Diagnostic method, program, and diagnostic system

Abstract

The diagnostic method includes a collection step (S11) of collecting data for a prescribed period, a time determination step (S12) of determining, based on the data, a time at which a state changes from a state not satisfying a specific condition to a state satisfying the specific condition, a division step (S13) of dividing the prescribed period with the time to generate a plurality of intervals that are continuous in time, and setting each of the generated plurality of intervals as an aggregation interval of the data, a generation step (S14) of performing aggregation processing on a value of a control target of an apparatus included in the data for each of the plurality of aggregation intervals in the prescribed period to generate diagnostic data, a state determination step (S15) of determining, based on the diagnostic data, whether a state of the apparatus in each of the plurality of aggregation intervals is normal, and a diagnosis step (S16) of diagnosing the state of the apparatus based on determination results for a plurality of continuous aggregation intervals among the plurality of aggregation intervals.

Description

Technical Field

[0001] This disclosure relates to diagnostic methods for diagnosing the condition of continuously operating equipment. Background Technology

[0002] Patent document 1 discloses a technique for diagnosing the state of a device using motion history.

[0003] Existing technical documents Patent documents Patent Document 1: Japanese Patent Application Publication No. 2019-160109 Summary of the Invention

[0004] The problem that the invention aims to solve In continuously operating equipment such as refrigerators, specific controls for cooling the interior (e.g., compressor operation or damper opening) are performed irregularly and continuously at set intervals, varying according to the internal temperature. As disclosed in Patent Document 1, when using the operation history for each fixed period to diagnose the equipment's condition, deviations sometimes occur in the number of times these specific controls are performed within each fixed period, and the summarized results of the operation history for each fixed period (e.g., the number of temperature rises or cooling events) also deviate. In such cases, it is difficult to accurately diagnose the equipment's condition.

[0005] Therefore, this disclosure provides diagnostic methods, etc., for easily and accurately diagnosing the condition of a device.

[0006] Methods for solving problems The diagnostic method disclosed herein diagnoses the state of continuously operating equipment, comprising: a collection step, collecting data over a specified period, the data being used to diagnose the state of the equipment; a time determination step, based on the data, determining the times within the specified period when a state change occurs irregularly and continuously at regular intervals, from not meeting a specific condition related to the equipment to meeting the specific condition; a setting step, dividing the specified period by the times to generate multiple temporally continuous intervals, and setting each of the generated multiple intervals as a summary interval serving as a unit for summarizing the data; a generation step, for each of the multiple summary intervals within the specified period, summarizing the values ​​of the control objects of the equipment contained in the data to generate diagnostic data; a state determination step, based on the diagnostic data, determining whether the state of the equipment in each of the multiple summary intervals is normal; and a diagnostic step, diagnosing the state of the equipment based on the determination results for the multiple consecutive summary intervals within the multiple summary intervals.

[0007] The program disclosed herein is a program for causing a computer to perform the diagnostic methods described above.

[0008] The diagnostic system disclosed herein diagnoses the state of continuously operating equipment, comprising: a collection unit that collects data over a predetermined period, the data being used to diagnose the state of the equipment; a time determination unit that, based on the data, determines the times during the predetermined period when a state change occurs irregularly and continuously at regular intervals, changing from a state that does not meet a specific condition related to the equipment to a state that meets the specific condition; a setting unit that divides the predetermined period into multiple time-continuous intervals by the times, and sets each of the generated multiple intervals as a summary interval serving as a unit for summarizing the data; a generation unit that, for each of the multiple summary intervals within the predetermined period, summarizes the values ​​of the control objects of the equipment contained in the data, thereby generating diagnostic data; a state determination unit that, based on the diagnostic data, determines whether the state of the equipment in each of the multiple summary intervals is normal; and a diagnostic unit that, based on the determination results for the multiple consecutive summary intervals within the multiple summary intervals, diagnoses the state of the equipment.

[0009] Furthermore, these general or specific technical solutions can be implemented through systems, methods, integrated circuits, computer programs, or computer-readable CD-ROMs and other recording media, or through any combination of systems, methods, integrated circuits, computer programs, and recording media.

[0010] Invention Effects The condition of the equipment can be easily and accurately diagnosed using the diagnostic methods and other methods disclosed herein. Attached Figure Description

[0011] Figure 1 This is a diagram illustrating an example of the structure of a diagnostic system according to an implementation method.

[0012] Figure 2 This is a flowchart illustrating an example of the operation of a diagnostic system implemented in this way.

[0013] Figure 3 This is a diagram schematically illustrating an example of the operation of a diagnostic system according to an implementation method.

[0014] Figure 4 This is a graph representing an example of data for each summary interval.

