Evaluation device, evaluation method, and program

Abstract

This evaluation device comprises: an extraction unit that extracts, from time-series data obtained by measuring the temperature of a control target of a heat source device, an element included in a monitoring section from a prescribed start condition to an end condition of temperature control; an estimation unit that, on the basis of the extracted element, estimates a dead time estimation value of a response of the temperature with respect to the temperature control and a time constant estimation value of a first-order lag response; and an evaluation unit that creates evaluation information about the heat source device based on at least one of the dead time estimation value and the time constant estimation value.

Description

Evaluation device, evaluation method, and program

[0001] This application claims priority to Japanese Patent Application No. 2023-174187, filed on October 6, 2023, the contents of which are incorporated herein by reference.

[0002] Patent Document 1 describes a monitoring system that focuses on the fact that the time it takes to reach the load setting (set temperature) increases due to factors such as deterioration over time and modulation of air conditioners, and determines that modulation of the air conditioner has occurred if the difference between the set temperature and the room temperature does not reach an acceptable value within a specified time from the start of operation.

[0003] Japanese Patent Application Laid-Open No. 2002-106929

[0004] The time it takes for the set temperature to be reached after operation starts varies depending on various factors, such as the operating mode (cooling or heating), a decline in air conditioning performance, clogged filters, etc. Therefore, if an evaluation is simply conducted using the time it takes to reach the set temperature (measured value) as an indicator, it may be difficult to accurately assess whether there is performance degradation or an abnormality in the air conditioner.

[0005] An object of the present disclosure is to provide an evaluation device, an evaluation method, and a program that can provide evaluation information that enables a more accurate evaluation of whether or not a heat source device has performance degradation or an abnormality.

[0006] According to one aspect of the present disclosure, the evaluation device includes an extraction unit that extracts elements included in a monitoring interval from a predetermined start condition to an end condition of temperature control from time series data measuring the temperature of a controlled object of a heat source device, an estimation unit that estimates a dead time estimate of the temperature response to the temperature control and a time constant estimate of a first-order lag response based on the extracted elements, and an evaluation unit that creates evaluation information of the heat source device based on at least one of the dead time estimate and the time constant estimate.

[0007] According to one aspect of the present disclosure, the evaluation method includes the steps of: extracting elements included in a monitoring interval from a predetermined start condition to an end condition of temperature control from time series data measuring the temperature of a controlled object of a heat source device; estimating a dead time estimate of the temperature response to the temperature control and a time constant estimate of a first-order lag response based on the extracted elements; and creating evaluation information for the heat source device based on at least one of the dead time estimate and the time constant estimate.

[0008] According to one aspect of the present disclosure, the program causes an evaluation device to perform the following steps: extracting elements included in a monitoring interval from a predetermined start condition to an end condition of temperature control from time series data measuring the temperature of a controlled object of the heat source device; estimating a dead time estimate of the temperature response to the temperature control and a time constant estimate of a first-order lag response based on the extracted elements; and creating evaluation information for the heat source device based on at least one of the dead time estimate and the time constant estimate.

[0009] According to the above aspect, it is possible to provide evaluation information that allows for a more accurate evaluation of whether or not there is performance degradation or abnormality in the heat source device.

[0010] FIG. 1 is a diagram showing the functional configuration of an air conditioning system according to a first embodiment. FIG. 2 is a flowchart showing an example of a process for estimating a thermal response parameter according to the first embodiment. FIG. 3 is a diagram showing an example of time-series data of an indoor temperature according to the first embodiment. FIG. 4 is a flowchart showing an example of an evaluation process according to the first embodiment. FIG. 5 is a diagram showing an example of evaluation information according to the first embodiment. FIG. 6 is a diagram showing an example of allocation of explanatory variables and level categories according to the first embodiment. FIG. 7 is a diagram showing an example of use of evaluation information according to the first embodiment.

[0011] First Embodiment An evaluation method according to a first embodiment will be described below with reference to the drawings. The evaluation method according to this embodiment can be applied to the control of various heat source devices such as air conditioners, water heaters, and refrigerators, but the following description will be given taking the case where the method is applied to an air conditioner as an example.

