Water heater failure estimation system

Abstract

To provide a failure estimation system for a water heater which can urge exchange of components at a proper timing to various kinds of water heaters.SOLUTION: In a failure estimation system for a water heater, a management computer 2 includes: a data storing unit 22 for storing a use environment of each of a plurality of water heaters; a data acquiring unit 21 for acquiring basic information data and operation information data from each of the plurality of water heaters through a data communication network DN; a diagnosis unit 23A for diagnosing maintenance of a water heater 1 as a diagnosis target by comparing specification information of each of the plurality of water heaters, a reference value set for group data corresponding to the specification information acquired from the water heater 1 as the diagnosis target, and the operation information data acquired from the water heater 1 as the diagnosis target; and a notification unit 24 for notifying a user of a maintenance timing of the water heater 1 based on a diagnosis result of the diagnosis unit.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a failure estimation system for a water heater. [Background technology]

[0002] For example, as shown in Patent Document 1 and Patent Document 2, there are known water heater management systems that utilize IoT. In the water heater data transmission system disclosed in Patent Document 1, data is transmitted from each of a large number of water heaters to a cloud system, and faults in the water heaters are estimated by AI analysis of the data transmitted to the cloud system. In the hot water system disclosed in Patent Document 2, the usage limits of each part of the water heater (referred to as "water heater" in the document) are stored in advance in an external server, and the external server automatically orders replacement parts that are approaching their usage limits. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2018-120505 [Patent Document 2] Patent Publication No. 2020-52709 Summary of the Invention [Problem to be solved by the invention]

[0004] However, there are many different types of water heaters on the market, and some models are installed in such a small number that sufficient data cannot be obtained for AI analysis. In addition, in the configuration of the external server disclosed in Patent Document 2, for example, if water heaters are installed in each of large houses sold in large quantities at once, it is possible that the timing of replacement of parts that reach the limit of use will overlap for many water heaters. In particular, if the replacement timing overlaps with the busy season for workers, there is a risk that maintenance of the water heater will be delayed until the water heater actually breaks down.

[0005] An object of the present invention is to provide a water heater failure inference system that can prompt part replacement at an appropriate time for a wide variety of water heaters. [Means for solving the problem]

[0006] The present invention is a failure estimation system for a water heater installed in each home, comprising: a data storage unit that stores specification information and a usage environment of each of a plurality of the water heaters; a data acquisition unit that acquires the specification information and operation information data related to the operation state of the water heater from each of the plurality of water heaters via a data communication network; and a data acquisition unit that acquires the specification information stored in the data storage unit. and The use At the border the water heater to be diagnosed by comparing a reference value set in the group data corresponding to the specification information obtained from the water heater to be diagnosed with the operation information data obtained from the water heater to be diagnosed; and a notification unit that notifies the time for maintenance of the water heater based on the diagnosis results of the diagnosis unit.

[0007] The lifespan of a water heater often varies greatly depending on the specifications and the environment of use, but it is believed that if the specifications and environment of use are the same, the lifespans of the water heaters are often similar even if the models are different. According to the present invention, a plurality of group data are generated based on the specification information and environment of use of the water heater, and a reference value is set for each of the plurality of group data. As a result, it is possible to include water heaters with common specification information and environment of use in one group data, even if the water heaters are from different manufacturers or models. Then, the group data corresponding to the specification information included in the basic information data sent from the water heater is selected, and the reference value set in the selected group data is compared with the operation information data sent from the water heater, thereby performing a fault diagnosis of the water heater. As a result, even if the number of water heaters installed is small and sufficient data for AI analysis cannot be obtained, the use limit of parts, etc. can be diagnosed in combination with water heaters with common specifications and environment of use. In other words, according to the present invention, the notification unit notifies the appropriate maintenance time according to the specifications and environment of the water heater. In addition, even if water heaters are installed in each large house sold at once, the maintenance times will differ depending on the usage environment. Therefore, the present invention reduces the risk that the timing of replacement of parts that have reached their usage limit will overlap for many water heaters. This realizes a water heater failure estimation system that can prompt part replacement at the appropriate time for a wide variety of water heaters.

