JP2010078447A - Q value analysis system, q value analysis method, and q value analysis program - Google Patents

Abstract

Provided is a Q value measurement system in which a building is one room, a Q value of a building after construction is easily calculated, combined with a design Q value, and a relative evaluation of the Q value of the building can be performed.
SOLUTION: Using a thermal circuit model showing heat exchange inside and outside with a building as one room, the room temperature determined by the disturbance and any heat generation is the product of the temperature of the disturbance and the response coefficient of the room temperature, It is a composition that adds the product of the response coefficient of room temperature to the room temperature and is an equation with multiple undetermined coefficients including disturbances and total heat flow resistance between the rooms. There is an expected room temperature calculation unit that calculates the undetermined coefficient that minimizes the mean square error between the predicted room temperatures, and a Q value calculation unit that takes the inverse of the value obtained by multiplying the total heat flow resistance by the total floor area of the building as the Q value In addition, the expected room temperature calculation unit calculates the undetermined coefficient in time series, the Q value calculation unit calculates the Q value in time series, and calculates the range ΔQ value in which the mean square error of the measured measurement Q value is below the threshold, The Q value at which this ΔQ value becomes the minimum value is output as the analysis result.
[Selection] Figure 1

Description

  The present invention relates to a Q value analysis system, a Q value analysis method, and a Q value analysis program for calculating a Q value which is a thermal performance index value of a building.

Conventionally, it has been pointed out that it is important to promote energy saving of buildings as one of the measures to prevent global warming, and heat insulation of houses has become one of the basic technologies for building buildings. Insulation of houses in Japan has been promoted as a national policy, with the establishment of energy-saving standards in 1980, except in cold regions.
In addition, it is positioned as a necessary performance for housing in laws and public systems such as the Basic Act on Housing and Living and the housing performance display system.

On the other hand, when evaluating and inspecting the heat insulation performance, desk evaluation of calculating and evaluating a heat transmissibility and a heat loss coefficient is used as the only method in practice (see, for example, Patent Document 1).
Although the method itself for inspecting a completed building was proposed over 30 years ago (for example, see Non-Patent Document 1), the thermal insulation of the building may not actually permeate. I don't ask for a value.
Japanese Patent Laid-Open No. 2002-4403 Yo Matsuo and Heizo Saito, “Estimation of Thermal Characteristics of Houses Based on Field Measurements”, Architectural Institute of Japan, Environmental Engineering, No. 3, pp. 13-18, 1981

The above-mentioned Q value is a typical thermal performance index of a building, and the government's housing performance display system uses a heat loss coefficient (hereinafter referred to as a design Q value) calculated based on design books. It is considered good to judge the grade.
However, it has been found that the heat insulating performance of a building is determined not only by the performance and thickness of the heat insulating material but also by the construction method, the construction situation, and the airtight performance.
Therefore, since the actual Q value of the building after construction cannot be measured with the design Q value, if the measured Q value in the building after construction can be obtained, it is more accurate by using it together with the design Q value. It can be used as a high thermal performance index.

  The present invention has been made in view of such circumstances. The building is made into one room (room temperature in each room is uniform), and the Q value of the building after construction is easily calculated and combined with the design Q value. Accordingly, an object of the present invention is to provide a Q-value measuring system, a Q-value measuring method, and a Q-value measuring program capable of performing relative evaluation of the Q value of a building.

