Diagnosis device, diagnosis method, and recording medium

Abstract

A diagnosis system (100) according to the present disclosure is provided with: a storage unit (40) that stores a detection result of a sensor (11) indicating a deterioration state of oil; and a control unit (30) that diagnoses a change time of the oil on the basis of the detection result stored in the storage unit (40) and notifies a notification destination associated with the sensor (11) of change information indicating the diagnosed change time.

Description

Diagnostic device, diagnostic method, and recording medium

[0001] (Cross-reference to related applications) This application claims the benefit of priority from Japanese Patent Application Nos. 2023-128863 and 2023-128864, each filed on August 7, 2023, the entireties of which are incorporated herein by reference. (Technical Field) The present disclosure relates to a diagnostic device, a diagnostic method, and a recording medium.

[0002] Patent Document 1 describes a method for diagnosing deterioration of lubricating oil using a sensor.

[0003] Japanese Patent Application Laid-Open No. 2019-78718

[0004] Oils such as lubricants are supplied by wholesalers to users via suppliers (such as agents or authorized dealers), or by wholesalers to users. Generally, oil deteriorates over time and depending on the environment in which it is used. Continuing to use deteriorated oil can lead to problems with machinery and other equipment that uses it, so users need to change the oil at the appropriate time. However, until now, there has been no easy way for suppliers or users to determine when it is time to change the oil.

[0005] The present disclosure aims to diagnose the timing of oil change using a simple means.

[0006] Disclosed to achieve the above object is a diagnostic device that includes a memory unit that stores the detection results of a sensor that indicate the deterioration state of oil, and a control unit that diagnoses the time to change the oil based on the detection results stored in the memory unit and notifies a notification destination associated with the sensor of the change information that indicates the diagnosed time to change the oil.

[0007] Other features of the present disclosure will become apparent from the description of this specification and the accompanying drawings.

[0008] According to the present disclosure, the timing for oil change can be diagnosed using a simple means.

[0009] 1 is an explanatory diagram of a diagnostic system; FIG. 2 is an explanatory diagram of a sensor unit; FIG. 3 is an explanatory diagram of a modified example of the sensor unit; FIG. 4 is an explanatory diagram of a hardware configuration of a diagnostic device; FIG. 5 is a flow diagram of a setting process; FIG. 6 is an explanatory diagram of an example of an oil database; FIG. 7 is an explanatory diagram of an example of a profile database; FIG. 8 is a graph showing the relationship between time and gradation value, and also showing the time change in the detection results of the color sensor and the time change in the remaining rate of the antioxidant contained in the oil; FIG. 9 is a graph showing the relationship between time and gradation value, and also showing the time change in the detection results of the color sensor and the time change in the remaining rate of the antioxidant contained in the oil; FIG. 10 is a graph showing the relationship between time and gradation value, and also showing the time change in the detection results of the color sensor and the time change in the remaining rate of the antioxidant contained in the oil; FIG. 11 is an explanatory diagram of an example of a supplier database and a user database; FIG. 12 is an explanatory diagram of an example of a customer database; FIG. 13 is an explanatory diagram of an example of a sensor database; FIG. 14 is an explanatory diagram of an example of a diagnostic setting database; FIG. 15 is a flow diagram of a data acquisition process; FIG. 16 is an explanatory diagram of an example of a detection result database; FIG. 17 is a flow diagram of a notification process; FIG. 18 is an explanatory diagram of a replacement time and a remaining period; FIG. 19 is an explanatory diagram of an alert screen; FIG. 19 is an explanatory diagram of an alert screen; FIG. 19 is an explanatory diagram of a list notification process; FIG. 10 is an explanatory diagram of an example of a list created in S303. FIG. 11 is an explanatory diagram of another example of a list transmitted to a supplier terminal. FIG. 12 is a flow chart of another list notification process. FIG. 13 is an explanatory diagram of a replacement history database. FIG. 14 is a table showing the correlation between the remaining rate of antioxidant and RGB data.

[0010] At least the following aspects will become apparent from the description of this specification and the accompanying drawings.

[0011] In one aspect, a diagnostic device includes a storage unit that stores detection results from a sensor that indicate the deterioration state of the oil, and a control unit that diagnoses when the oil should be changed based on the detection results stored in the storage unit and notifies a notification destination associated with the sensor of change information indicating the diagnosed oil change time. This diagnostic device allows the diagnosis of when the oil should be changed using a simple means.

[0012] The diagnostic device according to aspect 2 is the diagnostic device according to aspect 1, and is capable of setting at least one of the user of the oil and the supplier who supplied the oil to the user as the notification destination. This allows the notification destination to be set in accordance with the actual circumstances of oil transactions.

[0013] A diagnostic device according to a third aspect is the diagnostic device according to the first or second aspect, wherein the control unit calculates the time when the detection result reaches a change threshold as the time when the oil will be changed. This makes it possible to diagnose the time when the oil will deteriorate to the point where an oil change is required.

[0014] A diagnostic device according to a fourth aspect is the diagnostic device according to the third aspect, and is capable of setting the replacement threshold value in association with the sensor. This allows the end of the oil life to be set in accordance with each oil.

[0015] A diagnostic device according to a fifth aspect is the diagnostic device according to any one of the first to fourth aspects, wherein the control unit diagnoses the oil change timing using the most recent detection result among the detection results stored in the memory unit, thereby enabling the oil change timing to be diagnosed with high accuracy.

[0016] A diagnostic device according to a sixth aspect is the diagnostic device according to any one of the first to fifth aspects, wherein the control unit notifies the notification destination of the replacement information when the remaining period reaches a period threshold. This allows notification to be performed at a predetermined timing.

[0017] A diagnostic device according to a seventh aspect is the diagnostic device according to the sixth aspect, and is capable of setting the period threshold in association with the sensor. This allows notifications to be made at timings suited to each requirement.

[0018] A diagnostic device according to an eighth aspect is the diagnostic device according to the sixth or seventh aspect, wherein the control unit, when notifying the destination of the replacement information, notifies the destination of the supplier that supplied the oil to the user of a list including the replacement information of other oils supplied to the user of the oil. This enables the supplier to easily diagnose the replacement times of multiple oils used by the user.

[0019] A diagnostic device according to a ninth aspect is the diagnostic device according to any one of the first to eighth aspects, wherein the control unit notifies the notification destination of a list including the replacement information corresponding to each of the plurality of sensors, thereby enabling the change times of the plurality of oils to be easily diagnosed.

[0020] A diagnostic device according to a tenth aspect is the diagnostic device according to the ninth aspect, wherein the control unit notifies the list in which the plurality of pieces of change information are arranged in order of remaining life. This allows the list to be arranged in order of the likelihood of needing an oil change.

[0021] A diagnostic device according to an eleventh aspect is the diagnostic device according to the ninth or tenth aspect, wherein the control unit identifies the plurality of sensors associated with the user to whom the oil supplier supplies the oil, and notifies the supplier of the list including the replacement information corresponding to each of the identified plurality of sensors. This enables the supplier to easily diagnose the replacement times of the plurality of oils used by the user.

[0022] A diagnostic device according to a twelfth aspect is the diagnostic device according to the ninth aspect, wherein when a user of the oil requests the list, the control unit notifies the supplier that supplied the oil to the user that the user has requested the list, thereby enabling the supplier to know that the user is interested in an oil change.

[0023] A diagnostic device according to a thirteenth aspect is the diagnostic device according to any one of aspects one to eleven, wherein when a user of the oil requests the oil change information, the control unit notifies the supplier that supplied the oil to the user that the user has requested the oil change information, thereby enabling the supplier to know that the user is interested in an oil change.

[0024] A diagnostic device according to a fourteenth aspect is the diagnostic device according to the twelfth or thirteenth aspect, wherein the control unit notifies the supplier of information relating to past oil changes of the user, thereby enabling the supplier to grasp the user's tendency regarding oil changes.

[0025] A diagnostic device according to aspect 15 is the diagnostic device according to any one of aspects 1 to 13, wherein the sensor is a color sensor. Because the color of oil changes as the oil deteriorates, the deterioration state of the oil can be detected by using a color sensor.

[0026] A diagnostic device according to Aspect 16 is the diagnostic device according to any one of Aspects 1 to 15, wherein the control unit diagnoses oil deterioration based on detection results of light of different wavelengths depending on the type of oil from among the detection results of the sensor. Aspect 17 is a diagnostic method that acquires detection results from a sensor that detects the oil deterioration state, diagnoses the oil change time based on the detection results, and notifies a notification destination associated with the sensor of replacement information indicating the diagnosed replacement time. Such a diagnostic method allows the oil change time to be diagnosed using a simple means. Aspect 18 is a computer-readable recording medium that stores a program for causing a computer to execute the steps of acquiring detection results from a sensor that detects the oil deterioration state, diagnosing the oil change time based on the detection results, and notifying a notification destination associated with the sensor of replacement information indicating the diagnosed replacement time. Aspect 19 is a diagnostic device comprising a storage unit that stores a light reception result when light from oil is received, and a control unit that diagnoses the oil degradation based on the light reception result, wherein the control unit diagnoses the oil degradation based on the light reception result of light having a wavelength corresponding to the type of oil. Note that the "control unit" performs predetermined arithmetic processing and does not necessarily perform control processing on predetermined hardware. Aspect 20 is the diagnostic device according to Aspect 19, wherein the control unit diagnoses the first oil degradation based on the light reception result of light having a first wavelength when diagnosing a first oil, and diagnoses the second oil degradation based on the light reception result of light having a second wavelength different from the first wavelength when diagnosing a second oil different from the first oil. Aspect 21 is a computer-readable recording medium that stores a program for causing a computer to execute the steps of acquiring the light reception result when light from oil is received, and diagnosing the oil degradation based on the light reception result of light having a wavelength corresponding to the type of oil from the light reception result.Aspect 22 is a diagnostic method for diagnosing oil degradation, in which, when diagnosing a first oil, degradation of the first oil is diagnosed based on a result of receiving light of a first wavelength, and when diagnosing a second oil different from the first oil, degradation of the second oil is diagnosed based on a result of receiving light of a second wavelength different from the first wavelength. This diagnostic method allows appropriate diagnosis of oil degradation. Aspect 23 is the diagnostic method of Aspect 22, in which the result of receiving light of the first wavelength for the first oil is more strongly correlated with the residual rate of an antioxidant contained in the first oil than the result of receiving light of the second wavelength for the first oil, and the result of receiving light of the second wavelength for the second oil is more strongly correlated with the residual rate of an antioxidant contained in the second oil than the result of receiving light of the first wavelength for the second oil. According to this diagnostic method, it is possible to appropriately diagnose deterioration due to a decrease in the residual rate of the antioxidant in both the first oil and the second oil.

