Determination device, determination method and determination program

Abstract

To properly determine an abnormal state of air conditioning equipment other than failure conditions set beforehand.SOLUTION: A determination device 100 includes a collection part 121, a characteristic value calculation part 122, a difference calculation part 123, and a determination part 124. The collection part 121 collects data regarding the indoor environment where air conditioning equipment is installed in each of a plurality of designated periods. The characteristic value calculation part 122 performs a simulation of the indoor environment respectively based on data in each period collected by the collection part 121, and calculates the characteristic value from the simulation result in each period. The difference calculation part 123 calculates a difference between a characteristic value in each period calculated by the characteristic value calculation part 122 and a value contained in the data regarding the indoor environment in each period collected by the collection part 121 respectively for the corresponding time with each other in the plurality of periods. The determination part 124 determines the abnormality of the air conditioning equipment based on the distribution of differences calculated by the difference calculation part 123.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a determination device, a determination method, and a determination program. [Background technology]

[0002] In recent years, as buildings have become larger, many air conditioning units are installed in one building, and the burden of operation and management work has increased. In such a situation, if a malfunction or defect occurs in the air conditioning equipment of a building and the abnormality is not discovered and dealt with quickly, it will cause the indoor environment to deteriorate, waste energy, and increase costs, so it is necessary to take action immediately.

[0003] Traditionally, when it comes to air conditioning malfunctions or breakdowns, people have primarily identified discrepancies between set values ​​and measured values ​​and visually inspected the equipment. However, when it comes to equipment located within a tenant, it is difficult for a manager to enter the premises to inspect, so it is necessary to identify the cause of the problem by some means other than visual inspection.

[0004] Therefore, a technology has been proposed that sets failure conditions in advance, and uses the results of simulating those failure conditions and the results of simulating normal conditions to establish criteria that can distinguish between normal and abnormal conditions, thereby determining abnormal conditions that may indicate a failure or malfunction in the air conditioning equipment (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2004-234302 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, the conventional technology has a problem in that it may not be possible to appropriately determine abnormal conditions of the air conditioning equipment other than the preset failure conditions. For example, the conventional technology detects failures only in the failure conditions of the air conditioning equipment process that are assumed in advance, and has a problem in that it cannot determine the discrepancy between the set temperature and the measured temperature caused by insufficient capacity of the equipment relative to the load due to changes in the internal load, differences in the surrounding environment, etc. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the object, the judgment device of the present invention is characterized by having a collection unit that collects data regarding the environment in a room in which an air conditioning equipment is installed for each of a plurality of specified periods; a characteristic value calculation unit that performs a simulation of the indoor environment based on the data for each period collected by the collection unit and calculates a characteristic value from the simulation results for each period; a difference calculation unit that calculates, for corresponding times in the plurality of periods, the difference between the characteristic value for each period calculated by the characteristic value calculation unit and the value included in the data regarding the indoor environment for each period collected by the collection unit; and a judgment unit that judges an abnormality in the air conditioning equipment based on the distribution of the differences calculated by the difference calculation unit. Effect of the Invention

[0008] According to the present invention, it is possible to appropriately determine an abnormal state of an air conditioning equipment other than a preset failure condition. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing an overview of an abnormality determination system including a determination device according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of a determination device according to an embodiment. [Diagram 3] FIG. 3 is a diagram showing a specific example of data stored in the determination device according to the embodiment. [Figure 4]FIG. 4 is a diagram illustrating an example of target selection according to the embodiment. [Diagram 5] FIG. 5 is a diagram showing a specific example of a process performed by the determination device according to the embodiment. [Figure 6] FIG. 6 is a diagram showing a specific example of an image output by the determination device according to the embodiment. [Figure 7] FIG. 7 is a flowchart illustrating an example of a processing procedure of the determination device according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of a determination device, a determination method, and a determination program according to the present application will be described in detail with reference to the drawings. Note that the determination device, the determination method, and the determination program according to the present application are not limited to the embodiments.