  The Q-value analysis system of the present invention considers a building as one room, expresses the building with a thermal resistance and a heat capacity, and uses a thermal circuit model that indicates the heat exchange relationship between the inside and the outside of the building. A Q value analysis system for analyzing a Q value that is a heat loss coefficient, and a product of a calorific value and a room temperature response coefficient with respect to the calorific value as a product of a disturbance temperature and a room temperature response coefficient with respect to the disturbance. The room temperature of the room determined by an arbitrary disturbance and an arbitrary heat generation is calculated by using a plurality of coefficients including a disturbance and a total heat flow resistance between the rooms as an undetermined coefficient. And calculating the predicted room temperature while adjusting the undetermined coefficient of the predicted room temperature calculating unit for identifying a plurality of undetermined coefficients that minimize the mean square error between the measured room temperature and the predicted room temperature, and the identified total heat flow Total floor area of the building to resistance A Q value calculating unit that multiplies and outputs the reciprocal of the multiplied numerical value as a Q value, wherein the predicted room temperature calculation unit identifies the undetermined coefficient in time series, and the Q value calculation unit performs time series Q A value is calculated, and a range ΔQ value in which the mean square error of the Q value in a measurement range measured in time series is not more than a preset threshold value is obtained, and the Q value at which this ΔQ value is the minimum value is calculated. A Q value analysis system characterized in that the Q value is output as a Q value.

  The Q value analysis system of the present invention sets an initial value for a power coefficient that should be a power of an exponential distribution that is one of the undetermined coefficients, which is a coefficient indicating a response of thermal change with respect to a temperature measurement period. An average error comparison unit that sequentially changes the coefficient, and the predicted room temperature calculation unit sets the power to be constant at a set value and adjusts other undecided coefficients to minimize the mean square error. A coefficient is identified, the mean square error obtained immediately before by the mean error comparison unit is compared with the current mean square error, and an undetermined coefficient for obtaining a Q value is identified.

  In the Q value analysis system of the present invention, in the comparison between the mean square error obtained immediately before by the mean error comparison unit and the current mean square error, when the last mean square error is smaller, the previous undetermined coefficient is calculated. When the obtained Q value is an analysis result and is equal to or larger than the immediately preceding mean square error, the power coefficient is changed, and the minimum value of the mean square error is set again with the power coefficient changed to the predicted room temperature calculation unit. The present invention is characterized in that the current mean square error is compared with the previous one.

  In the Q value analysis method of the present invention, a building is regarded as one room, the building is expressed by a thermal resistance and a heat capacity, and a thermal circuit model indicating a heat exchange relationship between the inside and the outside of the building is used. A Q-value analysis method using a Q-value analysis system for analyzing a Q-value, in which an expected room temperature calculation unit adds a calorific value and a room temperature with respect to the calorific value to a product of a disturbance temperature and a room temperature response coefficient with respect to the disturbance. This is a configuration that adds the product of the response coefficient and the response coefficient, and is determined by an arbitrary disturbance and an arbitrary heat generation in a calculation formula in which a plurality of coefficients including the disturbance and the total heat flow resistance between the rooms are undetermined coefficients. The room temperature of the room is calculated as an estimated room temperature while adjusting the plurality of undetermined coefficients, and an expected room temperature calculation process for identifying a plurality of undetermined coefficients that minimize the mean square error between the measured room temperature and the predicted room temperature; Before the Q value calculator is identified A Q value calculation step of multiplying the total heat flow resistance by the total floor area of the building and outputting the reciprocal of the multiplied value as a Q value, and the predicted room temperature calculation unit identifies the undetermined coefficient in time series The Q value calculation unit calculates a Q value in time series, and sequentially obtains a range ΔQ value in which the mean square error of the Q value in a measurement range measured in time series is equal to or less than a preset threshold value. The Q value having the minimum value is output as the Q value of the analysis result.