[0015] Figure 5 This is a graph representing an example of data for each summary interval when chronic adverse events occur. Detailed Implementation

[0016] Hereinafter, embodiments will be described in detail with appropriate reference to the accompanying drawings. However, sometimes unnecessary detailed descriptions are omitted. For example, detailed descriptions of matters already known or repeated descriptions of substantially the same structures are sometimes omitted. This is to avoid making the following description unnecessarily lengthy and to facilitate understanding by those skilled in the art.

[0017] Furthermore, the inventors have provided the accompanying drawings and the following description in order to enable those skilled in the art to fully understand this disclosure, but they are not intended to limit the subject matter of the claims.

[0018] (Implementation Method) The following uses Figures 1 to 5 The diagnostic methods and diagnostic systems for the implementation methods are described.

[0019] Figure 1 This is a diagram illustrating an example of the structure of the diagnostic system 100 according to an embodiment. Furthermore, in Figure 1 In addition to the diagnostic system 100, device 200 is also shown.

[0020] The diagnostic system 100 is a system for diagnosing the state of a continuously operating device 200. Device 200 is a device that operates substantially continuously, such as a refrigerator. To maintain a constant internal temperature, the refrigerator performs specific controls such as cooling the interior (e.g., controlling the compressor or opening the damper). These specific controls begin when the internal temperature exceeds a target temperature range and end when it falls below that range, thus being executed continuously at irregular intervals (e.g., every tens of minutes) depending on the internal temperature. Alternatively, the specific controls can be for heating the interior (e.g., defrosting control), in which case the specific control begins after a time equivalent to a parameter set based on the external temperature has elapsed since the last control and ends when the temperature exceeds a specific limit. In summary, device 200 continuously executes specific controls at irregular intervals during its continuous operation.

[0021] The diagnostic system 100 includes a collection unit 10, a time determination unit 20, a setting unit 30, a generation unit 40, a status determination unit 50, and a diagnostic unit 60. The diagnostic system 100 is a computer including a processor (microprocessor) and memory. The memory is ROM (Read Only Memory) or RAM (Random Access Memory), etc., and is capable of storing programs executed by the processor. The collection unit 10, time determination unit 20, setting unit 30, generation unit 40, status determination unit 50, and diagnostic unit 60 are implemented by a processor that executes programs stored in the memory.

[0022] For example, the diagnostic system 100 can be a single-shell computer (device) or a system composed of multiple computers. For example, the diagnostic system 100 can also be a server. Furthermore, the components of the diagnostic system 100 can be configured on a single server or distributed across multiple servers. Additionally, for example, the diagnostic system 100 can also be mounted on device 200.

[0023] The collection unit 10 collects data that is data within a specified period and is used to diagnose the status of the device 200. This data used to diagnose the status of the device 200 will also be referred to as raw data. For example, if the specified period is two days, the collection unit 10 collects raw data for those two days. For example, the raw data is data measured at regular intervals (e.g., 5 minutes) within the device 200. For example, the raw data includes information such as the internal temperature of the refrigerator (temperature of the refrigerator compartment, vegetable compartment, or freezer compartment, etc.), the compressor frequency, the opening and closing status of the damper, and the defrosting operation status. For example, the diagnostic system 100 has a communication interface, and the diagnostic system 100 receives the raw data from the device 200 wirelessly or via a wired connection, thereby enabling the collection unit 10 to collect this data.

[0024] The timing determination unit 20, based on the raw data, determines the moments (hereinafter also referred to as moments when specific conditions are met) that occur irregularly and continuously within a specified period, changing from a state that does not meet specific conditions related to the device 200 to a state that meets those specific conditions. Specific conditions can be conditions such as receiving specific control as shown in the above-described example of device 200 operation, conditions such as a specific operation performed by the user, or conditions such as the internal temperature being above a specified temperature. For example, the moment when a specific condition is met is the start or end time of control to drive the compressor, control to open the damper, or control to defrost. By parsing the raw data, the timing determination unit 20 can determine the timing when the compressor frequency changes from 0Hz to 1Hz or higher as the start time of compressor control, the timing when the damper opens as the start time of damper control, and the timing when defrosting begins as the start time of defrosting control. Furthermore, by analyzing the raw data, the timing determination unit 20 can determine the timing when the compressor frequency changes from above 1Hz to 0Hz as the end time of compressor control, the timing when the damper closes as the end time of damper opening control, and the timing when defrosting ends as the end time of defrosting control. These specific controls—compressor control, damper opening control, and defrosting control—are executed continuously at irregular timings (e.g., every tens of minutes), therefore, the start or end time corresponding to the irregular timing that varies according to the internal temperature is determined respectively.