[0012] (Overall Configuration of Air Conditioning System) FIG. 1 is a diagram showing the functional configuration of an air conditioning system according to a first embodiment. As shown in FIG. 1, the air conditioning system 100 includes an air conditioner 1 and a terminal device 20. The air conditioner 1 includes an outdoor air temperature sensor 2, an indoor temperature sensor 3, a memory 4, an indoor unit 5, and an outdoor unit 6. The outdoor air temperature sensor 2 and the indoor temperature sensor 3 are connected to an evaluation device 10, and the evaluation device 10 acquires the temperatures measured by the outdoor air temperature sensor 2 and the indoor temperature sensor 3. The indoor unit 5 and the outdoor unit 6 are connected to the evaluation device 10, and the evaluation device 10 detects the operating states of the indoor unit 5 and the outdoor unit 6. The indoor unit 5 and the outdoor unit 6 are controlled by a control device (not shown) according to setting conditions, such as a set temperature and air volume, set by a user. The evaluation device 10 and the terminal device 20 are connected to each other so as to be able to communicate with each other via a network NW. The terminal device 20 is a mobile terminal such as a smartphone or tablet, or a computer such as a server, used by service engineers of the manufacturer of the air conditioner 1 or a maintenance company.

[0013] (Functional Configuration of Evaluation Device) The evaluation device 10 is a computer equipped with a CPU (Central Processing Unit) such as a microcomputer or the like and an MPU (Micro Processing Unit). The evaluation device 10 includes an information acquisition unit 11, an extraction unit 12, a division unit 13, an estimation unit 14, an evaluation unit 15, an alarm unit 16, and a communication unit 17.

[0014] The information acquisition unit 11 acquires the outdoor air temperature measured by the outdoor air temperature sensor 2 and the indoor temperature measured by the indoor temperature sensor 3. It also acquires the operating states of the indoor unit 5 and the outdoor unit 6. The operating states include the ON / OFF state of the air conditioner 1, the operating mode (cooling operation or heating operation), and setting conditions such as the set temperature and air volume.

[0015] The extraction unit 12 extracts elements included in the monitoring period from a specified start condition to an end condition of air conditioning control by the air conditioner 1 from the time series data of the indoor temperature in the room (air-conditioned space) where the air conditioner 1 is installed.

[0016] The dividing unit 13 divides the elements in the effective section from the point where the indoor temperature in the effective section starts to decrease during cooling operation, and from the point where the indoor temperature in the effective section starts to increase during heating operation, as first-order lag response elements, and divides the elements in the effective section other than the first-order lag response as dead time elements.

[0017] The estimation unit 14 estimates the length of the dead time as a dead time estimate value L, and estimates a time constant estimate value τ that minimizes the curve approximation error with the room temperature in the first-order lag response section. Parameters including the first-order lag time constant estimate value τ and the dead time estimate value L are also referred to as thermal response parameters.

[0018] The evaluation unit 15 creates evaluation information for the air conditioner 1 based on at least one of the dead time estimated value L and the time constant estimated value τ.

[0019] The warning unit 16 issues an alert when it is determined that there is a performance degradation or abnormality in the air conditioner 1 based on the evaluation information.

[0020] The communication unit 17 communicates with the terminal device 20. For example, the communication unit 17 transmits evaluation information created by the evaluation unit 15 to the terminal device 20. The communication unit 17 may also transmit an alert from the alarm unit 16 to the terminal device 20.

[0021] (Process for Estimating Thermal Response Parameters) FIG. 2 is a flowchart showing an example of a process for estimating thermal response parameters according to the first embodiment. Here, the flow of the process by which the evaluation device 10 estimates thermal response parameters will be described with reference to FIG. 2. Note that when the air conditioner 1 is operating, the evaluation device 10 repeatedly performs the series of processes shown in FIG. 2 at predetermined control intervals (e.g., every 50 ms). During this time, the information acquisition unit 11 sequentially acquires sensor measurement values ​​such as the outdoor air temperature, indoor temperature, and air volume, as well as setting conditions, from the outdoor air temperature sensor 2, indoor temperature sensor 3, indoor unit 5, etc.

[0022] First, the extraction unit 12 determines whether the start condition of the monitoring period has been met (step S100). The monitoring period is a period for monitoring (extracting and storing) data to estimate thermal response parameters in the air conditioning control of the air conditioner 1. For example, the extraction unit 12 determines that the start condition of the monitoring period has been met when the indoor unit 5 is switched on or the set temperature changes.

