CN115242664A - Intelligent machine room management method based on big data analysis model - Google Patents
Intelligent machine room management method based on big data analysis model Download PDFInfo
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- 238000007405 data analysis Methods 0.000 title claims abstract description 54
- 238000007726 management method Methods 0.000 title claims abstract description 50
- 238000012545 processing Methods 0.000 claims abstract description 55
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 39
- 238000004891 communication Methods 0.000 claims abstract description 24
- 238000000034 method Methods 0.000 claims abstract description 16
- 238000005286 illumination Methods 0.000 claims description 16
- 238000012790 confirmation Methods 0.000 claims description 12
- 238000012544 monitoring process Methods 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 7
- 230000005611 electricity Effects 0.000 claims description 7
- 238000013500 data storage Methods 0.000 claims description 6
- 238000013527 convolutional neural network Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 238000012098 association analyses Methods 0.000 claims description 3
- 238000013135 deep learning Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 5
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/80—Arrangements in the sub-station, i.e. sensing device
- H04Q2209/82—Arrangements in the sub-station, i.e. sensing device where the sensing device takes the initiative of sending data
- H04Q2209/823—Arrangements in the sub-station, i.e. sensing device where the sensing device takes the initiative of sending data where the data is sent when the measured values exceed a threshold, e.g. sending an alarm
Abstract
The invention discloses a machine room intelligent management method based on a big data analysis model, which comprises the following steps: collecting state information of all equipment in a machine room; storing the collected state information of all the devices; the core processing module processes the state information of all the devices; the big data analysis module acquires data from the database to perform big data analysis; the communication module is connected with the core processing module, the big data analysis module, the management module and the artificial intelligence module, and exchanges information of each module. According to the invention, all equipment in the machine room is automatically controlled by sending the intelligent control instruction through the artificial intelligent module, manual operation is not required, the use is convenient, the manual management cost is reduced, and the machine room management efficiency is improved.
Description
Technical Field
The invention relates to an intelligent machine room management method, in particular to an intelligent machine room management method based on a big data analysis model.
Background
Artificial intelligence is a new technical science for studying and developing theories, methods, techniques and application systems for simulating, extending and expanding human intelligence. The method can be used for solving various intelligent complex problems such as non-numerical operation, solution, reasoning, decision and the like.
The big data analysis is data analysis based on mass data, and the big data has the characteristics of large data volume, high speed, multiple types, high value, authenticity and the like. The big data analysis of the state grid power can accurately count and analyze the condition of regional power load, and can better calculate and predict the power consumption peak period. With the continuous development of 5G technology, artificial intelligence and big data analysis, the intelligent machine room management system method is gradually emphasized. Meanwhile, the scale of the machine room is continuously enlarged, more and more devices such as servers and computers are used, environmental parameters such as temperature, humidity and illumination intensity in the machine room are particularly important to the quality and service life of the devices and the safety of the machine room, meanwhile, most of the servers work all day for 24 hours, and the fact that the timely supply of electric power is guaranteed has important significance to the servers. At present, most machine rooms are managed manually, however, due to the fact that the machine rooms are large in area, large in equipment quantity and various, management personnel are needed extremely much, timely reflection can not be made in power failure and low-voltage periods, management efficiency is low, and potential safety hazards exist.
Disclosure of Invention
In view of the above situations, the present invention aims to provide an intelligent management method for a machine room based on a big data analysis model, which can effectively monitor environmental parameters such as temperature, humidity, illumination intensity and the like in the machine room and timely make adjustment or early warning; meanwhile, when the local power load is overlarge or the power failure tendency exists, the corresponding adjustment can be effectively made on the equipment in the machine room.
