CN113324701B - Machine room water leakage detection method for data center - Google Patents
Machine room water leakage detection method for data center Download PDFInfo
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- CN113324701B CN113324701B CN202110393080.1A CN202110393080A CN113324701B CN 113324701 B CN113324701 B CN 113324701B CN 202110393080 A CN202110393080 A CN 202110393080A CN 113324701 B CN113324701 B CN 113324701B
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Abstract
The invention provides a machine room water leakage detection method for a data center. The method comprises the following steps: based on the Internet of things, connecting the state parameters of the machine room with a water leakage detection network terminal by combining a water leakage detection protocol; determining machine room humidity data in current machine room state parameters, and storing the machine room humidity data; the stored humidity data of the machine room is uploaded to the water leakage detection network end through the Internet of things; detecting water leakage of the machine room based on the water leakage detection network end; when the water leakage of the machine room is detected, determining the specific position of the water leakage of the machine room by an image comparison method; the humidity data in the machine room is acquired through the Internet of things, and the humidity data in the machine room is processed and analyzed, so that whether the water leakage occurs in the machine room is rapidly and accurately judged.
Description
Technical Field
The invention relates to the technical field of machine room monitoring, in particular to a machine room water leakage detection method for a data center.
Background
At present, a large number of precise electronic information devices are arranged in a machine room and are extremely sensitive to water. Water trouble is one of the safety protection contents which cannot be ignored, and a plurality of water leakage sources such as a flushing water loop, a drain pipe and the like of an air conditioning unit are arranged in a machine room. Strong current, weak current, ground wire and cable under the floor of the machine room area are criss-cross, if water leakage happens carelessly, the water leakage is discovered and removed in time, the machine room equipment is damaged by a light person, and the service life is shortened; the serious person causes equipment damage and information loss, and serious and even irretrievable economic loss is brought.
However, at present, the machine room water leakage detection only depends on single manual inspection detection, and whether the machine room leaks water cannot be efficiently and accurately judged, and the detection result cannot be uploaded on the network, so that the reason of water leakage is inconvenient for background analysis, and therefore, the invention provides the machine room water leakage detection method for the data center.
Disclosure of Invention
The invention provides a machine room water leakage detection method for a data center, which is used for acquiring humidity data of a machine room through the Internet of things, processing and analyzing the humidity data of the machine room and quickly and accurately judging whether the machine room leaks water or not.
A machine room water leakage detection method for a data center comprises the following steps:
step 1: based on the Internet of things, acquiring a water leakage detection protocol according to the machine room state parameters, and connecting the water leakage detection protocol with a water leakage detection network;
step 2: determining machine room humidity data in current machine room state parameters, and storing the machine room humidity data;
and step 3: the stored humidity data of the machine room is uploaded to the water leakage detection network through the Internet of things;
and 4, step 4: detecting water leakage of the machine room based on the water leakage detection network;
step 5; when the water leakage of the machine room is detected, the specific position of the water leakage of the machine room is determined by an image comparison method.
Preferably, in step 1, after the water leakage detection protocol is connected to the water leakage detection network, the method further includes:
carry out the analogue test to the water pipe pipeline valve water leakage trouble in the computer lab, specific working process includes:
filling the water pipe with water, and controlling the water pipe to carry out full-load work in a preset time period;
meanwhile, monitoring temperature and humidity change values in the machine room in real time, and recording the highest temperature and humidity value in the machine room once in each preset time interval;
based on the Internet of things, combining the temperature and humidity change value in the machine room with the highest temperature and humidity value in the machine room recorded in each preset time interval, and transmitting a combination result to the water leakage detection network end;
based on the combination result, verifying whether the waterway redundancy meets the requirement through a water leakage detection network terminal; and obtaining a verification result;
and taking the verification result as a test result of the simulation test of the water leakage fault of the water pipe pipeline valve.
Preferably, in step 1, the specific working process of the water leakage detection protocol is obtained according to the machine room state parameters, and the method includes:
acquiring state parameters of the machine room, and splitting the state parameters;
filling the split state parameters into a sample extraction data list, and extracting sample data corresponding to the state parameters;
generating a public data tree corresponding to the sample extraction data list according to the sample data;
generating a data protocol matrix based on the common data tree;
acquiring a detection factor in the public data tree, and comparing each row of data in the data protocol matrix based on the detection factor;
acquiring the byte type of each line of data, and meanwhile, determining the sub-protocol content corresponding to each line of data based on the comparison result and the numerical value corresponding to each line of data;
and combining the sub-protocol contents in sequence to obtain the final water leakage detection protocol.