[0023] If the start condition is not met (step S100; NO), the extraction unit 12 ends the process. On the other hand, if the start condition is met (step S100; YES), the extraction unit 12 starts extracting and storing necessary information (step S101). Thereafter, the extraction unit 12 records the measured indoor temperature values ​​(time-series data) in a buffer secured in the memory 4 at each predetermined control period. In addition, only when the extraction unit 12 starts recording the indoor temperature, it records in the memory 4 the operating mode (heating operation or cooling operation) of the air conditioner 1 and explanatory variables used in the evaluation process described below. The explanatory variables include, for example, the time when storage of the measured values ​​began, the outdoor air temperature, the airflow rate of the indoor unit 5, and the temperature gap between the indoor temperature and the set temperature.

[0024] Next, the extractor 12 determines whether a predetermined termination condition is met (step S102). For example, the extractor 12 determines that the termination condition is met when the end of the buffer (the upper limit of the number or amount of time-series data) is reached, when the indoor unit 5 is switched off, when the set temperature is changed, etc.

[0025] If the termination condition is not met (step S102; NO), the extraction unit 12 temporarily terminates the process. At this time, the time-series data of the indoor temperature continues to be stored. Therefore, until the extraction unit 12 determines that the termination condition is met, the indoor temperature at each step of the control cycle is extracted and stored in a buffer. On the other hand, if the termination condition is met (step S102; YES), the extraction unit 12 further determines whether the monitoring interval is a valid interval (step S103).

[0026] For example, if the length of the data (time-series data of indoor temperature) recorded in the buffer is less than a threshold value, or if the indoor temperature does not reach the set temperature by the time the buffer reaches its end, the extraction unit 12 determines that the monitoring section is invalid (step S103; NO) if the time-series data does not meet a predetermined standard (i.e., it is difficult to estimate the thermal response parameters based on the time-series data). In this case, the extraction unit 12 clears the buffer (step S106) and ends the process. On the other hand, if the time-series data meets the standard, the extraction unit 12 determines that the monitoring section is valid (step S103; YES).

[0027] Next, the dividing unit 13 divides the time series data of the monitoring section into dead time elements and first-order lag elements (step S104).

[0028] FIG. 3 is a diagram illustrating an example of time-series data of indoor temperature according to the first embodiment. FIG. 3 illustrates an example of time-series data of indoor temperature during heating operation. In the example of FIG. 5, the extraction unit 12 extracts and records time-series data of indoor temperature in a monitoring period from time t0 to time t2. The division unit 13 first identifies elements of a first-order lag response from the time-series data. For example, during heating operation, the division unit 13 considers elements after the point at which the indoor temperature begins to rise in the monitoring period to be elements of a first-order lag response. More specifically, the division unit 13 searches for an extreme value (a minimum value during heating operation) in the time-series data and determines that the indoor temperature has begun to rise when the temperature rises from the extreme value by a predetermined temperature (e.g., 1°C) or more. In this case, the division unit 13 considers the extreme value immediately before the rise to be a boundary point and considers elements after the boundary point to be elements of a first-order lag response. In the example of FIG. 3, the indoor temperature rises from the minimum value by a predetermined temperature or more after time t1. Therefore, the dividing unit 13 regards the element at time t1, which is immediately before the indoor temperature starts to rise, as a boundary point, and regards the elements from time t1 to time t2 as elements of a first-order lag response.

[0029] Similarly, during cooling operation, the dividing unit 13 considers elements in the monitoring section after the point at which the indoor temperature starts to decrease as elements of a first-order lag response. More specifically, the dividing unit 13 detects an extreme value (a maximum value during cooling operation) from the time-series data, and determines that the indoor temperature has started to decrease when the temperature drops from the extreme value by a predetermined temperature (for example, 1°C) or more.

[0030] Furthermore, the dividing unit 13 considers elements other than the first-order lag response in the monitoring section to be elements of dead time. In the example of Fig. 3, the dividing unit 13 considers elements before time t1 to be elements of dead time.

[0031] Next, the estimating unit 14 estimates thermal response parameters (step S105). The estimating unit 14 according to this embodiment estimates the length of dead time and the time constant of the first-order lag response as thermal response parameters.

[0032] First, the estimator 14 obtains the length of the dead time (the number of array elements) divided from the time-series data by the divider 13 as the dead time estimated value L. In the example of FIG. 3 , the estimator 14 obtains the time from time t0 to t1 as the dead time estimated value L.