The purpose of the invention is realized by the following technical scheme:
a machine room intelligent management method based on a big data analysis model is characterized by comprising the following steps:
1) Collecting the running state information of all equipment in the machine room through an information collection module and sending the running state information to a core processing module;
2) The acquired equipment running state information is stored through a machine room data storage module; processing the acquired state information through a core processing module;
3) Local power utilization data are obtained through a database; processing and predicting the electricity utilization data through a big data analysis module;
4) The prediction information obtained after the big data analysis module processes and/or the state information processed by the core processing module is sent to the artificial intelligence module through the communication module;
5) The prediction result of the big data analysis module and the processing result of the core processing module are analyzed through the artificial intelligence module, and the processing result is sent to the management module through the communication module;
6) And checking the processing result of the core processing module, the analysis result of the artificial intelligence module and the intelligent control instruction through the intelligent terminal, sending a command to the artificial intelligence module, and sending information to inform a user through the early warning module.
In the invention, an information collection module collects the running state information of all equipment in a machine room;
the computer room data storage module is connected with the information collection module and used for storing and backing up the collected data of all the devices;
the core processing module is connected with the information collection module and executes related instructions according to the equipment information transmitted by the information collection module;
the early warning module is connected with the core processing module and sends early warning information to a user; the early warning module adopts an audible and visual alarm.
The big data analysis module is connected with the database and is used for carrying out big data analysis according to the related data;
the management module is connected with all the equipment in the machine room and is used for managing and controlling the equipment in the machine room according to related instructions;
the artificial intelligence module sends an intelligent control instruction to automatically control all equipment in the machine room, so as to realize automatic management and control on the equipment in the machine room;
the intelligent terminal checks the processing result of the processing module, the analysis result of the artificial intelligence module and the intelligent control instruction and sends a command to the artificial intelligence module;
the communication module is connected with the artificial intelligence module, the management module, the big data analysis module and the core processing module and transmits the big data information processed by the big data analysis module and the equipment running state information processed by the core processor to the artificial intelligence module;
wherein, the information collection module includes:
the air composition information collector is used for collecting main composition information of air in the machine room; the air information collector adopts an air analyzer based on a high-sensitivity electrochemical sensor.
The indoor and outdoor temperature information collector is used for collecting the temperature information inside and outside the machine room; the indoor and outdoor temperature information collector adopts a temperature sensor to collect information.
The illumination information collector is used for collecting illumination information of the machine room; the illumination information collector adopts a brightness sensor to collect information.
The monitoring equipment is used for acquiring video and image information in the machine room; the monitoring equipment adopts a camera and a hard disk camera to collect information.
And the information collecting module is connected with the air composition information collector, the indoor and outdoor temperature information collector, the illumination information collector and the monitoring equipment, and collects and integrates the air composition information, the temperature information, the illumination information and the video image information in the machine room.
Big data analysis module includes:
the data dimension reduction is carried out on the data in the database, so that dimension disasters are prevented; the data dimension reduction adopts a low variance filtering method to remove the rows with smaller variance of the data rows so as to achieve the purpose of dimension reduction;
extracting features, namely processing the data subjected to dimensionality reduction through a deep learning network to obtain deep features; the feature extraction adopts a method based on a Convolutional Neural Network (CNN), and the feature extraction is carried out on the data after the dimension reduction through a multilayer network;
learning a feature association rule, and performing association analysis on the extracted depth features to obtain associations among different features; and (4) learning the feature association rule, scanning the extracted depth features for multiple times by adopting an Aprior algorithm, and calculating corresponding confidence to generate a management rule.
The management module comprises:
a confirmation unit that performs a confirmation operation;
a permitting unit that performs a permitting operation;
a termination unit that performs a termination operation;
an adjustment unit that performs an adjustment operation;
an assist unit that performs an assist operation;
and the operation unit is connected with the confirmation unit, the permission unit, the termination unit, the regulation unit and the auxiliary unit and executes the respective operations of the confirmation unit, the permission unit, the termination unit, the regulation unit and the auxiliary unit.
The intelligent terminal is a mobile phone, a computer or a tablet computer.
