CN117612093B - Dynamic environment monitoring method, system, equipment and medium for data center - Google Patents
Dynamic environment monitoring method, system, equipment and medium for data center Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 78
- 238000000034 method Methods 0.000 title claims abstract description 37
- 239000000779 smoke Substances 0.000 claims abstract description 207
- 230000004927 fusion Effects 0.000 claims abstract description 10
- 238000004364 calculation method Methods 0.000 claims description 16
- 238000011161 development Methods 0.000 claims description 10
- 238000012806 monitoring device Methods 0.000 claims description 10
- 230000005484 gravity Effects 0.000 claims description 6
- 238000010606 normalization Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 230000010354 integration Effects 0.000 claims description 3
- 238000009792 diffusion process Methods 0.000 description 15
- 238000005286 illumination Methods 0.000 description 6
- 230000007613 environmental effect Effects 0.000 description 5
- 230000005540 biological transmission Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
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- 230000009286 beneficial effect Effects 0.000 description 1
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- 238000004891 communication Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
- H04N23/11—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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Abstract
The application relates to the field of environment monitoring, in particular to a method, a system, equipment and a medium for monitoring the dynamic environment of a data center, wherein the method comprises the following steps: acquiring an infrared image and a visible light image of a machine room corresponding to a dynamic environment of a data center; acquiring an infrared weight corresponding to an infrared image and a monitoring weight corresponding to a visible light image; extracting a first smoke feature of the infrared image and a second smoke feature of the visible image; based on the first smoke feature, the infrared weight, the second smoke feature and the monitoring weight, carrying out smoke feature fusion to obtain target smoke features in a machine room corresponding to the dynamic environment of the data center; and determining a fire result of the machine room corresponding to the power environment of the data center based on the target smoke characteristics so as to monitor the power environment of the data center. The application can determine the fire condition more quickly.
Description
Technical Field
The application relates to the technical field of environment monitoring, in particular to a method, a system, equipment and a medium for monitoring the dynamic environment of a data center.
Background
Data center power environments are an important component of a data center, including the power system and environmental systems of the data center. The power system is a system for providing infrastructure such as electric power and air conditioning for a data center, and comprises power distribution equipment, a power supply, a UPS, a cooling system and the like. These devices need to remain stable and reliable to ensure proper operation of the data center. An environmental system is a system for monitoring and managing environmental factors such as temperature, humidity, air quality, etc. of a data center. These environmental factors have an important impact on the equipment performance and reliability of the data center and therefore require real-time monitoring and adjustment.
The data center power environment presents a corresponding room, which is a room or building specifically designed to house computer systems, servers, network equipment, and related infrastructure. It provides a safe, reliable, efficient environment to ensure the security, availability and reliability of data. The main functions of the machine room comprise data storage, data processing, data transmission and data protection. It is equipped with high-performance servers and computer systems for processing and analyzing large amounts of data while transmitting the data to various departments and users via high-speed network connections. In addition, various safety measures are taken in the machine room, including a fireproof system, a waterproof immersion system, video monitoring and the like, so as to ensure the safety of the machine room.
At present, a fireproof system is realized through smoke monitoring of a machine room. The computer lab smog control is realized the conflagration and is prevented through the concentration of monitoring smog, and its inside adopts ion type smoke transducer.
However, when a fire occurs in the machine room and smoke is carried, it takes a certain time for the smoke to spread from the fire position to the smoke sensor position. Therefore, the time lag of fire prevention is realized through machine room monitoring.
Therefore, how to achieve more accurate power environment monitoring by determining the fire condition more quickly is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
In order to achieve more accurate power environment monitoring by determining fire conditions more quickly, the application provides a power environment monitoring method, a system, equipment and a medium of a data center.
In a first aspect, the present application provides a method for monitoring a power environment of a data center, which adopts the following technical scheme:
a method of dynamic environmental monitoring of a data center, comprising:
Acquiring an infrared image and a visible light image of a machine room corresponding to a dynamic environment of a data center;
Acquiring an image weight, wherein the image weight comprises an infrared weight corresponding to the infrared image and a monitoring weight corresponding to the visible light image;
Based on the infrared image, the infrared weight, the visible light image and the monitoring weight, extracting smoke characteristics to obtain smoke characteristics in a machine room corresponding to the dynamic environment of the data center;
based on the smoke characteristics, a fire result is determined to monitor the data center power environment.
By adopting the technical scheme, compared with the related art that the smoke concentration is detected by utilizing the smoke diffusion principle, the method and the device can acquire the infrared image and the visible light image of the machine room corresponding to the dynamic environment of the data center more quickly by utilizing the characteristics that the light transmission and the infrared radiation speed are both higher than the smoke diffusion speed; acquiring image weights to determine infrared weights corresponding to infrared images and monitoring weights corresponding to visible light images; based on the infrared image and the visible light image which are obtained faster, extracting smoke characteristics together with the monitoring weight and the infrared weight so as to obtain smoke characteristics in a machine room corresponding to the dynamic environment of the data center faster; based on the faster derived smoke characteristics, a fire outcome may be determined faster to more accurately monitor the data center power environment.