[0033] The estimator 14 also estimates the time constant τ of the first-order lag response based on the elements of the first-order lag response. For example, the estimator 14 performs a simulation (curve approximation) of the change in the indoor temperature over time for each assumed time constant value while sequentially changing the assumed time constant value from a lower limit value to an upper limit value in increments of a fixed time (e.g., one minute). Various known techniques may be used for this simulation. The estimator 14 calculates the error between the approximation curve for each assumed time constant value calculated by the simulation and the actual measured value (the first-order lag response portion of the time series divided by the divider 13), and determines the assumed time constant value that minimizes the error as the estimated time constant τ.

[0034] The estimation unit 14 stores the thermal response parameters, including the dead time estimated value L and the time constant estimated value τ, in the memory 4 in association with the previously recorded operation mode and explanatory variables (step S106). Thereafter, the estimation unit 14 clears the buffer (step S107) and ends the process.

[0035] (Evaluation Processing) FIG. 4 is a flowchart showing an example of evaluation processing according to the first embodiment. FIG. 5 is a first diagram showing an example of evaluation information according to the first embodiment. FIG. 6 is a diagram showing an example of explanatory variables and level category assignment according to the first embodiment. FIG. 7 is a diagram showing an example of use of evaluation information according to the first embodiment. Here, the flow of processing in which the evaluation device 10 evaluates the air conditioner 1 will be described with reference to FIGS. 4 to 7. The evaluation device 10 executes the series of processes shown in FIG. 4 at each predetermined evaluation period. The evaluation period may be set to any period, such as one month or one year.

[0036] First, the evaluation unit 15 extracts data for the evaluation period from the thermal response parameter estimates (dead time estimate L and first-order lag response time constant estimate τ) stored in the memory 4 (step S200). For example, as shown in FIG. 5 , the evaluation period is assumed to be July 2022. In this case, the evaluation unit 15 extracts and acquires from the memory 4 the combinations of the thermal response parameter estimates and explanatory variables estimated for July 2022.

[0037] Next, the evaluation unit 15 creates evaluation information D1 for the evaluation period based on the extracted data (step S201). The evaluation information D1 includes at least the average value of the time constant estimate value τ of the first-order lag response during the evaluation period. The evaluation information D1 may also include the standard deviation of the time constant estimate value τ of the first-order lag response during the evaluation period, the average value of the dead time estimate value L, and the standard deviation of the dead time estimate value L. The created evaluation information D1 is stored in the memory 4. The created evaluation information D1 may also be sent to the terminal device 20, accompanied by identification information (such as an air conditioner ID or serial number) that can identify the air conditioner 1. In this case, the terminal device 20 stores the evaluation information D1 for each air conditioner received from the evaluation device 10.

[0038] Note that the operating mode and setting conditions (explanatory variables) vary depending on the evaluation period. Therefore, for example, as shown in FIG. 6 , when using air volume and outdoor temperature as explanatory variables 1 and 2, the evaluation unit 15 pre-sets level categories according to the setting values ​​and measurements of each explanatory variable. Furthermore, as shown in FIG. 5 , the evaluation unit 15 may tally the number of samples of the thermal response parameters for each operating mode and for each combination of level categories of explanatory variables 1 and 2, and calculate the average values ​​and standard deviations of the estimated time constant τ and the estimated dead time L based on the estimated values ​​of the thermal response parameters belonging to the combination with the largest number of samples. In this way, estimates with a large number of samples and relatively high reliability can be used for evaluation. In the example of FIG. 5 , the combination of level 3 of explanatory variable 1 and level 4 of explanatory variable 2 has the largest number of samples. In this case, the evaluation unit 15 extracts only the estimated values ​​of the thermal response parameters belonging to this combination from the estimated values ​​of the thermal response parameters stored in the memory 4, and calculates the average values ​​and standard deviations of the time constant τ and the dead time L. In another embodiment, the evaluation unit 15 may calculate the average value and standard deviation of the time constant τ and the dead time L based on the estimated values ​​of all the thermal response parameters for the evaluation period, after weighting the values ​​according to the number of samples for each combination.

[0039] Furthermore, the warning unit 16 determines whether or not there is a performance degradation or abnormality in the air conditioner 1 based on the evaluation information D1 (step S202).

