CN105320184A - Intelligent monitoring system of indoor environment of building - Google Patents
Intelligent monitoring system of indoor environment of building Download PDFInfo
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- CN105320184A CN105320184A CN201410685580.2A CN201410685580A CN105320184A CN 105320184 A CN105320184 A CN 105320184A CN 201410685580 A CN201410685580 A CN 201410685580A CN 105320184 A CN105320184 A CN 105320184A
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Abstract
The present invention discloses an intelligent monitoring system of an indoor environment of a building. The intelligent monitoring system comprises a comfort degree monitoring and comprehensive evaluation system, an energy consumption control strategy and dispatching system, an indoor environment control system and a CPU control center. Information interactions between the comfort degree monitoring and comprehensive evaluation system and the CPU control center, between the energy consumption control strategy and dispatching system and the CPU control center and between the indoor environment control system and the CPU control center are performed through a communication module. The system integration of the invention has flexibility, personalized configuration of software and hardware products may be realized on the basis of standardization, such as wired or wireless communication mode, remote or local monitoring models and the like; and moreover, the optimization method and the strategy of the intelligent monitoring system of an indoor environment of a building has advancement, a comfortable environment with low energy consumption capable of satisfying a plurality of constraint conditions or composite demands may be provided for users on the basis of the advanced comfort degree evaluation method and the device energy consumption control strategy. Therefore the Intelligent monitoring system provided by the invention has substantial technical superiority.
Description
Technical field
The present invention relates to technical field of buildings, be specifically related to Building Indoor Environment intelligent monitor system.
Background technology
China is in the fast-developing period of urbanization, and large public building proportion in the covil construction of cities and towns is more and more higher.According to statistics, the world on average builds the ratio that total energy consumption accounts for social total energy consumption and is about 40%.In order to ensure that people contrast the demand of bright, comfortable humiture, fresh air, office and other specific functions, the unit area energy consumption of large public building can reach 10 ~ 20 times of ordinary residence.Under the dual-pressure of demand growth and energy-saving and emission-reduction, how both to ensure the high request of user for building interior environment (comfort level), effectively reduce again the energy consumption of large public building, promote building energy utilization to develop to intelligent direction, coordinate the relation of energy and environment, the sustainable development for China's economy, society is significant.
Summary of the invention
The object of the invention is to: for the above-mentioned technical matters existed in prior art, a kind of Building Indoor Environment intelligent monitor system is provided.
The present invention is achieved by the following technical solutions:
Building Indoor Environment intelligent monitor system, comprise: comfort level monitoring and overall evaluation system, energy consumption control strategy and dispatching system, indoor environmental condition control system and CPU control center, described comfort level is monitored with overall evaluation system, energy consumption control strategy and dispatching system, indoor environmental condition control system all by communication module and CPU control center interactive information; The integrated sensor group that described comfort level monitoring is made up of multiple sensor with overall evaluation system, described energy consumption control strategy and dispatching system comprise a data setting unit, and described indoor environmental condition control system comprises air precision air conditioning system, LED illumination System and central ventilation system.
Further, described integrated sensor group comprises Temperature Humidity Sensor, intensity of illumination sensor and UST environmental sensor.
In order to adapt to the demand of different Building Indoor Environments, described data setting unit can be arranged the value scope of the humiture of indoor, intensity of illumination, gas concentration lwevel, flue gas concentration and organic volatile substrate concentration according to the actual requirements voluntarily.
Further, described comfort level monitoring adopts fuzzy neural network to carry out comprehensive quantitative evaluation to indoor environment with the comprehensive evaluation algorithm of overall evaluation system, can calculate indoor global comfort quantized value, namely according to this algorithm
Further, described energy consumption control strategy and dispatching system foundation
Naxf (x
t, x
i, x
a)=ω
1[1-((x
t-T
set)/T
set)
2]+ω
2[1-((x
i-I
set)/I
set)
2]+ω
3[1-((x
a-A
set)/A
set)
2] and minf (x
t, x
i, x
a)=E
1(x
t)+E
2(x
i)+E
3(x
a) two objective functions, utilize multi-objective optimization algorithm, obtain system call strategy.