The present application may be further configured in a preferred example to:
the acquiring the infrared weight corresponding to the infrared image and the monitoring weight corresponding to the visible light image comprises the following steps:
Acquiring the total number of the lights in the machine room; calculating based on the total quantity of the preset lamps and the total quantity of the lighted lamps in the machine room to obtain initial monitoring weight;
acquiring a current indoor temperature, and calculating based on the current indoor temperature and a preset temperature range to obtain an initial infrared weight;
And performing normalization calculation based on the initial infrared weight, the initial monitoring weight and the total initial weight to obtain the infrared weight and the monitoring weight, wherein the total initial weight is the sum of the initial infrared weight and the initial monitoring weight.
The present application may be further configured in a preferred example to: the fire result is the presence or absence of a fire,
After the determination of the fire result based on the smoke characteristics, further comprising:
when the fire result is that the fire exists, acquiring smoke characteristics at preset time intervals to obtain target smoke characteristics corresponding to each moment;
Based on the target smoke characteristics corresponding to each moment, predicting a target fire area in a machine room corresponding to the dynamic environment of the data center by identifying a smoke track; and carrying out fire warning based on the target fire area.
The present application may be further configured in a preferred example to:
Based on the smoke characteristics corresponding to each of the plurality of moments, determining a target fire area in a machine room corresponding to the data center power environment by identifying a smoke track comprises the following steps:
Identifying a smoke track based on the target smoke characteristics corresponding to each of the plurality of moments;
acquiring machine room layout information of a power environment of a data center;
determining a plurality of initial determination areas in the machine room according to the machine room layout information;
The target fire region is determined from the plurality of initial fire determinations based on the smoke trajectory.
When an effective visible light image is acquired, judging whether an effective fire position exists or not based on the effective visible light image, wherein the effective fire position is the target fire position with open fire;
if so, carrying out position optimization on the effective fire position based on the effective fire position and the effective visible light image to obtain a final fire position corresponding to the effective fire position.
The present application may be further configured in a preferred example to: after determining the target fire area in the machine room corresponding to the data center power environment by identifying the smoke track based on all the smoke characteristics, the method further comprises the following steps:
Judging whether an effective fire area exists in the target fire area or not based on a visible light image corresponding to the target fire area, wherein the effective fire area is the target fire area with open fire;
if so, determining a fire position corresponding to the visible light image of the effective fire area according to the visible light image of the effective fire area.
The present application may be further configured in a preferred example to: when there are a plurality of visible light images of the effective fire area,
After determining the fire position corresponding to the visible light image with the effective fire area according to the visible light image with the effective fire area, the method further comprises the following steps:
And predicting the fire development trend according to all the fire positions and the wind direction of the fixed machine room, and carrying out early warning based on the fire development trend.
The present application may be further configured in a preferred example to: after predicting the target fire area in the machine room corresponding to the data center power environment by identifying the smoke track based on the smoke characteristics corresponding to each of the plurality of moments, the method further comprises:
determining a sliding rail area corresponding to the target fire area, and determining a plurality of temperature observation positions adjacent to the sliding rail area;
controlling temperature observation equipment to observe the temperature based on the plurality of temperature observation positions to obtain the observation temperatures corresponding to the plurality of temperature observation positions;
and obtaining an optimized fire area based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions.
In a second aspect, the present application provides a power environment monitoring device for a data center, which adopts the following technical scheme:
A power environment monitoring device for a data center, comprising:
the image acquisition module is used for acquiring an infrared image and a visible light image of the machine room corresponding to the dynamic environment of the data center;
the weight determining module is used for acquiring an infrared weight corresponding to the infrared image and a monitoring weight corresponding to the visible light image;
the feature extraction module is used for extracting first smoke features of the infrared image and second smoke features of the visible light image;
The characteristic fusion module is used for carrying out smoke characteristic fusion based on the first smoke characteristic, the infrared weight, the second smoke characteristic and the monitoring weight to obtain a target smoke characteristic in a machine room corresponding to the data center power environment;
And the fire result determining module is used for determining the fire result of the machine room corresponding to the data center power environment based on the target smoke characteristics so as to monitor the data center power environment.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
At least one processor;
A memory;
at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: a power environment monitoring method of a data center according to any of the first aspects is performed.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
A computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method of power environment monitoring of a data center according to any of the first aspects.
In summary, the application at least comprises the following beneficial technical effects:
Compared with the related art that the smoke concentration is detected by utilizing the smoke diffusion principle, the method and the device for detecting the smoke concentration of the computer room utilize the characteristic that the propagation of light and the speed of infrared radiation are both larger than the smoke diffusion speed, and acquire the infrared image and the visible light image of the computer room corresponding to the dynamic environment of the data center more quickly; acquiring image weights to determine infrared weights corresponding to the infrared images and monitoring weights corresponding to the visible light images; based on the infrared image and the visible light image which are obtained faster, extracting smoke characteristics together with the monitoring weight and the infrared weight so as to obtain smoke characteristics in a machine room corresponding to the dynamic environment of the data center faster; based on the faster obtained smoke characteristics, the fire results can be determined faster to more accurately monitor the data center power environment.