[0027] First Embodiment A preferred embodiment of the present disclosure will now be described with reference to the drawings. The same or equivalent components, members, etc. shown in each drawing will be designated by the same reference numerals, and redundant description will be omitted where appropriate.

[0028] <Configuration of Diagnostic System> FIG. 1 is an explanatory diagram of a diagnostic system 100 .

[0029] The diagnostic system 100 is a system for diagnosing when to change oil. The diagnostic system 100 includes a sensor unit 10 having a sensor 11 and a diagnostic device 20 having a control unit 30 and a memory unit 40. Communication is possible between the sensor unit 10 and the diagnostic device 20 via a communication network 90. ​​The communication network 90 is, for example, a network via telephone lines (public telephone lines, mobile phone lines), wireless communication, wired communication, etc., and examples of the network include the Internet, an intranet, a LAN, and a WAN. Here, the Internet is assumed. The communication network 90 is also connected to a terminal of an oil user (user terminal 61), a terminal of a dealer or distributor that supplies oil to the oil user (supplier terminal 71), and a terminal 71′ of an oil wholesaler. Communication is also possible between these terminals and the diagnostic device 20 via the communication network 90.

[0030] Here, "user" refers to a person who uses oil. Furthermore, "supplier" refers to a person who supplies oil to an oil user. Suppliers may include not only authorized dealers and distributors, but also oil wholesalers (and the supplier terminal 71 may also refer to the wholesaler's terminal 71'). However, "supplier" may also refer to a wholesaler without including the wholesaler. Furthermore, suppliers and users excluding wholesalers may be collectively referred to as "customers." Furthermore, "oil" here refers to oil that requires replacement when it deteriorates. Examples of oil include lubricating oils (processing oils, machine oils, etc.), cooling oils, and rust-preventive oils. Oil is composed of a base oil blended with additives such as antioxidants. Oil deteriorates as the residual rate of additives such as antioxidants decreases.

[0031] The oil user has a user terminal 61 and oil-using equipment 62. The user terminal 61 is a terminal used by the user. Here, the user terminal 61 is assumed to be a smartphone, but it may also be a personal computer or a tablet terminal. The user has one or more oil-using equipment 62. The equipment 62 is, for example, a machine tool or a compressor that uses lubricating oil (an example of oil). The equipment 62 is provided with a tank 63 (see FIGS. 2A and 2B) for storing oil. The oil in each equipment 62 is supplied, replaced, and collected by, for example, a supplier's worker. The oil-using equipment 62 (tank 63 for storing oil) is provided with a sensor unit 10 having a sensor 11.

[0032] The oil supplier has a supplier terminal 71. Here, the supplier terminal 71 is assumed to be a personal computer, but the supplier terminal 71 may also be a mobile terminal such as a smartphone or tablet terminal.

[0033] FIG. 2A is an explanatory diagram of the sensor unit 10.

[0034] The sensor unit 10 constitutes a measuring device (detection device) that measures oil. The sensor unit 10 includes a sensor 11, a control unit 12, and a communication unit 13. The sensor 11 detects the deterioration state of the oil used in the user's equipment 62. In this example, the sensor 11 is a color sensor that detects the color of the oil in the tank 63 and outputs RGB data (color data including R data, G data, and B data) indicating the gradation values ​​of each of the RGB (red, green, blue) colors. The R data is a gradation value indicating the result of receiving light of a red wavelength. The G data is a gradation value indicating the result of receiving light of a green wavelength. The B data is a gradation value indicating the result of receiving light of a blue wavelength. The sensor 11 does not have to be a color sensor as long as it can detect the deterioration state of the oil. For example, the sensor 11 may analyze the components of the oil and output component data as the detection result. The control unit 12 controls the sensor unit 10. The communication unit 13 communicates with the diagnostic device 20 via a communication network 90. For example, the control unit 12 is composed of an arithmetic processing unit such as a CPU or an MPU, and a storage device (main storage device or auxiliary storage device) such as a RAM or a ROM, and the arithmetic processing unit executes a program stored in the storage device, thereby receiving setting data (described later) from the diagnostic device 20 via the communication unit 13 and transmitting the detection results of the sensor 11 (RGB data in this case) to the diagnostic device 20.

[0035] 2B is an explanatory diagram of a modified example of the sensor unit 10. The sensor unit 10 may have multiple sensors 11. Each sensor 11 detects the deterioration state of the oil in the tank 63 of a different device 62. According to the modified sensor unit 10, a single sensor unit 10 (a single control unit 12) can detect the deterioration state of the oil in each of the tanks 63 of a plurality of devices 62.

[0036] In the first embodiment, the diagnostic system 100 can be constructed by attaching the sensor unit 10 (sensor 11) to an existing tank 63 of a device 62 that uses oil.

[0037] The diagnostic device 20 is a device for diagnosing oil deterioration. FIG. 3 is an explanatory diagram of the hardware configuration of the diagnostic device 20.

[0038] The diagnostic device 20 includes a processing unit 51, a storage device 52, and a communication device 53. The elements in the figure are connected via a bus (not shown). The processing unit 51 is configured, for example, by a CPU. The storage device 52 is configured, for example, by a main storage device such as RAM and an auxiliary storage device such as a hard disk drive or SSD. The processing unit 51 executes programs stored in the storage device 52, thereby realizing various functions shown in FIG. 1 . The communication device 53 is a device for connecting to the communication network 90 and is configured, for example, by a communication module for wired or wireless communication. The diagnostic device 20 may also include a display device 54 (e.g., a display) and an input device 55 (e.g., a keyboard, a mouse, etc.). The diagnostic device 20 may be configured by one computer or multiple computers. When the diagnostic device 20 is configured by multiple computers, multiple functions (such as the control unit 30 and the storage unit 40 shown in FIG. 1 ) may be realized by dividing the functions into separate computers, or the same functions may be distributed and processed by multiple computers. The computers constituting the user terminal 61 and supplier terminal 71 described above also have, as hardware, an arithmetic processing unit, a storage unit, a communication unit, an input unit, and a display unit, similar to the diagnostic device 20 shown in FIG.

[0039] As shown in FIG. 1 , the diagnostic device 20 includes a control unit 30 and a storage unit 40 .

[0040] As will be described later, the control unit 30 diagnoses the oil change time based on the detection results (RGB data in this case) of the sensor 11 stored in the storage unit 40. The control unit 30 also notifies the user terminal 61 and the supplier terminal 71 of change information indicating the diagnosed change time. The control unit 30 has a setting processing unit 31, a data acquisition unit 32, a diagnosis processing unit 33, a notification processing unit 34, and a history processing unit 35. The various functions of the control unit 30 will be described later.

[0041] The storage unit 40 stores the detection results of the sensor 11. The storage unit 40 also stores various data, which will be described later. Here, the storage unit 40 has a basic information database 41, a diagnostic setting database 42, a detection result database 43, and a replacement history database 44. Each database of the storage unit 40 will be described later.

[0042] <Various Processing> (Setting Processing) FIG. 4 is a flow diagram of the setting processing.

[0043] Of the processes shown in the figure, each process of the diagnostic device 20 is realized by the arithmetic processing device 51 executing a program stored in the storage device 52. Similarly, each process of the sensor unit 10 is realized by the arithmetic processing device of the sensor unit 10 executing a program stored in the storage device. This also applies to each process described below.

[0044] The setting processing unit 31 of the diagnostic device 20 sets the basic information database 41 in the storage unit 40 (S001 to S004). The basic information database 41 is a database that stores basic information. In this example, the basic information database 41 includes an oil database 411, a profile database 412, a supplier database 413, a user database 414, and a sensor database 415.

[0045] First, the setting processing unit 31 sets the oil database 411 and the profile database 412 in the storage unit 40 (S001). For example, when a new oil product is developed or released, information about the oil (oil information) is set in the oil database 411 and the profile database 412.

[0046] FIG. 5 is an explanatory diagram of an example of the oil database 411.

[0047] The oil database 411 is a database that stores data related to oil (oil data). The oil data is data that associates an oil ID with oil information. The oil ID is information (identification number) for specifying the type of oil. The oil information is information related to the oil, such as the oil name (product name) and ingredients (base oil and additives). Note that antioxidants may be included as additives.

[0048] FIG. 6 is an explanatory diagram of an example of the profile database 412. As shown in FIG.

[0049] The profile database 412 is a database that stores profile data related to oil characteristics. Here, the profile data is data that associates a profile ID with profile information. The profile ID is information (identification number) for identifying a profile. The profile information is information that indicates the characteristics of the oil. The profile data associates, as profile information, an oil ID, information (graph information) that indicates the relationship between time and gradation value, a diagnostic color, and an initial value of the change threshold. The oil IDs in the profile database 412 are associated with the oil IDs in the oil database 411. In other words, the oil IDs in the profile database 412 are information for identifying the oils that correspond to each piece of profile data.

[0050] 7A to 7C are example graphs showing the relationship between time and gradation value. Each of FIGS. 7A to 7C shows profile information for a different oil (Oil A to Oil C). The horizontal axis in each graph represents time. The vertical axis on the left represents the gradation values ​​of RGB (red, green, and blue), showing the detection results of sensor 11 when the oil color is detected by sensor 11. For illustrative purposes, the graphs in the figures show a dotted line representing the residual rate of additives contained in the oil. The vertical axis on the right represents the residual rate (%) of additives. Note that the additive residual rate graph (dotted line) is intended to illustrate the correlation between RGB data and additive residual rate, and the additive residual rate graph information does not need to be included in the profile information.