Preferably, a method for detecting water leakage in a machine room of a data center, includes: the concrete steps of storing the humidity data of the machine room comprise:
acquiring the data type of the machine room humidity data, and integrating the machine room humidity data with consistent data types to acquire a data packet;
extracting identification characters of the data packet, and establishing a public index value based on the identification characters;
encrypting the humidity data of the machine room according to the public index value to obtain a corresponding encryption matrix dimension;
acquiring the encryption length of the humidity data of the machine room based on the dimension of the encryption matrix;
encrypting the humidity data of the machine room according to the encryption length and by combining an encryption matrix;
distributing memory space to the encrypted machine room humidity data, and storing the encrypted machine room humidity data in the distributed memory space based on the public index value.
Preferably, in step 3, the specific working step of uploading the stored humidity data of the machine room to the water leakage detection network through the internet of things includes:
s101: preprocessing the humidity data of the machine room to obtain first processed data;
s102: acquiring a data identifier of the first processing data, and generating a data uploading rule based on the data identifier;
s103: acquiring N target fields of first processing data based on the data uploading rule;
meanwhile, field auditing is carried out on the target field of the first processing data according to the data uploading rule;
s104: generating a data queue by the first processing data which passes the examination, and acquiring a queue hash value of the data queue;
s105: establishing an incidence relation between the queue hash value and the Internet of things, and matching the incidence relation with the water leakage detection network side;
s106: if the incidence relation is matched with the water leakage detection network terminal, transmitting the data queue with the first processing data to the water leakage detection network terminal based on the incidence relation, and completing uploading the humidity data of the machine room to the water leakage detection network terminal through the Internet of things;
otherwise, defining the incidence relation as an invalid relation, and reestablishing the incidence relation until the incidence relation is matched with the water leakage detection network terminal;
s107: and performing data auditing treatment on the first processing data which do not pass through, acquiring second processing data, and repeating the steps S104-S106 to finish the uploading of the humidity data of the machine room to the water leakage detection network through the Internet of things.
Preferably, in step 4, the working process of detecting water leakage of the machine room based on the water leakage detection network terminal includes:
acquiring a humidity mean value of the humidity data of the machine room based on the water leakage detection network, and judging the humidity mean value in the range of a reference humidity alarm threshold value of the machine room;
and if the humidity mean value falls into the range of the reference humidity alarm threshold value of the machine room for multiple times, judging that water leakage occurs in the machine room, and simultaneously, carrying out alarm operation.
Preferably, in step 5, when water leakage in the machine room is detected, a specific location of the water leakage in the machine room is determined by an image-to-image ratio method, and the specific working process includes:
dividing the machine room into m position spaces, and collecting humidity values of the m position spaces one by one;
calculating the moisture content of the position space according to the humidity value and a preset algorithm, and determining the humidity concentration of the position space according to the moisture content;
comparing the humidity concentration with standard humidity concentration which can be normally used by a machine room;
acquiring a space position of which the humidity concentration is greater than the standard humidity concentration, and acquiring a target image corresponding to the space position;
fourier transforming the target image into a low-frequency part and a high-frequency part;
acquiring a low-frequency image segment by performing inverse transform of the Fourier transform on the low-frequency part and the same-order diagonal matrix, and acquiring a high-frequency image segment by performing inverse transform of the Fourier transform on the high-frequency part and the same-order diagonal matrix;
respectively carrying out noise reduction processing on the low-frequency image segment and the high-frequency image segment, and combining the processed low-frequency image segment and the processed high-frequency image segment to obtain a noise reduction target image;
acquiring the exposure degree of the noise-reduced target image, and determining the exposure parameter of the target image based on the exposure degree and the current environment brightness;
adjusting the noise reduction target image based on the exposure parameters, and acquiring a target processing image;
establishing an image analysis file based on the target processing image, and marking each element of the target processing image based on the image analysis file;
meanwhile, generating an evaluation index based on each marked element;
extracting the image characteristics of each block of the target processing image according to the evaluation index, and comparing the image characteristics with a pre-stored reference pattern;
if the image characteristics are consistent with the pre-stored reference patterns, judging that the specific position of the machine room water leakage is located at the position edge of the adjacent position space;
if the image characteristics are inconsistent with the pre-stored reference patterns, obtaining a comparison result;
obtaining a difference image based on the comparison result;
performing region delineation on the target processing image based on the differential image;
meanwhile, acquiring comprehensive image information in the defined area, and determining the specific position of the water leakage of the machine room based on the comprehensive information.