[0008] In the present invention, each of the plurality of group data is configured by a two-dimensional or more array table, and the plurality of reference values ​​are arranged in the array table in a state where they are classified according to the use environment, and the diagnosis unit acquires the reference values ​​from the water heater via the data communication network. The specification information, the specification information stored in the data storage unit, and the usage environment. and selecting the reference value according to the identified usage environment from among the plurality of reference values.

[0009] Since the lifespan of the water heater's parts and the like differs depending on the usage environment, with this configuration, a wide variety of reference values ​​can be set according to the usage environment, thereby enabling detailed diagnosis of the usage limits of parts and the like according to the usage environment.

[0010] In the present invention, it is preferable that the diagnosis unit is configured to estimate a time when the value of the driving information data exceeds the reference value as the time for maintenance.

[0011] With this configuration, the timing for maintenance of the water heater can be appropriately predicted, enabling, for example, an operator to arrange for replacement parts at the appropriate time.

[0012] In the present invention, it is preferable that, when the maintenance time overlaps with a busy period for an operator, the notification unit is configured to notify the operator of the maintenance time by shifting the maintenance time to a period before the busy period.

[0013] This configuration prevents the maintenance period from overlapping with busy periods, and avoids the risk of delaying maintenance of the water heater until the water heater actually breaks down. [Brief description of the drawings]

[0014] [Figure 1] FIG. 2 is a diagram showing the connection between the water heaters installed in each household and a management computer. [Diagram 2] FIG. 1 is a block diagram showing a water heater failure inference system. [Diagram 3] FIG. 13 is a diagram showing an arrangement table generated by a group data generating unit. [Figure 4] FIG. 11 is a flowchart showing a process for estimating a failure of a water heater. [Diagram 5] FIG. 11 is a graph showing a failure estimation based on a change over time in the rotation speed of the combustion fan. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] The failure estimation system estimates the time for maintenance of the water heater 1. The failure estimation system is constructed in a management computer 2 installed in, for example, a gas service center. As shown in FIG. 1, a water heater 1 is installed in each detached house and apartment building. Note that, although the water heater 1 in the apartment building is not shown in FIG. 1, a water heater 1 is installed in each household in the apartment building. The control units of the water heaters 1 installed in each household and the management computer 2 are connected via a data communication network DN consisting of the Internet, public lines, etc. This allows various information to be sent and received between the control units of the water heaters 1 and the management computer 2.

[0016] As shown in FIG. 2, the management computer 2 includes a data acquisition section 21, a data storage section 22, a fault diagnosis unit 23, and a notification section 24.

[0017] The operating status data and specification information of each of the multiple water heaters 1 are sent from the water heater 1 to the data acquisition unit 21 via the data communication network DN. In other words, the data acquisition unit 21 acquires the specification information of the water heater 1 and operating information data relating to the operating status of the water heater 1 from each of the multiple water heaters 1 via the data communication network DN. The frequency of sending the data from the water heater 1 to the data acquisition unit 21 may be once an hour or once a day. The operating status data is then stored in the data storage unit 22 as part of an operating status data group. The data stored in the data storage unit 22 includes an operating status data group and a basic information data group.

[0018] The operating state data group is a collection of operating state data sent from the water heater 1 to the data acquisition unit 21 via the data communication network DN. The operating state data group mainly includes data that is a predictor of a failure of the water heater 1. The operating state data group includes time series data such as the cumulative usage time of the water heater 1, the cumulative hot water usage amount of the water heater 1, the rotation speed (instantaneous value) of the combustion fan of the water heater 1, the current value (instantaneous value) of the combustion fan of the water heater 1, the rotation speed (instantaneous value) of the bath pump, the PWM ratio (instantaneous value) in the control unit, and the temperature (instantaneous value) of the thermistor provided in the water heater 1. The combustion fan of the water heater 1 is a fan that supplies air for combustion to the gas burner of the water heater 1. In addition, when the water heater 1 has, for example, a floor heating function and a bathroom drying and heating function, the usage time of the water heater 1 may be divided into, for example, the usage time of the hot water burner, the usage time of the floor heating burner, and the usage time of the bathroom drying and heating burner. When the water heater 1 has a floor heating function or a bathroom drying and heating function, the rotation speed of the heat medium pump may be included in the operation state data group.