The program of the present invention regards a building as one room, expresses the building by heat resistance and heat capacity, and calculates the Q value of the building by a thermal circuit model indicating the heat exchange relationship between the inside and outside of the building. A program for causing a computer to execute the operation of the Q value analysis system to be analyzed,
The predicted room temperature calculation unit is configured to add the product of the calorific value and the room temperature response coefficient to the calorific value to the product of the disturbance temperature and the room temperature response coefficient to the disturbance. Calculates the room temperature of the room determined by any disturbance and any heat generation as the expected room temperature while adjusting the plurality of undecided coefficients, using a calculation formula with a plurality of coefficients including the total heat flow resistance as undecided coefficients. And an estimated room temperature calculation process for identifying a plurality of undetermined coefficients that minimize the mean square error between the measured room temperature and the predicted room temperature, and a Q value calculation unit adds the identified heat flow resistance to the floor of the building A Q value calculation process of multiplying the total area and outputting the reciprocal of the multiplied numerical value as a Q value, wherein the predicted room temperature calculation unit identifies the undetermined coefficient in time series, and the Q value calculation unit Q value was calculated in time series and sequentially measured in time series This is a computer-readable program for obtaining a range ΔQ value in which the mean square error of the Q value in a fixed range is less than or equal to a preset threshold value, and outputting the Q value at which the ΔQ value is the minimum value as the Q value of the analysis result. .

  As described above, according to the present invention, the temperature in each room in the building is made uniform, the building is regarded as one room, the room temperature is raised while keeping the temperature in each room uniform, The temperature obtained from the calorific value is obtained from the measured temperature and the calorific value in order to obtain the Q value in the range where the ΔQ value, which is the Q value range where the predicted residual is equal to or less than the set value, as the measured Q value. The Q value can be calculated with high accuracy by selecting a Q value in a range where there is little variation with temperature.

In addition, according to the present invention, as described above, the Q value of the building after construction can be easily calculated, so the outline of the building, specifications, drawings (plan view of each floor, cross-section details), etc. Unlike the Q value calculated by the method indicated in the energy saving standards, the Q value error due to the design change or construction method is eliminated, and the effective Q value of the building can be measured. It becomes possible and can be used as an index of relative evaluation of each building with high accuracy.
The effect is obtained.

  The present invention is a Q value analysis system that calculates a Q value that is a thermal performance index of a building. A heating element such as a heater that radiates heat energy is arranged in each room of a building, The air is agitated to diffuse the thermal energy in the building, and the temperature of each room in the building is always equalized, so that the entire building is regarded as one room. The Q value is calculated in time series using the room temperature of this room, and the difference between the room temperature measured by the thermometer at that time and the room temperature calculated from the thermal circuit model based on the heat generation amount is minimal. The Q value that minimizes the ΔQ value that is the range of the Q value that is a preset difference is output as an analysis result in a region where the difference is minimum.

First, calculation formulas used for Q value analysis in the present invention will be described in the following order of Q value analysis algorithms.
FIG. 1 shows that the entire building is regarded as one container (ie, a room), and the difference between the temperature inside the container and the outside temperature increased due to heat generation inside the container due to the thermal resistance of the material of the wall forming the container. Correspondingly, it is a conceptual diagram illustrating a thermal circuit model showing that thermal energy is transmitted through the wall of the container by the thermal resistance and discharged to the outside of the container.

That is, as described above, if one building is regarded as one room and a heating element having a heating value H is present inside the room as in the thermal circuit model shown in FIG. Is obtained by calculating an increase in the room temperature (temperature at which the room temperature of each room of the building is equalized), thereby obtaining the phase heat flow resistance R, that is, obtaining the heat flow rate of the entire building, and calculating the heat flow rate of the building. The product divided by the total floor area is calculated as the Q value.
Here, modeled by the thermal circuit of FIG, applying Kirchhoff's law, the following (1) equation is obtained, a differential equation relating to rt theta _R. Equation (1) is solved under appropriate conditions, and the step response of room temperature (measured by an indoor thermometer 102 described later) due to disturbance θ _E and the step response of room temperature due to heat generation H are obtained.

For example, if the heat generation amount H is constant at time t> 0, such as a step function, dH / dt = 0 on the right side of the above equation (1).
The change in the calorific value is eliminated from the equation, and the following equation (2) is obtained.

Since this differential equation becomes a variable separation type if the disturbance θ _E is constant at time t> 0, θ _R can be solved as in the following equation (3).