[0025] The setting unit 30 divides the predetermined period into multiple temporally continuous intervals at times determined by the time determination unit 20 that occur irregularly and continuously within a predetermined period. Each of these multiple intervals is set as a summary interval serving as a unit for summarizing the original data. For the generated multiple intervals, the intervals between adjacent times are arranged temporally consecutively within the predetermined period. For example, a specific condition is met when the internal temperature exceeds a target temperature range; subsequently, the specific condition is no longer met when the internal temperature falls below the target temperature range; and then the specific condition is met again when the internal temperature exceeds the target temperature range. Therefore, the interval between adjacent start times is the period from when the specific condition is met until the next specific condition is met. In other words, a summary interval is set corresponding to the period during which the specific condition is met.

[0026] In addition, the timing when specific conditions are met is an irregular timing that varies depending on the temperature inside the chamber. Therefore, the time length of each of the multiple summary intervals within the specified period may not be fixed, but may differ from the time length of other summary intervals.

[0027] The generation unit 40 performs summary processing on the values ​​of the controlled objects of the device 200 contained in the original data for each of the multiple summary intervals within a specified period, thereby generating diagnostic data. For example, if the value of the controlled object of the device 200 is the internal temperature, the generation unit 40 generates the result of summarizing the internal temperature for each of the multiple summary intervals as diagnostic data.

[0028] Summary processing involves calculating statistical quantities (average, median, maximum, or minimum values, etc.) of the controlled object values ​​within a summary interval, or calculating changes. Furthermore, summary processing can also be performed on the values ​​of controlled objects within a portion of the summary interval. That is, summary processing does not necessarily have to be performed on the values ​​of all controlled objects within the entire summary interval. Specifically, summary processing can be performed on the values ​​of controlled objects of device 200 between the time when a state changes from not meeting a specific condition to meeting the specific condition, and the time when a state changes from meeting the specific condition to no longer meeting the specific condition (hereinafter also referred to as the time from meeting the specific condition to the time when the specific condition is no longer met). It can also be performed on the values ​​of controlled objects of device 200 between the time when a state changes from meeting the specific condition to no longer meeting the specific condition, and the time when the state changes from not meeting the specific condition to meeting the specific condition again (hereinafter also referred to as the time from the time when the specific condition is no longer met to the time when the specific condition is met again).

[0029] The status determination unit 50 determines whether the status of the device 200 in each of multiple summary intervals is normal based on diagnostic data. Details regarding the operation of the status determination unit 50 will be described later.

[0030] The diagnostic unit 60 diagnoses the status of the device 200 based on the determination results of multiple consecutive summary intervals from the status determination unit 50. Details regarding the operation of the diagnostic unit 60 will be described later.

[0031] Next, use Figure 2 and Figure 3 Specific examples will be provided to illustrate the details of the operation of the diagnostic system 100. Furthermore, the following will explain the moment when a specific condition is met as the start moment for starting a specific control.

[0032] Figure 2 This is a flowchart illustrating an example of the operation of the diagnostic system 100 according to an embodiment. Furthermore, the diagnostic method of this embodiment is a method executed by the diagnostic system 100, therefore... Figure 2 This is also a flowchart illustrating an example of a diagnostic method in an implementation. The operation of the collection unit 10 corresponds to the collection step in the diagnostic method, the operation of the time determination unit 20 corresponds to the time determination step in the diagnostic method, the operation of the setting unit 30 corresponds to the setting step in the diagnostic method, the operation of the generation unit 40 corresponds to the generation step in the diagnostic method, the operation of the state determination unit 50 corresponds to the state determination step in the diagnostic method, and the operation of the diagnostic unit 60 corresponds to the diagnostic step in the diagnostic method.

[0033] Figure 3 This is a diagram schematically illustrating an example of the operation of the diagnostic system 100 according to an embodiment.

[0034] First, the collection unit 10 collects raw data within a specified period (step S11). For example, if the device 200 measures data every 5 minutes, and the collection unit 10 collects raw data for 300 minutes, then... Figure 3 As shown, the collection unit 10 collects raw data with a sequence length (number of data points) of 60.

[0035] Next, based on the raw data, the timing determination unit 20 determines the times (start times) when the device 200 meets a specific condition and occurs continuously at irregular intervals within a specified period (step S12). For example, the time that meets the specific condition is when the compressor frequency changes from 0Hz to 1Hz or more. For example, if the timing determination unit 20 determines that there are 5 instances of the compressor frequency changing from 0Hz to 1Hz or more within a specified period (e.g., 300 minutes) by parsing the raw data, it determines each of the 5 timing instances as the start time for controlling the compressor.