[0011] 1. Introduction First, an overview of a system including a determination device 100 according to this embodiment will be described. Fig. 1 is a diagram showing an overview of an abnormality determination system including a determination device according to this embodiment.

[0012] 1, the determination device 100 is connected to an air conditioning system monitoring device 200 and a temperature sensor 300 by wire or wirelessly, and transmits and receives information to and from them. The air conditioning system monitoring device 200 is also connected to air conditioning systems 210 and 220. Note that, in the example of FIG. 1, the air conditioning system monitoring device 200 is connected to two air conditioning systems, but this is not limiting, and the number of air conditioning systems can be increased or decreased as desired.

[0013] Moreover, the air conditioning system 210 has an air conditioner 211, and a VAV (Variable Air Volume) 212 and a VAV 215 connected to the air conditioner 211. The VAV 212 is connected to an indoor temperature sensor 213, and corresponds to the air outlets 214-1 to 214-n. Similarly, the VAV 215 is connected to an indoor temperature sensor 216, and corresponds to the air outlets 217-1 to 217-n. Moreover, the configuration of the air conditioning system 220 beyond the air conditioner 221 is similar to that of the air conditioning system 210. Note that the configuration of the air conditioning system is not limited to the configuration shown in FIG. 1, and it is assumed that the number of air conditioners and the number of VAVs can be increased or decreased as desired.

[0014] The determination device 100 is a server device that receives indoor temperature measurements, VAV supply air volume, floor radiant temperature, etc. from the air conditioning system monitoring device 200 and the temperature sensor 300 and pre-stores the information as historical data, and is realized by a PC (Personal Computer), a cloud system, etc.

[0015] The determination device 100 collects data on the environment in a room in which an air conditioning device is installed for each of a plurality of specified periods, performs a simulation of the indoor environment based on the collected data for each period, and calculates a characteristic value from the simulation result for each period. The determination device 100 then calculates the difference between the calculated characteristic value for each period and the value included in the data on the indoor environment for each period for corresponding times in the plurality of periods, and determines an abnormality in the air conditioning device based on the distribution of the calculated differences.

[0016] The determination device 100 first collects data on the indoor environment in which the air conditioning equipment is installed for each of a plurality of designated periods. For example, the determination device 100 collects data on the indoor environment, such as the indoor temperature of a part of the target area in which the VAV is installed (hereinafter also referred to as the target) for each of a plurality of designated periods (hereinafter also referred to as the evaluation target periods), such as July of this year and July of last year, and the like (hereinafter also referred to as the evaluation target periods).

[0017] Next, the determination device 100 performs a simulation of the indoor environment based on the collected data for each period, and calculates characteristic values ​​from the simulation results for each period. For example, an input data set for CFD (Computational Fluid Dynamics) is created from the data for each period and each target, and CFD is performed using the data to calculate characteristic values ​​for each period and each target.

[0018] Then, for corresponding times in the multiple periods, the determination device 100 calculates the difference between the calculated characteristic value for each period and the value included in the data on the indoor environment for each period. For example, for each target, the determination device 100 calculates the difference between the characteristic value and the actual measured value of the indoor environment for each date for July of last year and July of this year.

[0019] Thereafter, the determination device 100 determines an abnormality in the air conditioning equipment based on the distribution of the calculated differences. For example, the determination device 100 statistically compares the difference data for July of last year with the difference data for July of this year for each target, and determines that the VAV of the target is abnormal if there is a significant difference between the data for the two periods.

[0020] The air conditioning system monitoring device 200 monitors the control status of air conditioning equipment such as air conditioners 211 and VAVs 212 belonging to each air conditioning system. The air conditioning system monitoring device 200 then transmits information about the indoor environment, such as the supply air volume of each VAV and the temperature of each target, to the determination device 100.

[0021] The air conditioner 211 is an air conditioning facility composed of, for example, a cooling coil, a heating coil, and a blower, and its operation is monitored by the air conditioning system monitoring device 200. In addition, conditioned air blown out by the air conditioner 211 and the air conditioner 221 is supplied to each area via an air supply duct. The VAV 212 and the VAV 215 are air conditioning facilities that control the amount of conditioned air taken in from the air conditioner 211 so as to eliminate the air conditioning load of each zone. In addition, the VAV 212 and the VAV 215 adjust the amount of air supplied from each air outlet by controlling the opening degree of the damper.