Preferably, in step 4, after the water leakage detection is performed on the machine room based on the water leakage detection network, the method for detecting water leakage of a machine room for a data center further includes:
based on the detection result, when the machine room leaks water, determining the water leakage position of the machine room, calculating the water leakage speed of the water leakage position, calculating the water leakage amount of the machine room in a standard time period based on the water leakage speed, and measuring the current safety degree of the machine room according to the water leakage amount, wherein the specific working process comprises the following steps:
determining an area function of the water leakage position based on the water leakage position, and calculating the water leakage speed of the machine room in unit time according to the estimated area of the water leakage position;
wherein v represents the water leakage speed of the machine room in unit time; f' (x) represents an area function; x represents the number of region blocks; a represents a region lower limit of the region block; b represents an area upper limit of the area block; s represents an estimated area of the water leakage position; p represents water leakage frequency; t represents a unit time; h represents the distance from the water leakage position to the ground;
calculating the water leakage amount of the machine room within a standard time period according to the water leakage speed;
wherein l represents the water leakage amount of the machine room in a standard time period; ρ represents the density of water; v represents the volume of water leakage; d represents the momentum of the water from the water leakage position to the ground; g represents the acceleration of gravity, and is generally 9.8m/s 2 (ii) a T represents the standard time period; v represents the water leakage speed of the machine room in unit time; h represents the distance from the water leakage position to the ground;
determining a current humidity value of the machine room based on the water leakage amount of the machine room in a standard time period;
comparing the humidity value of the machine room with a safe humidity threshold value of the machine room;
if the humidity value of the machine room is smaller than the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is high, and meanwhile, filling the water leakage position;
if the humidity value of the machine room is equal to the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is moderate, and filling the water leakage position;
if the humidity value of the machine room is larger than the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is low;
and when the safety degree of the machine room is low, controlling the running equipment of the machine room to stop working, performing drying operation, and simultaneously replacing the water leakage position.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a method for detecting water leakage in a machine room of a data center according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the embodiment provides a method for detecting water leakage in a machine room of a data center, as shown in fig. 1, the method includes:
step 1: based on the Internet of things, acquiring a water leakage detection protocol according to the machine room state parameters, and connecting the water leakage detection protocol with a water leakage detection network;
step 2: determining machine room humidity data in current machine room state parameters, and storing the machine room humidity data;
and step 3: the stored humidity data of the machine room is uploaded to the water leakage detection network through the Internet of things;
and 4, step 4: detecting water leakage of the machine room based on the water leakage detection network;
step 5; when the water leakage of the machine room is detected, the specific position of the water leakage of the machine room is determined by an image comparison method.
In this embodiment, the state parameters of the machine room include humidity, temperature, dust concentration, and the like inside the machine room.
In this embodiment, the water leakage detection protocol is a series of regulations for ensuring that the water leakage detection network can effectively and reliably obtain the internal state parameters of the computer room, and the regulations include the appropriateness and order of data.
In this embodiment, the water leakage detection network refers to a platform or a system for determining whether water leakage occurs in the machine room according to the humidity data in the machine room.
The beneficial effects of the above technical scheme are: the humidity data in the machine room is acquired through the Internet of things, and the humidity data in the machine room is processed and analyzed, so that whether the water leakage occurs in the machine room is rapidly and accurately judged.
Example 2:
on the basis of the foregoing embodiment 1, this embodiment provides a method for detecting water leakage in a computer room of a data center, where in step 1, after connecting a water leakage detection protocol with a water leakage detection network, the method further includes:
carry out the analogue test to the water pipe pipeline valve water leakage trouble in the computer lab, specific working process includes:
filling the water pipe with water, and controlling the water pipe to carry out full-load work in a preset time period;
meanwhile, monitoring temperature and humidity change values in the machine room in real time, and recording the highest temperature and humidity value in the machine room once in each preset time interval;
based on the Internet of things, combining the temperature and humidity change value in the machine room with the highest temperature and humidity value in the machine room recorded in each preset time interval, and transmitting a combination result to the water leakage detection network end;
based on the combination result, verifying whether the waterway redundancy meets the requirement through a water leakage detection network terminal; and obtaining a verification result;
and taking the verification result as a test result of the simulation test of the water leakage fault of the water pipe pipeline valve.
In this embodiment, the preset time period refers to 30 minutes of operation under a full load condition, which is set in advance, the preset time interval is 3 minutes, for example, 30 minutes of full load operation, 2-point faults which are the least beneficial to the chilled water pipeline are simulated, the temperature change in the machine room is monitored in real time at the BMS terminal, and the maximum temperature in the machine room is recorded every 3 minutes.
In this embodiment, the redundancy of the water path refers to determining whether there is a surplus water path.