[0051] In all of Figures 7A to 7C, for oils used under certain conditions, the residual percentage of additives contained in the oil decreases over time, as shown by the dotted line graphs. Furthermore, in all of Figures 7A to 7C, the detection results of sensor 11 change as the residual percentage of additives changes, as shown by the solid line graphs. For example, in the case of Oil A, as shown in Figure 7A, the B data (data indicating the blue gradation value) output by sensor 11 decreases as the residual percentage of additives decreases, but the R data and G data (data indicating the red and green gradation values) hardly decrease. In the case of Oil B and Oil C, as shown in Figures 7B and 7C, not only the B data but also the R data and G data decrease as the residual percentage of additives decreases. Note that in the case of Oil B, as shown in Figure 7B, the B data is more strongly correlated with the residual percentage of additives than the R data and G data. On the other hand, in the case of Oil C, as shown in Figure 7C, the G data, but not the B data, is more strongly correlated with the residual percentage of additives than the other colors (R data and B data). In this way, the detection results of the sensor 11 differ for each type of oil. Therefore, when a new oil product is developed or released, profile information about that oil is set in the profile database 412.

[0052] The diagnostic color (see FIG. 6 ) included in the profile information is information for identifying the data to be used in diagnosing the oil from the RGB data that is the detection result of the sensor 11. If the diagnostic color is set to "blue (B)," the "B data" of the RGB data will be used in diagnosing the oil. If the diagnostic color is set to "green (G)," the "G data" of the RGB data will be used in diagnosing the oil. Here, the B data is set to be used in diagnosing oils A and B, and the G data is set to be used in diagnosing oil C.

[0053] Although a single color is used as the diagnostic color here, two or more colors may be set as the diagnostic color. For example, if impurities are mixed into the oil, all colors of the RGB data change, so all colors may be set as the diagnostic color for diagnosing impurity-containing oil. When two or more colors are set as diagnostic colors, a change threshold may be set for each color. In this case, the time for an oil change may be determined based on the data for all colors corresponding to the two or more colors set as diagnostic colors reaching the change threshold, or the time for an oil change may be determined based on the data for any one color reaching the change threshold. For example, when all colors are set as diagnostic colors for diagnosing impurity-containing oil, the time for an oil change is determined based on the data for all colors of the RGB data reaching the change threshold.

[0054] In the case of oils A and B, the B data is more strongly correlated with the residual rate of additives than the R data and the G data (see FIGS. 7A and 7B). Therefore, the diagnostic color associated with oils A and B is set to "blue (B)." On the other hand, in the case of oil C, as shown in FIG. 7C, the G data is more strongly correlated with the residual rate of additives than the R data and the B data. Therefore, the diagnostic color associated with oil C is set to "green (G)."

[0055] The change threshold included in the profile information (see FIG. 6 ) is a threshold used to determine whether an oil change is necessary. A “gradation value” is set as the change threshold. For example, for oil A, a gradation value of “50” is set as the change threshold. Therefore, when determining whether oil A needs to be changed, the gradation value indicated by the “B data” of the RGB data output by the sensor 11 is compared with the threshold value of “50.” An initial value of the change threshold is set in the profile database 412. When the detection result of the sensor 11 reaches the change threshold, it indicates that the oil has deteriorated to the point where an oil change is required. In other words, the change threshold is a reference value for determining whether the oil needs to be changed (in other words, the change threshold is a reference value for determining the lifespan of the oil). As will be described later, the setting of the change threshold used to determine whether an oil change is necessary can be changed by using a change threshold (adjustment value) set in the diagnostic setting database 42.

[0056] Here, the "gradation value" is set as the change threshold, but the change threshold is not limited to the gradation value and may be, for example, "slope (rate of change in gradation value over time)." In this case, the timing of oil change is determined based on whether the slope of the data corresponding to the diagnostic color (rate of change in gradation value over time) has reached (or has not reached) the change threshold.

[0057] The profile information (graph information, diagnostic color, and change threshold) may be directly incorporated into the oil database 411 as part of the oil information, thereby integrating the profile database 412 into the oil database 411. In this way, the basic information database 41 may not include some of the other types of databases. Furthermore, the basic information database 41 may further include other types of databases. This also applies to other types of databases described below.

[0058] The setting processing unit 31 of the diagnostic device 20 sets the supplier database 413 and the user database 414 in the storage unit 40 (S002, S003). For example, when a contract is concluded between an oil wholesaler and an authorized dealer (an example of a supplier), the supplier registers its own information (supplier information) in the diagnostic device 20 using the supplier terminal 71 (S011), or a person in charge of the wholesaler registers information about the supplier in the diagnostic device 20 using the terminal 71' (S011), and the information about the supplier is set in the supplier database 413 (S002). Also, when a contract is concluded between the supplier and the user, the user registers its own information (user information) in the diagnostic device 20 using the user terminal 61 (S012), or the supplier registers information about the user in the diagnostic device 20 using the supplier terminal 71 (S012), and the information about the user (user information) is set in the user database 414 (S003).

[0059] FIG. 8A is an explanatory diagram of an example of the supplier database 413 and the user database 414.

[0060] The supplier database 413 is a database that stores data related to suppliers (supplier data). The supplier data is data that associates a supplier ID with supplier information. The supplier ID is information (identification number) for identifying a supplier. The supplier information is information related to a supplier, such as the supplier's name, address, and contact information (e.g., email address).

[0061] The user database 414 is a database that stores data related to users (user data). The user data is data that associates a user ID with user information. The user ID is information (identification number) for identifying the user. The user information is information related to the user, such as the user's name, address, and contact information (e.g., email address). A supplier ID is associated with the user data as user information. The supplier ID included in the user data indicates the supplier that supplies oil to the user, and is associated with the supplier ID in the supplier database 413.

[0062] Fig. 8B is an explanatory diagram of an example of a customer database 414'. As shown in Fig. 8B, the supplier database 413 and the user database 414 shown in Fig. 8A may be combined into one database (customer database 414').

[0063] The customer database 414′ is a database that stores data (customer data) related to customers, including suppliers and users, and serves as a substitute for the supplier database 413 and user database 414 described above. The customer data is data that associates a customer ID with customer information. The customer ID is information (identification number) for identifying a customer (supplier or user). The customer information is information about a customer, such as the customer's name, address, and contact information (e.g., email address). The customer information includes information about the supplier who supplies oil to that customer (here, the customer ID corresponding to the supplier). In the figure, "Customer ID: X" is the supplier, and customer "Customer ID: AAA" is the user. Here, the supplier information for "Customer ID: X" does not include a customer ID indicating the supplier, but an ID indicating the wholesaler may be included. As described above, the basic information database 41 may include a customer database 414′ instead of the supplier database 413 and user database 414.

[0064] The setting processing unit 31 of the diagnostic device 20 sets the sensor database 415 in the storage unit 40 (S004). For example, when the supplier installs the sensor unit 10 in the equipment 62 (equipment 62 that uses oil) at the user's location, the user registers information about the sensor 11 in the diagnostic device 20 using the user terminal 61 (S013), or the supplier registers information about the sensor 11 in the diagnostic device 20 using the supplier terminal 71 (S013), and the information about the sensor 11 (sensor information) is set in the sensor database 415 (S004).

[0065] FIG. 9 is a diagram illustrating an example of the sensor database 415. As shown in FIG.

[0066] The sensor database 415 is a database that stores data (sensor data) related to the sensor 11. The sensor data is data that associates a sensor ID with sensor information. The sensor ID is information (identification number) for identifying the sensor 11. Here, the sensor ID is a serial number of the sensor 11 that is preset in the sensor 11. However, the sensor ID may be a number that is assigned each time a new sensor 11 is added to the sensor database 415. The sensor information is information related to the sensor 11. The sensor information includes device information, an oil ID, and a user ID. The device information is information related to the device 62 to which the sensor 11 is attached. The device information includes information such as the name, manufacturer, model number, and tank capacity (or the amount of oil stored in the tank 63) of the device 62 to which the sensor 11 is attached. The oil ID in the sensor database 415 is associated with the oil ID in the oil database 411 and is information for identifying the oil to be detected by the sensor 11. The user ID in the sensor database 415 is associated with the user ID in the user database 414, and is information for identifying the user of the device 62 to which the sensor 11 is attached. Other information may be associated as sensor information. For example, if the sensor ID and the serial number of the sensor 11 are different, the serial number of the sensor 11 may be associated as sensor information with the sensor ID. Note that a separate device database that associates device IDs with device information may be prepared, and the device ID may be associated as device information for the sensor data. In this case, the device database associates device information such as the device name, manufacturer, model number, and tank capacity with the device ID.

[0067] Through the above processing (S001 to S004), the basic information database 41 (oil database 411, profile database 412, supplier database 413, user database 414, and sensor database 415) is set in the storage unit 40 of the diagnostic device 20. In the above explanation, the setting processing unit 31 of the diagnostic device 20 registers each database constituting the basic information database 41 in the storage unit 40 in the order of the oil database 411, profile database 412, supplier database 413, user database 414, and sensor database 415, but the order in which each database is registered is not limited to this.

[0068] Next, the setting processing unit 31 of the diagnostic device 20 sets the diagnostic setting database 42 in the storage unit 40 (S005). For example, when a supplier installs the sensor unit 10 in a device 62 (device 62 that uses oil) at the user's location, setting information (diagnostic setting information) for a diagnostic process using the sensor 11 is set in the diagnostic device 20. The diagnostic setting information is set in the diagnostic setting database 42 (S005) when the user registers information about the sensor 11 in the diagnostic device 20 using the user terminal 61 (S014) or when the supplier registers information about the sensor 11 in the diagnostic device 20 using the supplier terminal 71 (S014).

[0069] FIG. 10 is an explanatory diagram of an example of the diagnostic setting database 42. As shown in FIG.

[0070] The diagnostic setting database 42 is a database that stores data (diagnostic setting data) related to the settings of diagnostic processing using the sensor 11. The diagnostic setting data is data that associates a sensor ID with diagnostic setting information. The sensor ID is information (identification number) for identifying the sensor 11, and is associated with the sensor ID in the sensor database 415. The diagnostic setting information is information related to the settings of diagnostic processing using the sensor 11. Here, the diagnostic setting data includes, as the diagnostic setting information, information related to the detection timing, thresholds (replacement threshold and period threshold), and notification destination.

[0071] The detection timing in the diagnostic setting information is information that sets the timing at which the sensor 11 detects oil. Here, the detection timing is set to a time interval such as "every hour" or "every 24 hours," but the detection timing may also be set to a time such as "8:00 AM."