[0022] The indoor temperature sensor 213, the indoor temperature sensor 216, and the temperature sensor 300 are measuring devices that measure nearby temperatures, and measure not only the indoor temperature but also the radiant temperatures of the walls, ceiling, and floor. The temperatures measured by each temperature sensor are transmitted to the determination device 100 together with the time of measurement, etc.

[0023] 2. Configuration of Determination Device 100 Next, the configuration of the determination device 100 shown in Fig. 1 will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the determination device according to the embodiment. As shown in Fig. 2, the determination device 100 according to the embodiment includes a communication unit 110, a control unit 120, and a storage unit 130.

[0024] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to each of the air conditioning system monitoring device 200 and the temperature sensor 300 by wire or wirelessly, and transmits and receives information.

[0025] The storage unit 130 is realized by a storage device such as a RAM (Random Access Memory) or a hard disk. The storage unit 130 stores data and programs necessary for various processes by the control unit 120, and includes a history data storage unit 131, a characteristic value data storage unit 132, a difference data storage unit 133, and a judgment data storage unit 134 as units closely related to the present invention.

[0026] The history data storage unit 131 stores data on past indoor environments that are used in the determination process described below. For example, the history data storage unit 131 stores data on indoor environments, such as the supply air temperature, VAV air volume, indoor temperature, radiant temperature of the floor, and the number of people present in the room, at any time in the past, as time-series data for each date and time. Note that the data on the indoor environment may be stored in advance before the process of the determination device 100 is performed.

[0027] The characteristic value data storage unit 132 stores the characteristic values ​​calculated by the characteristic value calculation unit 122 described later. For example, the characteristic value data storage unit 132 stores the characteristic values ​​such as the indoor temperature calculated by the characteristic value calculation unit 122 described later for each selected target.

[0028] The difference data storage unit 133 stores data on the difference between the characteristic value and the actual measurement value calculated by the difference calculation unit 123 described later. For example, the difference data storage unit 133 stores, for each target, the difference between the indoor temperature calculated as the characteristic value by simulation and the actual measurement value of the indoor temperature stored in the history data storage unit 131 for each date.

[0029] The determination data storage unit 134 stores the determination data generated by the determination unit 124 described later. For example, the determination data storage unit 134 stores a target for which the air conditioning equipment has been determined to be abnormal by the determination unit 124 described later, together with information about the VAV corresponding to the target (such as the location where the target is installed).

[0030] Here, a specific example of data stored in the history data storage unit 131 and data stored in the difference data storage unit 133 will be described with reference to Fig. 3. Fig. 3 is a diagram showing a specific example of data stored in the determination device according to the embodiment. Fig. 3(A) shows data stored in the history data storage unit 131, and Fig. 3(B) shows data stored in the difference data storage unit 133.

[0031] In the example of FIG. 3(A), for each date and time at regular intervals such as "2022 / 07 / 01 9:00" and "2022 / 07 / 01 10:00", actual measured values ​​of supply air temperature, VAV airflow, indoor temperature, etc. at the corresponding time are linked and stored. In the example of FIG. 3(B), for each target to be judged such as "target 1", for each date such as "07 / 01" and "07 / 02", the difference values ​​between the characteristic values ​​and actual measured values ​​for the specified periods of "23 / 07 (July 2023)" and "22 / 07 (July 2022)" are stored in order.

[0032] Returning to the description of Fig. 2, the control unit 120 is realized by a CPU (Central Processing Unit), MPU (Micro Processing Unit), or the like executing various programs stored in a storage device inside the determination device 100 using a RAM as a working area. The control unit 120 is also realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 120 has a collection unit 121, a characteristic value calculation unit 122, a difference calculation unit 123, and a determination unit 124, and may have a display unit 125 as necessary.