The beneficial effects of the above technical scheme are: through carrying out full load operation with the water pipe in the time quantum that predetermines to obtain the inside humiture change value of computer lab under full load operation, combine the inside highest temperature humidity value of computer lab, accomplish and carry out the analogue test to water pipe pipeline valve fault of leaking, whether accurate judgement valve takes place to leak, thereby whether accurate judgement computer lab takes place to leak, also is convenient for investigate the water source that leaks.
Example 3:
on the basis of the foregoing embodiment 1, this embodiment provides a method for detecting water leakage in a machine room of a data center, and in step 1, a specific working process of a water leakage detection protocol is obtained according to a machine room status parameter, where the method includes:
acquiring state parameters of the machine room, and splitting the state parameters;
filling the split state parameters into a sample extraction data list, and extracting sample data corresponding to the state parameters;
generating a public data tree corresponding to the sample extraction data list according to the sample data;
generating a data protocol matrix based on the common data tree;
acquiring a detection factor in the public data tree, and comparing each row of data in the data protocol matrix based on the detection factor;
acquiring the byte type of each line of data, and meanwhile, determining the sub-protocol content corresponding to each line of data based on the comparison result and the numerical value corresponding to each line of data;
and combining the sub-protocol contents in sequence to obtain the final water leakage detection protocol.
In this embodiment, the sample data refers to specific data corresponding to a state parameter inside the machine room, for example, specific humidity data corresponding to humidity, and specific temperature data corresponding to temperature.
In this embodiment, the common data tree is used to store specific data corresponding to each state parameter in the computer room.
In this embodiment, the data protocol matrix refers to matrix arrangement of data corresponding to the state parameters in the machine room in the common data tree, so as to facilitate comparison of the data corresponding to the state parameters.
In this embodiment, the detection factor is set in advance, and is used to detect whether the data in the data protocol matrix meets the requirement.
In this embodiment, the comparison with each row of data in the data protocol matrix based on the detection factor is because the byte type of each row of data is different, and the comparison with each row of data makes the acquired byte type more strict, so that the acquired sub-protocol content is more accurate.
The beneficial effects of the above technical scheme are: by acquiring the state parameters inside the machine room and acquiring corresponding sample data according to the state parameters, the data protocol matrix corresponding to the state parameters is determined, and finally the data protocol matrix is processed to obtain a final water leakage detection protocol, so that strict and regular detection is conveniently carried out on the water leakage condition inside the machine room according to the water leakage detection protocol, and whether water leakage occurs inside the machine room or not is quickly and accurately judged.
Example 4:
on the basis of the foregoing embodiment 1, the present embodiment provides a method for detecting water leakage in a machine room of a data center, where in step 2: the specific steps of storing the humidity data of the machine room comprise:
acquiring data types of the computer room humidity data, integrating the computer room humidity data with consistent data types, and acquiring a data packet;
extracting identification characters of the data packet, and establishing a public index value based on the identification characters;
encrypting the humidity data of the machine room according to the public index value to obtain a corresponding encryption matrix dimension;
acquiring the encryption length of the humidity data of the machine room based on the dimension of the encryption matrix;
encrypting the humidity data of the machine room according to the encryption length and by combining an encryption matrix;
distributing memory space to the encrypted machine room humidity data, and storing the encrypted machine room humidity data in the distributed memory space based on the public index value.
In this embodiment, the identification character is a type of tag used to represent the data packet, and the data type of the data packet can be determined according to the identification character.
In this embodiment, the common index value refers to one or more key fields in the data packet.
In this embodiment, the dimension of the encryption matrix is used to represent the dimension for encrypting the humidity data of the computer room, and the encryption length required for encrypting the data of the computer room is determined according to the dimension of the encryption matrix, so that the humidity data of the computer room can be encrypted strictly.
The beneficial effects of the above technical scheme are: through the data type of confirming computer lab humidity data to encrypt humidity data, look for available memory space, save the inside humidity data of computer lab, be convenient for when leaking the detection to the computer lab, acquire the humidity data of computer lab in real time, thereby whether quick accurate judgement computer lab leaks and cause the reason of leaking.