[0019] The basic information data group includes specification information of the water heater 1, the usage environment of the water heater 1, etc. The specification information of the water heater 1 includes, for example, the hot water output number of the water heater 1, the structure (e.g., 1 can for 2 water, 2 cans for 3 water, etc.), the functions (hot water supply, automatic bath, reheating, floor heating, bathroom heating), the type of fuel (13A, LPG, kerosene, etc.), exhaust variation, the presence or absence of a latent heat recovery mechanism, the presence or absence of a drainage system, the manufacturer, the date of manufacture, etc. The usage environment of the water heater 1 includes, for example, the installation date (years of use) of the water heater 1, the family composition of the household in which the water heater 1 is used, the number of people in the household, the total floor area of ​​the house, the insulation performance and airtightness performance of the house, the classification of the house (classification of detached house / apartment building, new building / existing building, owned property / rented property, etc.), and the area information in which the water heater 1 is used, etc. The area information includes the installation location of the water heater 1, exemplified by areas A, B, and C in Fig. 1, water quality information of the tap water at the installation location of the water heater 1, and the distance from the coast to the installation location of the water heater 1. The water quality information includes chlorine concentration distribution, the presence or absence of defects due to water quality factors in each area, hydrogen ion exponent, impurity concentration, etc. In this way, the data storage unit 22 stores the usage environment of each of the multiple water heaters 1. In addition, the basic information data group also stores the maintenance history of each of the multiple water heaters 1 (e.g., part replacement history, etc.).

[0020] The basic information data group is a collection of specification information acquired by data acquisition unit 21 via data communication network DN and offline data acquired without via data communication network DN. The offline data may be, for example, information acquired by an operator when installing water heater 1, or information acquired from a questionnaire filled out by a user.

[0021] Fault diagnosis unit 23 includes diagnosis section 23A and group data generation section 23B. Fault diagnosis unit 23 diagnoses whether or not the operating state data acquired from water heater 1 meets a fault criterion, based on the group data (arrangement table in this embodiment) generated by group data generation section 23B.

[0022] Group data generating unit 23B creates a plurality of arrangement tables as shown in FIG. 3 based on the data stored in data storage unit 22, and stores the arrangement tables. That is, group data generating unit 23B generates a plurality of group data based on the specification information of each of the plurality of water heaters 1 and the use environment of each of the plurality of water heaters 1. In FIG. 3, four two-dimensional arrangement tables are shown as the plurality of group data. That is, each of the plurality of group data is composed of a two-dimensional arrangement table. In FIG. 3, an arrangement table (a) for a water heater 1 with one can and two water units installed in an apartment house, an arrangement table (b) for a water heater 1 with one can and two water units installed in a detached house, an arrangement table (c) for a water heater 1 with two cans and three water units installed in an apartment house, and an arrangement table (d) for a water heater 1 with two cans and three water units installed in a detached house are shown. In each arrangement table, the number of years of use is shown in the row direction, and the number of family members (number of people in a household) is shown in the column direction.

[0023] In other words, multiple water heaters 1 that are assumed to have similar usage conditions are grouped into rows and columns in the array table based on the specification information of the water heater 1, household information for the installation location of the water heater 1, etc. The deterioration level of the water heaters 1 grouped within one row is assumed to be the same.

[0024] A threshold value (reference value) for diagnosing a failure of the water heater 1 is set in each of the cells of the rows and columns in the arrangement table. The threshold value set in each of the cells of the rows and columns in the arrangement table may be set, for example, based on statistical information of past failure history, or may be set by machine learning using artificial intelligence. Also, one threshold value may be set in one cell, or multiple threshold values ​​may be set for each type of part.

[0025] Diagnosis unit 23A diagnoses the maintenance of water heater 1 to be diagnosed by comparing a reference value set in an arrangement table corresponding to the specification information acquired from water heater 1 to be diagnosed with the operation information data acquired from water heater 1 to be diagnosed. Details of diagnosis unit 23A will be described later.

