CN109828618A - Data center apparatus measure and control device based on artificial intelligence technology - Google Patents
Data center apparatus measure and control device based on artificial intelligence technology Download PDFInfo
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Abstract
The invention proposes a kind of data center apparatus measure and control device based on artificial intelligence technology including data center apparatus and monitors the temperature measurement and control instrument of the data center apparatus temperature.The advantages of data center apparatus measure and control device of the device based on artificial intelligence technology, both comprehensive video detection and temperature sense, realize data center apparatus failure detection intelligent.
Description
Technical field
The invention belongs to fault detection technique fields, and in particular to a kind of data center apparatus based on artificial intelligence technology
Measure and control device.
Background technique
In recent years, the outer cabinet of communication user and data center to center communications computer room largely build use, in computer room cabinet in data
Heart equipment heating amount is big and concentrates, and heat dissipation, energy conservation problem seems especially prominent and important.
Traditional temperature of communication equipment Energy Saving Control scheme is all to control refrigeration equipment by detection indoor and outdoor temperature,
Start heat exchanger or new wind devices when lower temperature, start air-conditioning when temperature is higher and freeze, control strategy is benefit
With current detection temperature compared with a certain setting value carries out size, by comparison result come the relevant refrigeration equipment of start and stop, such control
Method processed can not pace of change to computer room temperature and trend make accurate judgement, poor for applicability, same control method is not
There are great differences for the computer room of same region, climatic environment and device configuration, such as good in the energy-saving effect in a certain computer room season,
But other computer rooms are transplanted to because of the thermic load of equipment, installation arrangement and environmental difference, often will appear overtemperature or fractional energy savings is low, very
To not energy-efficient situation.
Thus, control program more advanced at present improves on the basis of above scheme, and it is micro- to have incorporated proportional, integral-
The algorithm for dividing (Proportion Integration Differentiation, PID) control or fuzzy control, can be accurate
Reflect the pace of change and trend of computer room temperature field, and carry out the judgement and control of foresight, can quickly adjust temperature, meets
The stability requirement of temperature control reaches effective energy-efficient purpose.But up to the present, the operational parameter of such control program still office
It is limited to computer room temperature.
Summary of the invention
In view of the above analysis, the main purpose of the present invention is to provide one kind, and above-mentioned data center in the prior art to be overcome to set
The data center apparatus measure and control device based on artificial intelligence technology of standby fault detection drawback, comprehensive video detection and temperature sense
The advantages of answering the two realizes data center apparatus failure detection intelligent.
The purpose of the present invention is what is be achieved through the following technical solutions.
Technical solution of the present invention is related to a kind of data center apparatus measure and control device based on artificial intelligence technology, including number
According to central apparatus and monitor the temperature measurement and control instrument of the data center apparatus temperature.
Further, the temperature measurement and control instrument include power supply, processor module, temperature sense module, video detection module,
Analog-to-digital conversion module, temperature sense module are used for the temperature of sensed data central apparatus, and signal processing mould is passed through in signal output
After block processing, send to analog-to-digital conversion module, then handled by processor module, and video detection module is simultaneously also in data
The heat distribution of heart equipment is detected to obtain the detection image signal of correcting action, and detection image signal is also sent to processor
Module is handled, and the data center apparatus temperature data that processor module is obtained according to temperature sense module is referring to video detection
The data center apparatus temperature data that module obtains is corrected.
Further, the reference voltage of 3.3V is converted to constant current using amplifier by temperature sense module, works as electric current
It will generate voltage drop when flowing through thermal resistance (Rt), then be amplified the weak pressure drop signal by amplifier, by amplified letter
Number be sent into analog-to-digital conversion module.