Example 5:
on the basis of embodiment 1, this embodiment provides a machine room water leakage detection method for a data center, and in step 3, the specific working step of uploading the stored humidity data of the machine room to the water leakage detection network through the internet of things includes:
s101: preprocessing the humidity data of the machine room to obtain first processed data;
s102: acquiring a data identifier of the first processing data, and generating a data uploading rule based on the data identifier;
s103: acquiring N target fields of first processing data based on the data uploading rule;
meanwhile, field auditing is carried out on the target field of the first processing data according to the data uploading rule;
s104: generating a data queue by the first processing data which passes the examination, and acquiring a queue hash value of the data queue;
s105: establishing an incidence relation between the queue hash value and the Internet of things, and matching the incidence relation with the water leakage detection network side;
s106: if the incidence relation is matched with the water leakage detection network terminal, transmitting the data queue with first processing data to the water leakage detection network terminal based on the incidence relation, and completing uploading the humidity data of the machine room to the water leakage detection network terminal through the Internet of things;
otherwise, defining the incidence relation as an invalid relation, and reestablishing the incidence relation until the incidence relation is matched with the water leakage detection network terminal;
s107: and performing data auditing treatment on the first processing data which do not pass through, acquiring second processing data, and repeating the steps S104-S106 to finish the uploading of the humidity data of the machine room to the water leakage detection network through the Internet of things.
In this embodiment, the association relationship may be data matching between the queue hash value and data in the internet of things, after matching is successful, a matching node is obtained, and a relationship between the queue hash value and the internet of things is established according to the matching node, where the matching node is a hub of the association relationship.
In this embodiment, the preprocessing includes washing, screening, etc. the data.
In this embodiment, the data identifier refers to a character capable of representing a data type, and a category to which the data belongs can be accurately determined according to the data identifier.
In this embodiment, the data uploading rule may be determined according to the data identifier, for example, if the data identifier is floating data, the data is uploaded by using the first data uploading rule, and if the data identifier is integer data, the data is uploaded by using the second data uploading rule.
In this embodiment, the target field refers to that the first processing data is equally divided to obtain a plurality of data fields, and the data fields are the target fields.
The beneficial effects of the above technical scheme are: through carrying out the preliminary treatment with the inside humidity of computer lab to carry out the queueing with the humidity data after the preliminary treatment, establish incidence relation with the thing networking, finally upload the humidity data of computer lab inside to the detection network end that leaks through the thing networking, be convenient for leak and carry out the analysis with the humidity data of survey network terminal to the computer lab according to the data of uploading, whether quick accurate judgement computer lab leaks, improved the efficiency that the computer lab detected that leaks.
Example 6:
on the basis of the foregoing embodiment 1, this embodiment provides a method for detecting water leakage of a machine room in a data center, and in step 4, a working process of detecting water leakage of the machine room based on the water leakage detection network end includes:
acquiring a humidity mean value of the humidity data of the machine room based on the water leakage detection network, and judging the humidity mean value in a range of a reference humidity alarm threshold value of the machine room;
and if the average value of the humidity falls into the range of the reference humidity alarm threshold value of the machine room for multiple times, judging that water leakage occurs in the machine room, and simultaneously, carrying out alarm operation.
In this embodiment, the range of the reference humidity alarm threshold is preset, and is used to measure the degree of the humidity average value inside the machine room, which is a standard for determining whether the machine room leaks water.
The beneficial effects of the above technical scheme are: by acquiring the average value of the humidity in the machine room, judging the acquired moderate average value within the range of the reference humidity alarm threshold value, quantifying the humidity in the machine room, and accurately judging whether water leaks in the machine room, the judgment accuracy is improved.
Example 7:
on the basis of the foregoing embodiment 1, this embodiment provides a method for detecting water leakage in a machine room of a data center, and in step 5, when water leakage in the machine room is detected, a specific location of the water leakage in the machine room is determined by an image contrast method, where the specific working process includes:
dividing the machine room into m position spaces, and collecting humidity values of the m position spaces one by one;
calculating the moisture content of the position space according to the humidity value and a preset algorithm, and determining the humidity concentration of the position space according to the moisture content;
comparing the humidity concentration with standard humidity concentration which can be normally used by a machine room;
acquiring a space position with the humidity concentration larger than the standard humidity concentration, and acquiring a target image corresponding to the space position;
fourier transforming the target image into a low-frequency part and a high-frequency part;
acquiring a low-frequency image segment by performing inverse transform of the Fourier transform on the low-frequency part and the same-order diagonal matrix, and acquiring a high-frequency image segment by performing inverse transform of the Fourier transform on the high-frequency part and the same-order diagonal matrix;
respectively carrying out noise reduction processing on the low-frequency image segment and the high-frequency image segment, and combining the processed low-frequency image segment and the processed high-frequency image segment to obtain a noise reduction target image;
acquiring the exposure degree of the noise-reduced target image, and determining the exposure parameter of the target image based on the exposure degree and the current environment brightness;
adjusting the noise reduction target image based on the exposure parameters, and acquiring a target processing image;
establishing an image analysis file based on the target processing image, and marking each element of the target processing image based on the image analysis file;
meanwhile, generating an evaluation index based on each marked element;
extracting the image characteristics of each block of the target processing image according to the evaluation index, and comparing the image characteristics with a pre-stored reference pattern;
if the image characteristics are consistent with the pre-stored reference patterns, the specific position of the machine room water leakage is determined to be located at the position edge of the adjacent position space;
if the image characteristics are inconsistent with the pre-stored reference patterns, obtaining a comparison result;
obtaining a difference image based on the comparison result;
performing region delineation on the target processing image based on the differential image;
meanwhile, acquiring comprehensive image information in the defined area, and determining the specific position of the water leakage of the machine room based on the comprehensive information.
