Diagnostic device, diagnostic method, and recording medium

Abstract

A diagnostic system (100) according to the present disclosure is provided with: a storage unit (40) for storing the detection results of a sensor (11) indicating the state of deterioration of oil; and a control unit (30) that diagnoses the replacement time of the oil on the basis of the detection results stored in the storage unit (40), and notifies a notification target associated with the sensor (11) of replacement information indicating the diagnosed replacement time.

Description

[0001] (Mutual reference to related applications)

[0002] This application claims priority to Japanese Patent Application No. 2023-128863 and Japanese Patent Application No. 2023-128864, filed on August 7, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to diagnostic devices, diagnostic methods, and recording media. Background Technology

[0004] Patent document 1 describes a method for diagnosing the deterioration of lubricating oil using a sensor.

[0005] Patent Document 1: Japanese Patent Application Publication No. 2019-78718

[0006] Lubricating oils and other oils are supplied to users either from general distributors through suppliers (agents, authorized dealers, etc.) or directly from general distributors to users. Generally, oil deteriorates depending on usage time and environment. Continued use of deteriorated oil can lead to malfunctions in machinery, etc., so users need to change the oil at appropriate intervals. However, until now, suppliers and users have no simple way to diagnose when to change the oil. Summary of the Invention

[0007] The purpose of this disclosure is to provide a simple way to diagnose when oil needs to be changed.

[0008] The present invention provides a diagnostic device for achieving the above objectives, comprising: a storage unit for storing detection results of a sensor indicating the deterioration state of oil; and a control unit for diagnosing the oil replacement period based on the detection results stored in the storage unit, and notifying a notification object corresponding to the sensor of replacement information indicating the diagnosed replacement period.

[0009] Other features of this disclosure will become clear from the description in this specification and the accompanying drawings.

[0010] According to this disclosure, it is possible to diagnose oil change intervals in a simple manner. Attached Figure Description

[0011] Figure 1 This is an explanatory diagram of the diagnostic system.

[0012] Figure 2A This is an explanatory diagram of the sensor unit.

[0013] Figure 2B This is an explanatory diagram of a modified example of the sensor unit.

[0014] Figure 3 This is an explanatory diagram of the hardware configuration of the diagnostic device.

[0015] Figure 4 This is a flowchart for setting up the process.

[0016] Figure 5 This is an illustrative diagram of an example of an oil database.

[0017] Figure 6 This is an illustrative diagram of an example of a short-form database.

[0018] Figure 7A It is a graph showing the relationship between time and grayscale value, and also a graph showing the time change of the color sensor's detection results and the time change of the residual rate of antioxidants contained in the oil.

[0019] Figure 7B It is a graph showing the relationship between time and grayscale value, and also a graph showing the time change of the color sensor's detection results and the time change of the residual rate of antioxidants contained in the oil.

[0020] Figure 7C It is a graph showing the relationship between time and grayscale value, and also a graph showing the time change of the color sensor's detection results and the time change of the residual rate of antioxidants contained in the oil.

[0021] Figure 8A This is an illustrative diagram of an example of a supplier database and a user database.

[0022] Figure 8B This is an illustrative diagram of an example of a customer database.

[0023] Figure 9 This is an illustrative diagram of an example of a sensor database.

[0024] Figure 10 This is an illustrative diagram of an example of a diagnostic settings database.

[0025] Figure 11 This is a flowchart of data acquisition and processing.

[0026] Figure 12 This is an illustrative diagram of an example of a database of test results.

[0027] Figure 13 This is a flowchart of the notification processing.

[0028] Figure 14 This is an explanatory diagram of the replacement period and the remaining period.

[0029] Figure 15A This is an explanatory diagram of the warning screen.

[0030] Figure 15B This is an explanatory diagram of the warning screen.

[0031] Figure 15C This is an explanatory diagram of the warning screen.

[0032] Figure 16 This is a flowchart of list notification processing.

[0033] Figure 17A This is an illustrative diagram of an example of a list created in S303.

[0034] Figure 17B This is another example of a list sent to the supplier terminal.

[0035] Figure 18 This is a flowchart for other list notification processing.

[0036] Figure 19 This is an illustration of changing the resume database.

[0037] Figure 20 This is a table showing the correlation between the residual rate of antioxidants and RGB data. Detailed Implementation

[0038] From the description in this specification and the accompanying drawings, at least the following becomes clear.