In other words, room temperature is considered to be a combination of response to the disturbance (excitation) given to the outside of the wall (excitation) and response to the room heat generation (excitation) (endothermic response). An analytical solution of the partial differential equation of 1) is obtained by Laplace transform, and a solution of a through-flow response and an endothermic response is obtained according to this analytical solution (2).
Here, θ _i = initial room temperature (room temperature at t = 0), R = R ₁ + R ₂ , and λ = 1 / (C · R ₁ ). Furthermore, equation (3) takes a simpler form under the following simple conditions.
Further, based on the solution of the unit flow-through response, the flow-through response when the excitation is an isosceles triangular wave is obtained by integration or the like. Similarly, based on the solution of the unit endothermic response, the endothermic response when the excitation is a rectangular wave is obtained.
a. When the disturbance is a step function In the equation (3), θ _E = 1, θ _i = 0, and H = 0 are sufficient.
The following expression (4) is a “unit flow response” in the thermal circuit model.

b. When the calorific value is a step function In equation (3), θ _E = 0, θ _i = b ₀ -b, H = 1, R = b ₀ can be used. “Unit endothermic response”.

Next, a prediction formula for room temperature by the response coefficient method will be described.
By using the unit responses given by the equations (4) and (5), the response coefficient φ _i and the heat generation when the disturbance θ _E is an isosceles triangular wave as shown in the following equation (6) are rectangular waves. In this case, the response coefficient ψ is obtained. However, when a response to an isosceles triangular wave is obtained, integration of a unit response or the like is necessary, but the explanation thereof is omitted because it is general. Given the disturbance theta _E Synthesis of a number of isosceles triangle, the disturbance component of the room temperature theta _R is represented by the convolution of the flow response (convolution). Similarly, if room heat generation is considered to be a combination of a large number of rectangular waves, a heat generation component at room temperature is represented by a product of endothermic responses.

In the above equation (6), the suffix j is the order when the time is discretized, and is defined as j = −∞,..., −1, 0,.
Δt is a time interval at that time (for example, a temperature measurement cycle), and is r = e ^−λΔt (a coefficient indicating a response to a thermal change in the temperature measurement cycle). As described above, the room temperature for an arbitrary disturbance and an arbitrary heat generation is obtained by adding the combined product of H and ψ to the combined product of θ _E and φ _i. For example, if the room temperature at t = nΔt) is θR _{, n} , the following equation (7) is obtained. The calorific value H used here is a total value obtained by adding the calorific values measured in each measurement unit unit for each measurement period. r ^j is a power of a coefficient r that is an exponential distribution indicating a response of thermal change to the temperature measurement period.

  By substituting the obtained equation (7) into the equation (6), the equation is transformed into a form that does not include disturbance since the start of measurement (ie, j <0). Further, in consideration of H = 0 when j <0, finally, the disturbance is expressed by the combination of the outside air temperature and the external radiation component as in the following equation (8).

By expressing the outside air temperature and the external radiation component as in the above equation (8), the prediction equation shown in the following equation (9) of the room temperature used in this actual measurement method can be obtained.
In this equation (8), θ ₀ measured by an outdoor thermometer (outdoor thermometer 101 described later) is an outside air temperature, and Δθ is a measured temperature of a horizontal SAT (equivalent outside air temperature) meter (SAT thermometer 103 described later). This is a value obtained by subtracting the outside temperature θ ₀ , and a is an undetermined coefficient indicating the degree of influence of external radiation (sunlight and nighttime radiation).

In the present embodiment, external radiation is handled with the simplest configuration as in the above equation (8), and α is simply defined as a statistically determined coefficient.
That is, the undetermined coefficient is set so that the root mean square of the difference between the predicted room temperature θ _{R, n} and the measured room temperature θ _{R, n} ^* given by the above equation (9) is minimized. Identify (least squares). Here, the average residual δ is expressed by equation (10) as shown below.