In this embodiment, the image integration information may be chrominance information, luminance box RGC tristimulus value information, of all pixels in the delineating region.
In this embodiment, the exposure parameter may be a shutter speed, an EV correction value, an aperture value, or the like of the acquisition device.
In this embodiment, the moisture content refers to the mass of water vapor in the humid air of the location space concurrently with one kilogram of dry air.
In this embodiment, the image analysis file may analyze the underlying features and the overlying structures by using a preset mathematical model and combining with an image processing technique, so as to precisely complete the marking of each element of the target processing image.
In this embodiment, each element may be an image texture, an image sharpness, a pixel point in an image, and the like in the target processing image.
In this embodiment, the evaluation index is used to measure the image characteristics, so as to accurately extract the image characteristics of each block, for example, when the evaluation index is the first index, the image characteristics of the image are that the image texture is uniform and has no abnormality, and each pixel point is also uniform; when the evaluation index is the second index, the image characteristics of the image are that the image texture is abnormal, and uneven places appear in the pixel points, and the like.
In this embodiment, the preset algorithm may be
Wherein: p represents air pressure (Pa), Ps represents water vapor partial pressure (Pa), and Φ represents humidity value. d reflects exactly how much water vapor is contained in the air.
The beneficial effects of the above technical scheme are: through acquireing the highest position space of humidity concentration in the computer lab, and then carry out image acquisition to the position space, simultaneously, handle the target image for the definition of target image is higher, and the analysis of being more convenient for is through the analysis to the target processing image, thereby accurately acquires the concrete position that the computer lab leaked.
Example 8:
on the basis of embodiment 1, this embodiment provides a method for detecting water leakage of a machine room in a data center, and in step 4, after detecting water leakage of the machine room based on the water leakage detection network, the method further includes:
based on the detection result, when the machine room leaks water, the water leakage position of the machine room is determined, meanwhile, the water leakage speed of the water leakage position is calculated, meanwhile, based on the water leakage speed, the water leakage amount of the machine room in a standard time period is calculated, and the current safety degree of the machine room is measured according to the water leakage amount, wherein the specific working process comprises the following steps:
determining an area function of the water leakage position based on the water leakage position, and calculating the water leakage speed of the machine room in unit time according to the estimated area of the water leakage position;
wherein v represents the water leakage speed of the machine room in unit time; f' (x) represents an area function; x represents the number of region blocks; a represents a region lower limit of the region block; b represents an area upper limit of the area block; s represents an estimated area of the water leakage position; p represents water leakage frequency; t represents a unit time; h represents the distance from the water leakage position to the ground;
calculating the water leakage amount of the machine room in a standard time period according to the water leakage speed;
wherein l represents the water leakage amount of the machine room in a standard time period; ρ represents the density of water; v represents the volume of water leakage; d represents the momentum of the water from the water leakage position to the ground; g represents the acceleration of gravity, and is generally 9.8m/s 2 (ii) a T represents the standard time period; v represents the water leakage speed of the machine room in unit time; h represents the distance from the water leakage position to the ground;
determining a current humidity value of the machine room based on the water leakage amount of the machine room in a standard time period;
comparing the humidity value of the machine room with a safe humidity threshold value of the machine room;
if the humidity value of the machine room is smaller than the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is high, and meanwhile, filling the water leakage position;
if the humidity value of the machine room is equal to the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is moderate, and filling the water leakage position;
if the humidity value of the machine room is larger than the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is low;
and when the safety degree of the machine room is low, controlling the running equipment of the machine room to stop working, performing drying operation, and simultaneously replacing the water leakage position.
In this embodiment, the limited number of the area blocks may be obtained by dividing the area of the water leakage position into n equal parts and limiting, where x is the limited number of the area blocks.
In this embodiment, the safe humidity threshold represents the maximum humidity value that each device in the machine room can bear, and when the maximum humidity value is exceeded, the safety degree of each device in the machine room will not be guaranteed.
In the embodiment, when the safety degree of the machine room is low, the water leakage of the machine room is serious, and the machine room needs to be replaced.