Further, video detection module includes video acquisition processing module, the module include deformation machine learning module,
Data center apparatus image feature value seeks module, and extends image function foundation and processing module:
Deformation machine learning module, for carrying out video acquisition data central apparatus image to obtain the detection image
Before signal, picture centre is initially set up to image edge direction plane deformation updating formula, wherein due to video detection module
Camera lens is not exclusively parallel with imaging plane, therefore has the image deformation on the injustice line direction, i.e. generation strain image:
Wherein, (x, y) indicates the initial position of image, (xc,yc) be correction after position, r indicate video detection module away from
The deformation distance of data center apparatus, k1And k2For it is described from center to edge direction on deformation coefficient, | | Rarea(x, y) | |
For the modulus value of definite integral parameter；
In the top end face for the data center apparatus that video detection module faces, 1/8,1/16,1/ that 3 length are r is set
32 scale, one end of three scales are arranged on the top end face edge of data center apparatus, and the other end of each scale is along top
In-plane where end face extends outwardly, and three scales are spaced each other 120 ° of settings, pass through the collected figure of video detection module
The ratio of image of the smallest scale of length after deformation as in, i.e. length in image deformation and its physical length is calculated as just
Value, the ratio of length and its physical length in a manner of based on meanshift algorithm to other two scale in image deformation
Value is iterated respectively, and the result of iteration is respectively as k1And k2；
Data center apparatus image feature value seeks module, for generating color image I to image progress compressing and converting,
Corresponding black white image, that is, monochrome image is I ', and monochrome image gray value g is by color space linear expression are as follows:
G=αrIr+αgIg+αbIb
Wherein αr>=0, αg>=0, αb>=0, αr+αg+αb=1
α in formular, αg, αbFor optional parameters, Ir, Ig, IbIt is the color channel values of image I；
Building such as minor function V:
In formula, x, y are pixel, gx, gyThe respectively single color gradation value of x and y two o'clock, δX, yColor is converted into for image I
The European measurement of x when the model space, y pixel carries out monochrome image dimensionality reduction to above-mentioned function V using GAUSS sliding average
Processing, obtains different monochrome images:
Establish function L (x, y, σ, ρ)=ρ I ' (x, y) G (x, y, σ)
In formula, x, y are monochrome image coordinate value, and σ is scale factor, and ρ is zoom factor, and monochrome image is I ' (x, y)；
Extend image function to establish and processing module, for strain image to the extension extended outside data center apparatus
Region, which is established, extends image function fc(L (x, y, σ, ρ)), wherein L (x, y, σ, ρ) is standardized as [0,1], extends image function
Are as follows:
Wherein, λ is to extend slope, and the autocorrelation matrix of each pixel is calculated using Harris's matrix:
Wherein x, y are pixel coordinate, and N is image size, then extend the characteristic response function of image function are as follows:
R (x, y, c)=detA (x, y, fc)-k (traceA (x, y, fc))2
Wherein, k be invariant and its be k1And k2Arithmetic mean of instantaneous value；
It is obtained using definite integral is cumulative:
Further, processor module is obtained according to the temperature data that temperature sense module obtains with video detection module
It is corrected with the data center apparatus temperature data that detection image signal represents, temperature control is carried out according to correction result, it should
Processor module includes that heat setup module and temperature model establish module:
Heat setup module, for the initial temperature and environment temperature T in data center apparatus1When identical, if in data
Heart equipment is T (t) in the temperature of t moment, and heat is Q (t), then has:
Q (t)=Q1(t)+Q2(t)
In formula, Q1(t) --- the heat that data center apparatus itself generates；
Q2(t) --- the heat of transmission；
In formula, C is the thermal capacity of data center apparatus, and s is the detection image signal of video detection module acquisition by school
The color difference ratio of detection image signal when just rear and temperature is initial temperature；
Then the heat of data center apparatus is expressed as:
Temperature model establishes module, for obtaining to formula progress Laplace transform:
Establish the temperature model of data center apparatus are as follows:
K=aR, T=CR are enabled, then is had:
Wherein, K is amplification coefficient, and T is time constant, and τ is lag time.