[0033] The collection unit 121 collects data on the environment in a room in which an air conditioning device is installed for each of a plurality of specified periods. For example, the collection unit 121 refers to information stored in the history data storage unit 131 and collects data such as the supply air temperature and VAV air volume for a target selected from the outside for each evaluation period. Here, the evaluation period may be any period set from the outside, or two or more data periods may be set. Note that since seasonal factors have a large impact on the indoor environment, it is desirable to set the evaluation period to a period of the same season, such as the same month of the previous year.

[0034] The above-mentioned targets will be described with reference to FIG. 4. FIG. 4 is a diagram showing an example of target selection according to the embodiment. In the example of FIG. 4, first, the entire floor is divided into four VAV controlled areas 1 to 4. Then, room temperature sensors (1) to (4) are installed in each VAV controlled area. In addition to the VAV controlled areas, the entire floor is divided into 3×10 cells as a target area for the CFD simulation results used in the characteristic value calculation unit 122 described later.

[0035] Under the above-mentioned circumstances, for each VAV controlled area, an arbitrary square within the area is selected as a target and linked to an indoor temperature sensor. For example, for "VAV controlled area 1," the square that contains "temperature sensor (1)" is selected as "target 1" and linked to "temperature sensor (1)." Similarly, for each of VAV controlled areas 2 to 4, targets 2 to 4 are selected and linked to the corresponding indoor temperature sensors.

[0036] In other words, a target is selected from any square in each VAV control area that is the subject of abnormality judgment, and is linked to the corresponding indoor temperature sensor. This allows the judgment device 100 to perform simulation and judgment processing for each target (for each VAV corresponding to the target) using the actual measurement value of the temperature sensor linked to each target.

[0037] The indoor temperature sensor may be the one used for VAV control, or a temperature sensor installed separately for measuring the indoor environment may be used. The target may be selected from the outside, taking into consideration the usage of the target floor, or the mass closest to the indoor temperature sensor may be automatically set. Furthermore, while FIG. 4 shows an example of selecting a target for one floor, the present invention is not limited to this, and each floor of the entire building may be the target of selection, or only one air conditioning system may be the target of selection.

[0038] Returning to the explanation of Fig. 2, the characteristic value calculation unit 122 performs a simulation of the indoor environment based on the data for each period collected by the collection unit 121, and calculates a characteristic value from the simulation result for each period. Furthermore, the characteristic value calculation unit 122 can perform a simulation by computational fluid dynamics using the data for each period collected by the collection unit 121 for one or more of the indoor temperature distribution, the indoor air volume distribution, the indoor air speed distribution, the indoor pollutant (e.g., carbon dioxide) concentration distribution, and the indoor humidity distribution.

[0039] For example, the characteristic value calculation unit 122 first creates data of boundary conditions used in calculations by CFD from the data notified by the aforementioned collection unit 121. Thereafter, the characteristic value calculation unit 122 calculates the indoor temperature distribution by CFD using, for example, the created data set, and stores the calculated temperatures, which are aggregated by target unit, in the characteristic value data storage unit 132 as characteristic values.

[0040] As a counting method, the characteristic value calculation unit 122 may calculate the average value of the CFD results in the target, or may use the maximum value. Furthermore, the target of the CFD simulation is not limited to the temperature distribution in the room, and elements representing the indoor environment such as the indoor air volume, wind speed, CO2, and humidity can be used.

[0041] Here, the CFD used by the characteristic value calculation unit 122 will be described. In this embodiment, the CFD performs a simulation by inputting information that affects the space (supply air temperature, air volume, radiation temperature, etc.) as boundary conditions, and visualizes conditions such as air volume, wind speed, CO2, humidity, and temperature distribution. In addition, since the information that affects the space (supply air temperature, air volume, radiation temperature, etc.) is input as boundary conditions, the CFD can obtain reproducible results that combine multiple conditions while taking into account these disturbance elements.