[0026] The notification unit 24 notifies information regarding the failure of the water heater 1 to be diagnosed and / or the timing of maintenance, based on the diagnosis result of the failure diagnosis unit 23. Specifically, a notification signal from the notification unit 24 is transmitted to the external terminal 3 via the data communication network DN. The external terminal 3 is a terminal that is set in advance for notification, and may be, for example, a computer of a maintenance company, or a terminal owned by a user or a maintenance technician.

[0027] [Fault diagnosis unit diagnostic method] A diagnosis method of the fault diagnosis unit 23 will be described with reference to Figs. 4 and 5. The flowchart shown in Fig. 4 is performed in a periodic process such as on a daily basis. First, the fault diagnosis unit 23 collates the specification information sent from the water heater 1 to be diagnosed via the data communication network DN with the basic information data group stored in the data storage unit 22 (step #01). The basic information data group stored in the data storage unit 22 includes, in addition to the specification information of the water heater 1, information on the installation location and installation time of the water heater 1 of the model number, information on the building at the installation location (for example, information on detached house, apartment house, owner-occupied house, rental, age, insulation performance, etc.), information on the household information at the installation location (family composition, generational information), and other information on the usage environment. In other words, the basic information data group includes the specification information of the water heater 1, and the specification information sent from the water heater 1 of each household via the data communication network DN is linked to the basic information data group stored in the data storage unit 22. Then, based on the specification information sent from the water heater 1 of each home via the data communication network DN, basic information data linked to the specification information is read from the data storage unit 22. In this way, the diagnosis unit 23A identifies the usage environment of the water heater 1 based on the basic information data acquired from the water heater 1 via the data communication network DN.

[0028] When basic information data linked to the specification information of water heater 1 is read from data storage unit 22, diagnosis unit 23A selects the arrangement table that best matches the read basic information data from among the multiple arrangement tables stored in group data generation unit 23B (step #02). For example, assume that the read basic information data contains information on a one-can, two-water type as the structure of water heater 1, and information on a detached house is included in the building information on the installation location of water heater 1. In this case, diagnosis unit 23A selects the arrangement table of (b) "one-can, two water, detached house" from among the arrangement tables shown in FIG. 3.

[0029] The diagnosis unit 23A selects a square in the selected arrangement table that corresponds to the basic information data read from the data storage unit 22 (step #03). If the installation date of the water heater 1 is included in the read basic information data, the number of years of use of the water heater 1 is calculated. For example, assume that the household information for the installation location of the water heater 1 includes information on a four-person family, and that the number of years of use of the water heater 1 is seven years. In this case, the square in the third row and fourth column is selected in the arrangement table shown in FIG. 3. If the arrangement table of "1 can, 2 water, detached house" in FIG. 3 is selected in step #02, the square of "B47" in FIG. 3 is selected in step #03. A threshold value is set in the square. The diagnosis unit 23A is configured to select a threshold value according to the identified usage environment from a plurality of threshold values ​​arranged in the arrangement table.

[0030] The diagnosis unit 23A judges whether the numerical value of the operating state data reaches the standard set in the selected cell (step #04). The water heater 1 is provided with a combustion fan that sends air to the burner, and the threshold value of the rotation speed of the combustion fan as shown in FIG. 5, for example, is set in each cell of the arrangement table shown in FIG.

[0031] Fig. 5 shows a graph indicating the change over time in the rotation speed of the combustion fan. The horizontal axis of the graph in Fig. 5 is the time axis, and the vertical axis is the measured maximum rotation speed of the combustion fan. The time axis indicates the elapsed time from the time when the water heater 1 was installed. The threshold value set in the selected square is indicated on the vertical axis of the graph in Fig. 5 as the threshold value for the rotation speed of the combustion fan.

[0032] The operating status data sent from the water heater 1 via the data communication network DN includes the maximum measured rotation speed of the combustion fan. In the graph of Figure 5, the maximum measured rotation speed of the combustion fan is plotted over time. For example, if dust accumulates in the combustion fan or in the intake and exhaust piping, the amount of air supplied to the burner decreases, causing the rotation speed of the combustion fan to increase. For this reason, in the graph of Figure 5, the maximum measured rotation speed of the combustion fan increases over the years.