The four unknown coefficients (r, b ₀ , b, a) in equation (9) are fitted (identified) by numerical analysis so that the numerical value of δ shown in equation (10) is minimized (least square method). ) To determine the Q value.

Next, a Q value analysis system for calculating a Q value using the above-described Q value analysis algorithm will be described with reference to FIG. FIG. 2 is a block diagram illustrating a configuration example of the Q-value analysis system 1 according to the present embodiment.
In FIG. 2, the Q value analysis system 10 includes a time series data acquisition unit 1, an estimated room temperature calculation unit 2, a storage unit 3, an average residual comparison unit 4, and a Q value calculation unit 5.
The time-series data acquisition unit 1 reads the room temperature, the outside air temperature, the corresponding outside air temperature, and the heat generation amount of the heating element in the building necessary for analyzing the Q value as described later for each Q value analysis cycle, It writes in the memory | storage part 3 and memorize | stores it for every time of a period.

The predicted room temperature calculation unit 2 calculates the predicted temperature θ _R of the room temperature for each analysis period of the Q value according to the above equation (9) consisting of the outside air temperature, the equivalent outside air temperature, and four undetermined coefficients (r, b ₀ , b, a). _{, N} is a numerical value in which the undetermined coefficient r of the four undetermined coefficients (r, b ₀ , b, a) is assumed to be within the range of 0 <r <1, and the undetermined coefficient (b ₀ , b, a) is The undetermined coefficient (b ₀ , b, a) is obtained by sequentially changing and fitting so that the expected residual δ is minimized in Equation (10), and this expected residual δ is set as the minimum value in the current step. Then, it is written and stored in the storage unit 3.

The average residual residual comparison unit 4 compares δ output from the least square calculation unit 4 at the current step with δ ^{* at} the step immediately before reading from the storage unit 3, and if δ ^* > δ, the undetermined coefficient By changing r, the predicted room temperature calculation unit 2 calculates δ again. On the other hand, if δ ^* ≦ δ, δ ^* is output as the minimum δ.
When the undetermined coefficient b ₀ is obtained, the Q value calculating unit 5 calculates the Q value by using the following equation (11) based on the undetermined coefficient b ₀ and the sum A of the floor area of the building. Every time, it is written and stored in the storage unit 3.

Next, the Q value calculation process of the Q value analysis system 1 of FIG. 2 will be described with reference to FIG. FIG. 3 is a flowchart showing the operation of the Q value calculation process of the Q value analysis system 1.
Here, as can be seen from the above equation (9), since r appears as a power here, a method slightly different from a general least square method is used in this embodiment.
In step S1, the time series data acquisition unit 1 measures the room temperature, the outside temperature, the SAT temperature, and the calorific value in the analysis cycle of the Q value, writes them in the storage unit 4 in time series for each analysis cycle, and necessary data To get.

  In step S2, the average residual comparison unit 5 determines the value of r (where 0 <t <1, r is a positive value close to 0 (eg, 0.0001) or 1 close to 1 in the first step). It is set on the assumption that the value is less than 0.9999.

Next, in step S3, the predicted room temperature calculation unit 2 calculates the average room temperature δn using equation (10) in step S4 while calculating the room temperature using equation (9). Three undetermined coefficients (b ₀ , b, a) are obtained by numerical calculation using a general least square method so as to be minimized.

In step S5, the average residual comparison unit 5 compares the calculated average residual δ _n with the residual δ _n−1 obtained immediately before, and the average residual δn is greater than the average residual δn−1. If it is larger, the process proceeds to step S6. On the other hand, if the average residual δn is equal to or smaller than the average residual δn-1, it is considered that δ _n-1 one step before is minimum, and the undetermined value in the step at that time The coefficients (b ₀ , b, a) are used as identification values, and the process proceeds to step S7.

  In step S7, the average residual comparison unit 5 changes the numerical value of r by a set numerical value (for example, 0.0001), and returns the process to step S3. For example, when r is a positive numerical value close to 0, the initial value is increased by the above numerical value. On the other hand, when r is a positive numerical value close to 1, the initial value is decreased.