Technical solution of the present invention has the advantage that
Both the present invention temperature control mode compound by creatively proposition video detection and temperature sense, comprehensively utilize
Advantage, and specifically propose the concrete mode of image procossing in the circuit structure and video detection of temperature sense module, base
It is corrected in the machine vision information of thermal imaging, gives relatively reliable and accurate temperature controlled model, pass through
The practical control at MATLAB l-G simulation test and scene realizes good automatic temperature-adjusting control effect by verifying.
Detailed description of the invention
Attached drawing 1 is the composition block diagram of the data center apparatus measure and control device of the invention based on artificial intelligence technology；
Attached drawing 2 is the structure principle chart of temperature measurement and control instrument of the present invention；
Attached drawing 3 is the circuit diagram of temperature sense module of the present invention.
Specific embodiment
Referring to Fig. 1, preferred embodiment in accordance with the present invention, the present invention is based on the surveys of the data center apparatus of artificial intelligence technology
Controlling device includes data center apparatus and the temperature measurement and control instrument for monitoring the data center apparatus temperature.Referring to fig. 2, the temperature
Measure and control device includes power supply, processor module, temperature sense module, video detection module, analog-to-digital conversion module, temperature sense mould
Block is used for the temperature of sensed data central apparatus, and signal is exported after signal processing module is handled, sent to analog-to-digital conversion mould
Block, then handled by processor module, and video detection module simultaneously also detects the heat distribution of data center apparatus
To obtain the detection image signal of correcting action, detection image signal, which is also sent to processor module, to be handled, processor die
The data center apparatus temperature data that root tuber is obtained according to temperature sense module is set referring to the data center that video detection module obtains
Standby temperature data is corrected.
Preferably, the circuit diagram of temperature sense module as shown in Figure 3, temperature sense module is using amplifier by 3.3V's
Reference voltage is converted to constant current, and voltage drop will be generated when electric current flows through thermal resistance Rt, then by amplifier that this is weak
Amplified signal is being sent into analog-to-digital conversion module by pressure drop signal amplification.
Preferably, video detection module includes video acquisition processing module, which includes deformation machine learning module, number
Module is sought according to central apparatus image feature value, and extends image function foundation and processing module:
Deformation machine learning module, for carrying out video acquisition data central apparatus image to obtain the detection image
Before signal, picture centre is initially set up to image edge direction plane deformation updating formula, wherein due to video detection module
Camera lens is not exclusively parallel with imaging plane, therefore has the image deformation on the injustice line direction, i.e. generation strain image:
Wherein, (x, y) indicates the initial position of image, (xc,yc) be correction after position, r indicate video detection module away from
The deformation distance of data center apparatus, k1And k2For it is described from center to edge direction on deformation coefficient, | | Rarea(x, y) | |
For the modulus value of definite integral parameter；
In the top end face for the data center apparatus that video detection module faces, 1/8,1/16,1/ that 3 length are r is set
32 scale, one end of three scales are arranged on the top end face edge of data center apparatus, and the other end of each scale is along top
In-plane where end face extends outwardly, and three scales are spaced each other 120 ° of settings, pass through the collected figure of video detection module
The ratio of image of the smallest scale of length after deformation as in, i.e. length in image deformation and its physical length is calculated as just
Value, the ratio of length and its physical length in a manner of based on meanshift algorithm to other two scale in image deformation
Value is iterated respectively, and the result of iteration is respectively as k1And k2；
Data center apparatus image feature value seeks module, for generating color image I to image progress compressing and converting,
Corresponding black white image, that is, monochrome image is I ', and monochrome image gray value g is by color space linear expression are as follows:
G=αrIr+αgIg+αbIb
Wherein αr>=0, αg>=0, αb>=0, αr+αg+αb=1
α in formular, αg, αbFor optional parameters, Ir, Ig, IbIt is the color channel values of image I；
Building such as minor function V:
In formula, x, y are pixel, gx, gyThe respectively single color gradation value of x and y two o'clock, δX, yColor is converted into for image I
The European measurement of x when the model space, y pixel carries out monochrome image dimensionality reduction to above-mentioned function V using GAUSS sliding average
Processing, obtains different monochrome images:
Establish function L (x, y, σ, ρ)=ρ I ' (x, y) G (x, y, σ)
In formula, x, y are monochrome image coordinate value, and σ is scale factor, and ρ is zoom factor, and monochrome image is I ' (x, y)；
Extend image function to establish and processing module, for strain image to the extension extended outside data center apparatus
Region, which is established, extends image function fc(L (x, y, σ, ρ)), wherein L (x, y, σ, ρ) is standardized as [0,1], extends image function
Are as follows:
Wherein, λ is to extend slope, and the autocorrelation matrix of each pixel is calculated using Harris's matrix:
Wherein x, y are pixel coordinate, and N is image size, then extend the characteristic response function of image function are as follows:
R (x, y, c)=detA (x, y, fc)-k (ttaceA (x, y, fc))2
Wherein, k be invariant and its be k1And k2Arithmetic mean of instantaneous value；
It is obtained using definite integral is cumulative:
Preferably, processor module according to the temperature data that temperature sense module obtains with video detection module obtain with
The data center apparatus temperature data that detection image signal represents is corrected, and temperature control is carried out according to correction result, at this
Managing device module includes that heat setup module and temperature model establish module:
Heat setup module, for the initial temperature and environment temperature T in data center apparatus1When identical, if in data
Heart equipment is T (t) in the temperature of t moment, and heat is Q (t), then has:
Q (t)=Q1(t)+Q2(t)
In formula, Q1(t) --- the heat that data center apparatus itself generates；
Q2(t) --- the heat of transmission；
In formula, C is the thermal capacity of data center apparatus, and s is the detection image signal of video detection module acquisition by school
The color difference ratio of detection image signal when just rear and temperature is initial temperature；
Then the heat of data center apparatus is expressed as:
Temperature model establishes module, for obtaining to formula progress Laplace transform:
Establish the temperature model of data center apparatus are as follows:
K=aR, T=CR are enabled, then is had:
Wherein, K is amplification coefficient, and T is time constant, and τ is lag time.
After establishing model, processor is according to the temperature automatic control of the model realization data center apparatus.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (5)
1. a kind of data center apparatus measure and control device based on artificial intelligence technology, which is characterized in that including data center apparatus
And monitor the temperature measurement and control instrument of the data center apparatus temperature.
2. the data center apparatus measure and control device according to claim 1 based on artificial intelligence technology, which is characterized in that should
Temperature measurement and control instrument includes power supply, processor module, temperature sense module, video detection module, analog-to-digital conversion module, temperature sense
Temperature of the module for sensed data central apparatus is answered, signal exports after signal processing module is handled, and send to modulus and turns
Block is changed the mold, then is handled by processor module, and video detection module simultaneously also carries out the heat distribution of data center apparatus
To obtain the detection image signal of correcting action, detection image signal, which is also sent to processor module, to be handled for detection, processing
In the data that the data center apparatus temperature data that device module is obtained according to temperature sense module is obtained referring to video detection module
Heart device temperature data are corrected.
3. the data center apparatus measure and control device according to claim 2 based on artificial intelligence technology, which is characterized in that temperature
It spends induction module and the reference voltage of 3.3V is converted into constant current using amplifier, will be produced when electric current flows through thermal resistance Rt
Raw voltage drop, then amplified the weak pressure drop signal by amplifier, amplified signal is sent into analog-to-digital conversion module.
