligent computer room operation and maintenance, comprising the following steps: Perform data collection and preprocessing to obtain real-time data sets; Aggregate and correlate real-time data sets to obtain alarm data sets; Perform alarm processing based on aggregation and correlation analysis results, and visualize the alarm processing results.

[0006] Furthermore, the data collection and preprocessing are performed to obtain a real-time data set, including: Deploy various sensors and video acquisition equipment at preset key locations in the computer room; Based on various sensors and video acquisition devices, real-time collection of equipment status and environmental parameters is performed; Preprocess the real-time collected data to obtain a real-time data set.

[0007] Furthermore, the real-time data set is aggregated and correlated to obtain an alarm data set, including: Classify alarm information based on the obtained real-time data set and extract key features of various alarm information; Based on the key features of various types of alarm information, similar alarm information is aggregated; Perform correlation analysis on the aggregation results of various alarm information to identify possible compound alarm events, and then eliminate them to obtain the alarm data set.

[0008] Further, the alarm information is classified based on the obtained real-time data set, and key features of various types of alarm information are extracted, including the following steps: According to the source of the alarm information, the alarm information is divided into three categories: hardware alarm, software alarm and environmental alarm; According to the specific type of alarm information, each category of alarm information is subdivided into three types: fault alarm, performance alarm and safety alarm; Using feature extraction methods, key features of different types of warning information in different categories are extracted.

[0009] Further, the aggregation of similar alarm information based on key features of various alarm information includes the following steps: ① Take a certain type of alarm information as a sample set; ② Randomly select k samples as the initial centroid; ③For each sample in the sample set, calculate the class it should belong to; ④ For each class, recalculate the centroid of the class; ⑤ Repeat steps ③ to ④ until the centroid remains unchanged or changes less than the preset value, completing the aggregation of this type of alarm information; ⑥ For each type of alarm information, repeat steps ② to ⑤ to complete the aggregation of each type of alarm information.

[0010] Furthermore, when performing correlation analysis on the alarm information, an Apriori algorithm is used.

[0011] Further, the alarm processing based on the aggregation and correlation analysis results and the visualization of the alarm processing results include: Evaluate the priority of various alarm information according to their importance and urgency; The current alarm information is visualized according to the preset priority order and the alarm priority evaluation results.

[0012] In a second aspect, the present invention provides an alarm information fusion and processing system in intelligent computer room operation and maintenance, comprising: Data acquisition module, used for data acquisition and preprocessing to obtain real-time data sets; Aggregation and correlation analysis module, used to aggregate and correlate real-time data sets to obtain alarm data sets; The alarm processing module is used to perform alarm processing on the alarm data set and visualize the alarm processing results.

[0013] In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform any of the methods.

[0014] In a fourth aspect, the present invention provides a computing device, comprising: one or more processors and a memory, wherein the memory stores one or more programs and is configured to be executed by the one or more processors, and the one or more programs include instructions for executing any method.

[0015] The present invention adopts the above technical solution, which has the following advantages: 1. The present invention uses big data analysis and machine learning technology to precisely arrange various sensors, cameras and other equipment in the computer room, collect information such as equipment status and environmental parameters in real time, and effectively process alarm information in combination with big data analysis technology; 2. The present invention extracts key features of alarm information and uses clustering algorithms in machine learning to classify and cluster alarm information, thereby reducing duplicate alarms; 3. The present invention identifies compound alarm events through correlation analysis and adopts a priority evaluation model to ensure that important alarms are handled in a timely manner; 4. The present invention studies relevant standards, documents and manuals, refines various alarm processing indicators, and proposes alarm information processing standards in combination with the on-site operation and maintenance conditions of the computer room and environmental factors. It uses big data analysis methods to correct the weights of factors affecting alarm processing, and comprehensively calculates the alarm information processing model. The model has an automatic correction function and can continuously correct the weights of influencing factors according to real-time data during the calculation to improve the accuracy and efficiency of alarm information processing.