[0042] Furthermore, since CFD performs a simulation by inputting boundary conditions into an indoor model, if the boundary conditions are similar, the simulation results will also be similar, and the difference between the actual result and the simulation result will also be about the same. Therefore, the determination device 100 statistically compares the difference between the actual result and the simulation result for two periods with similar boundary conditions, and analyzes the distribution of the difference, thereby making it possible to determine that an abnormality has occurred in the equipment of the corresponding air conditioning system or the equipment of the corresponding indoor area.

[0043] The difference calculation unit 123 calculates, for corresponding times in a plurality of periods, the difference between the characteristic value for each period calculated by the characteristic value calculation unit 122 and the value included in the data related to the indoor environment for each period collected by the collection unit 121. For example, the difference calculation unit 123 refers to information stored in the history data storage unit 131 and the characteristic value data storage unit 132, calculates the difference between the characteristic value and the actual measured value at the same time in the evaluation period, and stores the difference in the difference data storage unit 133.

[0044] Here, the difference calculation unit 123 calculates, for each target, the difference between the characteristic value of the target and the actual measurement value of the temperature sensor linked to the target. Also, the difference calculation unit 123 may calculate the difference for each date (07 / 01...) of the evaluation period (July of this year: July of last year) (see FIG. 3(B)), or may calculate the difference for each arbitrary time of each date (07 / 01 9:00...).

[0045] That is, the interval for calculating the difference may be changed according to the evaluation period, for example, if the evaluation period is one month, the difference may be calculated for each day, and if the evaluation period is one day, the difference may be calculated for each hour. Note that, for example, when calculating the difference for each day, the difference calculation unit 123 may calculate the average value of the differences for each hour on the date as the difference for the date.

[0046] The determination unit 124 determines whether there is an abnormality in the air conditioning equipment based on the distribution of the differences calculated by the difference calculation unit 123. For example, the determination unit 124 determines whether there is a significant difference by referencing the information stored in the difference data storage unit 133 and statistically comparing multiple pieces of difference data for the evaluation period. The determination unit 124 then determines that the VAV in the VAV control area corresponding to the target determined to have a significant difference is abnormal, and stores information such as the installation area of ​​the VAV determined to be abnormal in the determination data storage unit 134.

[0047] In addition, the judgment unit 124 may judge whether there is an abnormality in the air conditioning equipment by using a corresponding testing method depending on whether the differences have equal variance or unequal variance from the distribution of the differences calculated by the difference calculation unit 123.

[0048] For example, the determination unit 124 first performs an F-test on the distribution of the two difference data for the evaluation period to determine whether the variances are equal or unequal. Next, for example, if the difference is equal variance, the determination unit 124 performs a t-test to determine whether there is a significant difference between the averages of the two evaluation periods. On the other hand, if the difference is unequal variance, the determination unit 124 performs a Welch's t-test to determine whether there is a significant difference between the averages of the two evaluation periods. Thereafter, the determination unit 124 determines that the VAV of the VAV control area corresponding to the target determined to have a significant difference is abnormal, in the same manner as in the above-mentioned process.

[0049] The display unit 125 displays an image relating to the area in which the air conditioning equipment determined to be abnormal by the determination unit 124 is located. For example, the display unit 125 refers to the information stored in the determination data storage unit 134, counts up the installation areas of the VAVs determined to be abnormal, and displays a list image in which the control areas of the VAVs installed on each floor are classified as either areas assumed to be normal or areas assumed to be defective.

[0050] 3. Examples Here, a specific example of the process performed by the determination device 100 will be described with reference to Fig. 5. Fig. 5 is a diagram showing a specific example of the process performed by the determination device according to the embodiment. Note that Fig. 5 shows an example of performing a CFD simulation on the temperature distribution in a room. First, the determination device 100 specifies two periods, "July of last year" and "July of this year", as the evaluation target periods, and selects targets 1 to 4.

[0051] Then, the collection unit 121 collects history data for each of the targets 1 to 4 at each date and time in July of last year, and history data for each of the targets 1 to 4 at each date and time in July of this year. After that, the characteristic value calculation unit 122 performs a simulation of temperature distribution by CFD using a data set created from the corresponding history data for each date and time in July of last year and each date and time in July of this year.