Drawings
Fig. 1 is a schematic flow chart of a power environment monitoring method of a data center according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a power environment monitoring device of a data center according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to fig. 1 to 3.
The present embodiment is merely illustrative of the present application and is not intended to limit the present application, and those skilled in the art, after having read the present specification, may make modifications to the present embodiment without creative contribution as necessary, but are protected by patent laws within the scope of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application are clearly and completely described, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Ion type smoke sensor working principle: when no smoke exists in the environment, the receiving tube in the alarm can not receive the infrared light emitted by the infrared emission tube, and the subsequent sampling circuit has no electric signal change. However, when smoke particles in the environment enter the maze, infrared light emitted by the emitting tube is scattered, the intensity of the scattered infrared light has a certain linear relation with the smoke concentration, and a subsequent sampling circuit changes. The main control chip built in the alarm is used for judging the variation to confirm whether a fire alarm occurs.
Embodiments of the application are described in further detail below with reference to the drawings.
The embodiment of the application provides a dynamic environment monitoring method of a data center, which is executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, or the like, but is not limited thereto, and the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, as shown in fig. 1, the method includes steps S101 to S105, where:
Step S101: and acquiring an infrared image and a visible light image of a machine room corresponding to the dynamic environment of the data center.
The infrared images comprise a plurality of Zhang Zigong infrared images, each sub-infrared image corresponds to a unique target area, and all target areas carry out full coverage on the dynamic environment of the data center; the visible light image comprises a plurality of sub visible light images, and each sub visible light image corresponds to a unique target area; it should be noted that for the same target area, there is a sub-infrared image and a sub-visible image corresponding to the target area.
The sub-infrared images correspond to the sub-visible light images corresponding to the sub-infrared images, and each pixel position corresponds to one by one.
It will be appreciated that the level of detail of the visible image is greater than the level of detail of the infrared image when the illumination is sufficient, but the level of detail of the infrared image is greater than the level of detail of the visible image when the illumination is insufficient. According to the scheme, the infrared image and the visible light image are acquired, so that more details in the machine room are acquired.
Step S102: and acquiring an infrared weight corresponding to the infrared image and a monitoring weight corresponding to the visible light image.
It can be understood that the more sufficient the illumination, the greater the detail level of the visible light, and simultaneously the detail level of the infrared image is reduced due to the influence of the illumination on the room temperature; similarly, the less the illumination, the greater the level of detail of the infrared image and the lower the level of detail of the visible image.
Therefore, the ratio of the details which can be represented by the infrared image and the visible image is different according to different illumination conditions and different room temperature.
Step S103: a first smoke feature of the infrared image and a second smoke feature of the visible image are extracted.
The first smoke features are smoke features extracted from the infrared image, and comprise a plurality of sub-first smoke features, and each sub-first smoke feature corresponds to a unique target area. The second smoke features are extracted from the visible light image and include a plurality of sub-second smoke features, each sub-second smoke feature corresponding to a unique target area. For the same target area, the target area corresponds to a sub-first smoke feature and a sub-second smoke feature.
The sub-first smoke feature and the sub-second smoke feature each comprise a gray value for a pixel of each smoke containing region.
Step S104: and carrying out smoke characteristic fusion based on the first smoke characteristic, the infrared weight, the second smoke characteristic and the monitoring weight to obtain the target smoke characteristic in the machine room corresponding to the dynamic environment of the data center.
Specifically, for the same pixel position corresponding to the same target area, based on a first gray value corresponding to the pixel position in the sub-first smoke feature corresponding to the target area and a second gray value corresponding to the pixel position in the sub-second smoke feature corresponding to the target area, a weighting calculation is performed to obtain a target gray value corresponding to the pixel position, where the weighting calculation may be implemented based on a weighting calculation formula, and the weighting calculation formula is: target gray value = first gray value x infrared weight + second gray value x monitor weight; for each target area, obtaining a target gray value set corresponding to the target area through integration based on the target gray values corresponding to all pixel positions corresponding to the target area; and taking the target gray value set as a sub-target smoke feature to obtain the target smoke feature comprising a plurality of sub-target smoke features.
Step S105: and determining a fire result of the machine room corresponding to the power environment of the data center based on the target smoke characteristics so as to monitor the power environment of the data center.
Specifically, when the target smoke characteristics meet the preset smoke characteristic standard, determining that the fire result is fire, otherwise, determining that the fire result is not fire. The preset smoke feature standard may refer to the related art, and embodiments of the present application are not specifically limited.
In the embodiment of the application, compared with the detection of the smoke concentration by utilizing the smoke diffusion principle in the related technology, the method and the device for detecting the smoke concentration by utilizing the infrared light have the advantages that the transmission speed of light and the infrared radiation speed are both higher than the smoke diffusion speed, and the infrared image and the visible light image of a machine room corresponding to the dynamic environment of the data center are obtained more quickly; acquiring image weights to determine infrared weights corresponding to the infrared images and monitoring weights corresponding to the visible light images; based on the infrared image and the visible light image which are obtained faster, extracting smoke characteristics together with the monitoring weight and the infrared weight so as to obtain smoke characteristics in a machine room corresponding to the dynamic environment of the data center faster; based on the faster obtained smoke characteristics, the fire results can be determined faster to more accurately monitor the data center power environment.