[0016] The present invention realizes the effective integration and accurate identification of alarm information, thereby improving the intelligent level of computer room operation and maintenance. Therefore, the present invention can be widely used in the field of intelligent operation and maintenance management of computer rooms. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Throughout the accompanying drawings, the same reference numerals are used to represent the same components. In the accompanying drawings: Figure 1 It is a flow chart of the alarm information fusion and processing method in the operation and maintenance of the intelligent computer room provided in an embodiment of the present invention; Figure 2 is a flow chart of the K-means clustering algorithm provided in an embodiment of the present invention; Figure 3 is a flowchart of alarm information correlation analysis provided in an embodiment of the present invention; Figure 4 It is a flowchart of alarm priority evaluation provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0019] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0020] In some embodiments of the present invention, a method for fusion and processing of alarm information in intelligent computer room operation and maintenance is provided. The method first uses clustering algorithm based on big data analysis and machine learning technology to reduce repeated alarms; then, composite alarm events are identified through association analysis; finally, a priority evaluation model is used to ensure that important alarms are processed in a timely manner. Through these technical means, the present invention realizes efficient processing and accurate identification of computer room alarm information, and significantly improves the intelligent level of computer room operation and maintenance.

[0021] Correspondingly, in some other embodiments of the present invention, a system, device and medium for fusion and processing of alarm information in operation and maintenance of an intelligent computer room are provided.

[0022] Example 1 like Figure 1 As shown, the present invention provides a method for merging and processing alarm information in intelligent computer room operation and maintenance, aiming to reduce duplicate alarms and improve the accuracy and efficiency of alarm processing by comprehensively analyzing various types of alarm information.

[0023] Specifically, the steps include: 1) Perform data collection and preprocessing to obtain real-time data sets; 2) Aggregate and correlate real-time data sets to reduce duplicate alarms and obtain alarm data sets; 3) Perform alarm processing on the alarm data set and visualize the alarm processing results.

[0024] Furthermore, in the above step 1), data collection and preprocessing are performed to obtain a real-time data set, including the following steps: 1.1) Deploy various sensors and video acquisition equipment at preset key locations in the computer room; 1.2) Based on various sensors and video acquisition devices, real-time collection of equipment status and environmental parameters is performed; 1.3) Preprocess the real-time collected data to obtain a real-time data set, providing a high-quality data foundation for subsequent alarm fusion.

[0025] Furthermore, in the above step 1.1), the various sensors deployed in the computer room mainly include temperature sensors, humidity sensors, smoke sensors, etc., and the deployment positions of the sensors must ensure that they can cover all key areas in the computer room.

[0026] The video acquisition equipment deployed in the computer room mainly includes cameras, radar-vision integrated devices, etc.

[0027] Furthermore, in the above step 1.2), after the sensors and video acquisition equipment are deployed in the computer room, the sensors are used to collect equipment status and environmental parameters such as temperature, humidity, and smoke concentration in real time; cameras, radar-vision integrated devices, etc. are used to record video images in the computer room in real time for auxiliary analysis.

[0028] Furthermore, in the above step 1.3), the real-time collected data is preprocessed, including data cleaning, data normalization, data integration and other operations on the collected raw data to ensure the quality and consistency of the data and provide a high-quality data foundation for subsequent alarm fusion. Among them, data cleaning is used to remove invalid data, outliers and noise, data normalization is used to unify different types of sensor data into the same scale range, and data integration is used to integrate data from different sources to form a unified data set.

[0029] In this embodiment, the Z-score method is used to detect outliers in real-time collected data, which is expressed as: (1) in, is a data point, is the mean, is the standard deviation. If >3, the data point is considered an outlier.

[0030] Min-Max normalization is used to map the original real-time acquisition data to the [0,1] interval, expressed as: (2) in, To normalize the data, is the minimum value of the data points, is the maximum value of the data points.

[0031] Furthermore, in the above step 2), the real-time data set is aggregated and correlated to obtain an alarm data set, which includes the following steps: 2.1) Classify the alarm information based on the obtained real-time data set and extract the key features of each type of alarm information; 2.2) Based on the key features of various types of alarm information, similar alarm information is aggregated to reduce duplicate alarms; 2.3) Conduct correlation analysis on the aggregation results of various alarm information to identify possible compound alarm events and further reduce duplicate alarms.