In step S <b> 6, the Q value calculation unit 5 calculates the Q value identified by actual measurement in the field from the above equation (11) using the identified undetermined coefficient b ₀ (that is, total heat flow resistance).
In the above equation (11), A is the total floor area of the building. Further, symbols used in the expressions (1) to (11) are shown below.

The room temperature, outside air temperature, equivalent outside air temperature (horizontal surface SAT meter temperature), and calorific value used in the above-described Q value analysis are obtained as data as shown in FIG.
FIG. 4 shows an outdoor thermometer 101 that measures the outdoor temperature, an indoor thermometer 102 that measures the room temperature in the building, a SAT thermometer 103 that measures the equivalent outdoor temperature composed of the SAT meter 103a and the thermometer 103b, It is a conceptual diagram which shows arrangement | positioning with the apparatus which measures the emitted-heat amount of the heat generating body 200 in a building.
For example, the outdoor thermometer 101 is arranged at a height of 1.2 m in the shaded area on the north side of the outdoor, the indoor thermometer 102 is arranged at a height of 1.2 m using a glove thermometer, and the SAT thermometer 103 is outdoor. It is arranged at a height of 4m in a sunny place on the south surface, and each temperature data is acquired at every temperature measurement cycle, and obtained by the flow already described. An arbitrary time point n in the above formula corresponds to a time point in each time series of the temperature measurement cycle.

The measured value of the heat loss coefficient identified and obtained as described above (hereinafter referred to as measured Q value) is a simple thermal circuit as shown in FIG. When applied to a phenomenon obtained from a model, it is interpreted as a statistically estimated numerical value.
For this reason, there is no mathematical correctness in the Q value in this embodiment, and it is evaluated with the obtained actual Q value how much the identified actual Q value is certain. It is necessary to show.

In the present embodiment, the certainty of the measured Q value is indicated by a ΔQ value. The ΔQ value is shown in FIG. 5 in which the horizontal axis indicates the Q value and the vertical axis indicates the average residual δ when the Q value is obtained. In FIG. 5, the minimum average residual δ _min and the average residual δ _The Q value range (Q value change width) having δ within a numerical value range 0.1K larger than _min is obtained as ΔQ.
Therefore, this ΔQ value is a numerical value indicating the kurtosis of the Q value in the vicinity of the average residual δ _min (coefficient of excess) in the function of the Q value and the average residual δ. It can be determined that the smaller the is, the more likely the measured Q value identified is.

As shown in FIG. 5, when creating a graph showing the change of δ with respect to the actual Q value, the Q value calculation unit 5 changes the Q value (that is, b ₀ ) slightly from the identification value, and the average residual at that time δ is calculated by equation (9). However, when the Q value is changed, an undetermined coefficient (r, b, a) other than b ₀ is calculated and the average residual δ is calculated so that the average residual δ is minimized at the changed Q value. To do.
In the present embodiment, this ΔQ value is used as an index for determining whether or not the measurement period is sufficiently long. That is, the Q value is always assumed within a certain measurement period, but changes with the length of the measurement period. Therefore, there is a problem that if the identification is performed at any time point (measurement period), the measurement period is sufficient and the identification result is likely.
Therefore, as described above, in the present embodiment, it is determined that the most probable Q value is obtained when the ΔQ value is minimized when the measurement period is gradually increased, and this ΔQ is obtained. The Q value with the smallest value is set as the actual Q value, and is output as the analysis result.