[0072] As already explained, the change threshold value in the diagnostic setting information is information for setting a reference value for determining whether the oil has reached the time for change (a reference value for diagnosing the oil's lifespan; a change threshold value Tc, described later). Here, an adjustment value for adjusting the change threshold value (initial value) in the profile database 412 is set as the change threshold value in the diagnostic setting database 42, and the reference value for determining whether the oil has reached the time for change (a change threshold value Tc, described later) is determined by adding the change threshold value (initial value) in the profile database 412 and the change threshold value (adjustment value) in the diagnostic setting database 42. Note that, instead of an adjustment value, a gradation value corresponding to the change threshold value Tc, described later, may be directly set in the diagnostic setting database 42.

[0073] The period threshold in the diagnostic setting information is a setting value for setting the timing of issuing an alert (described below). An alert is issued when the period until the oil needs to be changed reaches the period threshold (described below). Here, the period threshold is set in association with the sensor (sensor ID). However, the period threshold may be set in association with the profile ID, similar to the change threshold in the profile database 412. In this case, for example, by arbitrarily setting the period threshold in association with a profile ID in which all colors are set as diagnostic colors for diagnosing impurities, it is possible to set the system so that an alert is issued even when impurities in the oil are detected. The period threshold can be set to any value, including both positive and negative values. Because the period threshold can be set to any value, the timing of issuing an alert (described below) can be configured to meet various requirements.

[0074] The notification destination of the diagnostic setting information indicates the party to which an alert (described later) is to be notified. Here, "supplier," "user," or "both (supplier and user)" is set in association with the sensor 11 as the notification destination. Note that the aforementioned supplier ID or user ID (or customer ID) may also be associated as the notification destination of the diagnostic setting information.

[0075] In the first embodiment, at least one of the user and the supplier can be set as the notification destination in the diagnostic setting database 42. This allows the notification destination of an alert, which will be described later, to be set in accordance with the actual circumstances of each oil transaction.

[0076] Furthermore, even if the type of oil is the same, the oil lifespan may differ for each device 62 that uses the oil (or for each user of the device 62). For example, the allowable degree of oil deterioration is thought to differ between devices 62 that require high accuracy and devices 62 that can use relatively deteriorated oil, and therefore the oil lifespan is thought to differ. Therefore, in the first embodiment, the diagnostic setting database 42 allows the replacement threshold to be set in association with each sensor 11 (sensor ID). This allows the end of the oil life to be set to suit different requirements.

[0077] Furthermore, there is a demand for alert notification at different timings for each device 62 that uses oil (or for each user or supplier of the device 62). For example, in the case of a device 62 that requires high accuracy and does not allow the use of oil that has reached the end of its lifespan, it may be desirable to issue an oil change notification (an alert notification, described below) at an early timing, taking into account the period required for the oil change. On the other hand, in cases where the use of oil that has reached the end of its lifespan is permitted, it may be desirable to issue an oil change notification as close to the end of its lifespan as possible rather than at an early stage. Therefore, in the first embodiment, the diagnostic setting database 42 allows a period threshold to be set in association with the sensor 11 (sensor ID). This allows alert notification (described below) to be issued at a timing suited to different requirements.

[0078] When the diagnostic setting information is registered in the diagnostic setting database 42, the setting processing unit 31 of the diagnostic device 20 sets the diagnostic setting information in the diagnostic setting database 42 (S005) and transmits setting data including information on the detection timing to the sensor unit 10 corresponding to the diagnostic setting information (S006). The sensor unit 10 sets the detection timing based on the setting data received from the diagnostic device 20 (S021). As will be described later, the sensor unit 10 detects oil using the sensor 11 in accordance with the set detection timing and transmits the detection result to the diagnostic device 20. Note that if the detection timing is set in advance in the sensor unit 10, the detection timing does not need to be set in the diagnostic setting database 42, and a setting signal including information on the detection timing does not need to be transmitted from the diagnostic device 20 to the sensor unit 10.

[0079] (Data Acquisition Processing) FIG. 11 is a flow diagram of the data acquisition processing.

[0080] When the set detection timing arrives (YES in S101), the sensor unit 10 acquires RGB data from the sensor 11 (S102) and transmits the RGB data to the diagnostic device 20 (S103). The sensor unit 10 preferably adds a sensor ID (here, the serial number of the sensor 11) to the RGB data and transmits the RGB data to the diagnostic device 20. If the sensor ID is different from the serial number and the serial number of the sensor 11 is associated with the sensor ID as sensor information in the sensor database 415, the sensor unit 10 may add the serial number to the RGB data and transmit it to the diagnostic device 20, and the diagnostic device 20 may identify the sensor ID based on the serial number. Alternatively, the sensor unit 10 may add information indicating the detection time (detection date and time) to the RGB data and transmit it to the diagnostic device 20. The data acquisition unit 32 of the diagnostic device 20 receives the RGB data from the sensor unit 10 and stores the RGB data in the detection result database 43 (S111).

[0081] FIG. 12 is an explanatory diagram of an example of the detection result database 43. As shown in FIG.

[0082] The detection result database 43 is a database that stores the detection results of the sensor 11. In the detection result database 43, for each sensor ID, the detection time (detection date and time) is associated with the detection result (RGB data) of the sensor 11 at that detection time (though each column is blank in the figure, information on time and gradation value is stored). The sensor IDs in the detection result database 43 are associated with the sensor IDs in the sensor database 415. The diagnostic device 20 registers the received RGB data in the detection result database 43 in association with the sensor ID attached to the received RGB data. The diagnostic device 20 also registers the RGB data in association with information indicating the detection time attached to the RGB data, or in association with the detection time, using the time when the RGB data was received from the sensor unit 10 as the detection time (S111). The detection result database 43 stores RGB data corresponding to a plurality of detection times. That is, the detection result database 43 stores the history of the detection results (RGB data) of the sensor 11 .

[0083] (Notification Process) Fig. 13 is a flow diagram of the notification process. Fig. 14 is an explanatory diagram of the replacement time t1 and the remaining period Pr. The horizontal axis of Fig. 14 indicates time, and the vertical axis indicates gradation value. Time t0 indicates the current time. The solid line in Fig. 14 indicates the transition of the detection result of the sensor 11 (e.g., data B). The dotted line in the figure indicates the predicted transition of the future detection result. Before time t0, the solid line graph indicates the past detection result of the sensor 11, and after time t0, the dotted line graph indicates the predicted transition of the detection result of the sensor 11.

[0084] First, the diagnostic processing unit 33 of the diagnostic device 20 performs diagnostic processing (S201 to S204) to determine when the oil needs to be changed.

[0085] In the diagnostic process, the diagnostic processing unit 33 acquires information necessary for diagnosing the timing of an oil change from the storage unit 40 (S201). Here, the diagnostic processing unit 33 acquires the detection result, profile information, and threshold value of the sensor 11. At this time, the diagnostic processing unit 33 determines the diagnostic color set for the oil associated with the sensor ID. When diagnosing the oil detected by "sensor ID: sensor 001," the diagnostic processing unit 33 determines the diagnostic color to be "blue (B)" based on the profile database 412 because the oil ID associated with "sensor ID: sensor 001" in the sensor database 415 is "oil A." When diagnosing the oil detected by "sensor ID: sensor 003," the diagnostic processing unit 33 determines the diagnostic color to be "green (G)" based on the profile database 412 because the oil ID associated with "sensor ID: sensor 003" in the sensor database 415 is "oil C." After determining the diagnostic color, the diagnostic processing unit 33 acquires the detection result of the sensor 11 from the detection result database 43. At this time, the diagnostic processing unit 33 obtains data corresponding to the diagnostic color from the RGB data in the detection result database 43. For example, when obtaining a detection result corresponding to "sensor ID: sensor 001," the diagnostic color corresponding to "sensor ID: sensor 001" is "blue (B)" (see FIGS. 6 and 9 ). Therefore, the diagnostic processing unit 33 extracts B data from the RGB data for "sensor ID: sensor 001" in the detection result database 43. When obtaining a detection result corresponding to "sensor ID: sensor 003," the diagnostic processing unit 33 extracts G data from the RGB data for "sensor ID: sensor 003" in the detection result database 43. In this way, the diagnostic processing unit 33 may extract light reception results of different wavelengths depending on the type of oil (as a result, the diagnostic processing unit 33 diagnoses oil deterioration based on light reception results of different wavelengths depending on the type of oil). The diagnostic processing unit 33 also obtains profile information (graphic information showing the relationship between time and gradation value) corresponding to the sensor 11 from the profile database 412.At this time, the diagnostic processing unit 33 obtains graph information corresponding to the diagnostic color from the RGB graph information in the profile database 412 (for example, graph information of the blue (B) gradation value from the graph of each RGB gradation value). The diagnostic processing unit 33 may extract graph information of light with different wavelengths depending on the type of oil (as a result, the diagnostic processing unit 33 diagnoses oil deterioration based on the graph information of light with different wavelengths depending on the type of oil). The diagnostic processing unit 33 also adds the replacement threshold value (initial value) in the profile database 412 and the replacement threshold value (adjusted value) in the diagnostic setting database 42 to obtain the replacement threshold value Tc corresponding to the sensor 11. The diagnostic processing unit 33 also obtains the period threshold value Tp corresponding to the sensor 11 from the diagnostic setting database 42.

[0086] Next, the diagnostic processing unit 33 calculates a predicted transition of the detection results of the sensor 11 based on the detection results and the profile information (S202). For example, the diagnostic processing unit 33 expands or contracts the time axis of the profile information graph (see FIGS. 7A to 7C ) so as to fit the transition of the detection results of the sensor 11 up to now (see the solid-line graph in FIG. 14 ). The diagnostic processing unit 33 then fits the profile information graph with the changed time axis to the transition of the detection results of the sensor 11 up to now (see the solid-line graph in FIG. 14 ) (by fitting the graph after the change of the time axis to the solid-line graph in FIG. 14 ), thereby obtaining a predicted transition of the detection results (transition of the future detection results) shown by the dotted line in FIG. 14 . Note that the method for calculating the predicted transition of the detection results of the sensor 11 is not limited to this. For example, if the detection results of the sensor 11 change linearly (if the slope of the graph is constant), the predicted transition of the detection results of the sensor 11 can be obtained by calculating an extension line of the graph of the detection results of the sensor 11 up to now.