[0032] Furthermore, in the above step 2.1), the alarm information is classified based on the obtained real-time data set, and the key features of each type of alarm information are extracted, including the following steps: 2.1.1) According to the source of the alarm information, the alarm information is divided into hardware alarm, software alarm and environmental alarm; 2.1.2) According to the specific type of alarm information, each type of alarm information is subdivided into fault alarm, performance alarm and safety alarm; 2.1.3) Use feature extraction methods to extract key features of different types of warning information in different categories; In this embodiment, the key features of the alarm information mainly include the alarm source, alarm level, alarm time, etc. The formula for feature extraction is: (3) in, For the Features.

[0033] Furthermore, in the above step 2.2), based on the key features of various types of alarm information, when the alarm information of the same type is aggregated, the clustering algorithm K-means in machine learning is used to cluster the alarm information. Specifically, the steps include: 2.2.1) Taking a certain type of alarm information as a sample set; 2.2.2) Randomly select k samples as the initial centroids, expressed as: (4) 2.2.3) For each sample in the sample set, calculate the class it should belong to: (5) 2.2.4) For each class, recalculate the centroid of the class: (6) 2.2.5) Repeat steps 2.2.3) to 2.2.4) until the centroid remains unchanged or changes less than the preset value, completing the aggregation of this type of alarm information; 2.2.6) Repeat steps 2.2.2) to 2.2.5) for each type of alarm information to complete the aggregation of each type of alarm information.

[0034] Furthermore, in the above step 2.3), when performing correlation analysis on the alarm information, the Apriori algorithm is used. The Apriori algorithm is a well-known technology for those skilled in the art, and the present invention will not elaborate on it.

[0035] Furthermore, in the above step 3), alarm processing is performed on the alarm data set, and the alarm processing result is visualized, including the following steps: 3.1) According to the importance and urgency of the alarm information, the alarm priority of each type of alarm information is evaluated to ensure that important alarms are handled in a timely manner.

[0036] In this embodiment, the allocation of alarm weights needs to take the alarm levels into consideration. Based on literature research and feedback from on-site operation and maintenance personnel, the initial allocation of weights is as follows: The weight of an emergency alarm is 50%, the weight of a major alarm is 30%, and the weight of a general alarm is 20%.

[0037] 3.2) Visually display the current alarm information according to the preset priority order and alarm priority evaluation results.

[0038] In this embodiment, the processed alarm information is pushed to the administrator in the order of urgent, important, and general priorities, ensuring that each type of high-priority alarm is responded to in a timely manner.

[0039] Example 2 The above-mentioned embodiment 1 provides an alarm information fusion and processing method in the operation and maintenance of an intelligent computer room. Correspondingly, this embodiment provides an alarm information fusion and processing system in the operation and maintenance of an intelligent computer room. The system provided in this embodiment can implement the alarm information fusion and processing method in the operation and maintenance of an intelligent computer room of embodiment 1. The system can be implemented by software, hardware, or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to execute the corresponding steps in each method of embodiment 1. Since the system of this embodiment is basically similar to the method embodiment, the process described in this embodiment is relatively simple. For relevant matters, please refer to the partial description of embodiment 1. The embodiment of the system provided in this embodiment is merely illustrative.

[0040] The alarm information fusion and processing system in the intelligent computer room operation and maintenance provided in this embodiment includes: Data acquisition module, used for data acquisition and preprocessing to obtain real-time data sets; Aggregation and correlation analysis module, used to aggregate and correlate real-time data sets, reduce duplicate alarms, and obtain alarm data sets; The alarm processing module is used to perform alarm processing on the alarm data set and visualize the alarm processing results.

[0041] Example 3 This embodiment provides a processing device corresponding to the alarm information fusion and processing method in the intelligent computer room operation and maintenance provided in this embodiment 1. The processing device can be a processing device for a client, such as a mobile phone, a laptop computer, a tablet computer, a desktop computer, etc., to execute the method of embodiment 1.