In one possible implementation manner of the embodiment of the present application, acquiring an infrared weight corresponding to an infrared image and a monitoring weight corresponding to a visible light image may specifically include:
Acquiring the total number of the lights in the machine room; calculating based on the total quantity of the preset lamps and the total quantity of the lighted lamps in the machine room to obtain initial monitoring weight;
Acquiring the current indoor temperature, and calculating based on the current indoor temperature and a preset temperature range to obtain an initial infrared weight;
And performing normalization calculation based on the initial infrared weight, the initial monitoring weight and the total initial weight to obtain the infrared weight and the monitoring weight, wherein the total initial weight is the sum of the initial infrared weight and the initial monitoring weight.
The total preset lamps are the total number of the lamps which can be lighted in the machine room, and are related to specific settings in the machine room, and can be preset and stored in the electronic equipment by technicians according to actual conditions.
The preset temperature range includes a preset temperature maximum value and a preset temperature minimum value, and the calculating based on the current indoor temperature and the preset temperature range to obtain an initial infrared weight may specifically include: initial infrared weight= (current indoor temperature-temperature range min)/(temperature range max-temperature range min).
Monitor weight = initial monitor weight/total initial weight.
Infrared weight = initial infrared weight/total initial weight.
In the embodiment of the application, the total number of the lights in the machine room is obtained; calculating based on the total quantity of the preset lamps and the total quantity of the lighted lamps in the machine room to obtain a preliminary duty ratio, namely an initial monitoring weight, of the second smoke characteristics corresponding to the visible light in all the smoke characteristics; similarly, after the current indoor temperature is obtained, calculating is carried out based on the current indoor temperature and a preset temperature range, and an initial infrared weight is obtained so as to determine the ratio of the first smoke feature corresponding to the infrared image in all the smoke features; and carrying out normalization processing on the initial infrared weight and the initial monitoring weight to obtain the monitoring weight and the infrared weight so as to ensure the rationality of the fusion result.
In one possible implementation manner of the embodiment of the present application, the fire result is that there is a fire or no fire, and after determining the fire result based on the smoke feature, the method may further include:
When the fire result is that the fire exists, acquiring smoke characteristics at preset time intervals to obtain target smoke characteristics corresponding to each moment;
based on the respective corresponding target smoke characteristics at a plurality of moments, predicting a target fire area in a machine room corresponding to the dynamic environment of the data center by identifying a smoke track; and carrying out fire warning based on the target fire area.
When the fire result is that no fire exists, the fire area and the fire position do not need to be determined.
The preset time interval is considered to be set according to actual conditions, can be determined by a technician and stored in the electronic equipment, and the embodiment of the application is not limited in detail.
It can be understood that the situation of smoke diffusion changes with time, the smoke characteristics at the current moment corresponding to the multiple moments are compared in time sequence, and the diffusion positions of the target smoke characteristics corresponding to the multiple moments are compared so as to trace back the fire based on the current smoke diffusion direction, so that the existence of a target fire area is predicted, and the target fire area is a target fire area with the corresponding target smoke characteristics meeting the requirements of preset smoke characteristics.
In the embodiment of the application, when the fire result is determined to be the existence of the fire, the smoke characteristics are acquired at each English book time interval
According to one possible implementation manner of the embodiment of the application, based on the smoke characteristics corresponding to each of a plurality of moments, the target fire area in the machine room corresponding to the dynamic environment of the data center is determined by identifying the smoke track, and the method specifically comprises the following steps:
Identifying a smoke track based on the respective target smoke characteristics at a plurality of moments;
acquiring machine room layout information of a power environment of a data center;
Determining a plurality of initial determination areas in the machine room according to the layout information of the machine room;
A target fire zone is determined from a plurality of initially determined zones based on the smoke trajectory.
Based on the target smoke characteristics corresponding to each of the plurality of moments, the identifying the smoke track may specifically include: performing diffusion track recognition based on the respective corresponding target smoke characteristics at a plurality of moments to obtain a smoke diffusion track; trace backtracking is carried out on the smoke diffusion track until the trace backtracks to a certain source of the machine room layout, and trace backtracking tracks are obtained; and combining the trace-back track and the smoke expanding track to obtain the smoke track.
Determining a target fire zone from a plurality of initially determined zones based on the smoke trajectory may specifically include: and determining all target areas including the source in all initial determination areas, and determining the target areas including the source as target fire determination areas.
In the embodiment of the application, based on the respective corresponding target smoke characteristics at a plurality of moments, a smoke track is identified to determine the source of smoke diffusion; after the machine room layout information of the power environment of the data center is obtained, a plurality of initially-determined areas comprising equipment and/or inflammable objects are determined according to the machine room layout information; in an initial determination area where the risk of ignition of the lock is high, an area where a source of smoke exists is determined as a target fire area where a fire may exist.