Further, described communication module adopt wired or wireless in one or both and use, described wireless employing Zigbee protocol, described wired employing Modbus agreement.
In sum, owing to have employed technique scheme, the invention has the beneficial effects as follows:
The system integration of the present invention has dirigibility, and standardized basis also can realize the individual cultivation of soft and hardware product, as wired or wireless communication mode, long-range or local monitoring mode etc.; In addition, its optimization method and strategy have advance, based on the Comfort Evaluation method and apparatus energy consumption regulating strategy of advanced person, for user provides the low energy consumption a home from home that can meet multiple constraint condition or composite demand, have technical progress significantly.
Accompanying drawing explanation
Examples of the present invention will be described by way of reference to the accompanying drawings, wherein:
Fig. 1 is system architecture diagram of the present invention.
Embodiment
All features disclosed in this instructions, or the step in disclosed all methods or process, except mutually exclusive feature and/or step, all can combine by any way.
Arbitrary feature disclosed in this instructions (comprising any accessory claim, summary and accompanying drawing), unless specifically stated otherwise, all can be replaced by other equivalences or the alternative features with similar object.That is, unless specifically stated otherwise, each feature is an example in a series of equivalence or similar characteristics.
As shown in Figure 1, Building Indoor Environment intelligent monitor system, comprise: comfort level monitoring and overall evaluation system, energy consumption control strategy and dispatching system, indoor environmental condition control system and CPU control center, described comfort level is monitored with overall evaluation system, energy consumption control strategy and dispatching system, indoor environmental condition control system all by communication module and CPU control center interactive information; The integrated sensor group that described comfort level monitoring is made up of multiple sensor with overall evaluation system, described energy consumption control strategy and dispatching system comprise a data setting unit, and described indoor environmental condition control system comprises air precision air conditioning system, LED illumination System and central ventilation system.
Described integrated sensor group comprises Temperature Humidity Sensor, intensity of illumination sensor and UST environmental sensor, described communication module adopt wired or wireless in one or both and use, described wireless employing Zigbee protocol, described wired employing Modbus agreement.
In order to adapt to the demand of different Building Indoor Environments, described data setting unit can be arranged the value scope of the humiture of indoor, intensity of illumination, gas concentration lwevel, flue gas concentration and organic volatile substrate concentration according to the actual requirements voluntarily.
Comfort level monitoring and overall evaluation system comprise several and are arranged in indoor integrated sensor group, and integrated sensor group can carry out Real-time Collection to indoor temperature, humidity, intensity of illumination, gas concentration lwevel, flue gas concentration and organic volatile substrate concentration.Sensor group is integrated by electronics Temperature Humidity Sensor, intensity of illumination sensor and German UST environmental sensor, and direct current DC powers, and available power supply voltage range is-24V; Can actual measurement ambient temperature range be 0-50 DEG C, storage temperature range be between-10-75 DEG C, and can survey gas concentration lwevel scope is 0-5000ppm, and can survey cigarette 10V gas concentration range is 0-50ppm, and can survey total volatile organic compounds concentration range is 0-50ppm.The detecting distance of acquisition terminal sensor group is greater than 4 meters, and level angle is greater than 120 °, and vertical angle is greater than 60 °, and signal response time is less than 0.5s.According to doors structure, area, the configurable multiple integrated sensor group of application demand, and import CPU control center into by organizing environmental data more.CPU control center can utilize communication module, realizes the communication function between sensor group, database and each equipment control loop, wherein utilizes RS232 communication protocol to complete data transmission between sensor group and CPU control center; On the other hand, comprehensive evaluation is carried out to the data obtained from sensor group.Comprehensive evaluation program java language compilation, utilize the realization of T-S fuzzy neural network for the comprehensive quantitative evaluation of indoor global comfort, its evaluation procedure is as follows:
If the environmental parameter vector of Real-time Collection is
q represents the number of probes of image data.The indoor environment parameter kind that p representative gathers.T represents the sampling time, and in this example, the sampling time is set to 1 second.
represent six indexs such as indoor temperature, relative humidity, intensity of illumination, gas concentration lwevel, flue gas concentration and organic volatile substrate concentration successively.Adopt average algorithm to carry out analyzing and processing to image data in data processing, the environmental parameter input vector after process is
and have
output after fuzzy neural network calculates is that indoor current Comfort Evaluation grade is denoted as y, and this output variable dimension is 1.