[0040] For example, the warning unit 16 compares the average value of the estimated time constant τ, the standard deviation of the estimated time constant τ, the average value of the estimated dead time L, and the standard deviation of the estimated dead time L with thresholds for each parameter. If any one parameter (e.g., the average value of the estimated time constant τ) exceeds a threshold, or if two or more predetermined parameters (e.g., both the average value of the estimated time constant τ and the estimated dead time L) exceed a threshold, the warning unit 16 determines that the air conditioner 1 is experiencing performance degradation or an abnormality (step S202; YES). Which of these four parameters is used for the determination may be arbitrarily set. Furthermore, when multiple parameters are used for the determination, it may also be arbitrarily set whether performance degradation is determined to occur when any one of the parameters exceeds a threshold (satisfying an OR condition) or when all thresholds exceed the thresholds (satisfying an AND condition).

[0041] In another embodiment, the alarm unit 16 may determine whether performance degradation or an abnormality exists based on whether each parameter is on an increasing trend, rather than whether each parameter exceeds a threshold. For example, as shown in FIG. 8 , the alarm unit 16 compares the latest evaluation information D1 with past evaluation information D1 (e.g., evaluation information D1 for each month of the same year or the same month of the previous year) stored in the memory 4 to determine whether each parameter is on an increasing trend. The alarm unit 16 determines that performance degradation or an abnormality exists when the increase amount or rate from the previous month or the same month of the previous year exceeds an upper limit value set for each parameter. Note that while FIG. 7 shows an example of the average value and standard deviation of the time constant estimate value τ, the dead time estimate value L may also be used for the determination.

[0042] If the alarm unit 16 determines that the performance of the air conditioner 1 has deteriorated or is abnormal (step S202; NO), the process ends. On the other hand, if the alarm unit 16 determines that the performance of the air conditioner 1 has deteriorated or is abnormal (step S202; YES), the alarm unit 16 issues an alert (step S203). For example, the alarm unit 16 may notify the user that maintenance of the air conditioner 1 is required by turning on an indicator lamp on the indoor unit 5. The alarm unit 16 may also notify a service engineer of the manufacturer of the air conditioner 1, a maintenance company, or the like, that maintenance of the air conditioner 1 is required by issuing an alert to the terminal device 20. At this time, the service engineer may refer to the evaluation information D1 of the air conditioner 1 stored in the terminal device 20 to infer the location of the malfunction of the air conditioner 1 and suggest maintenance (repair, part replacement) or replacement to the user.

[0043] 4 has been described as an example in which the warning unit 16 of the evaluation device 10 determines whether or not there is a performance degradation or abnormality in the air conditioner 1 based on the evaluation information D1, but the present invention is not limited to this. In other embodiments, a service engineer may determine whether or not there is a performance degradation or abnormality in the air conditioner 1 based on the evaluation information D1.

[0044] The service engineer reads the evaluation information D1 of a certain air conditioner 1 from the terminal device 20 and determines whether there is any performance degradation or abnormality of this air conditioner 1 (step S202). For example, the terminal device 20 presents the service engineer with data (such as a graph) that allows comparison of the evaluation information D1 with each month of the same year and the same month of the previous year, as shown in FIG. 7. The service engineer refers to this data and determines whether there is any performance degradation or abnormality of the air conditioner 1. The determination method may be the same as that used by the alarm unit 16 described above.

[0045] Furthermore, the time constant and dead time of the first-order lag response are each affected by different physical phenomena of the air conditioner 1. For example, the time constant of the first-order lag response is affected by deterioration or abnormalities in the air conditioning performance of the air conditioner 1. That is, the average value may tend to increase or the standard deviation may vary due to aging or abnormalities in the heat medium system, etc., which affect the air conditioning performance of the air conditioner 1. Furthermore, the dead time may increase due to aging or abnormalities in the mechanical system of the air conditioner 1. Therefore, based on this knowledge, a service engineer may individually check the average values ​​and standard deviations of the time constant estimate value τ and the dead time estimate value L to not only check for performance deterioration or abnormalities in the air conditioner 1 itself, but also to infer which part of the air conditioner 1 is malfunctioning, and may make suggestions to the user, such as maintenance or replacement.

[0046] Furthermore, if the service engineer determines that there is a performance degradation or abnormality in the air conditioner 1 (step S202; YES), an alert is sent to the air conditioner 1 or a mobile terminal owned by the user of the air conditioner 1 via the terminal device 20 (step S203). Note that the service engineer may also notify the user that maintenance (part replacement) or replacement is required using various other methods, such as by telephone, email, or home visit.