One possible implementation manner of the embodiment of the present application, after determining the target fire area in the machine room corresponding to the power environment of the data center by identifying the smoke track based on all the smoke characteristics, may further include:
Judging whether an effective fire area exists in the target fire area based on a visible light image corresponding to the target fire area, wherein the effective fire area is the target fire area with open fire;
if so, determining a fire position corresponding to the visible light image of the effective fire area according to the visible light image of the effective fire area.
If not, the target fire area is regarded as the fire safety hidden trouble area.
In the embodiment of the application, whether a target fire area with open fire exists or not is judged by judging whether the visible light image of the target fire area with fire possibly exists; if so, determining a fire position corresponding to the visible light image of the effective fire area according to the visible light image of the effective fire area, so as to further determine the specific position of the fire in the target fire area.
In one possible implementation manner of the embodiment of the present application, when there are multiple visible light images of an effective fire area, after determining, according to the visible light image of the effective fire area, a fire position corresponding to the visible light image of the effective fire area, the method may further include:
and predicting the fire development trend according to all the fire positions and the wind direction of the fixed machine room, and carrying out early warning based on the fire development trend.
Specifically, determining a flame inclination angle and a flame covering position based on a fixed machine room wind direction; modeling and restoring flames corresponding to the fire position based on the flame covering position and the flame inclination angle to obtain a flame model corresponding to the fire position; and judging whether flame models corresponding to the adjacent flame positions are intersected or not according to the two adjacent flame positions, if yes, determining that the two adjacent flame positions are possibly connected, and generating large-area expected flame information to prompt technicians to pay attention to the machine room flame.
In the embodiment of the application, the influence of the wind direction of the fixed machine room on the fire development trend is considered, and the fire development trend is predicted according to all the fire positions and the wind direction of the fixed machine room so as to further predict whether a large-area fire is possible.
According to a possible implementation manner of the embodiment of the present application, after predicting a target fire area in a machine room corresponding to a data center power environment by identifying a smoke track based on smoke features corresponding to each of a plurality of moments, the method may further include:
Determining a sliding rail area corresponding to the target fire area, and determining a plurality of temperature observation positions adjacent to the sliding rail area;
Controlling temperature observation equipment to observe the temperature based on the plurality of temperature observation positions to obtain the respective corresponding observation temperatures of the plurality of temperature observation positions;
and obtaining an optimized fire area based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions.
It should be noted that the sliding rail is installed on the ceiling of the machine room in a grid-shaped form, a plurality of temperature sensors are installed on the sliding rail, and the electronic equipment can control any temperature sensor to reach a designated position through a shift instruction. In general, the common position of the temperature sensor is several preset temperature collection positions, where the preset temperature collection positions may be preset by a technician according to actual situations and stored in the electronic device. Each 'mouth' character lattice corresponds to a unique target area, and the 'mouth' character lattice is a sliding rail area.
Based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions, obtaining the optimized fire area may specifically include: connecting a plurality of temperature observation positions as vertexes, taking a region which is included after connection as the bottom surface of the cube, and taking the observation temperature corresponding to each observation position as the length of a prism taking the observation position as the vertex so as to obtain the cube capable of representing the relation between the temperature observation position and the observation temperature; and determining the center of gravity of the cube by taking the bottom surface of the cube as a standard, determining the projection point of the center of gravity of the cube on the bottom surface of the cube, and taking the position of the projection point as the position of the optimized fire area.
In the embodiment of the application, a sliding rail area corresponding to a target fire area is determined so as to determine a plurality of temperature observation positions adjacent to the sliding rail area; controlling temperature observation equipment to observe the temperature based on the plurality of temperature observation positions to obtain observation temperatures corresponding to the plurality of temperature observation positions, and determining the surrounding temperature of the target fire area; and further obtaining an optimized fire area based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions.
The above embodiments describe a method for monitoring the power environment of a data center from the perspective of a method flow, and the following embodiments describe a device for monitoring the power environment of a data center from the perspective of a virtual module or a virtual unit, specifically the following embodiments are described below.
The embodiment of the application provides a power environment monitoring device of a data center, as shown in fig. 2, which specifically may include:
the image acquisition module 201 is used for acquiring an infrared image and a visible light image of a machine room corresponding to the dynamic environment of the data center;
the weight determining module 202 is configured to obtain an infrared weight corresponding to the infrared image and a monitoring weight corresponding to the visible light image;
The feature extraction module 203 is configured to extract a first smoke feature of the infrared image and a second smoke feature of the visible light image;
The feature fusion module 204 is configured to perform smoke feature fusion based on the first smoke feature, the infrared weight, the second smoke feature, and the monitoring weight, so as to obtain a target smoke feature in a machine room corresponding to the power environment of the data center;
The fire result determining module 205 is configured to determine a fire result of the machine room corresponding to the power environment of the data center based on the target smoke feature, so as to monitor the power environment of the data center.