[0087] The rate at which oil deterioration progresses is thought to change depending on the usage of the device 62. For example, as the frequency of use of the device 62 increases, oil deterioration accelerates, and therefore the change in the detection result of the sensor 11 is thought to be more rapid. Conversely, as the frequency of use of the device 62 decreases, oil deterioration is suppressed, and therefore the change in the detection result of the sensor 11 is thought to be more slow. Because the rate at which oil deterioration progresses changes in this way, it is thought that predicting future trends in detection results based on the most recent progression of oil deterioration will improve prediction accuracy. Therefore, in the first embodiment, the predicted trend in detection results shown by the dotted line in FIG. 14 is obtained using the most recent detection results stored in the detection result database 43 (in other words, without using older detection results). This allows for highly accurate prediction of future trends in detection results and for highly accurate diagnosis of the oil change time. However, the predicted trend in detection results shown by the dotted line in FIG. 14 may also be obtained using the detection results of the sensor 11 from the beginning of oil use.

[0088] Next, the diagnostic processing unit 33 calculates the replacement time t1 at which the detection result of the sensor 11 reaches the replacement threshold Tc (S203). For example, the diagnostic processing unit 33 calculates the intersection of the dotted line graph in FIG. 14 with the replacement threshold Tc, and sets the time coordinate of the intersection as the replacement time t1. The replacement time t1 at which the detection result of the sensor 11 reaches the replacement threshold Tc corresponds to the time when the oil has deteriorated to the point where an oil change is required, and corresponds to the time when the oil reaches the end of its life. For this reason, in the following description, the time at which the detection result of the sensor 11 reaches the replacement threshold Tc may also be referred to as the "end of life date" of the oil.

[0089] The diagnostic processing unit 33 also calculates the remaining period Pr until the replacement time t1 (S204). For example, as shown in FIG. 14, the diagnostic processing unit 33 calculates the remaining period Pr by calculating the difference between the replacement time t1 and the current time t0. The remaining period Pr is the period (number of days) until the oil reaches its end of life, and therefore corresponds to the "remaining life (remaining life)" of the oil. If the detection result of the sensor 11 is already below the replacement threshold Tc, the remaining period Pr is expressed as a negative value.

[0090] The diagnostic processing unit 33 performs the diagnostic processing shown in S201 to S204 for each sensor 11, and calculates the oil change time t1 and remaining period Pr for each sensor 11 (in other words, for each oil detected by each sensor 11).

[0091] After the diagnostic processing is performed by the diagnostic processing unit 33 (S201 to S204), the notification processing unit 34 of the diagnostic device 20 performs notification processing (S205 to S207).

[0092] First, the notification processing unit 34 identifies a sensor ID for which the notification timing has arrived (S205). At this time, the notification processing unit 34 compares the remaining period Pr (see FIG. 14 ) calculated in S204 with the period threshold Tp (see FIG. 10 ). If the remaining period Pr is smaller than the period threshold Tp, the notification processing unit 34 determines that the notification timing has arrived. That is, the notification processing unit 34 identifies a sensor ID for which the remaining period Pr is smaller than the period threshold Tp, based on the remaining period Pr calculated for each sensor 11 (for each sensor ID) and the period threshold Tp set for each sensor 11 in the diagnostic setting database 42.

[0093] Next, the notification processing unit 34 identifies a notification destination corresponding to the sensor ID identified in S205 (S206). For example, if the sensor ID identified in S205 is "sensor 001," the notification processing unit 34 identifies the notification destination associated with "sensor 001" in the diagnostic setting database 42 as "user" (see FIG. 10), identifies the user ID associated with "sensor 001" in the sensor database 415 as "AAA" (see FIG. 9), and identifies the contact information (e.g., email address) associated with "AAA" in the user database 414 as the notification destination of the "user" corresponding to the sensor ID (see FIG. 8A). Note that if a supplier ID and a user ID (or customer ID) are associated as notification destinations of the diagnostic setting information in the diagnostic setting database 42, the notification processing unit 34 identifies the contact information, such as the supplier ID, associated with "sensor 001" in the diagnostic setting database 42. Also, for example, if the sensor ID identified in S206 is "sensor 002," the notification processing unit 34 identifies the notification destination associated with "sensor 002" in the diagnostic setting database 42 as "supplier," identifies the user ID associated with "sensor 002" in the sensor database 415 as "AAA" (see Figure 9), identifies the supplier ID associated with "AAA" in the user database 414 as "X" (see Figure 8A), and identifies the contact (e.g., email address) associated with "X" in the supplier database 413 as the notification destination of the "supplier" corresponding to the sensor ID (see Figure 8A).

[0094] Next, the notification processing unit 34 notifies the notification destination identified in S206 of an alert (S207). The alert notified from the notification processing unit 34 includes information (replacement information) indicating the replacement time diagnosed by the diagnosis processing unit 33. Note that the replacement information notified by the notification processing unit 34 may be information indicating the replacement time diagnosed by the diagnosis processing unit 33, and is not limited to date information indicating the replacement time t1. For example, the replacement information includes "information regarding the remaining period indicating the number of days until the replacement time" and "information indicating that the replacement time is approaching."

[0095] In the first embodiment, the notification processing unit 34 performs the notification processing of S205 to S207, thereby enabling an alert to be sent to the notification destination when the remaining period Pr reaches the period threshold Tp. This allows the alert to be sent at a predetermined timing. If the period threshold Tp is set to a positive value, the alert can be sent before the oil reaches the end of its life (before the oil's life end date). On the other hand, if the period threshold Tp is set to a negative value, the alert can be sent after the oil reaches the end of its life.

[0096] In the first embodiment, the period threshold can be set in association with each sensor 11 (sensor ID) in the diagnostic setting database 42. This allows alerts to be sent at timings suited to different requirements.

[0097] 15A to 15C are explanatory diagrams of the alert screen. When the notification processing unit 34 notifies the alert (S207), an alert screen showing the replacement information is displayed on the user terminal 61 or supplier terminal 71 that notified the alert. 15A to 15C show the alert screen displayed on the user terminal 61.

[0098] The alert screen is a screen that is displayed on the user terminal 61 or supplier terminal 71 that has received the alert. Information indicating the oil change timing diagnosed by the diagnosis processing unit 33 is displayed on the alert screen.

[0099] The alert screen shown in FIG. 15A displays the target equipment, end-of-life date, remaining life, and contact information. The "Target Equipment" field on the alert screen displays information (equipment information) about the equipment 62 using the oil to be replaced. The "End-of-Life Date" and "Remaining Life" fields on the alert screen display information corresponding to the replacement time t1 (see FIG. 14) and the remaining life Pr. The "Contact Information" field on the alert screen displays contact information for the oil supplier. Note that the screen displayed on the supplier terminal 71 may also display contact information for the oil user. The alert screen shown in FIG. 15A directly displays numerical values ​​such as the date and number of days corresponding to the replacement time t1 (see FIG. 14) and the remaining life Pr as replacement information (information indicating the replacement time diagnosed by the diagnostic processing unit 33).

[0100] 15B displays information about the device 62 using the oil to be replaced and information corresponding to the replacement time t1 (see FIG. 14; life end date). In this way, the alert screen may display only one of the information corresponding to the replacement time t1 and the remaining life Pr as replacement information.

[0101] 15C displays information about the device 62 using the oil to be changed and information indicating that the time for changing the oil is approaching. In this way, the change information displayed on the alert screen does not have to be a specific date or number of days, and may be information indicating that the time for change diagnosed by the diagnosis processing unit 33 is approaching.

[0102] By displaying the alert screen on the user terminal 61, the user can know when it is time to change the oil used in the target equipment, and will change the oil as necessary. Also, by displaying the alert screen on the supplier terminal 71, the supplier can know when it is time to change the oil used in the equipment 62 at the user's location, and will urge the user to change the oil as necessary. In this way, by notifying the alert by the notification processing unit 34 in S207, it is possible to urge the user or supplier to change the oil.

[0103] 13, an alert is issued for the oil in a certain device 62 (S207). However, in a situation where a user uses multiple devices 62, it would be convenient to be able to grasp information about other oils supplied to the user when notifying the user of oil information for a certain device 62. Therefore, the following describes the process of notifying a user of a list including information about the oil in multiple devices 62 used by the user.

[0104] Fig. 16 is a flow diagram of the list notification process. S207 in the diagram (and the process performed before S207) is the same as in Fig. 13, so a description thereof will be omitted here.

[0105] The notification processing unit 34 identifies the user ID to be included in the list (S301). Here, the notification processing unit 34 identifies the user ID corresponding to the sensor ID for which the notification timing has arrived. For example, if the sensor ID identified in the above-mentioned S205 is "sensor 001," the notification processing unit 34 identifies, based on the sensor database 415 (see FIG. 9), that the user ID to be included in the list is "AAA."

[0106] Next, the notification processing unit 34 identifies the sensor ID corresponding to the user ID identified in S301 (S302). For example, if the user ID identified in S301 is "AAA," the notification processing unit 34 identifies "sensor 001" and "sensor 002" as the sensor IDs to be included in the list based on the sensor database 415 (see FIG. 9). The notification processing unit 34 then extracts information about the oil corresponding to the sensor ID identified in S302 and creates a list (S303).

[0107] Fig. 17A is an explanatory diagram of an example of the list created in S303. Note that Fig. 17A is also an explanatory diagram of an example of the list transmitted to the supplier terminal 71 in S304.

[0108] The list shows information about the oil used in the device 62 corresponding to the user ID. In a situation where a user uses multiple devices 62, the list will include information about the oil in each of the multiple devices 62 used by the user. The list shown in FIG. 17A includes not only information about the oil corresponding to "sensor 001" for which the user was notified of an alert, but also information about another oil (oil corresponding to "sensor 002").

[0109] The list in the figure includes information such as a sensor ID, an oil ID, device information, a lifespan end date, a remaining lifespan, and whether or not a notification has been issued. The sensor ID is information (identification number) about the sensor 11 attached to the device 62 used by the user. The oil ID is information for identifying the oil to be detected by the sensor 11. The device information is information about the device 62 in which the oil is used. The lifespan end date corresponds to the replacement time t1 (see FIG. 14). The remaining lifespan corresponds to the remaining period Pr (see FIG. 14). The presence or absence of a notification indicates whether or not the above-mentioned alert notification has been issued. The list in the figure includes information such as the lifespan end date (the replacement time t1 calculated by the diagnostic processing unit 33) and the remaining lifespan (the remaining period Pr calculated by the diagnostic processing unit 33) as replacement information (information indicating the replacement time diagnosed by the diagnostic processing unit 33). However, the replacement information included in the list may be either the lifespan end date or the remaining lifespan, or may be other information. The list may also include user ID information associated with the sensor ID.