[0052] Then, the characteristic value calculation unit 122 calculates the average temperature value for each target from the simulation result, and sets it as the characteristic value. Note that, by the processing up to this point, the characteristic values ​​of targets 1 to 4 have been calculated for each date and time in July of last year and each date and time in July of this year.

[0053] Next, the difference calculation unit 123 calculates the difference between each calculated characteristic value and the actual measurement value corresponding to that characteristic value. For example, if the characteristic value is "10:00 on July 1st last year, target 1: 26°C", the actual measurement value corresponds to "10:00 on July 1st last year, measurement value of the temperature sensor corresponding to target 1: 25.5°C", and the difference is "0.5°C". After that, the difference calculation unit 123 calculates the average value for each date for the calculated difference to obtain the difference for each date. In other words, by combining the differences calculated for each time by date, the differences for each target 1 to 4 are calculated for each date in July last year (1st to 31st) and for each date in July this year (1st to 31st).

[0054] After that, the determination unit 124 performs an F-test on the difference data from July of last year and July of this year for each of the targets 1 to 4, and determines whether the difference has equal or unequal variance. If the difference has equal variance, the determination unit 124 performs a t-test, and if the difference has unequal variance, the determination unit 124 performs a Welch's t-test to determine whether there is a significant difference.

[0055] Next, for targets that are determined to have a significant difference, the display unit 125 outputs the determination result to the outside by displaying an image indicating that a change has occurred in the state of the VAV corresponding to that target and that there is a possibility of a fault occurring (abnormal state).

[0056] Through the series of processes described above, the determination device 100 can determine changes (abnormalities) in the state of the air conditioning equipment by statistically comparing the differences between the simulation results and the actual measured values ​​for July of last year and July of this year, which have similar boundary conditions.

[0057] Next, a specific example of an image related to a VAV in which a fault may occur, which is displayed by the display unit 125, will be described with reference to Fig. 6. Fig. 6 is a diagram showing a specific example of an image output by a determination device according to an embodiment. The example of Fig. 6 shows the possibility of a fault occurring in "VAV1 to VAV10" installed on each of the "1st to 20th floors" of a building in which the VAV to be determined is located.

[0058] 6, a VAV floor with a "◯" indicates a VAV controlled area where the air conditioning equipment is assumed to be in a normal state, and a VAV floor with an "X" indicates a VAV controlled area where the air conditioning equipment is assumed to be in a malfunction. By displaying a list such as the example in Fig. 6 to a user involved in the facility management and operation of a building, the display unit 125 of the determination device 100 allows the user to understand the determination result of the abnormal state of the air conditioning equipment for each VAV controlled area.

[0059] 4. Processing procedure by the determination device Next, an example of a processing procedure by the determination device 100 according to the embodiment will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of a processing procedure in the determination device according to the embodiment.

[0060] The determination device 100 first specifies a period to be determined (evaluation period) (step S101). Then, the determination device 100 selects a location to be determined (target) (step S102). Next, the collection unit 121 collects information on the indoor environment under the conditions of the specified period and the selected location (step S103).

[0061] Then, the characteristic value calculation unit 122 creates an input data set for CFD based on the collected information (step S104). Subsequently, the characteristic value calculation unit 122 performs CFD using the generated data set and calculates characteristic values ​​(step S105). After that, the difference calculation unit 123 calculates the difference between the characteristic values ​​calculated by performing CFD and the actual measurement values ​​corresponding to the characteristic values ​​collected in S103 (step S106).

[0062] Next, the judgment unit 124 judges whether the calculated difference for each evaluation period is equal variance or unequal variance (step S107). If the calculated difference is equal variance (step S107; Yes), the judgment unit 124 performs a t-test, which is a test corresponding to equal variance (step S108). On the other hand, if the calculated difference is unequal variance (step S107; No), the judgment unit 124 performs a Welch's t-test, which is a test corresponding to unequal variance (step S109).