In one possible implementation manner of the embodiment of the present application, the weight determining module 202 is specifically configured to, when executing obtaining an infrared weight corresponding to an infrared image and a monitoring weight corresponding to a visible light image:
Acquiring the total number of the lights in the machine room; calculating based on the total quantity of the preset lamps and the total quantity of the lighted lamps in the machine room to obtain initial monitoring weight;
Acquiring the current indoor temperature, and calculating based on the current indoor temperature and a preset temperature range to obtain an initial infrared weight;
And performing normalization calculation based on the initial infrared weight, the initial monitoring weight and the total initial weight to obtain the infrared weight and the monitoring weight, wherein the total initial weight is the sum of the initial infrared weight and the initial monitoring weight.
In one possible implementation manner of the embodiment of the present application, the fire result is that there is a fire or no fire, and the power environment monitoring device of the data center further includes:
The fire zone warning module is used for:
When the fire result is that the fire exists, acquiring smoke characteristics at preset time intervals to obtain target smoke characteristics corresponding to each moment;
based on the respective corresponding target smoke characteristics at a plurality of moments, predicting a target fire area in a machine room corresponding to the dynamic environment of the data center by identifying a smoke track; and carrying out fire warning based on the target fire area.
According to one possible implementation manner of the embodiment of the application, when the fire area warning module executes the smoke characteristics corresponding to each moment based on a plurality of moments, and the target fire area in the machine room corresponding to the dynamic environment of the data center is determined by identifying the smoke track, the fire area warning module is used for:
Identifying a smoke track based on the respective target smoke characteristics at a plurality of moments;
acquiring machine room layout information of a power environment of a data center;
Determining a plurality of initial determination areas in the machine room according to the layout information of the machine room;
A target fire region is determined from a plurality of initial fire determinations based on the smoke trajectory.
In one possible implementation manner of the embodiment of the present application, a power environment monitoring device of a data center further includes:
A fire position determination module for:
Judging whether an effective fire area exists in the target fire area based on a visible light image corresponding to the target fire area, wherein the effective fire area is the target fire area with open fire;
if so, determining a fire position corresponding to the visible light image of the effective fire area according to the visible light image of the effective fire area.
In one possible implementation manner of the embodiment of the present application, when there are a plurality of visible light images in an effective fire area, the power environment monitoring device of the data center further includes:
The fire trend carries out early warning module for:
and predicting the fire development trend according to all the fire positions and the wind direction of the fixed machine room, and carrying out early warning based on the fire development trend.
In one possible implementation manner of the embodiment of the present application, a power environment monitoring device of a data center further includes:
The fire area optimizing module is used for:
Determining a sliding rail area corresponding to the target fire area, and determining a plurality of temperature observation positions adjacent to the sliding rail area;
Controlling temperature observation equipment to observe the temperature based on the plurality of temperature observation positions to obtain the respective corresponding observation temperatures of the plurality of temperature observation positions;
and obtaining an optimized fire area based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, a specific working process of the power environment monitoring device of the data center described above may refer to a corresponding process in the foregoing method embodiment, which is not described herein again.
In an embodiment of the present application, as shown in fig. 3, an electronic device shown in fig. 3 includes: a processor 301 and a memory 303. Wherein the processor 301 is coupled to the memory 303, such as via a bus 302. Optionally, the electronic device may also include a transceiver 304. It should be noted that, in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device is not limited to the embodiment of the present application.
The Processor 301 may be a CPU (Central Processing Unit ), general purpose Processor, DSP (DIGITAL SIGNAL Processor, data signal Processor), ASIC (Application SPECIFIC INTEGRATED Circuit), FPGA (Field Programmable GATE ARRAY ) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with this disclosure. Processor 301 may also be a combination that implements computing functionality, e.g., comprising one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.
Bus 302 may include a path to transfer information between the components. Bus 302 may be a PCI (PERIPHERAL COMPONENT INTERCONNECT, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture ) bus, or the like. Bus 302 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 3, but not only one bus or type of bus.
The Memory 303 may be, but is not limited to, a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, an EEPROM (ELECTRICALLY ERASABLE PROGRAMMABLE READ ONLY MEMORY ), a CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 303 is used for storing application program codes for executing the inventive arrangements and is controlled to be executed by the processor 301. The processor 301 is configured to execute the application code stored in the memory 303 to implement what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. But may also be a server or the like. The electronic device shown in fig. 3 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the application.
Embodiments of the present application provide a computer-readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above. Compared with the related art, the embodiment of the application detects the smoke concentration by utilizing the smoke diffusion principle, and the scheme utilizes the characteristics that the light transmission and the infrared radiation speed are both higher than the smoke diffusion speed to acquire the infrared image and the visible light image of the machine room corresponding to the dynamic environment of the data center more quickly; acquiring image weights to determine infrared weights corresponding to the infrared images and monitoring weights corresponding to the visible light images; based on the infrared image and the visible light image which are obtained faster, extracting smoke characteristics together with the monitoring weight and the infrared weight so as to obtain smoke characteristics in a machine room corresponding to the dynamic environment of the data center faster; based on the faster obtained smoke characteristics, the fire results can be determined faster to more accurately monitor the data center power environment.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present application, and such modifications and adaptations should and are intended to be comprehended within the scope of the present application.