Next, FIG. 6 shows a graph in which the heat loss coefficient (hereinafter referred to as the calculated Q value) obtained by correcting the design Q value with the building conditions at the time of actual measurement is associated with the actual Q value. Here, the horizontal axis of the graph of FIG. 6 indicates the calculated Q value, and the vertical axis indicates the actually measured Q value. The dotted line indicates the inclination “1”, and the solid line indicates the correspondence between the calculated Q value and the actually measured Q value. Here, the square marks indicate the buildings built by the conventional wooden frame construction method, the circle marks indicate the framed wall method, and the diamond marks indicate the steel frame ramen method.
In the solid line in the figure, if the vertical axis is y and the horizontal axis is x, a straight line represented by the equation y = p · x + q is obtained. The coefficients p and q in this equation are obtained from actual measurement and change depending on the number of building samples, for example, p = 0.6184 and q = 0.4522.
In this graph, it can be seen that the measured Q value is relatively in agreement with the calculated Q value in a building having a high thermal insulation performance with a calculated Q value of 2 W / (m ² · K) or less.
In addition, as the calculated Q value becomes larger than ² W / (m ² · K) (insulation performance decreases), the measured Q value tends to be slightly lower than the calculated Q value. It turns out that a close numerical value is obtained.
From the results described above, it can be seen that the Q value analysis system according to the present embodiment can obtain the measured Q value with a numerical value that does not deviate so much from the calculated Q value.
As a result, it is possible to compare the relative Q value of each building after construction by measuring the actual Q value of the actual building after construction and combining the actual Q value and the calculated Q value. .

  Note that a program for realizing the function of the Q value analysis system in FIG. 2 is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read into the computer system and executed to measure Q. A value calculation process may be performed. Here, the “computer system” includes an OS and hardware such as peripheral devices. The “computer system” includes a WWW system having a homepage providing environment (or display environment). The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Further, the “computer-readable recording medium” refers to a volatile memory (RAM) in a computer system that becomes a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. In addition, those holding programs for a certain period of time are also included.

  The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

It is Blocks which shows the example of a structure of the Q value measurement system by one Embodiment of this invention. It is a block diagram which shows the structural example of the Q value measurement process part 10 in FIG. It is a block diagram which shows the structural example of the measurement unit control part 11 in FIG. It is a flowchart which shows the flow of Q value measurement using the Q value measurement system 1 of FIG. It is a conceptual diagram which shows the input screen of the building data (Measurement outline data of the building which measures actual Q value) which the control part 105 of FIG. 2 displays on the display part 104. FIG. It is a conceptual diagram which shows the input screen of the building data (Building outline data of the building which measures actual Q value) which the control part 105 of FIG. 2 displays on the display part 104. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Time series data acquisition part 2 ... Expected room temperature calculation part 3 ... Memory | storage part 4 ... Average residual comparison part 5 ... Q value calculation part 10 ... Q value analysis system 101 ... Outdoor thermometer 102 ... Indoor thermometer 103 ... SAT temperature Total 103a ... SAT total 103b ... Thermometer 200 ... Heating element 500 ... Building

Claims (5)