[0036] Next, the setting unit 30 divides the specified period into multiple time-continuous intervals by the start time, and sets each of the multiple intervals between the generated start times as a summary interval as a summary unit for the original data (step S13). For example, as Figure 3 As shown, the setting unit 30 sets the interval from the start time of the first execution of the control that drives the compressor for a certain period within a specified period to the start time of the second execution of the control that drives the compressor for a certain period as the summation interval 1 of the sequence length 10. Similarly, the setting unit 30 sets the summation interval 2 of the sequence length 12, the summation interval 3 of the sequence length 20, the summation interval 4 of the sequence length 8, and the summation interval 5 of the sequence length 10.

[0037] For example, the start time of a specific control is determined based on the type of abnormality of the diagnostic object in order to set the summary interval. Specifically, if the diagnostic object is an abnormality of equipment 200 related to the internal temperature of the chamber, the start time of the control for cooling the internal chamber (such as the drive of the compressor or the control for opening the damper) or the control for heating the internal chamber (such as the defrost control) is determined, and the summary interval is set based on the start time.

[0038] The generation unit 40 summarizes the values ​​of the controlled objects of the device 200 contained in the original data for each of the multiple summary intervals within a specified period, thereby generating diagnostic data (step S14). For example, as... Figure 3 As shown, the generation unit 40 performs summary processing on the temperature inside the chamber and other data for each of the summary intervals 1 to 5, generating diagnostic data with a sequence length of 5.

[0039] For example, diagnostic data, for each of multiple summary intervals within a specified period, includes a condition-compliant change, which is the change in the value of the controlled object of device 200 during the period from the moment a specific condition is met (e.g., the start time of a specific control) to the moment when that specific condition is no longer met (e.g., the end time of a specific control that began at the aforementioned start time). Specifically, the condition-compliant change is the difference between the value of the controlled object at the start time and the value of the controlled object at the end time. For example, the condition-compliant change is the change in the internal temperature of the compressor during operation or the change in the internal temperature of the damper during operation.

[0040] Additionally, for example, the diagnostic data for each of multiple summary intervals includes a change in the amount of time the condition is not met. This change in the amount of time the condition is not met is the change in the value of the controlled object of device 200 from the moment when the specific condition is no longer met (e.g., the end time of a specific control) to the moment when the specific condition is met again (the start time of the specific control in the next summary interval). Specifically, the change in the amount of time the condition is not met is the difference between the value of the controlled object measured by device 200 immediately after the end time (e.g., 5 minutes later) and the value of the controlled object measured by device 200 immediately before the start time in the next summary interval (e.g., 5 minutes earlier). For example, the change in the amount of time the condition is not met is the change in the chamber temperature during compressor shutdown or the change in the chamber temperature during damper closure.

[0041] Additionally, for example, the diagnostic data for each of multiple summary intervals includes a statistic of the values ​​of the controlled objects of device 200 within that summary interval. Specifically, the statistic is the average, median, maximum, or minimum value of the controlled objects of device 200 within the summary interval.

[0042] For example, the type of summary processing is determined based on the type of abnormality of the diagnostic object. Specifically, when a summary range corresponding to the control of cooling inside the chamber is set, when diagnosing an abnormality where the temperature inside the chamber does not decrease, the summary processing of the change in the amount of change when the condition is met is performed; when diagnosing an abnormality where the temperature inside the chamber does not rise, the summary processing of the change in the amount of change when the condition is not met is performed; and when diagnosing an abnormality where the temperature inside the chamber is too high or too low, the summary processing of the statistical quantity is performed.

[0043] The status determination unit 50 determines whether the status of the device 200 in each of the multiple summary intervals is normal based on diagnostic data (step S15). For example, the status determination unit 50 determines whether the status of the device 200 in each summary interval is normal by comparing the diagnostic data and the hypothetical data for each summary interval. The hypothetical data is data expected to be obtained by satisfying specific conditions; in other words, it is data expected to be obtained by executing specific controls. For example, by executing specific controls when the device 200 is normal, it is possible to predict how the value of the controlled object will change, and hypothetical data expected to be obtained by executing specific controls can be generated for each summary interval. Therefore, by comparing the diagnostic data with the hypothetical data expected to be obtained by satisfying specific conditions, for example, if specific controls were executed during a period when specific conditions were satisfied, it is easy to determine whether the summary result in the summary interval corresponding to that specific control is as assumed. Furthermore, the value of the controlled object can change according to the value of the controlled object in the previous summary interval, so the hypothetical data is also data that can change dynamically for each summary interval. That is, the hypothetical data is generated by making predictions for each summary interval.

[0044] For example, it is possible to predict or predetermine the change in the value of the controlled object during the period from the start time to the end time of a specific control when the device 200 is operating normally (hypothetical data). Therefore, the state determination unit 50 can also determine whether the state of the device 200 in the summary interval is normal by comparing the change when the condition is met with the hypothetical data corresponding to the change when the condition is met (i.e., by comparing by each summary interval). By comparing the change when the condition is met with the hypothetical data corresponding to the change when the condition is met, it is possible to determine whether the state of the device 200 in the period from the time the specific condition is met until the specific condition is no longer met, which is included in the summary interval.