By the calculating of membership function, input vector can be obtained
the degree of membership of the indices under fuzzy set, the comfortable opinion rating of indoor environment of output is divided into five etc., and also the item environment evaluation index parameter of input is divided into five regions as required respectively in order to the comfortable grade of quantitative description.If the indoor comfortable opinion rating exported is I (I=1,2 ..., 5), then there is Iff (U
1, U
2, U
3, U
4, U
5) ∈ l, theny=I
Wherein, the selected fuzzy operator of function f representative.According to fuzzy inference rule generating principle, the fuzzy rule form defining this system is " if-then " form.Suppose that the fuzzy rule being used for reasoning adds up to m (i=1,2,3 ... .m).Following reasoning process is had for the i-th rule:
Wherein,
represent the fuzzy set of indoor environment input variable under regular Ri;
it is the parameter of fuzzy system; The comfortable opinion rating of output environment that yi calculates according to fuzzy rule Ri.For the importation (if part) of inference rule, its result of calculation is fuzzy, and output (then part) its result of calculation is accurate, and final output form is the linear combination of input variable.Detailed computation process is as follows:
First, the degree of membership of each input environment variable xp is calculated according to selected membership function type:
p=1,2,...,5;i=1,2,...,m(1)
In formula,
represent center and the width of Gauss's membership function respectively; K represents the number of input variable; M represents fuzzy subset's number.
i=1,2,...,m(2)
Formula (2) calculates for fuzzy reasoning, and its fuzzy operator adopts to connect takes advantage of form.
According to result of calculation, export under fuzzy rule Ri, system exports y
icalculated by following formula:
T-8 fuzzy neural network forms by four layers: input layer, obfuscation layer, fuzzy reasoning computation layer and output layer.Input layer is directly connected with the input vector of system, and this node layer number is identical with the dimension of input vector.Adopt the membership function form as shown in equation (1), after system input carries out Fuzzy Processing by obfuscation layer, obtain corresponding degree of membership μ.Company in equation (2) takes advantage of operator for calculating weights omega at fuzzy reasoning layer.Network finally exports and is calculated by equation (3) in output layer.
For indoor environment evaluation, the dynamic learning algorithm of fuzzy neural network is as follows:
System expects that environment exports opinion rating and the actual error exported between evaluation result is calculated by following formula:
Wherein, yd and yc is that network desired output and the world export respectively; E is the deviation of desired output and actual outlet chamber.
For fuzzy inference rule Ri, the correction factor of each environmental variance is calculated by following formula:
the correction factor of a jth environment input variable for fuzzy rule Ri; α is the learning rate of neural network; ω
iit is the degree of membership continued product of input environment parameter.
The parameters revision algorithm of network is as follows:
with
represent center and the width of membership function respectively.
Considers that humiture, intensity of illumination and air quality three indexs are as the principal element affecting indoor comfortable situation, and adopt method of weighted mean to integrate this three environmental evaluation indexs, therefore overall comfort evaluation index is calculated by following formula:
F (x
t, x
i, x
a) representing the comprehensive comfortable evaluation of estimate of architecture indoor, its codomain scope is [0,1].Under normal circumstances in order to ensure user's overall comfort, f (x within the scope of codomain
t, x
i, x
a) the larger agent's room of value in comfort level higher.ω
1, ω
2, ω
3represent for the user-defined weight coefficient of the comfortable evaluation index of indoor individual event, ω
i(i=1,2,3) ∈ [0,1] and have ω
1+ ω
2+ ω
3=1.T
set, L
set, A
setrepresent the optimum setting point of humiture, intensity of illumination and air quality respectively, choosing of set point and weight is according to the preference of user and can reflects that the control law of the indoor daily behavior of user is determined.
Comfort level is monitored the indoor environment evaluation result obtained with overall evaluation system by energy consumption control strategy and dispatching system according to CPU control center, carry out rational allocation, to reach the coordinating and unifying of system energy consumption target and comfortable target to indoor environment equipment.