The communication module includes:
the sending unit is used for sending the intelligent control instruction and the information data;
an accepting unit that receives the status information;
the router selects a line for transmitting the intelligent control instruction and the state information, improves the communication speed, lightens the communication load of the network system, fully utilizes the resources of the network system, saves the resources of the network system and improves the smooth rate of the network system;
and the network unit is connected with the router and transmits the intelligent control command and the state information data. The network unit includes a wired network and a wireless network.
The invention collects the running state information of all equipment in a machine room through an information collection module and sends the running state information to a core processing module, the obtained equipment running state information is stored through a machine room data storage module, the obtained state information is processed through the core processing module, local electricity utilization data is obtained through a power grid database, the electricity utilization data is processed and predicted through a big data analysis module, the prediction information obtained after the big data analysis module processes and/or the state information processed through the core processing module is sent to an artificial intelligence module through a communication module, the prediction result of the big data analysis module and the processing result of the core processing module are analyzed through the artificial intelligence module, the processing result is sent to a management module through the communication module, the processing result of the core processing module, the analysis result of the artificial intelligence module and an intelligent control instruction are checked through an intelligent terminal, a command is sent to the artificial intelligence module, and information is sent to a user through an early warning module.
The invention has the advantages that the big data analysis module can be used for calculating and analyzing the collected data, the operation condition of equipment in the machine room can be adjusted in time before voltage is low or power failure occurs, and data loss of a server in the machine room and property loss caused by the data loss are prevented; the artificial intelligence module can send an intelligent control instruction to the management module to automatically control all equipment in the machine room, so that the personnel operation is reduced, and the labor cost is reduced; the machine room parameters are monitored in real time through the artificial intelligence module, and the early warning module sends out early warning information to inform a user, so that the safety is improved, the potential safety hazard of the machine room is reduced, and the management efficiency is improved.
Drawings
FIG. 1 is a schematic block diagram of a machine room intelligent management method based on a big data analysis model.
FIG. 2 is a schematic block diagram of an information collection module of the present invention.
FIG. 3 is a functional block diagram of a management module of the present invention.
Fig. 4 is a schematic block diagram of a communication module according to the present invention.
FIG. 5 is a schematic block diagram of a big data analysis module according to the present invention.
Detailed Description
A machine room intelligent management method based on a big data analysis model comprises the following steps:
the method comprises the steps that operating state information of all equipment in a machine room is collected through an information collection module and sent to a core processing module, the obtained equipment operating state information is stored through a machine room data storage module, the obtained state information is processed through the core processing module, local electricity utilization data are obtained through an electric network database, the electricity utilization data are processed and predicted through a big data analysis module, the prediction information obtained after the big data analysis module processes and/or the state information processed through the core processing module are sent to an artificial intelligence module through a communication module, the prediction result of the big data analysis module and the processing result of the core processing module are analyzed through the artificial intelligence module, the processing result is sent to a management module through the communication module, the processing result of the core processing module, the analysis result of the artificial intelligence module and an intelligent control instruction are checked through an intelligent terminal, a command is sent to the artificial intelligence module, and information is sent to a user through an early warning module.
As shown in fig. 1, the information collection module collects operation state information of all devices (including computers, servers, switches, and air conditioners) in a machine room;
the computer room data storage module is connected with the information collection module and used for storing and backing up the collected data of all the devices;
the core processing module is connected with the information collection module and executes related instructions according to the equipment information transmitted by the information collection module;
the early warning module is connected with the core processing module and sends early warning information to a user;
the big data analysis module is connected with the national grid power database and is used for carrying out big data analysis according to the related data;
the management module is connected with all the equipment in the machine room and used for managing and controlling the equipment in the machine room according to related instructions;
the artificial intelligence module sends an intelligent control instruction to automatically control all equipment in the machine room, so as to realize automatic management and control on the equipment in the machine room;
the intelligent terminal checks the processing result of the processing module, the analysis result of the artificial intelligence module and the intelligent control instruction and sends a command to the artificial intelligence module;
the communication module is connected with the artificial intelligence module, the management module, the big data analysis module and the core processing module, transmits the state network power big data information processed by the big data analysis module and the equipment running state information processed by the core processor to the artificial intelligence module, the artificial intelligence sends an intelligent control instruction according to related information, and the communication module transmits the instruction control instruction to the management module;
as shown in fig. 2, the information collection module includes:
the air composition information collector is used for collecting main composition information of air in the machine room;
the indoor and outdoor temperature information collector is used for collecting the temperature information inside and outside the machine room;
the illumination information collector is used for collecting illumination information of the machine room;
the monitoring equipment is used for acquiring video and image information in the machine room;
and the information collecting module is connected with the air composition information collector, the indoor and outdoor temperature information collector, the illumination information collector and the monitoring equipment, and collects and integrates the air composition information, the temperature information, the illumination information and the video image information in the machine room.