Claims (6)
1. A method for monitoring a power environment of a data center, comprising:
Acquiring an infrared image and a visible light image of a machine room corresponding to a dynamic environment of a data center;
acquiring an infrared weight corresponding to the infrared image and a monitoring weight corresponding to the visible light image;
extracting a first smoke feature of the infrared image and a second smoke feature of the visible light image, wherein the first smoke feature comprises a plurality of sub-first smoke features, each sub-first smoke feature corresponds to a unique target area, the second smoke feature comprises a plurality of sub-second smoke features, each sub-second smoke feature corresponds to a unique target area, for the same target area, the target area corresponds to a sub-first smoke feature and a sub-second smoke feature, and the sub-first smoke feature and the sub-second smoke feature both comprise gray values of pixels of each smoke-containing area;
And performing a smoke feature fusion based on the first smoke feature, the infrared weight, the second smoke feature and the monitoring weight to obtain a target smoke feature in a machine room corresponding to the dynamic environment of the data center, wherein for the same pixel position corresponding to the same target area, a first gray value corresponding to the pixel position is calculated based on a first gray value corresponding to the pixel position in a sub-first smoke feature corresponding to the target area, and a second gray value corresponding to the pixel position is calculated in a sub-second smoke feature corresponding to the target area to obtain a target gray value corresponding to the pixel position, wherein the weighted calculation is realized based on a weighted calculation formula, and the weighted calculation formula is as follows: target gray value = first gray value x infrared weight + second gray value x monitor weight; for each target area, obtaining a target gray value set corresponding to the target area through integration based on the target gray values corresponding to all pixel positions corresponding to the target area; taking the target gray value set as a sub-target smoke feature to obtain the target smoke feature comprising a plurality of sub-target smoke features;
Based on the target smoke characteristics, determining a fire result of a machine room corresponding to the data center power environment so as to monitor the data center power environment;
the acquiring the infrared weight corresponding to the infrared image and the monitoring weight corresponding to the visible light image comprises the following steps:
Acquiring the total number of the lights in the machine room; calculating based on the total quantity of the preset lamps and the total quantity of the lighted lamps in the machine room to obtain initial monitoring weight;
acquiring a current indoor temperature, and calculating based on the current indoor temperature and a preset temperature range to obtain an initial infrared weight;
Performing normalization calculation based on the initial infrared weight, the initial monitoring weight and the total initial weight to obtain the infrared weight and the monitoring weight, wherein the total initial weight is the sum of the initial infrared weight and the initial monitoring weight;
the fire result is the presence or absence of a fire,
After the determination of the fire result based on the smoke characteristics, further comprising:
when the fire result is that the fire exists, acquiring smoke characteristics at preset time intervals to obtain target smoke characteristics corresponding to each moment;
Identifying a smoke track based on the target smoke characteristics corresponding to each of the plurality of moments;
acquiring machine room layout information of a power environment of a data center;
Determining a plurality of initial determination areas in the machine room according to the machine room layout information, wherein the initial determination areas are areas with flammable risks including equipment and/or inflammable objects;
Determining a target fire zone from the plurality of initially determined zones based on the smoke trajectory;
after predicting the target fire area in the machine room corresponding to the data center power environment by identifying the smoke track based on the smoke characteristics corresponding to each of the plurality of moments, the method further comprises:
determining a sliding rail area corresponding to the target fire area, and determining a plurality of temperature observation positions adjacent to the sliding rail area;
controlling temperature observation equipment to observe the temperature based on the plurality of temperature observation positions to obtain the observation temperatures corresponding to the plurality of temperature observation positions;
Based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions, obtaining an optimized fire area specifically comprises: connecting a plurality of temperature observation positions as vertexes, taking the connected areas as the bottom surface of the cube, and taking the observation temperature corresponding to each observation position as the length of a prism taking the observation position as the vertex to obtain the cube capable of representing the relation between the temperature observation position and the observation temperature; and determining the center of gravity of the cube by taking the bottom surface of the cube as a standard, determining the projection point of the center of gravity of the cube on the bottom surface of the cube, and taking the position of the projection point as the position of the optimized fire area.
2. The method for monitoring the power environment of the data center according to claim 1, further comprising, after the determining the target fire area in the machine room corresponding to the power environment of the data center by identifying a smoke track based on all the smoke features:
Judging whether an effective fire area exists in the target fire area or not based on a visible light image corresponding to the target fire area, wherein the effective fire area is the target fire area with open fire;
if so, determining a fire position corresponding to the visible light image of the effective fire area according to the visible light image of the effective fire area.
3. The method for monitoring a dynamic environment of a data center according to claim 2, wherein when there are a plurality of visible light images of an effective fire area,
After determining the fire position corresponding to the visible light image with the effective fire area according to the visible light image with the effective fire area, the method further comprises the following steps:
And predicting the fire development trend according to all the fire positions and the wind direction of the fixed machine room, and carrying out early warning based on the fire development trend.