4. the data center apparatus measure and control device according to claim 3 based on artificial intelligence technology, which is characterized in that view
Frequency detection module includes video acquisition processing module, which includes deformation machine learning module, data center apparatus image spy
Value indicative seeks module, and extends image function foundation and processing module:
Deformation machine learning module, for carrying out video acquisition data central apparatus image to obtain the detection image signal
In the past, picture centre is initially set up to image edge direction plane deformation updating formula, wherein due to video detection module camera lens
It is not exclusively parallel with imaging plane, therefore have the image deformation on the injustice line direction, that is, generate strain image:
Wherein, (x, y) indicates the initial position of image, (xc, yc) be correction after position, r indicate video detection module away from data
The deformation distance of central apparatus, k1And k2For it is described from center to edge direction on deformation coefficient, | | Rarea(x, y) | | it is fixed
The modulus value of integral parameter；
In the top end face for the data center apparatus that video detection module faces, 1/8,1/16,1/32 that 3 length are r is set
Scale, one end of three scales are arranged on the top end face edge of data center apparatus, and the other end of each scale is along top end face
Place in-plane extends outwardly, and three scales are spaced each other 120 ° of settings, by video detection module acquired image
Image of the smallest scale of length after deformation, i.e. length in image deformation and the ratio of its physical length are calculated as initial value, with
The ratio of length and its physical length of the mode based on meanshift algorithm to other two scale in image deformation is distinguished
It is iterated, the result of iteration is respectively as k1And k2；
Data center apparatus image feature value seeks module, for carrying out compressing and converting to image, generates color image I, corresponds to
Black white image, that is, monochrome image be I ', monochrome image gray value g is by color space linear expression are as follows:
G=αrIr+αgIg+αbIb
Wherein αr>=0, αg>=0, αb>=0, αr+αg+αb=1
α in formular, αg, αbFor optional parameters, Ir, Ig, IbIt is the color channel values of image I；
Building such as minor function V:
In formula, x, y are pixel, gx, gyThe respectively single color gradation value of x and y two o'clock, δX, yColour model is converted into for image I
The European measurement of x when space, y pixel carries out monochrome image dimension-reduction treatment to above-mentioned function V using GAUSS sliding average,
Obtain different monochrome images:
Establish function L (x, y, σ, ρ)=ρ I ' (x, y) G (x, y, σ)
In formula, x, y are monochrome image coordinate value, and σ is scale factor, and ρ is zoom factor, and monochrome image is I ' (x, y):
Extend image function to establish and processing module, for strain image to the elongated area extended outside data center apparatus
It establishes and extends image function fc(L (x, y, σ, ρ)), wherein L (x, y, σ, ρ) is standardized as [0,1], extends image function are as follows:
Wherein, λ is to extend slope, and the autocorrelation matrix of each pixel is calculated using Harris's matrix:
Wherein x, y are pixel coordinate, and N is image size, then extend the characteristic response function of image function are as follows:
R (x, y, c)=detA (x, y, fc)-k (traceA (x, y, fc))2
Wherein, k be invariant and its be k1And k2Arithmetic mean of instantaneous value；
It is obtained using definite integral is cumulative:
5. the data center apparatus measure and control device according to claim 4 based on artificial intelligence technology, which is characterized in that place
Reason device module is represented according to the temperature data that temperature sense module obtains with what video detection module obtained with detection image signal
Data center apparatus temperature data be corrected, according to correction result carry out temperature control, which includes heat
Setup module and temperature model establish module:
Heat setup module, for the initial temperature and environment temperature T in data center apparatus1When identical, if data center apparatus
It is T (t) in the temperature of t moment, heat is Q (t), then has:
Q (t)=Q1(t)+Q2(t)
In formula, Q1(t) --- the heat that data center apparatus itself generates；
Q2(t) --- the heat of transmission；
In formula, C is the thermal capacity of data center apparatus, and s is after the detection image signal of video detection module acquisition is corrected
With temperature be initial temperature when detection image signal color difference ratio；
Then the heat of data center apparatus is expressed as:
Temperature model establishes module, for obtaining to formula progress Laplace transform:
Establish the temperature model of data center apparatus are as follows:
K=aR, T=CR are enabled, then is had:
Wherein, K is amplification coefficient, and T is time constant, and τ is lag time.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113556518A (en) * | 2021-09-23 | 2021-10-26 | 成都派沃特科技股份有限公司 | Video data scheduling method, device, equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202793050U (en) * | 2012-09-16 | 2013-03-13 | 景德镇陶瓷学院 | Device for monitoring temperature of kiln through flame images and thermocouples |
| CN103761745A (en) * | 2013-07-31 | 2014-04-30 | 深圳大学 | Estimation method and system for lung motion model |
| CN105159138A (en) * | 2015-07-31 | 2015-12-16 | 中国电子科技集团公司第二十二研究所 | Radiometer temperature control system heat transfer mathematical model establishment method |
| CN106338203A (en) * | 2016-08-31 | 2017-01-18 | 宝钢发展有限公司 | Real-time monitoring system for inside view field and temperature of rotary hearth furnace and control method |
| CN107507243A (en) * | 2016-06-14 | 2017-12-22 | 华为技术有限公司 | A kind of camera parameters method of adjustment, instructor in broadcasting's video camera and system |
| CN108490959A (en) * | 2018-05-22 | 2018-09-04 | 国网天津市电力公司 | A kind of artificial intelligence computer room crusing robot for supporting deep learning operation principle |
| CN108833141A (en) * | 2018-05-28 | 2018-11-16 | 广州供电局有限公司 | Data center's operation and maintenance device and system |
| CN109357771A (en) * | 2018-12-05 | 2019-02-19 | 江西迪比科股份有限公司 | The formal detection method of batteries of electric automobile temperature self-correcting |
-
2019
- 2019-02-28 CN CN201910151116.8A patent/CN109828618A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202793050U (en) * | 2012-09-16 | 2013-03-13 | 景德镇陶瓷学院 | Device for monitoring temperature of kiln through flame images and thermocouples |
| CN103761745A (en) * | 2013-07-31 | 2014-04-30 | 深圳大学 | Estimation method and system for lung motion model |
| CN105159138A (en) * | 2015-07-31 | 2015-12-16 | 中国电子科技集团公司第二十二研究所 | Radiometer temperature control system heat transfer mathematical model establishment method |
| CN107507243A (en) * | 2016-06-14 | 2017-12-22 | 华为技术有限公司 | A kind of camera parameters method of adjustment, instructor in broadcasting's video camera and system |
| CN106338203A (en) * | 2016-08-31 | 2017-01-18 | 宝钢发展有限公司 | Real-time monitoring system for inside view field and temperature of rotary hearth furnace and control method |
| CN108490959A (en) * | 2018-05-22 | 2018-09-04 | 国网天津市电力公司 | A kind of artificial intelligence computer room crusing robot for supporting deep learning operation principle |
| CN108833141A (en) * | 2018-05-28 | 2018-11-16 | 广州供电局有限公司 | Data center's operation and maintenance device and system |
| CN109357771A (en) * | 2018-12-05 | 2019-02-19 | 江西迪比科股份有限公司 | The formal detection method of batteries of electric automobile temperature self-correcting |
Non-Patent Citations (2)
| Title |
|---|
| 孟琭: "《计算机视觉原理与应用》", 30 November 2012 * |
| 赵小川: "《MATLAB图像处理-能力提高与应用案例》", 31 January 2014 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113556518A (en) * | 2021-09-23 | 2021-10-26 | 成都派沃特科技股份有限公司 | Video data scheduling method, device, equipment and storage medium |
| CN113556518B (en) * | 2021-09-23 | 2021-12-17 | 成都派沃特科技股份有限公司 | Video data scheduling method, device, equipment and storage medium |
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Application publication date: 20190531 |
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| RJ01 | Rejection of invention patent application after publication |