[0047] (Actions and Effects) As described above, the evaluation device 10 according to this embodiment includes an extraction unit 12 that extracts elements included in a monitoring period from a predetermined start condition to an end condition of air conditioning control by the air conditioner 1 from time series data obtained by measuring the indoor temperature; an estimation unit 14 that estimates an estimated dead time L of the indoor temperature response to the air conditioning control and an estimated time constant τ of the first-order lag response based on the extracted elements; and an evaluation unit 15 that creates evaluation information D1 for the air conditioner 1 based on at least one of the estimated dead time L and the estimated time constant τ.

[0048] In this way, the evaluation device 10 can provide evaluation information D1 that separately evaluates the dead time of the thermal response and the first-order lag response of the air conditioner 1. As described above, the time constant and dead time of the first-order lag response are each affected by different physical phenomena in the air conditioner 1. Therefore, it becomes possible for a service engineer, for example, to more accurately estimate performance degradation or abnormalities in the air conditioner 1, as well as the location of the malfunction, than simply observing the time it takes for the set temperature to be reached.

[0049] The evaluation unit 15 also generates evaluation information D1 including at least one of the average value of the time delay estimate L, the standard deviation of the time delay estimate, the average value of the time constant estimate τ, and the standard deviation of the time constant estimate τ in a predetermined evaluation period.

[0050] In general, abnormality detection and failure prediction require comprehensive monitoring of numerous sensor values, such as the pressure and temperature of each component, placing a heavy burden on the monitor (service engineer). In contrast, the evaluation device 10 can provide evaluation information D1 that quantitatively and intuitively indicates performance degradation and abnormal conditions of the air conditioner 1, thereby reducing the burden on the service engineer.

[0051] The evaluation device 10 further includes an alarm unit 16 that issues an alert when it is determined that there is a performance degradation or abnormality in the air conditioner 1 based on the evaluation information D1.

[0052] In this way, the evaluation device 10 can quickly notify a user or a service engineer of the presence or absence of performance degradation or abnormality in the air conditioner 1. By knowing the presence or absence of performance degradation, the user or service engineer can take measures such as performing maintenance before the air conditioner 1 actually breaks down.

[0053] Other Embodiments Although one embodiment has been described in detail above with reference to the drawings, the specific configuration is not limited to the above, and various design modifications are possible. That is, in other embodiments, the order of the above-described processes may be changed as appropriate. Furthermore, some processes may be executed in parallel.

[0054] For example, in the above-described embodiment, a configuration example in which the evaluation device 10 is provided inside the air conditioner 1 has been described, but this is not limiting. In other embodiments, the evaluation device 10 may be provided in an external server or a terminal device 20 used by a service engineer. In this case, the evaluation device 10 associates the sensor measurement values, operation mode, setting conditions, etc. of each air conditioner 1 with the identification information of the air conditioner 1 and collects them at predetermined intervals. Then, through processing by each of the above-described functional units, evaluation information D1 is created for each air conditioner 1 and the presence or absence of performance degradation or abnormality is determined. Furthermore, some of the functional units of the evaluation device 10 (e.g., the evaluation unit 15 and the alarm unit 16) may be separated and implemented in the terminal device 20. Even in such an embodiment, the same effects as those of the above-described embodiment can be obtained.

[0055] <Additional Notes> The evaluation device, evaluation method, and program described in the above-described embodiments can be understood, for example, as follows.

[0056] (1) According to the first aspect, the heat source device 1 includes an extraction unit 12 that extracts elements included in a monitoring period from a predetermined start condition to an end condition of the temperature control from time series data obtained by measuring the temperature of the controlled object of the heat source device 1; an estimation unit 14 that estimates an estimated dead time value L of the temperature response to the temperature control and an estimated time constant τ of the first-order lag response based on the extracted elements; and an evaluation unit 15 that creates evaluation information D1 of the heat source device 1 based on at least one of the estimated dead time value L and the estimated time constant τ.

[0057] In this way, the evaluation device 10 can provide evaluation information D1 that separately evaluates the dead time and first-order lag response of the thermal response of the heat source device 1. As described above, the time constant and dead time of the first-order lag response are each affected by different physical phenomena of the heat source device 1. Therefore, it becomes possible for a service engineer, for example, to more accurately estimate the presence or absence of performance degradation or abnormality in the heat source device 1, as well as the location of the malfunction, than simply observing the time it takes for the set temperature to be reached.