[0063] Then, after the process of S108 or the process of S109, the display unit 125 displays the determination result of the abnormal state of the air conditioning equipment as a result of carrying out the inspection (step S110), and the determination device 100 ends the process.

[0064] 5. Effects of the embodiment As described above, the determination device 100 according to this embodiment includes the collection unit 121, the characteristic value calculation unit 122, the difference calculation unit 123, and the determination unit 124. The collection unit 121 collects data on the environment of a room in which an air-conditioning device is installed for each of a plurality of specified periods. The characteristic value calculation unit 122 performs a simulation of the indoor environment based on the data for each period collected by the collection unit 121, and calculates a characteristic value from the simulation result for each period.

[0065] The difference calculation unit 123 calculates, for corresponding times in a plurality of periods, the difference between the characteristic value for each period calculated by the characteristic value calculation unit 122 and the value included in the data related to the indoor environment for each period collected by the collection unit 121. The determination unit 124 determines an abnormality in the air conditioning equipment based on the distribution of the differences calculated by the difference calculation unit 123.

[0066] As a result, the determination device 100 can automatically determine air conditioning equipment that is highly likely to have a malfunction or defect in the air conditioning system based on data related to the air conditioning environment accumulated in advance, thereby achieving the effect of being able to appropriately determine abnormal states of the air conditioning equipment other than those that meet pre-set malfunction conditions.

[0067] In addition, since the determination device 100 does not require settings for normal and abnormal conditions in advance, it is possible to reduce the burden on the operation manager and the like and to allow efficient maintenance and management of the air conditioning system. Furthermore, the determination device 100 can appropriately determine abnormalities in air conditioning equipment and quickly respond to air conditioning equipment that is experiencing a breakdown or malfunction, thereby preventing the deterioration of the indoor environment and reducing energy consumption.

[0068] Furthermore, the characteristic value calculation unit 122 of the determination device 100 performs a simulation of one or more of the indoor temperature distribution, the indoor air volume distribution, the indoor air speed distribution, the indoor pollutant (e.g., carbon dioxide) concentration distribution, and the indoor humidity distribution by computational fluid dynamics using the data for each period collected by the collection unit 121. As a result, the determination device 100 achieves the effect of being able to determine a change in the state of the air conditioning equipment by comparing the distribution of differences between the simulation results and the actual measured values ​​by performing CFD, which can obtain reproducible results by inputting information about the indoor environment as boundary conditions, on indices that represent the indoor environment, such as the indoor temperature distribution and the indoor air speed distribution.

[0069] Furthermore, the determination unit 124 of the determination device 100 determines an abnormality in the air conditioning equipment by using a corresponding testing method depending on whether the differences have equal variance or unequal variance from the distribution of the differences calculated by the difference calculation unit 123. This provides the effect that the determination device 100 can determine a change in the state of the air conditioning equipment by using an appropriate testing method from the distribution of the differences for each data period to be determined and determining the presence or absence of a significant difference.

[0070] Furthermore, the determination device 100 has a display unit 125. The display unit 125 displays an image relating to an area in which an air conditioning unit determined to be abnormal by the determination unit 124 is located. This provides an effect that the determination device 100 can easily allow a user to grasp whether the state of each air conditioning unit located on each floor is normal or abnormal.

[0071] [6. Hardware configuration] The determination device 100 according to the embodiment described above is realized, for example, by a computer 1000 configured as shown in Fig. 8. Fig. 8 is a diagram showing an example of a hardware configuration. The computer 1000 has a configuration in which a CPU 1100, a RAM 1200, a ROM 1300, an auxiliary storage device 1400, a communication I / F (interface) 1500, and an input / output I / F (interface) 1600 are connected by a bus 1800.

[0072] The CPU 1100 operates and controls each unit based on a program stored in the ROM 1300 or the auxiliary storage device 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, programs that depend on the hardware of the computer 1000, and the like.