[0045] For example, it is possible to predict or predetermine the change in the value of the controlled object (hypothetical data) during the period from the end of a specific control when the device 200 is operating normally to the start of a specific control in the next summary interval. Therefore, the state determination unit 50 can also determine whether the state of the device 200 in the summary interval is normal by comparing the change when the condition is not met with the hypothetical data corresponding to the change when the condition is not met (i.e., after the specific control ends) expected to be obtained (for example, by comparing by each summary interval). By comparing the change when the condition is not met with the hypothetical data corresponding to the change when the condition is not met, it is possible to determine whether the state of the device 200 in the period from when the specific condition is no longer met to when the specific condition is met again, which is included in the summary interval.

[0046] For example, a statistic can be used to predict or predetermine the value of the control object in the summary interval when the device 200 is operating normally. Therefore, the status determination unit 50 can also determine whether the status of the device 200 in the summary interval is normal by comparing the statistic with the hypothetical data corresponding to the statistic that is expected to be obtained by meeting specific conditions (for example, by comparing by each summary interval). By comparing the statistic with the hypothetical data corresponding to the statistic, it is possible to determine whether the status of the device 200 in the summary interval is normal.

[0047] Furthermore, the diagnostic unit 60 diagnoses the status of the device 200 based on the determination results of the status determination unit 50 for multiple consecutive summary intervals among multiple summary intervals (step S16).

[0048] For example, the diagnostic unit 60 can also diagnose the state of the device 200 based on the number of consecutive intervals deemed abnormal. For instance, if the number of consecutive intervals deemed abnormal is more than a predetermined number, the diagnostic unit 60 diagnoses the device 200 as having a chronic abnormality. The predetermined number is not particularly limited. For example, if the predetermined number is 3 times... Figure 3 If summary intervals 1 and 2 are judged as normal, and summary intervals 3-5 are judged as abnormal, and the number of consecutive abnormal summary intervals is 3, the diagnostic unit 60 diagnoses the equipment 200 as having a chronic malfunction. Thus, when there are many consecutive abnormal summary intervals, a chronic defect can be diagnosed. Furthermore, for example, in... Figure 3 If the summary intervals 1, 2, 4, and 5 are judged as normal, and the summary interval 3 is judged as abnormal, the number of consecutive times the summary interval is judged as abnormal is 1. The diagnostic unit 60 diagnoses that a temporary increase in load has occurred in the equipment 200, such as the refrigerator door being opened.

[0049] For example, the diagnostic unit 60 can also diagnose the state of the device 200 based on the continuous duration of the summary intervals deemed abnormal. For instance, if the continuous duration of the summary intervals deemed abnormal exceeds a predetermined time, the diagnostic unit 60 diagnoses the device 200 as having a chronic abnormality. The predetermined time is not particularly limited. For example, if the predetermined time is 180 minutes... Figure 3 If summary intervals 1 and 2 are judged as normal, and summary intervals 3-5 are judged as abnormal, and the continuous time of the summary intervals judged as abnormal is 190 minutes (sequence length 38 × 5 minutes), the diagnostic unit 60 diagnoses the device 200 as having a chronic malfunction. Thus, when the continuous time of the summary intervals judged as abnormal is long, a chronic malfunction can be diagnosed. Furthermore, for example, in... Figure 3 If the summary intervals 1, 2, 4, and 5 are judged as normal, and the summary interval 3 is judged as abnormal, the continuous time of the summary interval judged as abnormal is 100 minutes (sequence length 20 × 5 minutes). The diagnostic unit 60 diagnoses that a temporary increase in load has occurred in the equipment 200, such as the refrigerator door being opened.

[0050] Next, use Figure 4 Examples of data for each summary interval are provided.

[0051] Figure 4 This is a graph representing an example of data for each summary interval. In Figure 4 The data is shown for six consecutive summary intervals. The shaded area represents the period during which cooling of the chamber was implemented as a specific control (hereinafter referred to as the cooling period).

[0052] In the first and second summary intervals, the length of the cooling period, the maximum temperature, and the minimum temperature remained stable, indicating that equipment 200 was in normal condition. In the third and fourth summary intervals, the cooling period lengthened, indicating that the maximum temperature was increasing. In the fifth and sixth summary intervals, the length of the cooling period remained stable, indicating that the minimum temperature was increasing.

[0053] Next, use Figure 5 Examples of data for each summary interval when chronic adverse events occur are provided.

[0054] Figure 5 This is a graph representing an example of data for each summary interval when chronic adverse events occur. The shaded area is... Figure 4 It is also during the cooling period.