As shown in fig. 3, the management module includes:
a confirmation unit that performs a confirmation operation;
a permitting unit that performs a permitting operation;
a termination unit that performs a termination operation;
an adjustment unit that performs an adjustment operation;
an assist unit that performs an assist operation;
and the operation unit is connected with the confirmation unit, the permission unit, the termination unit, the regulation unit and the auxiliary unit and executes the respective operations of the confirmation unit, the permission unit, the termination unit, the regulation unit and the auxiliary unit.
As shown in fig. 4, the communication module includes:
the sending unit is used for sending the intelligent control instruction and the information data;
an accepting unit that receives the status information;
the router selects a line for transmitting the intelligent control instruction and the state information, improves the communication speed, lightens the communication load of the network system, fully utilizes the resources of the network system, saves the resources of the network system and improves the smooth rate of the network system;
and the network unit is connected with the router and transmits the intelligent control instruction and the state information data.
The early warning module adopts audible and visual alarm, can in time report to the police to the user.
The intelligent terminal can be a mobile phone, a computer, a tablet computer and the like, and is wide in application range and convenient to use.
As shown in fig. 5, the big data analysis module includes:
reducing the dimension of the data, namely reducing the dimension of the data in the database to prevent dimension disasters;
extracting features, namely processing the data subjected to dimensionality reduction through a deep learning network to obtain deep features;
learning a feature association rule, and performing association analysis on the extracted depth features to obtain associations among different features;
the data in the database can be calculated and analyzed through the big data analysis module, the running condition of equipment in the machine room can be adjusted in time before voltage is low or power failure occurs, and data loss of a server in the machine room and property loss caused by the data loss are prevented; the artificial intelligence module can send an intelligent control instruction to the management module to automatically control all equipment in the machine room, so that the personnel operation is reduced, and the labor cost is reduced; the machine room parameters are monitored in real time through the artificial intelligence module, and the early warning module sends out early warning information to inform a user, so that the safety is improved, the potential safety hazard of the machine room is reduced, and the management efficiency is improved.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention.
Claims (10)
1. A machine room intelligent management method based on a big data analysis model is characterized by comprising the following steps:
1) Collecting the running state information of all equipment in the machine room through an information collection module and sending the running state information to a core processing module;
2) The acquired equipment running state information is stored through a machine room data storage module; processing the acquired state information through a core processing module;
3) Local electricity utilization data are obtained through a database; processing and predicting the electricity utilization data through a big data analysis module;
4) The prediction information obtained after the big data analysis module processes and/or the state information processed by the core processing module is sent to the artificial intelligence module through the communication module;
5) The prediction result of the big data analysis module and the processing result of the core processing module are analyzed through the artificial intelligence module, and the processing result is sent to the management module through the communication module;
6) And checking the processing result of the core processing module, the analysis result of the artificial intelligence module and the intelligent control instruction through the intelligent terminal, sending a command to the artificial intelligence module, and sending information to inform a user through the early warning module.