[0058] (2) According to the second aspect, in the evaluation device 10 according to the first aspect, the evaluation unit 15 generates evaluation information D1 including at least one of the average value of the time-delay estimate value L, the standard deviation of the time-delay estimate value L, the average value of the time constant estimate value τ, and the standard deviation of the time constant estimate value τ in a predetermined evaluation period.

[0059] In general, abnormality detection and failure prediction require comprehensive monitoring of numerous sensor values, such as the pressure and temperature of each component, placing a heavy burden on the monitor (service engineer). In contrast, the evaluation device 10 can provide evaluation information D1 that quantitatively and intuitively indicates performance degradation and abnormal conditions of the heat source device 1, thereby reducing the burden on the service engineer.

[0060] (3) According to the third aspect, the evaluation device 10 according to the first or second aspect further includes an alarm unit 16 that issues an alert when it is determined that there is a performance degradation or abnormality in the heat source device 1 based on the evaluation information D1.

[0061] In this way, the evaluation device 10 can quickly notify a user or a service engineer of the presence or absence of performance degradation or abnormality in the air conditioner 1. By knowing the presence or absence of performance degradation, the user or service engineer can take measures such as performing maintenance before the heat source device 1 actually breaks down.

[0062] (4) According to the fourth aspect, the evaluation method includes the steps of: extracting elements included in a monitoring interval from a predetermined start condition to an end condition of the temperature control from time series data obtained by measuring the temperature of the controlled object of the heat source device 1; estimating a dead time estimate L of the temperature response to the temperature control and a time constant estimate τ of the first-order lag response based on the extracted elements; and creating evaluation information D1 of the heat source device 1 based on at least one of the dead time estimate L and the time constant estimate τ.

[0063] (5) According to the fifth aspect, the program causes the evaluation device 10 to execute the following steps: extracting elements included in a monitoring interval from a predetermined start condition to an end condition of the temperature control from time series data obtained by measuring the temperature of the controlled object of the heat source device 1; estimating, based on the extracted elements, an estimated dead time value L of the temperature response to the temperature control and an estimated time constant value τ of the first-order lag response; and creating evaluation information D1 of the heat source device 1 based on at least one of the estimated dead time value L and the estimated time constant value τ.

[0064] According to the above aspect, it is possible to provide evaluation information that allows for a more accurate evaluation of whether or not there is performance degradation or abnormality in the heat source device.

[0065] REFERENCE SIGNS LIST 100 Air conditioning system 1 Air conditioner (heat source device) 2 Outdoor air temperature sensor 3 Indoor temperature sensor 4 Memory 5 Indoor unit 6 Outdoor unit 10 Evaluation device 11 Information acquisition unit 12 Extraction unit 13 Division unit 14 Estimation unit 15 Evaluation unit 16 Alarm unit 17 Communication unit 20 Terminal device

Claims

1. An evaluation device comprising: an extraction unit that extracts elements included in a monitoring period from a predetermined start condition to an end condition of temperature control from time series data measuring the temperature of a controlled object of a heat source device; an estimation unit that estimates a dead time estimate of the temperature response to the temperature control and a time constant estimate of a first-order lag response based on the extracted elements; and an evaluation unit that creates evaluation information of the heat source device based on at least one of the dead time estimate and the time constant estimate.

2. The evaluation device according to claim 1, wherein the evaluation unit creates evaluation information including at least one of an average value of the dead time estimate value in a predetermined evaluation period, a standard deviation of the dead time estimate value, an average value of the time constant estimate value, and a standard deviation of the time constant estimate value.

3. The evaluation device according to claim 1 or 2, further comprising an alarm unit that issues an alert when it is determined that there is a performance degradation or abnormality in the heat source device based on the evaluation information.

4. An evaluation method comprising the steps of: extracting elements included in a monitoring period from a predetermined start condition to an end condition of temperature control from time series data measuring the temperature of a controlled object of a heat source device; estimating a dead time estimate of the temperature response to the temperature control and a time constant estimate of a first-order lag response based on the extracted elements; and creating evaluation information of the heat source device based on at least one of the dead time estimate and the time constant estimate.

5. A program for causing an evaluation device to execute the steps of: extracting elements included in a monitoring period from a predetermined start condition to an end condition of temperature control from time series data measuring the temperature of a controlled object of a heat source device; estimating a dead time estimate of the temperature response to the temperature control and a time constant estimate of a first-order lag response based on the extracted elements; and creating evaluation information of the heat source device based on at least one of the dead time estimate and the time constant estimate.

Images