[0055] like Figure 5 As shown, after 14:00, although it was cooling, the temperature inside the chamber rose and remained at a high temperature, so it can be diagnosed as a chronic malfunction.

[0056] As explained above, a summary interval is set corresponding to the period during which specific conditions are met. For each of the set summary intervals, the value of the controlled object of device 200 is summarized. Therefore, for example, if a specific control is executed during the period when specific conditions are met, it is easy to determine whether the summary result in the summary interval corresponding to that specific control is as assumed, i.e., whether the state of device 200 is normal. Furthermore, by using the results of the determination of multiple consecutive summary intervals, it is possible to diagnose whether a temporary increase in load has occurred, or whether a chronic malfunction has occurred. In this way, the state of device 200 can be easily and accurately diagnosed.

[0057] (Other implementation methods) As described above, embodiments have been presented as examples of the technology disclosed in this application. However, the technology in this disclosure is not limited thereto, and can be applied to embodiments with appropriate modifications, substitutions, additions, omissions, etc. Furthermore, new embodiments can be created by combining the constituent elements described in the above embodiments.

[0058] For example, this disclosure can be implemented as a program for causing a computer (processor) to perform the steps included in a diagnostic method. Furthermore, this disclosure can be implemented as a non-transitory computer-readable recording medium such as a CD-ROM containing the program.

[0059] For example, when this disclosure is implemented by a program (software), the steps are executed by utilizing the computer's hardware resources such as the CPU, memory, and input / output circuits. That is, the CPU retrieves data from the memory or input / output circuits and performs calculations, or outputs the calculation results to the memory or input / output circuits, thereby executing the steps.

[0060] Furthermore, in the above embodiments, each component of the diagnostic system 100 may be constructed using dedicated hardware, or implemented by executing software programs suitable for each component. Each component may also be implemented by having a program execution unit such as a CPU or processor read and execute software programs recorded on a recording medium such as a hard disk or semiconductor memory.

[0061] The diagnostic system 100 of the above embodiments typically implements some or all of its functions as an integrated circuit, i.e., an LSI. These can be implemented as a single chip, or as a single chip including some or all of the functions. Furthermore, integrated circuit implementation is not limited to LSIs; it can also be implemented using dedicated circuits or general-purpose processors. LSIs can also utilize FPGAs (Field Programmable Gate Arrays) that can be programmed after manufacturing, or reconfigurable processors that can reconfigure the connections and settings of the circuit cells within the LSI.

[0062] Furthermore, if an integrated circuit technology that replaces the LSI emerges with the advancement of semiconductor technology or other derived technologies, then of course this technology can also be used to integrate the various components included in the diagnostic system 100.

[0063] Furthermore, this disclosure also includes various modifications to the embodiments that would be conceived by those skilled in the art, and methods implemented by arbitrarily combining the constituent elements and functions of each embodiment without departing from the spirit of this disclosure.

[0064] (Postscript) The following technology has been disclosed through the above description of the embodiments.

[0065] (Technology 1) A diagnostic method for diagnosing the state of continuously operating equipment, comprising: a collection step of collecting data over a specified period, the data being used to diagnose the state of the equipment; a time determination step of determining, based on the data, the times during which, within the specified period, a state change occurs irregularly and continuously at regular intervals, from not meeting a specific condition related to the equipment to meeting the specific condition; a setting step of dividing the specified period by the times to generate multiple temporally continuous intervals, and setting each of the generated multiple intervals as a summary interval serving as a summary unit for the data; a generation step of summarizing the values ​​of control objects of the equipment contained in the data for each of the multiple summary intervals within the specified period, thereby generating diagnostic data; a state determination step of determining, based on the diagnostic data, whether the state of the equipment in each of the multiple summary intervals is normal; and a diagnostic step of diagnosing the state of the equipment based on the results of the determination for the multiple consecutive summary intervals within the multiple summary intervals.

[0066] Therefore, a summary interval is set corresponding to the period during which specific conditions are met. For each of the set summary intervals, the value of the controlled object of the equipment is summarized. Thus, for example, if a specific control is executed during the period when specific conditions are met, it is easy to determine whether the summary result in the summary interval corresponding to that specific control is as assumed, i.e., whether the equipment is in normal condition. Furthermore, by using the results of the determination of multiple consecutive summary intervals, it is possible to diagnose whether a temporary increase in load has occurred, or whether a chronic malfunction has occurred. In this way, according to the diagnostic method of this disclosure, the condition of the equipment can be easily and accurately diagnosed.

[0067] (Technology 2) According to the diagnostic method of Technology 1, in the diagnostic step, the state of the device is diagnosed based on the number of consecutive summary intervals that are determined to be abnormal.