[0042] The processing device includes a processor, a memory, a communication interface and a bus, and the processor, the memory and the communication interface are connected through the bus to complete mutual communication. The memory stores a computer program that can be run on the processor, and the processor executes the alarm information fusion and processing method in the operation and maintenance of the intelligent computer room provided in this embodiment 1 when running the computer program.

[0043] Preferably, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0044] Preferably, the processor may be a central processing unit (CPU), a digital signal processor (DSP) or other general-purpose processors of various types, which are not limited here.

[0045] Example 4 The alarm information fusion and processing method in the intelligent computer room operation and maintenance of this embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the alarm information fusion and processing method in the intelligent computer room operation and maintenance described in this embodiment 1 are loaded.

[0046] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0047] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 One or more processes and / or boxes Figure 1 A function specified in one or more boxes. These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for fusion and processing of alarm information in intelligent computer room operation and maintenance, characterized in that: The following steps are involved: Perform data collection and preprocessing to obtain real-time data sets; Aggregate and correlate real-time data sets to obtain alarm data sets; Perform alarm processing on the alarm data set and visualize the alarm processing results.

2. The method for fusion and processing of alarm information in intelligent computer room operation and maintenance according to claim 1, characterized in that: The data collection and preprocessing are performed to obtain a real-time data set, including: Deploy various sensors and video acquisition equipment at preset key locations in the computer room; Based on various sensors and video acquisition devices, real-time collection of equipment status and environmental parameters is performed; Preprocess the real-time collected data to obtain a real-time data set.

3. The method for fusion and processing of alarm information in intelligent computer room operation and maintenance according to claim 1, characterized in that: The real-time data set is aggregated and correlated to obtain an alarm data set, including: Classify alarm information based on the obtained real-time data set and extract key features of various alarm information; Based on the key features of various types of alarm information, similar alarm information is aggregated; Perform correlation analysis on the aggregation results of various alarm information to identify possible compound alarm events, and then eliminate them to obtain the alarm data set.

4. The method for fusion and processing of alarm information in intelligent computer room operation and maintenance according to claim 3, characterized in that: The method of classifying the alarm information based on the obtained real-time data set and extracting key features of various types of alarm information includes the following steps: According to the source of the alarm information, the alarm information is divided into three categories: hardware alarm, software alarm and environmental alarm; According to the specific type of alarm information, each category of alarm information is subdivided into three types: fault alarm, performance alarm and safety alarm; Using feature extraction methods, key features of different types of warning information in different categories are extracted.

5. The method for fusion and processing of alarm information in intelligent computer room operation and maintenance according to claim 4, characterized in that: The method of aggregating the same type of alarm information based on the key features of the alarm information includes the following steps: ① Take a certain type of alarm information as a sample set; ② Randomly select k samples as the initial centroid; ③For each sample in the sample set, calculate the class it should belong to; ④ For each class, recalculate the centroid of the class; ⑤ Repeat steps ③ to ④ until the centroid remains unchanged or changes less than the preset value, completing the aggregation of this type of alarm information; ⑥ For each type of alarm information, repeat steps ② to ⑤ to complete the aggregation of each type of alarm information.

6. The method for fusion and processing of alarm information in intelligent computer room operation and maintenance according to claim 4, characterized in that: When performing correlation analysis on the alarm information, the Apriori algorithm is used.

7. The method for fusion and processing of alarm information in intelligent computer room operation and maintenance according to claim 1, characterized in that: The alarm processing of the alarm data set and visualization of the alarm processing result include: Evaluate the priority of various alarm information according to their importance and urgency; The current alarm information is visualized according to the preset priority order and the alarm priority evaluation results.

8. An alarm information fusion and processing system in intelligent computer room operation and maintenance, characterized in that: include: Data acquisition module, used for data acquisition and preprocessing to obtain real-time data sets; Aggregation and correlation analysis module, used to aggregate and correlate real-time data sets to obtain alarm data sets; The alarm processing module is used to perform alarm processing on the alarm data set and visualize the alarm processing results.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform any one of the methods of claims 1 to 7.

10. A computing device, characterized in that include: One or more processors and a memory, wherein the memory stores one or more programs and is configured to be executed by the one or more processors, wherein the one or more programs include instructions for executing any one of the methods described in claims 1 to 7.

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