In this embodiment, the water leakage frequency may be the number of times of water drops at the water leakage position of the machine room in a unit time.
The beneficial effects of the above technical scheme are: when the machine room leaks, the water leakage position of the machine room is determined, and meanwhile, the water leakage speed of the water leakage position is accurately calculated, so that the water leakage of the machine room in a standard time period is accurately calculated, the safety of the current machine room is effectively measured according to the water leakage, and the detection efficiency of water leakage of the machine room is indirectly improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (6)
1. A method for detecting water leakage of a machine room of a data center is characterized by comprising the following steps:
step 1: based on the Internet of things, acquiring a water leakage detection protocol according to the machine room state parameters, and connecting the water leakage detection protocol with a water leakage detection network;
and 2, step: determining machine room humidity data in current machine room state parameters, and storing the machine room humidity data;
and step 3: the stored humidity data of the machine room is uploaded to the water leakage detection network through the Internet of things;
and 4, step 4: detecting water leakage of the machine room based on the water leakage detection network;
in step 1, the specific working process of the water leakage detection protocol is obtained according to the state parameters of the machine room, and the working process comprises the following steps:
acquiring state parameters of the machine room, and splitting the state parameters;
filling the split state parameters into a sample extraction data list, and extracting sample data corresponding to the state parameters;
generating a public data tree corresponding to the sample extraction data list according to the sample data;
generating a data protocol matrix based on the common data tree;
acquiring a detection factor in the public data tree, and comparing each row of data in the data protocol matrix based on the detection factor;
acquiring the byte type of each line of data, and meanwhile, determining the sub-protocol content corresponding to each line of data based on the comparison result and the numerical value corresponding to each line of data;
merging the subprotocol contents in sequence to obtain a final water leakage detection protocol;
in step 4, after the water leakage detection is performed on the machine room based on the water leakage detection network, the method further includes:
based on the detection result, when the machine room leaks water, determining the water leakage position of the machine room, calculating the water leakage speed of the water leakage position, calculating the water leakage amount of the machine room in a standard time period based on the water leakage speed, and measuring the current safety degree of the machine room according to the water leakage amount, wherein the specific working process comprises the following steps:
determining an area function of the water leakage position based on the water leakage position, and calculating the water leakage speed of the machine room in unit time according to the estimated area of the water leakage position;
wherein v represents the water leakage speed of the machine room in unit time; f' (x) represents an area function; x represents the number of region blocks; a represents a lower limit of the region block; b represents an area upper limit of the area block; s represents an estimated area of the water leakage position; p represents water leakage frequency; t represents a unit time; h represents the distance from the water leakage position to the ground;
calculating the water leakage amount of the machine room in a standard time period according to the water leakage speed;
wherein l represents the water leakage amount of the machine room in a standard time period; ρ represents the density of water; v represents the volume of water leakage; d represents the momentum of the water from the water leakage position to the ground; g represents the gravitational acceleration, generally 9.8m/s 2 (ii) a T represents the standard time period; v represents a water leakage speed of the machine room in unit time; h represents the distance from the water leakage position to the ground;
determining a current humidity value of the machine room based on the water leakage amount of the machine room in a standard time period;
comparing the humidity value of the machine room with a safe humidity threshold value of the machine room;
if the humidity value of the machine room is smaller than the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is high, and meanwhile, filling the water leakage position;
if the humidity value of the machine room is equal to the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is moderate, and filling the water leakage position;
if the humidity value of the machine room is larger than the safety humidity threshold value of the machine room, judging that the safety degree of the machine room is low;
and when the safety degree of the machine room is low, controlling the operation equipment of the machine room to stop working, performing drying operation, and simultaneously replacing the water leakage position.
2. The method according to claim 1, wherein in step 1, after the connection between the water leakage detection protocol and the water leakage detection network, the method further comprises:
carry out analogue test to the water pipe pipeline valve water leakage fault in the computer lab, concrete working process includes:
filling the water pipe with water, and controlling the water pipe to carry out full-load work in a preset time period;
meanwhile, monitoring temperature and humidity change values in the machine room in real time, and recording the highest temperature and humidity value in the machine room once in each preset time interval;
combining the temperature and humidity change value in the machine room with the highest temperature and humidity value in the machine room recorded in each preset time interval, and transmitting a combination result to the water leakage detection network end;
based on the combination result, verifying whether the waterway redundancy meets the requirement through a water leakage detection network terminal; and obtaining a verification result;
and taking the verification result as a test result of the simulation test of the water leakage fault of the water pipe pipeline valve.