[0110] After creating the list, the notification processing unit 34 notifies the supplier terminal 71 of the list (S304). By notifying the list, the notification processing unit 34 can display the oil change information for each of the multiple devices 62 used by the user on the supplier terminal 71. Based on the list, the supplier can grasp the oil change information for each of the multiple devices 62 used by the user. This allows the supplier to, for example, make a comprehensive proposal to the user that includes not only the oil change for which the alert was notified, but also the change of other oils. In other words, this allows the supplier to easily diagnose the change times for multiple oils used by the user. In this way, when notifying an alert for oil in a certain device 62, it is effective to notify the supplier terminal 71 of a list including information on other oils supplied to that user.

[0111] (List notification process in response to a request) In the list notification process described above, when an alert is notified regarding oil in a certain device 62, the list is notified to the supplier terminal 71. However, as will be described next, the list may also be notified in response to a request from the user (or supplier).

[0112] 18 is a flow diagram of another list notification process, which shows a flow diagram for notifying a list in response to a request from the user terminal 61.

[0113] When the notification processing unit 34 receives a request for the list from the user terminal 61, it identifies the user ID that is the target of the list (S301). As shown in the flow chart, if the terminal that requested the list is the user terminal 61, the notification processing unit 34 identifies the user ID corresponding to the user terminal 61 in S301. If the terminal that requested the list is the supplier terminal 71, the notification processing unit 34 identifies the supplier ID corresponding to the supplier terminal 71 in S301 and identifies the user ID associated with the identified supplier ID (if the supplier supplies oil to multiple users, multiple user IDs will be identified in S301).

[0114] 16, the notification processing unit 34 identifies the sensor ID corresponding to the user ID identified in S301 (S302), and extracts information about the oil corresponding to the sensor ID identified in S302 to create a list (S303). When creating the list in S303, the diagnosis processing unit 33 obtains replacement information necessary for the list (for example, calculates the replacement time t1 corresponding to the end of life date and the remaining period Pr corresponding to the remaining life).

[0115] After creating the list, the notification processing unit 34 notifies the terminal that requested the list (here, the user terminal 61) of the list (S304). Note that in S304 in the figure, the user terminal 61 is notified of the list. However, if a list request is received from the supplier terminal 71, the notification processing unit 34 will notify the supplier terminal 71 of the list. That is, when a list request is received from the supplier terminal 71, the notification processing unit 34 identifies the supplier ID (S301), identifies multiple sensor IDs associated with the identified supplier ID (S302), creates a list including replacement information corresponding to each of the identified multiple sensor IDs (S303), and notifies the supplier terminal 71 of the list (S304). This allows the supplier to easily diagnose the timing of oil change. Furthermore, if the supplier supplies oil to multiple users, the notification processing unit 34 will notify the supplier terminal 71 of the lists of the multiple users (S304).

[0116] The list sent by the notification processing unit 34 includes replacement information corresponding to each of the multiple sensors 11. This allows the change times for multiple oils to be diagnosed using a simple method. It is desirable for the notification processing unit 34 to send a list in which the multiple pieces of replacement information are arranged in order of the remaining life. This makes it easier for the supplier to check the information, as the list lists the information for multiple oils in order of the likelihood of needing an oil change.

[0117] Incidentally, when a request for a list or replacement information is received from the user terminal 61, it can be assumed that the user is interested in oil changes. Therefore, when a request for a list or replacement information is received from the user terminal 61, the notification processing unit 34 notifies the supplier terminal 71 that a request for a list or replacement information has been received from the user terminal 61 (S401). This allows the supplier to understand that the user is interested in oil changes. When a request for a list is received from the user terminal 61, the notification processing unit 34 may send the list that was sent to the user terminal 61 to the supplier terminal 71 as a notification to that effect. This makes it easier for the supplier to make a comprehensive proposal to the user, including changing the oil in the list.

[0118] (List notification process using change history) The history processing unit 35 of the control unit 30 sets information about oil changes that were performed in the past (actual change information) in the change history database 44. For example, after an oil change is performed, the user registers the information about the oil change (actual change information) in the diagnostic device 20 using the user terminal 61, or the supplier registers the information about the oil change (actual change information) in the diagnostic device 20 using the supplier terminal 71, whereby the information about the oil change that was actually performed (actual change information) is set in the change history database 44.

[0119] FIG. 19 is an explanatory diagram of the replacement history database 44.

[0120] The change history database 44 is a database that stores information about past oil changes (actual change information). The change history database 44 accumulates actual change information for each sensor ID. Here, the actual change information includes information such as the date of the oil change, the oil ID, and the remaining life span. The remaining life span in the actual change information indicates the remaining life span of the oil at the time of the actual oil change. Specifically, the remaining life span in the actual change information indicates the difference between the change time t1 (the time when the detection result of the sensor 11 is diagnosed as reaching the change threshold Tc, or the time when the detection result of the sensor 11 reaches the change threshold Tc) and the time when the oil change was actually performed. If the oil change was performed earlier than the diagnosed change time t1, the remaining life span will be a positive value. On the other hand, if the oil change was performed later than the change time t1, the remaining life span will be a negative value. The remaining life span in the change history database 44 serves as information that indicates the user's tendency toward oil change timing.

[0121] Fig. 17B is an explanatory diagram of another example of the list transmitted to the supplier terminal 71. Note that the list shown in Fig. 17B may also include information on the user ID in association with the sensor ID.

[0122] As already described, in S401 of FIG. 18 , the notification processing unit 34 may transmit a list to the supplier terminal 71. In this case, the list transmitted to the supplier terminal 71 may include information about the user's past oil changes. The information about past oil changes preferably includes information about the remaining life of the oil at the previous oil change (the remaining period of actual change information in the change history database 44), as shown in FIG. 17B . This allows the supplier to understand the user's tendency toward oil change timing and to recommend an oil change to the user based on the user's tendency. For example, upon receiving the list of FIG. 17B , the supplier can determine that the user's oil change timing is relatively late and recommend an oil change to the user. Here, the notification processing unit 34 notifies the supplier terminal 71 of information about the remaining life of the oil at the previous oil change. However, the actual change information notified to the supplier terminal 71 is not limited to the remaining life of the oil and may include other actual change information.

[0123] <Summary> As described above, the diagnostic system 100 of the first embodiment includes the sensor 11, the storage unit 40 that stores the detection results of the sensor 11, and the control unit 30. The control unit 30 of the first embodiment diagnoses the oil change timing based on the detection results stored in the storage unit 40 (see detection result database 43 in FIG. 12 ) (see S203 in FIG. 13 ), and notifies the notification destination associated with the sensor 11 of change information indicating the diagnosed change timing (see S207 in FIG. 13 ). According to the diagnostic system 100 of the first embodiment configured in this manner, because the change information is notified to the notification destination associated with the sensor 11, it is possible to easily grasp the oil change timing detected by the sensor 11, and to diagnose the oil change timing using a simple means.

[0124] Furthermore, in the diagnostic method of the first embodiment, the detection result is obtained from the sensor 11 (see FIG. 11), the time for oil change is diagnosed based on the detection result of the sensor 11 (see S203 in FIG. 13), and replacement information indicating the diagnosed time for oil change is notified to a notification destination associated with the sensor (see S207 in FIG. 13). According to this diagnostic method, since the replacement information is notified to the notification destination associated with the sensor 11, it is possible to easily grasp the time for oil change detected by the sensor 11 and diagnose the time for oil change by a simple means.

[0125] In the above description, the sensor 11 that detects the deterioration state of the oil is a color sensor. Because the color of the oil changes depending on the remaining rate of additives (see Figures 7A to 7C), it is possible to detect the deterioration state of the oil using a color sensor. However, the sensor 11 does not have to be a color sensor. For example, the sensor 11 may analyze the components of the oil and output component data as the detection result. In this case, the aforementioned replacement threshold is not a gradation value, but a value corresponding to the component data when the oil has reached the end of its life. In this way, the replacement threshold is not limited to a gradation value. The sensor 11 may also detect the deterioration state of the oil by analyzing impurities contained in the oil, such as the amount of iron powder.

[0126] Second Embodiment Next, a second embodiment of the present disclosure will be described.

[0127] Patent Document 1 describes that lubricating oils contain various additives, including load-bearing additives such as oiliness agents, antiwear agents, and extreme-pressure additives (extreme-pressure agents), as well as antioxidants and antifoaming agents. Patent Document 1 also describes estimating the concentration of additives contained in lubricating oil based on the value B in the color data. However, when diagnosing the residual rate of an antioxidant, which is one of the additives, estimation based on the value B may be less accurate.

[0128] The second embodiment aims to appropriately diagnose oil deterioration.

[0129] <Regarding the Diagnostic Method> Figures 7A to 7C are graphs showing the time-varying detection results of a color sensor and the time-varying remaining rate of antioxidant contained in oil used under certain conditions. In each graph, the horizontal axis represents time. The vertical axis on the left represents the gradation values ​​of each of the RGB colors (red, green, and blue). The vertical axis on the right represents the remaining rate (%) of the additive (here, antioxidant). The solid line graph represents the time-varying detection results (RGB data) of the color sensor when the color of the oil is detected by the color sensor. The dotted line graph represents the time-varying remaining rate of antioxidant. Figures 7A to 7C each show graphs for different oils (oil A to oil C).

[0130] The color sensor is a sensor (color detector) for detecting the color of oil. The color sensor has a light-emitting unit and a light-receiving unit. The light-emitting unit irradiates light toward the oil, and the light-receiving unit receives the light from the oil. The color sensor outputs RGB data (color data including R data, G data, and B data) indicating the gradation values ​​of each of RGB (red, green, blue) according to the amount of light of each color received by the light-receiving unit. Note that the R data is a gradation value indicating the result of receiving light of a red wavelength. The G data is a gradation value indicating the result of receiving light of a green wavelength. The B data is a gradation value indicating the result of receiving light of a blue wavelength.