[0033] As shown in the graph of FIG. 5, the diagnostic unit 23A calculates future estimated data based on past performance data, and calculates the maintenance time when the measured maximum rotation speed of the combustion fan is predicted to reach the threshold value. Then, when the measured maximum rotation speed of the combustion fan has reached the threshold value, or when the measured maximum rotation speed of the combustion fan is about to reach the threshold value, the diagnostic unit 23A determines that the numerical value of the operation state data has reached the standard (step #04: Yes). The maintenance time may be a time when the water heater 1 is estimated to break down, or may be a time when the water heater 1 is estimated to require maintenance even if the water heater 1 does not break down. In this way, the diagnostic unit 23A is configured to estimate the time when the value of the operation information data exceeds the standard value as the maintenance time.

[0034] If the determination in step #04 is Yes, the notification unit 24 performs notification processing (step #05), and a notification signal from the notification unit 24 is transmitted to the external terminal 3 via the data communication network DN. This prompts, for example, a user or a maintenance person to replace parts of the water heater 1 or perform maintenance.

[0035] If the measured maximum rotation speed of the combustion fan does not reach the threshold value and the result of the determination in step #04 is No, the diagnosis unit 23A determines whether the period when the numerical value of the operating state data is predicted to exceed the threshold value is a busy period based on the maintenance period (step #06). A busy period is a period when the schedule of workers tends to be overcrowded due to, for example, frequent breakdowns of the water heater 1.

[0036] The busy period may be set artificially in the management computer 2 based on, for example, past trends, or may be set to a period when the maintenance periods for multiple water heaters 1 overlap at the same time. If the maintenance period overlaps with the busy period (step #06: Yes), the notification unit 24 shifts the maintenance period to a period before the busy period and performs the notification process (step #07). For example, the notification unit 24 may perform the notification process by avoiding periods that are considered to be busy periods based on past trends, or may perform the notification process at a period that does not overlap much with the notification processes for other water heaters 1. If the maintenance period does not overlap with the busy period (step #06: No), the process ends.

[0037] In this way, the fault diagnosis unit 23 selects an arrangement table based on the specification information sent from the water heater 1 via the data communication network DN, and further selects a cell within the arrangement table. The fault diagnosis unit 23 also determines whether the numerical value of the operating state data sent from the water heater 1 via the data communication network DN reaches the standard set for that cell. The deterioration level of water heaters 1 grouped within one cell is assumed to be the same. For this reason, even for water heaters 1 of a model that is installed in small numbers and has not been adequately analyzed, it is possible to perform the same diagnosis as for other water heaters 1 in the same cell. This makes it possible to perform fault diagnosis on a wide variety of water heaters 1.

[0038] There are many water heaters 1 that are not connected to the data communication network DN, and it is desirable to have a configuration that can estimate the maintenance time as accurately as possible for such water heaters 1. When the water heater 1 is not connected to the data communication network DN, the most suitable arrangement table is selected from multiple arrangement tables stored in the group data generation unit 23B based on the offline data of the basic information data group stored in the data storage unit 22 (family composition, presence or absence of floor heating function, presence or absence of bathroom drying and heating function, insulation performance of the house, etc.). Then, the general usage state is estimated based on the operating state data of the water heater 1 that is actually connected to the data communication network DN. As a result, even if the water heater 1 is not connected to the data communication network DN, the diagnosis unit 23A can estimate the maintenance time based on the number of years of use of the water heater 1.

[0039] A basic information data group of the water heater 1 to be maintained is stored in data storage unit 22. When maintenance work such as part replacement is performed on water heater 1 at the maintenance time, the basic information data group of the water heater 1 to be maintained is updated, and the maintenance history of water heater 1 is overwritten and saved in the basic information data group. Diagnosis unit 23A recalculates an estimate for the next maintenance time for water heater 1 based on the maintenance history. Note that the process of updating the basic information data group may be executed by an operator manually operating management computer 2 or external terminal 3, or may be configured to be executed automatically when the control unit of water heater 1 automatically reads out the serial number of the replacement part and detects a change in the serial number.