[0068] Therefore, if there are many consecutive instances of abnormal summary intervals, a chronic adverse event can be diagnosed.

[0069] (Technology 3) According to the diagnostic method of Technology 1, in the diagnostic step, the state of the device is diagnosed based on the continuous time of the summary interval that is determined to be abnormal.

[0070] Therefore, if the summary intervals judged as abnormal are continuous for a long period of time, it can be diagnosed as a chronic adverse event.

[0071] (Technology 4) The diagnostic method according to any one of Technologies 1 to 3, wherein, in the state determination step, the state of the device in the summary interval is determined to be normal by comparing the diagnostic data with assumed data expected to be obtained by satisfying the specific conditions.

[0072] Therefore, by comparing diagnostic data with hypothetical data expected to be obtained by meeting specific conditions, it is easy to determine, for example, whether the summary results in the summary interval corresponding to a specific control during a period in which specific conditions are met are as assumed.

[0073] (Technology 5) According to the diagnostic method of Technology 4, wherein the diagnostic data for each of the plurality of summation intervals includes a condition-compliant change, which is the change in the value of the controlled object of the device during the period from the moment when the state of not meeting the specific condition changes to the moment when the state of meeting the specific condition changes to the moment when the state of no longer meeting the specific condition. In the state determination step, the state of the device in the summation interval is determined to be normal by comparing the condition-compliant change with the assumed data corresponding to the condition-compliant change that is expected to be obtained by meeting the specific condition.

[0074] In this way, by comparing the change when the condition is met with the hypothetical data corresponding to the change when the condition is met, it is possible to determine whether the status of the equipment in the summary interval is normal during the period from when the specific condition is met to when the specific condition is no longer met.

[0075] (Technology 6) According to the diagnostic method of Technology 4 or 5, wherein the diagnostic data for each of the plurality of summation intervals includes a change in the amount of time when a condition is not met, the change in the amount of time when a condition is not met is the amount of change in the value of the controlled object of the device during the period from the moment when the state of satisfying the specific condition changes to the moment when the state of not satisfying the specific condition changes to the moment when the state of satisfying the specific condition changes, and in the state determination step, the state of the device in the summation interval is determined to be normal by comparing the change in the amount of time when a condition is not met with the assumed data corresponding to the change in the amount of time when a condition is not met after the specific condition is no longer satisfied.

[0076] In this way, by comparing the change when the condition is not met with the hypothetical data corresponding to the change when the condition is not met, it is possible to determine whether the status of the equipment is normal during the period from when the specific condition is no longer met until the next time the specific condition is met, which is included in the summary interval.

[0077] (Technology 7) The diagnostic method according to any one of Technologies 4 to 6, wherein the diagnostic data for each of the plurality of summary intervals includes a statistic of the value of the controlled object of the device in the summary interval, and in the state determination step, the state of the device in the summary interval is determined to be normal by comparing the statistic with assumed data corresponding to the statistic that is expected to be obtained by satisfying the specific condition.

[0078] In this way, by comparing the statistical measure with the hypothetical data corresponding to the statistical measure, it is possible to determine whether the status of the equipment in the summary interval is normal.

[0079] (Technology 8) The diagnostic method according to any one of Technologies 1 to 7, wherein the device is a refrigerator, and the value of the controlled object of the device is the internal temperature of the refrigerator.

[0080] The condition of a refrigerator can be easily and accurately diagnosed using the diagnostic methods described in this disclosure.

[0081] (Technology 9) According to the diagnostic method of Technology 8, the moment when the specific condition is met is the start or end moment of the control of driving the compressor, the control of opening the damper, or the control of defrosting.

[0082] Therefore, it is easy to accurately diagnose the refrigerator's condition related to the control of the compressor drive, the control of the damper opening, or the defrosting control.

[0083] (Technology 10) A program for causing a computer to perform any one of the diagnostic methods described in Techniques 1 to 9.

[0084] This enables the provision of a program that allows for easy and accurate diagnosis of the device's condition.

[0085] (Technology 11) A diagnostic system for diagnosing the state of continuously operating equipment, comprising: a collection unit for collecting data over a predetermined period, the data being data used to diagnose the state of the equipment; a time determination unit for determining, based on the data, the times during which a state change occurs irregularly and continuously at regular intervals within the predetermined period, changing from a state that does not meet a specific condition related to the equipment to a state that meets the specific condition; a setting unit for dividing the predetermined period by the times to generate multiple time-continuous intervals, and setting each of the generated multiple intervals as a summary interval serving as a summary unit for the data; a generation unit for summarizing the values ​​of control objects of the equipment contained in the data for each of the multiple summary intervals within the predetermined period, thereby generating diagnostic data; a state determination unit for determining, based on the diagnostic data, whether the state of the equipment in each of the multiple summary intervals is normal; and a diagnostic unit for diagnosing the state of the equipment based on the determination results for the multiple consecutive summary intervals within the multiple summary intervals.