[0131] 7A to 7C, the residual rate of the antioxidant contained in the oil decreases over time, as shown by the dotted line graph. As the residual rate of the antioxidant changes, the detection results of the color sensor also change, as shown by the solid line graph.

[0132] 7A to 7C, the relationship between changes in the antioxidant residual rate and changes in the detection results of the color sensor varies depending on the type of oil. For example, in the case of Oil A, as shown in FIG. 1A, as the antioxidant residual rate decreases, the B data (data indicating the blue gradation value) decreases, but the R data and G data (data indicating the red and green gradation values) hardly decrease. In the case of Oil B and Oil C, as shown in FIGS. 7B and 7C, as the antioxidant residual rate decreases, not only the B data but also the R data and G data decrease.

[0133] FIG. 20 is a table showing the correlation between the residual rate of the antioxidant and the RGB data.

[0134] The values ​​in the table indicate correlation coefficients. The closer the absolute value of the correlation coefficient is to 1, the stronger the correlation. Note that the closer the correlation coefficient is to 1, the stronger the positive correlation, and the closer the correlation coefficient is to -1, the stronger the negative correlation. As shown in FIG. 1 , for Oil A and Oil B, the B data is more strongly correlated with the antioxidant residual rate than the other colors (R data and G data). On the other hand, for Oil C, the G data is more strongly correlated with the antioxidant residual rate than the other colors (R data and B data). When the antioxidant residual rate is strongly correlated with the B data, as in Oil A and Oil B, it is desirable to diagnose the antioxidant residual rate based on the B data. On the other hand, when the antioxidant residual rate is strongly correlated with the G data, as in Oil C, diagnosing the antioxidant residual rate based on the G data allows for more accurate diagnosis of the antioxidant residual rate than diagnosing the antioxidant residual rate based on the B data.

[0135] When a new oil product is developed, the components (base oil and antioxidant) contained in the oil are determined, along with the blending ratio of each component. Therefore, at this timing, the relationship between changes in the antioxidant residual rate in the oil and changes in the color sensor detection results is determined. Therefore, by measuring the time change in the antioxidant residual rate of the developed oil under given operating conditions and measuring the time change in the detection results (RGB data output from the color sensor) when the oil is detected with the color sensor, measurement results (graphic information) such as those shown by the dotted and solid lines in Figures 7A to 7C are obtained. Based on these measurement results, correlation coefficients for each color of the R data, G data, and B data with the antioxidant residual rate are calculated, as shown in Figure 20, and data from the RGB data that are highly correlated with the antioxidant residual rate are identified. In this way, wavelengths (colors) that are highly correlated with the antioxidant residual rate can be identified for each type of oil.

[0136] In the second embodiment, oil degradation is diagnosed based on the results of receiving light of different wavelengths depending on the type of oil. That is, when diagnosing a first oil (e.g., oil A or oil B), the degradation of the first oil is diagnosed based on the results of receiving light of the first wavelength (e.g., B data), and when diagnosing a second oil (e.g., oil C), the degradation of the second oil is diagnosed based on the results of receiving light of the second wavelength (e.g., G data). This allows appropriate diagnosis of oil degradation to be performed depending on the type of oil.

[0137] Furthermore, when diagnosing oil degradation in this manner, it is desirable that the light reception results (e.g., B data) of the first wavelength for the first oil (e.g., oil A or oil B) correlate more strongly with the residual rate of the antioxidant contained in the first oil than the light reception results (e.g., G data) of the second wavelength. This allows for appropriate diagnosis of degradation of the first oil due to a decrease in the residual rate of the antioxidant. It is also desirable that the light reception results (e.g., G data) of the second wavelength for the second oil (e.g., oil C) correlate more strongly with the residual rate of the antioxidant contained in the second oil than the light reception results (e.g., B data) of the first wavelength. This allows for appropriate diagnosis of degradation of the second oil due to a decrease in the residual rate of the antioxidant.

[0138] Furthermore, the diagnostic device for diagnosing oil degradation of the second embodiment diagnoses the degradation of a first oil (e.g., oil A or oil B) based on the light reception results of a first wavelength (e.g., B data) when diagnosing a first oil, and diagnoses the degradation of a second oil (e.g., oil C) based on the light reception results of a second wavelength (e.g., G data) when diagnosing a second oil. For example, diagnostic device 20, described below, diagnoses the oil degradation based on the B data when diagnosing oil A or oil B (corresponding to the first oil), and diagnoses the oil degradation based on the G data when diagnosing oil C. This allows appropriate diagnosis of oil degradation depending on the type of oil.

[0139] <Example of Use of Diagnostic Method> The configuration of the diagnostic system of the second embodiment is the same as the configuration of the diagnostic system 100 shown in FIG. 1 and described in the first embodiment, and therefore a description thereof will be omitted.

[0140] 2A and 2B , the sensor unit 10 includes a color sensor 11, a control unit 12, and a communication unit 13. As already described, the color sensor 11 detects the color of the oil and outputs RGB data. The control unit 12 controls the sensor unit 10. The communication unit 13 communicates with the diagnostic device 20 via a communication network 90. ​​For example, the control unit 12 transmits the detection result of the color sensor 11 (here, RGB data) to the diagnostic device 20 via the communication unit 13.

[0141] The control unit 30 of the diagnostic device 20 diagnoses the timing of oil change based on the detection results (RGB data in this case) of the color sensor 11 stored in the storage unit 40 .

[0142] As shown in FIG. 6 , the diagnostic color included in the profile information is information for identifying which of the RGB data detected by the color sensor 11 is used for diagnosing the oil. If the diagnostic color is set to “blue (B),” the “B data” of the RGB data is used for diagnosing the oil. If the diagnostic color is set to “green (G),” the “G data” of the RGB data is used for diagnosing the oil. If the diagnostic color is set to “red (R),” the “R data” of the RGB data is used for diagnosing the oil. Here, the B data is set to be used for diagnosing oils A and B, and the G data is set to be used for diagnosing oil C. As will be described later, the diagnostic color of the profile information is information for switching between the functioning of the diagnostic processing unit 33 as a first diagnostic unit and a second diagnostic unit.

[0143] The change threshold included in the profile information is a threshold used to diagnose whether an oil change is necessary. A "gradation value" is set as the change threshold. For example, in the case of oil A, a gradation value of "50" is set as the change threshold. Therefore, when diagnosing oil A, the gradation value indicated by the "B data" of the RGB data output by the color sensor 11 is compared with the threshold value of "50." When the detection result of the color sensor 11 reaches the change threshold, it indicates that the oil has deteriorated to the point where an oil change is required. In other words, the change threshold is a reference value for determining when the oil needs to be changed (in other words, the change threshold is a reference value for diagnosing the lifespan of the oil).

[0144] The diagnostic processing unit 33 of the control unit 30 diagnoses oil degradation based on the light reception results of the color sensor 11 (light reception results when receiving light from the oil; here, RGB data). As described below, when diagnosing oil A or oil B (corresponding to the first oil), the diagnostic processing unit 33 is configured to diagnose oil degradation based on B data (the light reception results of light of a first wavelength), and when diagnosing oil C (corresponding to the second oil), the diagnostic processing unit 33 is configured to diagnose oil degradation based on G data (the light reception results of light of a second wavelength). In other words, the diagnostic processing unit 33 functions as a first diagnostic unit that diagnoses oil degradation based on B data and a second diagnostic unit that diagnoses oil degradation based on G data. Note that the diagnostic processing unit may also be configured to diagnose oil degradation based on R data. The arithmetic processing unit of the diagnostic device 20 executes a program stored in the storage device to realize each process of the control unit 30 (diagnostic processing unit 33) described below.

[0145] The diagnostic processing unit 33 determines the diagnostic color (see FIG. 6) set for the oil associated with the sensor ID. For example, when diagnosing the oil detected by "sensor ID: sensor 001," the diagnostic processing unit 33 determines the diagnostic color to be "blue (B)" based on the profile database 412 (FIG. 6) because the oil ID associated with "sensor ID: sensor 001" in the sensor database 421C (see FIG. 9) is "oil A." On the other hand, when diagnosing the oil detected by "sensor ID: sensor 003," the diagnostic processing unit 33 determines the diagnostic color to be "green (G)" based on the profile database 412 (FIG. 6) because the oil ID associated with "sensor ID: sensor 003" in the sensor database 421C (see FIG. 9) is "oil C."

[0146] If the diagnostic color is determined to be "blue (B)," the diagnostic processing unit 33 (first diagnostic unit) extracts B data from the RGB data in the detection result database 43. Therefore, when diagnosing the oil detected by "sensor ID: sensor 001" (here, oil A), B data is extracted from the RGB data for "sensor ID: sensor 001" in the detection result database 43. The diagnostic processing unit 33 also obtains graph information for blue (B) gradation values ​​from the graph information for RGB gradation values ​​in the profile database 412 (see FIG. 1A ). The diagnostic processing unit 33 determines the oil change timing and remaining life as an oil deterioration diagnosis based on the B data extracted from the detection result database 43 and the graph information for blue (B) gradation values ​​obtained from the profile database 412.

[0147] The diagnostic processing unit 33 expands or contracts the time axis of the graph of blue (B) gradation values ​​acquired from the profile database 412 so that it matches the transition of the color sensor 11's detection results to date (see the solid-line graph in FIG. 14 ). The diagnostic processing unit 33 then fits the graph with the altered time axis to the transition of the color sensor 11's detection results to date (see the solid-line graph in FIG. 14 ) (by fitting the altered time axis graph to the solid-line graph in FIG. 14 ), thereby obtaining a predicted transition of the detection results (the transition of future detection results) shown by the dotted line in FIG. 14 . Next, the diagnostic processing unit 33 calculates the replacement time t1, when the detection results of the color sensor 11 reach a predetermined threshold Tc. The replacement time t1 corresponds to the time when the oil has deteriorated to the point where an oil change is required, and is the "life end date" when the oil reaches its end of life. Furthermore, the diagnostic processing unit 33 calculates the remaining life Pr by calculating the difference between the replacement time t1 and the current time t0, as shown in FIG. 14 . The remaining period Pr is the period (number of days) until the end of the oil's life, and therefore corresponds to the "remaining life" of the oil.