3. The method for detecting water leakage in the machine room of the data center according to claim 1, wherein in the step 2: the concrete steps of storing the humidity data of the machine room comprise:
acquiring data types of the computer room humidity data, integrating the computer room humidity data with consistent data types, and acquiring a data packet;
extracting identification characters of the data packet, and establishing a public index value based on the identification characters;
encrypting the humidity data of the machine room according to the public index value to obtain a corresponding encryption matrix dimension;
acquiring the encryption length of the humidity data of the machine room based on the dimension of the encryption matrix;
encrypting the humidity data of the machine room according to the encryption length and by combining an encryption matrix;
and distributing a memory space to the encrypted computer room humidity data, and storing the encrypted computer room humidity data in the distributed memory space based on the public index value.
4. The method according to claim 1, wherein in step 3, the specific working step of uploading the stored humidity data of the machine room to the water leakage detection network through the internet of things comprises:
s101: preprocessing the humidity data of the machine room to obtain first processed data;
s102: acquiring a data identifier of the first processing data, and generating a data uploading rule based on the data identifier;
s103: acquiring N target fields of first processing data based on the data uploading rule;
meanwhile, field auditing is carried out on the target field of the first processing data according to the data uploading rule;
s104: generating a data queue by the first processing data which passes the examination, and acquiring a queue hash value of the data queue;
s105: establishing an incidence relation between the queue hash value and the Internet of things, and matching the incidence relation with the water leakage detection network side;
s106: if the incidence relation is matched with the water leakage detection network terminal, transmitting the data queue with first processing data to the water leakage detection network terminal based on the incidence relation, and completing uploading the humidity data of the machine room to the water leakage detection network terminal through the Internet of things;
otherwise, defining the association relationship as an invalid relationship, and reestablishing the association relationship until the association relationship is matched with the water leakage detection network end;
s107: and performing data auditing treatment on the first processing data which do not pass, acquiring second processing data, and repeating the steps S104-S106 to finish the uploading of the humidity data of the machine room to the water leakage detection network through the Internet of things.
5. The method for detecting water leakage of the machine room in the data center according to claim 1, wherein in the step 4, the working process of detecting water leakage of the machine room based on the water leakage detection network terminal comprises:
acquiring a humidity mean value of the humidity data of the machine room based on the water leakage detection network, and judging the humidity mean value in a range of a reference humidity alarm threshold value of the machine room;
and if the humidity mean value falls into the range of the reference humidity alarm threshold value of the machine room for multiple times, judging that water leakage occurs in the machine room, and simultaneously, carrying out alarm operation.
6. The method according to claim 1, wherein in step 4, after detecting water leakage in the machine room based on the water leakage detection network, the method further comprises determining a specific location of water leakage in the machine room when water leakage in the machine room is detected, and the specific working process includes:
dividing the machine room into m position spaces, and collecting humidity values of the m position spaces one by one;
calculating the moisture content of the position space according to the humidity value and a preset algorithm, and determining the humidity concentration of the position space according to the moisture content;
comparing the humidity concentration with standard humidity concentration which can be normally used by a machine room;
acquiring a space position with the humidity concentration larger than the standard humidity concentration, and acquiring a target image corresponding to the space position;
fourier transforming the target image into a low-frequency part and a high-frequency part;
obtaining a low-frequency image section by carrying out inverse transformation on the Fourier transform on the low-frequency part and the same-order diagonal matrix, and simultaneously obtaining a high-frequency image section by carrying out inverse transformation on the Fourier transform on the high-frequency part and the same-order diagonal matrix;
respectively carrying out noise reduction processing on the low-frequency image segment and the high-frequency image segment, and combining the processed low-frequency image segment and the processed high-frequency image segment to obtain a noise reduction target image;
acquiring the exposure degree of the noise-reduced target image, and determining the exposure parameter of the target image based on the exposure degree and the current environment brightness;
adjusting the noise reduction target image based on the exposure parameters, and acquiring a target processing image;
establishing an image analysis file based on the target processing image, and marking each element of the target processing image based on the image analysis file;
meanwhile, generating an evaluation index based on each marked element;
extracting the image characteristics of each block of the target processing image according to the evaluation index, and comparing the image characteristics with a pre-stored reference pattern;
if the image characteristics are consistent with the pre-stored reference patterns, judging that the specific position of the machine room water leakage is located at the position edge of the adjacent position space;
if the image characteristics are inconsistent with the pre-stored reference patterns, obtaining a comparison result;
obtaining a difference image based on the comparison result;
performing region delineation on the target processing image based on the differential image;
meanwhile, acquiring comprehensive image information in the defined area, and determining the specific position of the water leakage of the machine room based on the comprehensive information.
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