2. The intelligent management method for the computer room based on the big data analysis model as claimed in claim 1, wherein the information collection module is used for collecting the operation state information of all the devices in the computer room; the method comprises the following steps:
the air composition information collector is used for collecting main composition information of air in the machine room;
the indoor and outdoor temperature information collector is used for collecting the temperature information inside and outside the machine room;
the illumination information collector is used for collecting illumination information of the machine room;
the monitoring equipment is used for acquiring video and image information in the machine room;
and the information collecting module is connected with the air composition information collector, the indoor and outdoor temperature information collector, the illumination information collector and the monitoring equipment, and collects and integrates the air composition information, the temperature information, the illumination information and the video image information in the machine room.
3. The intelligent management method for the computer room based on the big data analysis model is characterized in that the air composition information collector adopts an air analyzer based on a high-sensitivity electrochemical sensor;
the indoor and outdoor temperature information collector collects information by adopting a temperature sensor;
the illumination information collector collects information by adopting a brightness sensor;
the monitoring equipment adopts a camera and a hard disk camera to collect information.
4. The intelligent management method for the machine room based on the big data analysis model as claimed in claim 1, wherein the big data analysis module is connected with a database and performs big data analysis according to related data; the method comprises the following steps:
reducing the dimension of the data, namely reducing the dimension of the data in the power database to prevent dimension disasters;
extracting features, namely processing the data subjected to dimensionality reduction through a deep learning network to obtain deep features;
and (4) learning a feature association rule, and performing association analysis on the extracted depth features to obtain the association among different features.
5. The intelligent management method for the machine room based on the big data analysis model as claimed in claim 4, wherein the dimension reduction of the data adopts a low variance filtering method to remove the column with the smaller variance of the data column so as to achieve the purpose of dimension reduction;
the characteristic extraction adopts a method based on a Convolutional Neural Network (CNN), and the characteristic extraction is carried out on the data after the dimension reduction through a multilayer network;
and (3) learning the feature association rule, scanning the extracted depth feature for multiple times by adopting an Apriori algorithm, and calculating a corresponding confidence coefficient to generate a management rule.
6. The intelligent management method for the machine room based on the big data analysis model as claimed in claim 1, wherein the management module is connected with all the devices in the machine room and manages and controls the devices in the machine room according to the related instructions; the management module comprises:
a confirmation unit that performs a confirmation operation;
a permitting unit that performs a permitting operation;
a termination unit that performs a termination operation;
an adjustment unit that performs an adjustment operation;
an assist unit that performs an assist operation;
and the operation unit is connected with the confirmation unit, the permission unit, the termination unit, the regulation unit and the auxiliary unit and executes the respective operations of the confirmation unit, the permission unit, the termination unit, the regulation unit and the auxiliary unit.
7. The intelligent management method for the machine room based on the big data analysis model as claimed in claim 1, wherein the communication module is connected with the artificial intelligence module, the management module, the big data analysis module and the core processing module, and transmits big data information processed by the big data analysis module and equipment operation state information processed by the core processor to the artificial intelligence module, the artificial intelligence sends an intelligent control instruction according to related information, and the communication module transmits the instruction control instruction to the management module, so as to realize automatic intelligent management of equipment in the machine room; the communication module includes:
the sending unit is used for sending the intelligent control instruction and the information data;
an accepting unit that receives the status information;
the router selects a line for transmitting the intelligent control instruction and the state information, improves the communication speed, lightens the communication load of the network system, fully utilizes the resources of the network system, saves the resources of the network system and improves the smooth rate of the network system;
and the network unit is connected with the router and transmits the intelligent control command and the state information data.
8. The intelligent management method for the computer room based on the big data analysis model as claimed in claim 7, wherein the network unit comprises a wired network and a wireless network.
9. The intelligent management method for the computer room based on the big data analysis model as claimed in claim 1, wherein the intelligent terminal checks the processing result of the processing module, the analysis result of the artificial intelligence module and the intelligent control instruction, and sends a command to the artificial intelligence module; the intelligent terminal is a mobile phone, a computer or a tablet computer.
10. The intelligent management method for the machine room based on the big data analysis model as claimed in claim 1, wherein the early warning module is connected with the core processing module and sends early warning information to a user; the early warning module adopts an audible and visual alarm.
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