[0086] Therefore, a diagnostic system is able to provide easy and accurate diagnosis of the condition of equipment.

[0087] Industrial applicability This disclosure can be applied to systems used for diagnosing the condition of refrigerators, etc.

[0088] Explanation of reference numerals in the attached figures 10 Collection Department 20 Time Judgment Department 30. Setting Department 40 Production Department 50 Status Determination Unit 60. Diagnostic Department 100 Diagnostic System 200 devices

Claims

1. A diagnostic method for diagnosing the condition of continuously operating equipment, wherein, include: The collection step involves collecting data over a specified period, which is used to diagnose the condition of the device. The time determination step, based on the data, determines the time when, within the specified period, an irregular, timed, continuous change occurs from a state that does not meet a specific condition related to the device to a state that meets the specific condition. The steps involve dividing the specified period into multiple time-continuous intervals by the specified time, and setting each of the multiple intervals as a summary interval that serves as the summary unit for the data. The generation step involves summarizing the values ​​of the controlled objects of the device contained in the data for each of the multiple summarization intervals within the specified period, thereby generating diagnostic data. The status determination step, based on the diagnostic data, determines whether the status of the device in each of the plurality of summary intervals is normal; as well as The diagnostic step diagnoses the state of the device based on the results of the determinations made for consecutive summation intervals among the plurality of summation intervals.

2. The diagnostic method according to claim 1, wherein, In the diagnostic step, the state of the device is diagnosed based on the number of consecutive summary intervals that are determined to be abnormal.

3. The diagnostic method according to claim 1, wherein, In the diagnostic step, the state of the device is diagnosed based on the continuous time of the aggregate interval that is determined to be abnormal.

4. The diagnostic method according to claim 1, wherein, In the status determination step, the status of the device in the summary interval is determined to be normal by comparing the diagnostic data with the assumed data expected by satisfying the specific conditions.

5. The diagnostic method according to claim 4, wherein, The diagnostic data, for each of the plurality of summarizing intervals, includes a condition-compliant change, which is the change in the value of the device's controlled object during the period from the moment the state changes from not meeting the specific condition to meeting the specific condition to the moment the state changes from meeting the specific condition to no longer meeting the specific condition. In the state determination step, the state of the device in the summary interval is determined to be normal by comparing the change when the condition is met with the assumed data corresponding to the change when the condition is met, which is expected to be obtained by satisfying the specific condition.

6. The diagnostic method according to claim 4, wherein, The diagnostic data, for each of the plurality of summarizing intervals, includes a change in the amount of time a condition is not met. This change in the amount of time a condition is not met is the change in the value of the controlled object of the device during the period from the moment when the state changes from a state that meets the specific condition to a state that no longer meets the specific condition, until the moment when the state changes from a state that does not meet the specific condition to a state that meets the specific condition again. In the state determination step, the state of the device in the summary interval is determined to be normal by comparing the change amount when the condition is not met with the assumed data corresponding to the change amount when the condition is not met after the specific condition is no longer met.

7. The diagnostic method according to claim 4, wherein, The diagnostic data, for each of the plurality of summary intervals, includes statistics on the values ​​of the controlled objects of the device within the summary interval. In the status determination step, the status of the device in the summary interval is determined to be normal by comparing the statistic with the hypothetical data corresponding to the statistic that is expected to be obtained by satisfying the specific conditions.

8. The diagnostic method according to claim 1, wherein, The device is a refrigerator. The value controlled by the device is the internal temperature of the chamber.

9. The diagnostic method according to claim 8, wherein, The moment when the specific condition is met is the start or end moment of the control that drives the compressor, the control that opens the damper, or the control that defrosts.

10. A program for causing a computer to perform the diagnostic method according to any one of claims 1 to 9.

11. A diagnostic system for diagnosing the condition of continuously operating equipment, wherein, have: The collection unit collects data over a specified period, which is used to diagnose the condition of the device. The timing determination unit, based on the data, determines the time when a state change from not satisfying a specific condition related to the device to satisfying the specific condition occurs irregularly and continuously within the specified period. The setting unit divides the specified period into multiple time-continuous intervals by the specified time, and sets each of the multiple intervals as a summary interval that serves as the summarization unit of the data. The generation unit performs summary processing on the values ​​of the controlled objects of the device contained in the data for each of the multiple summary intervals within the specified period, thereby generating diagnostic data; The status determination unit determines, based on the diagnostic data, whether the status of the device in each of the plurality of summary intervals is normal; as well as The diagnostic unit diagnoses the state of the device based on the results of the determinations made for consecutive summary intervals among the multiple summary intervals.

Images