[0148] The rate at which oil deterioration progresses is thought to change depending on the usage conditions of the equipment using the oil. For example, as the frequency of use of the equipment increases, oil deterioration accelerates, and therefore the change in the detection results of the color sensor 11 is thought to be more rapid. Conversely, as the frequency of use of the equipment decreases, oil deterioration is suppressed, and therefore the change in the detection results of the color sensor 11 is thought to be more slow. Because the rate at which oil deterioration progresses changes in this way, it is thought that predicting future trends in detection results (see the dotted line in Figure 14) based on the most recent progression of oil deterioration will result in higher prediction accuracy. Therefore, it is desirable to use newer detection results stored in the detection result database 43 (in other words, without using older detection results) to obtain the predicted trend in the detection results shown by the dotted line in Figure 14. This allows for highly accurate prediction of future trends in the detection results and for highly accurate diagnosis of the oil change time t1. However, the predicted trend in the detection results shown by the dotted line in Figure 14 may also be obtained using the detection results of the color sensor 11 from the beginning of oil use.

[0149] If the diagnostic color is determined to be "green (G)," the diagnostic processing unit 33 (second diagnostic unit) extracts G data from the RGB data in the detection result database 43. Therefore, when diagnosing the oil detected by "sensor ID: sensor 003" (here, oil C), the diagnostic processing unit 33 extracts G data from the RGB data for "sensor ID: sensor 003" in the detection result database 43. The diagnostic processing unit 33 also obtains graph information for green (G) gradation values ​​from the graph information for RGB gradation values ​​in the profile database 412 (see FIG. 7C ). Based on the G data extracted from the detection result database 43 and the graph information for green (G) gradation values ​​obtained from the profile database 412, the diagnostic processing unit 33 determines the oil change time t1 and remaining life Pr as an oil deterioration diagnosis. The method for calculating the change time t1 and remaining life Pr is as shown in FIG. 14 , and therefore will not be described here.

[0150] If the remaining period Pr is less than a predetermined threshold (for example, 14 days), the notification processing unit 34 of the control unit 30 (see FIG. 1) sends an alert to the user terminal 61 and the supplier terminal 71 .

[0151] As described above, when diagnosing a first oil (e.g., oil A or oil B), the control unit 30 (diagnosis processing unit 33) diagnoses the deterioration of the first oil based on the light reception result of the first wavelength (e.g., B data), and when diagnosing a second oil (e.g., oil C), the control unit 30 (diagnosis processing unit 33) diagnoses the deterioration of the second oil based on the light reception result of the second wavelength (e.g., G data). This allows appropriate diagnosis of oil deterioration to be made depending on the type of oil.

[0152] The diagnostic device is not limited to the diagnostic device 20 described above. For example, the control unit 12 of the sensor unit 10 shown in FIG. 2B may be provided with the functions of the diagnostic processing unit 33 described above, so that the sensor unit 10 (or the control unit 12) constitutes a diagnostic device that diagnoses oil degradation. Furthermore, the diagnostic device that diagnoses oil degradation does not need to notify the user terminal 61 or the supplier terminal 71 of an alert. In other words, the diagnostic device 20 does not need to be provided with the notification processing unit 34.

[0153] Furthermore, the diagnosis of oil degradation is not limited to diagnosing the oil change timing t1 or remaining life Pr. For example, the remaining percentage of antioxidant contained in the oil may also be diagnosed as a diagnosis of oil degradation. When diagnosing the remaining percentage of antioxidant contained in the oil, it is desirable that the profile database 412 further includes data indicating the relationship between time and gradation value of the antioxidant remaining percentage (data shown in the dotted line graphs in Figures 7A to 7C). The diagnostic processing unit 33 (first diagnostic unit) calculates the remaining percentage of antioxidant corresponding to the gradation value indicated by the B data (corresponding to the light reception result of the first wavelength) of the color sensor 11. The diagnostic processing unit 33 (second diagnostic unit) calculates the remaining percentage of antioxidant corresponding to the gradation value indicated by the G data (corresponding to the light reception result of the second wavelength) of the color sensor 11. Even in this case, the diagnosis of oil degradation can be appropriately performed depending on the type of oil.

[0154] ===Modifications=== The above embodiments are intended to facilitate understanding of the present disclosure and are not intended to limit the present disclosure. Furthermore, the present disclosure may be modified or improved without departing from the spirit thereof, and it goes without saying that the present disclosure includes equivalents thereof.

[0155] For example, in the first embodiment, the sensor 11 is described as a color sensor, but the type of sensor may be a contact sensor or a non-contact sensor. Non-contact sensors include the above-mentioned color sensor, as well as image sensors and chemical sensors. Furthermore, the sensor 11 may be an optical sensor, an ultrasonic sensor, a temperature sensor, or the like. Examples of optical sensors include a visible light sensor, an infrared sensor, and an ultraviolet sensor.

[0156] Furthermore, in the first embodiment, the case has been described in which the control unit 30 notifies the replacement information to a notification destination associated with the sensor 11, but the replacement information may also be notified to a notification destination associated with the sensor unit 10, the device 62, or the tank 63. Even in this case, the "notification destination associated with the sensor 11" includes the "notification destination associated with the sensor unit 10, the device 62, or the tank 63" because the sensor unit 10, the device 62, or the tank 63 has the sensor 11. Furthermore, the control unit 30 may notify the replacement information not to a notification destination associated with the sensor 11, but simply to a notification destination selected by an administrator or a notification destination selected by a user.

[0157] Furthermore, in the first and second embodiments, the storage device 52 has been described as a recording medium for recording a program, but the recording medium is not limited to this. The recording medium may be, for example, a storage device such as a hard disk drive (HDD) or solid state drive (SSD) built into a computer system, or a portable recording medium such as a magneto-optical disk, a read-only memory (ROM), a compact disc (CD)-ROM, or a flash memory.

[0158] 10 Sensor unit, 11 Sensor, 12 Control unit, 13 Communication unit, 20 Diagnostic device, 30 Control unit, 31 Setting processing unit, 32 Data acquisition unit, 33 Diagnostic processing unit, 34 Notification processing unit, 35 History processing unit, 40 Storage unit, 41 Basic information database, 411 Oil database, 412 Profile database, 413 Supplier database, 414 User database, 414' Customer database, 415 Sensor database, 42 Diagnostic setting database, 43 Detection result database, 44 Replacement history database, 51 Processing device, 52 Storage device, 53 Communication device, 54 Display device, 55 Input device, 61 User terminal, 62 Equipment, 63 Tank, 71 Supplier terminal, 90 Communication network, 100 Diagnostic system,

Claims

1. A diagnostic device comprising: a memory unit that stores detection results of a sensor that indicate the deterioration state of oil; and a control unit that diagnoses when to change the oil based on the detection results stored in the memory unit, and notifies a notification destination associated with the sensor of replacement information indicating the diagnosed replacement time.

2. A diagnostic device according to claim 1, wherein at least one of a user of the oil and a supplier who has supplied the oil to the user can be set as the notification destination.

3. A diagnostic device according to claim 1, wherein the control unit calculates, as the replacement time, the time when the detection result will reach a replacement threshold value.

4. A diagnostic device according to claim 3, wherein the replacement threshold value can be set in association with the sensor.

5. A diagnostic device according to claim 1, wherein the control unit diagnoses the replacement time by using the most recent detection result among the detection results stored in the memory unit.

6. A diagnostic device according to claim 1, wherein the control unit notifies the notification destination of the exchange information when the remaining period reaches a period threshold.

7. A diagnostic device according to claim 6, wherein the period threshold can be set in association with the sensor.

8. A diagnostic device as claimed in claim 6 or 7, wherein, when notifying the destination of the replacement information, the control unit notifies the destination of the supplier who supplied the oil to the user of a list including the replacement information of other oils supplied to the user of the oil.

9. A diagnostic device according to claim 1, wherein the control unit notifies the notification destination of a list including the replacement information corresponding to each of the plurality of sensors.

10. A diagnostic device according to claim 9, wherein the control unit notifies the list in which a plurality of pieces of exchange information are arranged in order of remaining periods.

11. A diagnostic device as claimed in claim 9 or 10, wherein the control unit identifies a plurality of sensors associated with a user to whom the oil supplier is supplying the oil, and notifies the supplier of the list including the replacement information corresponding to each of the identified plurality of sensors.

12. A diagnostic device according to claim 9, wherein, when a user of the oil requests the list, the control unit notifies a supplier of the oil to the user that the user has requested the list.

13. A diagnostic device as claimed in claim 1, wherein, when a user of the oil requests the replacement information, the control unit notifies a supplier of the oil to the user that the user has requested the replacement information.

14. A diagnostic device according to claim 12 or 13, wherein the control unit notifies the supplier of information regarding past oil changes of the user.

15. The diagnostic device according to claim 1, wherein the sensor is a color sensor.

16. The diagnostic device according to claim 1, wherein the control unit diagnoses deterioration of the oil based on the detection results of the sensor, the detection results of light having a wavelength corresponding to the type of oil.

17. A diagnostic method comprising: acquiring detection results from a sensor that detects the deterioration state of oil; diagnosing when to change the oil based on the detection results; and notifying a notification destination associated with the sensor of change information indicating the diagnosed change time.

18. A computer-readable recording medium that records a program for causing a computer to execute the steps of: acquiring detection results from a sensor that detects the deterioration state of oil; diagnosing when to change the oil based on the detection results; and notifying a notification destination associated with the sensor of replacement information indicating the diagnosed replacement time.

19. A diagnostic device comprising: a memory unit that stores the results of receiving light from oil; and a control unit that diagnoses deterioration of the oil based on the results of receiving light, wherein the control unit diagnoses deterioration of the oil based on the results of receiving light of a wavelength corresponding to the type of oil.

20. A diagnostic device as described in claim 19, wherein the control unit, when diagnosing a first oil, diagnoses the deterioration of the first oil based on the result of receiving light of a first wavelength, and, when diagnosing a second oil different from the first oil, diagnoses the deterioration of the second oil based on the result of receiving light of a second wavelength different from the first wavelength.

21. A computer-readable recording medium having recorded thereon a program for causing a computer to execute the steps of: acquiring light reception results when light is received from oil; and diagnosing deterioration of the oil based on the light reception results of light having a wavelength corresponding to the type of oil.

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