Energy consumption control strategy and dispatching system are the central control units of Building Indoor Environment intelligent monitor system, supply electric energy consumption, thus be optimized whole building system operation reserve for coordinates user side comfort need and grid side.The comfortableness demand of user side and power consumption constraint can be configured by graphic user interface (Graphicaluserinterface, GUI), and are reported to user by gui interface.Energy consumption control strategy and dispatching system by transmitting with the data of CPU control center, real time environment supplemental characteristic and comprehensive Comfort Evaluation result in continuous collecting chamber; Meanwhile, energy consumption control strategy and dispatching system also communicate with the control loop of each field apparatus, obtain actual consumption information.
In building system, power dissipation obj ectives function E (x) experimentally obtains according to profits such as interior space size, equipment choosing situations.Power dissipation obj ectives function E (x) in the present invention is determined by following formula.
minf(x
T,x
I,x
A)=E
1(x
T)+E
2(x
I)+E
3(x
A)(10)
In formula, power dissipation obj ectives function E (x) is made up of three parts, and various piece energy consumption size exists quantitative relationship with respective environment parameter drift-out optimum setting degree.Wherein, t is air-conditioning equipment working time, energy consumption penalty coefficient when c is fan operation.
Different from according to season in dispatching system of energy consumption control strategy, can be arranged the parameter value such as indoor temperature and humidity, intensity of illumination by data setting unit voluntarily, based on comprehensive comfort level quantizating index, define economic operation model storehouse and comfortable running mode storehouse respectively.In order under the prerequisite meeting the comprehensive comfortableness of indoor user, reduce the energy consumption of system as far as possible, in energy consumption control strategy and dispatching system, adopt multi-objective genetic algorithm to carry out the optimization of system cloud gray model scheme.According to (9) and (10) two objective functions, multi-objective optimization algorithm is utilized to carry out optimizing in the acceptable comfort zone of human body, obtain system call strategy, and then select to determine current operational mode from economic operation model storehouse and comfortable running mode storehouse, and dependent instruction is handed down to indoor environmental condition control system.
Indoor environmental condition control system is made up of jointly air precision air conditioning system, LED illumination System, central ventilation system, by the dispatch command that DDC control loop reception CPU control center is transmitted, also pass real time energy consumption information by CPU control center back to energy consumption control strategy and dispatching system simultaneously, between each DDC control loop of CPU control center and indoor environmental condition control system, adopt Modbus communications protocol.Air precision air conditioning system mainly contains humidification/dehumidifying and refrigerating/heating function, VMC (Ventilation Mechanical Control System) is made up of with the new blower fan being connected indoor and outdoor multiple scavenger fan be arranged in room, its major function be ventilation to ensure that IAQ (indoor air quality) situation is in the acceptable scope of user, LED illumination System provides the room lighting of brightness-adjustable.
Building Indoor Environment intelligent monitor system is the important step improving living environment, the high-efficiency comprehensive utilization energy, progressively becomes important component part indispensable in modern energy supply system.According to the climatic characteristic of China, the time in most area Heating Season and refrigeration season is all longer, the long operational time of building interior environment conditioning equipment, and plant factor is high; Meanwhile, because large public building is built in load center usually, rational managing power consumption is implemented to it and also can provide strong support to the safe operation of electrical network.China pays much attention to Building Energy-saving always, and give in policy and fund aspect and support energetically, in this context, this patent has a good application prospect.
Above-described specific embodiment, further describes object of the present invention, technical scheme and beneficial effect, and institute it should be understood that and the foregoing is only specific embodiments of the invention, is not limited to the present invention.The present invention expands to any new feature of disclosing in this manual or any combination newly, and the step of the arbitrary new method disclosed or process or any combination newly.
Claims (8)
1. Building Indoor Environment intelligent monitor system, it is characterized in that, comprise: comfort level monitoring and overall evaluation system, energy consumption control strategy and dispatching system, indoor environmental condition control system and CPU control center, described comfort level is monitored with overall evaluation system, energy consumption control strategy and dispatching system, indoor environmental condition control system all by communication module and CPU control center interactive information; The integrated sensor group that described comfort level monitoring is made up of multiple sensor with overall evaluation system, described energy consumption control strategy and dispatching system comprise a data setting unit, and described indoor environmental condition control system comprises air precision air conditioning system, LED illumination System and central ventilation system.