[0040] [Another embodiment] The present invention is not limited to the configurations exemplified in the above-described embodiments, and other representative embodiments of the present invention will be described below.

[0041] (1) In the above embodiment, each of the plurality of group data is configured as a two-dimensional array table, but the array table may be configured in three or more dimensions. Also, the group data may be configured as, for example, a hash table.

[0042] (2) The four arrangement tables shown in Fig. 3 are configured with combinations of 1 can, 2 water / 2 cans, 3 water, and detached house / apartment house, but are not limited to this embodiment. For example, the multiple arrangement tables may be configured with combinations of manufacturer, hot water number of water heater 1, new building / existing building, presence or absence of latent heat recovery mechanism in water heater 1, fuel type, hot water supply method of water heater 1 (instantaneous / storage type), water quality of the installation location, etc. In other words, group data generation unit 23B only needs to generate multiple group data based on at least one of the specification information stored in data storage unit 22 and the usage environment.

[0043] (3) In the four arrangement tables shown in Fig. 3, the years of use are shown in the row direction and the number of family members in the column direction, but this is not limited to this embodiment. For example, the distance from the coast where the water heater 1 is installed may be shown in the row direction, and the age group of the user of the water heater 1 may be shown in the column direction. In other words, it is sufficient that multiple reference values ​​are arranged in the arrangement table in a state where they are classified according to the usage environment of the water heater 1.

[0044] (4) In the graph of FIG. 5, the vertical axis shows the measured maximum rotation speed of the combustion fan, but this vertical axis may also show, for example, the current value of the motor that rotates the combustion fan, the rotation speed of the bath pump, the rotation speed of the floor heating pump, the PWM ratio in the control unit, the temperature of the thermistor provided in the water heater 1, etc.

[0045] (5) In the above embodiment, the basic information data group and the driving state data group are stored in the data storage unit 22 of the management computer 2, but this is not limiting. For example, the basic information data group and the driving state data group may be stored in a cloud server separate from the management computer 2.

[0046] The configurations disclosed in the above-mentioned embodiments (including other embodiments, the same applies below) can be applied in combination with configurations disclosed in other embodiments, unless a contradiction occurs. In addition, the embodiments disclosed in this specification are merely examples, and the present invention is not limited to these embodiments, and can be appropriately modified within the scope of the present invention. [Industrial Applicability]

[0047] The present invention can be applied to a failure estimation system for a water heater. [Explanation of symbols]

[0048] 1: Water heater 21: Data acquisition section 22: Data storage section 23A: Diagnostics Department 23B: Group data generation unit 24: Information Department DN: Data communication network

Claims

1. A failure estimation system for a water heater installed in each home, A data storage unit that stores specification information and usage environment of each of the plurality of water heaters; A data acquisition unit that acquires the specification information and operation information data related to the operation state of the water heater from each of the plurality of water heaters via a data communication network; a group data generating unit that generates a plurality of group data based on the specification information and the usage environment stored in the data storage unit; a diagnosis unit that diagnoses the maintenance of the water heater to be diagnosed by comparing a reference value set in the group data corresponding to the specification information acquired from the water heater to be diagnosed with the operation information data acquired from the water heater to be diagnosed; A water heater failure inference system comprising: an alarm unit that notifies the user when it is time to perform maintenance on the water heater based on the diagnosis results of the diagnosis unit.

2. Each of the plurality of group data is configured by a two- or more-dimensional array table, The plurality of reference values ​​are arranged in the array table in a state where they are classified according to the usage environment, The water heater failure estimation system of claim 1, wherein the diagnostic unit is configured to identify the usage environment of the water heater based on the specification information obtained from the water heater via the data communication network and the specification information and the usage environment stored in the data storage unit, and to select the reference value corresponding to the identified usage environment from the multiple reference values.

3. 3. The water heater failure inference system according to claim 1, wherein the diagnosing unit is configured to infer that the maintenance time is determined based on a time when the value of the operation information data exceeds the reference value.

4. The water heater failure estimation system of claim 3, wherein the notification unit is configured to, if the maintenance period overlaps with a busy period for workers, shift the maintenance period to a period before the busy period and notify the user.

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