Considering a building as one room, the building is expressed by heat resistance and heat capacity, and the Q value, which is the heat loss coefficient of the building, is analyzed by a thermal circuit model showing the heat exchange relationship between the inside and outside of the building Q-value analysis system that
This is a configuration in which the product of the heat generation amount and the room temperature response coefficient for the heat generation amount is added to the product of the temperature of the disturbance and the room temperature response coefficient for the disturbance, and includes the total heat flow resistance between the disturbance and the room. The room temperature determined by an arbitrary disturbance and arbitrary heat generation is calculated as an estimated room temperature while adjusting the plurality of undetermined coefficients in a calculation formula using a plurality of coefficients as undetermined coefficients. And a predicted room temperature calculation unit for identifying a plurality of undetermined coefficients that minimize the mean square error between the predicted room temperature and the predicted room temperature,
A Q value calculating unit that multiplies the identified total heat flow resistance by the sum of the floor area of the building, and outputs a reciprocal of the multiplied value as a Q value;
The predicted room temperature calculation unit identifies the undetermined coefficient in time series, the Q value calculation unit calculates the Q value in time series, and the mean square error of the Q value in the measurement range measured in time series in advance A Q value analysis system characterized by obtaining a range ΔQ value that is equal to or less than a set threshold value and outputting a Q value at which the ΔQ value is a minimum value as a Q value of an analysis result. An average error comparison unit that sets an initial value for a power coefficient that should be a power of an exponential distribution that is one of the undetermined coefficients, and that sequentially changes the power coefficient, which is a coefficient indicating a thermal change response to a temperature measurement cycle. Further comprising
The predicted room temperature calculation unit makes the power constant at a set value, adjusts other undetermined coefficients to identify other undetermined coefficients that minimize the mean square error, and the average error comparison unit obtains immediately before 2. The Q value analysis system according to claim 1, wherein the mean square error is compared with a current mean square error to identify an undetermined coefficient for obtaining a Q value.   In the comparison between the mean square error obtained immediately before by the mean error comparison unit and the current mean square error, if the immediately preceding mean square error is smaller, the Q value obtained from the immediately-preceding coefficient is used as the analysis result, If it is equal to or greater than the previous mean square error, the power coefficient is changed, and the predicted room temperature calculation unit again determines the minimum value of the mean square error with the changed power coefficient, and the previous and current mean square errors are obtained. The Q value analysis system according to claim 2, wherein an error is compared. A Q-value analysis system that considers a building as one room, expresses the building with thermal resistance and heat capacity, and analyzes the Q-value of the building by a thermal circuit model that indicates the heat exchange relationship between the inside and the outside of the building Q value analysis method using
The predicted room temperature calculation unit is configured to add the product of the calorific value and the room temperature response coefficient to the calorific value to the product of the disturbance temperature and the room temperature response coefficient to the disturbance. Calculates the room temperature of the room determined by any disturbance and any heat generation as the expected room temperature while adjusting the plurality of undecided coefficients, using a calculation formula with a plurality of coefficients including the total heat flow resistance as undecided coefficients. A predicted room temperature calculation process for identifying a plurality of undetermined coefficients that minimize the mean square error between the measured room temperature and the predicted room temperature;
A Q-value calculating unit that multiplies the identified total heat-flow resistance by the total floor area of the building and outputs a reciprocal of the multiplied value as a Q-value;
The predicted room temperature calculation unit identifies the undetermined coefficient in time series, the Q value calculation unit calculates the Q value in time series, and the mean square error of the Q value in the measurement range measured in time series in advance A Q value analysis method characterized in that a range ΔQ value that is equal to or less than a set threshold is obtained, and a Q value at which the ΔQ value is a minimum value is output as a Q value of an analysis result. A Q-value analysis system that considers a building as one room, expresses the building with thermal resistance and heat capacity, and analyzes the Q-value of the building by a thermal circuit model that indicates the heat exchange relationship between the inside and the outside of the building Is a program that causes a computer to execute the operation of
The predicted room temperature calculation unit is configured to add the product of the calorific value and the room temperature response coefficient to the calorific value to the product of the disturbance temperature and the room temperature response coefficient to the disturbance. Calculates the room temperature of the room determined by any disturbance and any heat generation as the expected room temperature while adjusting the plurality of undecided coefficients, using a calculation formula with a plurality of coefficients including the total heat flow resistance as undecided coefficients. A predicted room temperature calculation process for identifying a plurality of undetermined coefficients that minimize the mean square error between the measured room temperature and the predicted room temperature;
A Q-value calculating unit that multiplies the identified total heat flow resistance by the total floor area of the building, and outputs a reciprocal of the multiplied value as a Q-value;
The predicted room temperature calculation unit identifies the undetermined coefficient in time series, the Q value calculation unit calculates the Q value in time series, and the mean square error of the Q value in the measurement range measured in time series in advance A computer-readable program that obtains a range ΔQ value that is less than or equal to a set threshold and outputs the Q value at which the ΔQ value is a minimum value as the Q value of the analysis result.

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