2. Building Indoor Environment intelligent monitor system according to claim 1, is characterized in that, described integrated sensor group comprises Temperature Humidity Sensor, intensity of illumination sensor and UST environmental sensor.
3. Building Indoor Environment intelligent monitor system according to claim 1, it is characterized in that, described data setting unit can be arranged the value scope of the humiture of indoor, intensity of illumination, gas concentration lwevel, flue gas concentration and organic volatile substrate concentration according to the actual requirements voluntarily.
4. Building Indoor Environment intelligent monitor system according to claim 1, it is characterized in that, described comfort level monitoring adopts fuzzy neural network to carry out comprehensive quantitative evaluation to indoor environment with the comprehensive evaluation algorithm of overall evaluation system, indoor global comfort quantized value can be calculated, namely according to this algorithm
5. Building Indoor Environment intelligent monitor system according to claim 1, is characterized in that, described energy consumption control strategy and dispatching system are according to maxf (x
t, x
i, x
a)=ω
1[1-((x
t-T
set)/T
set)
2]+ω
2[1-((x
i-I
set)/I
set)
2]+ω
3[1-((x
a-A
set)/A
set)
2] and minf (x
t, x
i, x
a)=E
1(x
t)+E
2(x
i)+E
3(x
a) two objective functions, utilize multi-objective optimization algorithm, obtain system call strategy.
6. Building Indoor Environment intelligent monitor system according to claim 1, is characterized in that, one or both during described communication module employing is wired or wireless are also used.
7. Building Indoor Environment intelligent monitor system according to claim 4, is characterized in that, described wireless employing Zigbee protocol.
8. Building Indoor Environment intelligent monitor system according to claim 4, is characterized in that, described wired employing Modbus agreement.
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Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20070095712A (en) * | 2006-03-22 | 2007-10-01 | 주식회사 와이더맥스 | Indoor environment management system and indoor environment management method using the same |
CN202150063U (en) * | 2011-06-20 | 2012-02-22 | 镇江市诚翔电器有限责任公司 | Wireless temperature-humidity centralized control device for power distribution room heating ventilation air conditioner |
CN102866684A (en) * | 2012-08-24 | 2013-01-09 | 清华大学 | Indoor environment integrated control system and method based on user comfort |
CN202854587U (en) * | 2012-10-24 | 2013-04-03 | 成都翰东科技有限公司 | Intelligent monitoring management system used for agricultural greenhouse |
-
2014
- 2014-11-26 CN CN201410685580.2A patent/CN105320184B/en not_active Expired - Fee Related
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20070095712A (en) * | 2006-03-22 | 2007-10-01 | 주식회사 와이더맥스 | Indoor environment management system and indoor environment management method using the same |
CN202150063U (en) * | 2011-06-20 | 2012-02-22 | 镇江市诚翔电器有限责任公司 | Wireless temperature-humidity centralized control device for power distribution room heating ventilation air conditioner |
CN102866684A (en) * | 2012-08-24 | 2013-01-09 | 清华大学 | Indoor environment integrated control system and method based on user comfort |
CN202854587U (en) * | 2012-10-24 | 2013-04-03 | 成都翰东科技有限公司 | Intelligent monitoring management system used for agricultural greenhouse |
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CN105867334A (en) * | 2016-05-11 | 2016-08-17 | 华中农业大学 | Intelligent environment parameter control system for watermelons in greenhouse |
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CN109885118A (en) * | 2019-03-15 | 2019-06-14 | 中国建筑科学研究院有限公司 | Environmental control system |
CN109919513B (en) * | 2019-03-22 | 2021-06-04 | 吉林建筑大学 | Physical environment evaluation method based on cold region assembly type residential building |
CN109919513A (en) * | 2019-03-22 | 2019-06-21 | 吉林建筑大学 | A kind of physical environment evaluation method based on cold ground assembled folk building object |
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