[0073] The auxiliary storage device 1400 stores programs executed by the CPU 1100, data used by the programs, etc. The communication I / F 1500 receives data from other devices via a predetermined communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0074] The CPU 1100 controls output devices such as a display and a printer, and an input / output device 1700 such as a keyboard and a mouse, via the input / output I / F 1600. The CPU 1100 acquires data from the input / output device 1700 via the input / output I / F 1600. The CPU 1100 also outputs generated data to the input / output device 1700 via the input / output I / F 1600.

[0075] For example, when the computer 1000 functions as the determination device 100 according to this embodiment, the CPU 1100 of the computer 1000 executes a program loaded onto the RAM 1200 to realize the functions of the control unit 120 .

[0076] [7.Other] Of the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0077] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0078] The above-mentioned components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the so-called equivalent range. Furthermore, the above-mentioned embodiments can be appropriately combined within a range that does not cause contradictions in the processing contents.

[0079] Moreover, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, a control section can be read as control means or a control circuit.

[0080] Although some of the embodiments of the present invention have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section. [Explanation of symbols]

[0081] 100 Judgment device 110 Communications Department 120 Control section 121 Collection Department 122 Characteristic value calculation unit 123 Difference calculation section 124 Judgment section 125 Display section 130 Storage section 131 History data storage unit 132 Characteristic value data storage unit 133 Differential data storage unit 134 Judgment data storage unit 200 Air conditioning system monitoring device 210, 220 Air conditioner system 211, 221 Air conditioner 212, 215 VAV 213, 216 Indoor temperature sensor 214-1~214-n, 217-1~217-n air outlet 300 Temperature Sensor

Claims

1. A collection unit that collects data on the environment of a room in which an air conditioning device is installed for each of a plurality of specified periods; a characteristic value calculation unit that performs a simulation of an indoor environment based on the data for each period collected by the collection unit and calculates a characteristic value from a simulation result for each period; a difference calculation unit that calculates, for corresponding times in the plurality of time periods, a difference between the characteristic value for each time period calculated by the characteristic value calculation unit and a value included in the data related to the indoor environment for each time period collected by the collection unit; a determination unit that determines an abnormality in the air conditioning equipment based on the distribution of the differences calculated by the difference calculation unit; A determination device comprising:

2. The characteristic value calculation unit performs a simulation by computational fluid dynamics using the data for each period collected by the collection unit for one or more of an indoor temperature distribution, an indoor air volume distribution, an indoor air speed distribution, an indoor pollutant concentration distribution, and an indoor humidity distribution.

2. The determination device according to claim 1.

3. The determination unit determines whether the air conditioning equipment is abnormal by using a corresponding test method depending on whether the differences have equal variances or unequal variances from the distribution of the differences calculated by the difference calculation unit.

2. The determination device according to claim 1.

4. The air conditioning system further includes a display unit that displays an image relating to an area in which the air conditioning system is determined to be abnormal by the determination unit.

2. The determination device according to claim 1.

5. A determination method executed by a determination device, comprising: A collection step of collecting data on the environment in a room in which the air conditioning equipment is installed for each of a plurality of specified periods; a characteristic value calculation step of simulating an indoor environment based on the data for each period collected by the collection step, and calculating characteristic values ​​from the simulation results for each period; a difference calculation step of calculating, for each corresponding time in the plurality of time periods, a difference between the characteristic value for each time period calculated in the characteristic value calculation step and a value included in the data related to the indoor environment for each time period collected in the collection step; a determination step of determining an abnormality in the air conditioning equipment based on the distribution of the differences calculated by the difference calculation step; A method for determining whether or not a particular

6. A collection procedure for collecting data on the environment in a room in which the air conditioning equipment is installed for each of a number of specified periods; a characteristic value calculation step of simulating an indoor environment based on the data for each period collected by the collection step, and calculating a characteristic value from the simulation result for each period; a difference calculation step of calculating, for each corresponding time in the plurality of time periods, a difference between the characteristic value for each time period calculated by the characteristic value calculation step and a value included in the data related to the indoor environment for each time period collected by the collection step; a determination procedure for determining an abnormality in the air conditioning equipment based on a distribution of the differences calculated by the difference calculation procedure; A determination program that causes a computer to execute the above steps.

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