4. A power environment monitoring device for a data center, comprising:
the image acquisition module is used for acquiring an infrared image and a visible light image of the machine room corresponding to the dynamic environment of the data center;
the weight determining module is used for acquiring an infrared weight corresponding to the infrared image and a monitoring weight corresponding to the visible light image;
The feature extraction module is used for extracting first smoke features of the infrared image and second smoke features of the visible light image, wherein the first smoke features comprise a plurality of sub-first smoke features, each sub-first smoke feature corresponds to a unique target area, the second smoke features comprise a plurality of sub-second smoke features, each sub-second smoke feature corresponds to a unique target area, and for the same target area, the target area corresponds to a sub-first smoke feature and a sub-second smoke feature, and the sub-first smoke feature and the sub-second smoke feature both comprise gray values of pixels of each smoke-containing area;
The feature fusion module is configured to perform a smoke feature fusion based on the first smoke feature, the infrared weight, the second smoke feature and the monitoring weight to obtain a target smoke feature in a machine room corresponding to the data center power environment, where, for a same pixel position corresponding to a same target area, based on a first gray value corresponding to the pixel position in a sub-first smoke feature corresponding to the target area, and based on a second gray value corresponding to the pixel position in a sub-second smoke feature corresponding to the target area, perform a weighted calculation to obtain a target gray value corresponding to the pixel position, where the weighted calculation is implemented based on a weighted calculation formula, and the weighted calculation formula is as follows: target gray value = first gray value x infrared weight + second gray value x monitor weight; for each target area, obtaining a target gray value set corresponding to the target area through integration based on the target gray values corresponding to all pixel positions corresponding to the target area; taking the target gray value set as a sub-target smoke feature to obtain the target smoke feature comprising a plurality of sub-target smoke features;
The fire result determining module is used for determining a fire result of the machine room corresponding to the data center power environment based on the target smoke characteristics so as to monitor the data center power environment;
the weight determining module is used for acquiring the infrared weight corresponding to the infrared image and the monitoring weight corresponding to the visible light image, and is used for:
Acquiring the total number of the lights in the machine room; calculating based on the total quantity of the preset lamps and the total quantity of the lighted lamps in the machine room to obtain initial monitoring weight;
acquiring a current indoor temperature, and calculating based on the current indoor temperature and a preset temperature range to obtain an initial infrared weight;
Performing normalization calculation based on the initial infrared weight, the initial monitoring weight and the total initial weight to obtain the infrared weight and the monitoring weight, wherein the total initial weight is the sum of the initial infrared weight and the initial monitoring weight;
Further comprises:
The fire area warning module is used for acquiring smoke characteristics at preset time intervals when the fire result is that a fire exists, so as to obtain target smoke characteristics corresponding to each moment;
Identifying a smoke track based on the target smoke characteristics corresponding to each of the plurality of moments;
acquiring machine room layout information of a power environment of a data center;
Determining a plurality of initial determination areas in the machine room according to the machine room layout information, wherein the initial determination areas are areas with flammable risks including equipment and/or inflammable objects;
Determining a target fire zone from the plurality of initially determined zones based on the smoke trajectory:
the fire area optimizing module is used for: determining a sliding rail area corresponding to the target fire area, and determining a plurality of temperature observation positions adjacent to the sliding rail area;
controlling temperature observation equipment to observe the temperature based on the plurality of temperature observation positions to obtain the observation temperatures corresponding to the plurality of temperature observation positions;
Based on the plurality of temperature observation positions and the observation temperatures corresponding to the plurality of temperature observation positions, obtaining an optimized fire area specifically comprises: connecting a plurality of temperature observation positions as vertexes, taking the connected areas as the bottom surface of the cube, and taking the observation temperature corresponding to each observation position as the length of a prism taking the observation position as the vertex to obtain the cube capable of representing the relation between the temperature observation position and the observation temperature; and determining the center of gravity of the cube by taking the bottom surface of the cube as a standard, determining the projection point of the center of gravity of the cube on the bottom surface of the cube, and taking the position of the projection point as the position of the optimized fire area.
5. An electronic device, comprising:
At least one processor;
A memory;
At least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: a power environment monitoring method of performing the data center of any one of claims 1 to 3.
6. A computer-readable storage medium, having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method of power environment monitoring of a data center according to any of claims 1 to 3.
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| CN112560657A (en) * | 2020-12-12 | 2021-03-26 | 南方电网调峰调频发电有限公司 | Smoke and fire identification method and device, computer equipment and storage medium |
| CN117037065A (en) * | 2023-08-15 | 2023-11-10 | 中国南方电网有限责任公司超高压输电公司电力科研院 | Flame smoke concentration detection method, device, computer equipment and storage medium |
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| CN110349117B (en) * | 2019-06-28 | 2023-02-28 | 重庆工商大学 | Infrared image and visible light image fusion method and device and storage medium |
| CN113947555A (en) * | 2021-09-26 | 2022-01-18 | 国网陕西省电力公司西咸新区供电公司 | Infrared and visible light fused visual system and method based on deep neural network |
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| CN112560657A (en) * | 2020-12-12 | 2021-03-26 | 南方电网调峰调频发电有限公司 | Smoke and fire identification method and device, computer equipment and storage medium |
| CN117037065A (en) * | 2023-08-15 | 2023-11-10 | 中国南方电网有限责任公司超高压输电公司电力科研院 | Flame smoke concentration detection method, device, computer equipment and storage medium |
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