[0039] Method 1 provides a diagnostic device comprising: a storage unit for storing detection results from a sensor indicating the deterioration state of oil; and a control unit for diagnosing the oil replacement period based on the detection results stored in the storage unit, and notifying a notification object corresponding to the sensor of replacement information indicating the diagnosed replacement period. According to such a diagnostic device, the oil replacement period can be diagnosed in a simple manner.

[0040] In the diagnostic device according to Method 2, and according to the diagnostic device according to Method 1, at least one of the oil user and the oil supplier can be set as the notification recipient. Therefore, the notification recipient can be set according to the actual situation of oil transactions.

[0041] In the diagnostic device according to Method 3, based on the diagnostic device according to Method 1 or Method 2, the control unit calculates the period when the detection result reaches the replacement threshold as the replacement period. Therefore, it is possible to diagnose the period when the oil has deteriorated to the point of requiring oil replacement.

[0042] In the diagnostic device according to method 4, and according to the diagnostic device according to method 3, the replacement threshold can be set in correspondence with the aforementioned sensor. Therefore, the lifespan of the oil can be set according to each oil.

[0043] In the diagnostic device according to Method 5, based on any one of Methods 1 to 4, the control unit uses new test results stored in the storage unit to diagnose the oil replacement period. This allows for highly accurate diagnosis of the oil replacement period.

[0044] In the diagnostic device according to Method 6, or any one of Methods 1 to 5, the control unit notifies the notification recipient of the replacement information when the remaining period reaches a time threshold. This allows for notification at a predetermined time.

[0045] In the diagnostic device according to method 7, and according to the diagnostic device according to method 6, the aforementioned period threshold can be set correspondingly with the aforementioned sensor. Therefore, notifications can be sent at timings that meet various requirements.

[0046] In the diagnostic device according to method 8, and according to the diagnostic device according to method 6 or 7, when the control unit notifies the notification recipient of the replacement information, it also notifies the notification recipient list of the supplier that supplies the oil to the user. This list contains the replacement information of other oils supplied to the user. Thus, the supplier can easily diagnose the replacement periods of multiple oils used by the user.

[0047] In the diagnostic device according to Method 9, based on the diagnostic device according to any one of Methods 1 to 8, the control unit notifies the notification recipients of a list containing the replacement information corresponding to each of the plurality of sensors. Thus, the replacement periods for multiple oils can be easily diagnosed.

[0048] In the diagnostic device according to method 10, and according to the diagnostic device according to method 9, the control unit notifies the list to arrange multiple replacement information items in the list according to the order of remaining time. Thus, it is possible to arrange multiple oil information items in the list according to the order in which they are considered to be most necessary for oil replacement.

[0049] In the diagnostic device according to method 11, and according to the diagnostic device according to method 9 or 10, the control unit determines a plurality of sensors and notifies the supplier of the list, which corresponds to users of the oil supplied by the oil supplier. The list contains replacement information corresponding to each of the determined plurality of sensors. Thus, the supplier can easily diagnose the replacement periods of the various oils used by the user.

[0050] In the diagnostic device according to method 12, and according to the diagnostic device according to method 9, the control unit notifies the supplier that the user has requested the list when the user of the oil requests it, and the supplier supplies the oil to the user. Thus, the supplier is able to understand the user's concern regarding oil changes.

[0051] In the diagnostic device according to method 13, and according to any one of methods 1 to 11, the control unit notifies the supplier that the user has requested the replacement information when the user of the oil requests it, and the supplier supplies the oil to the user. Thus, the supplier is able to understand the user's concern regarding oil replacement.

[0052] In the diagnostic device according to method 14, as in the diagnostic device according to method 12 or 13, the control unit notifies the supplier of information related to the user's past oil changes. Thus, the supplier is able to understand the user's tendencies related to oil changes.

[0053] In the diagnostic device according to method 15, or any one of methods 1 to 13, the sensor is a color sensor. Since the color of the oil changes as it deteriorates, the deterioration state of the oil can be detected by using a color sensor.

[0054] In the diagnostic device according to method 16, the control unit diagnoses the deterioration of the oil based on the detection results of light of a different wavelength corresponding to the type of oil in the detection results of the sensor.

[0055] Method 17 provides a diagnostic method in which detection results are obtained from a sensor that detects the deterioration state of oil, the oil replacement period is diagnosed based on the detection results, and replacement information indicating the diagnosed replacement period is notified to a notification object corresponding to the sensor. According to this diagnostic method, the oil replacement period can be diagnosed in a simple manner.

[0056] Method 18 provides a computer-readable recording medium, wherein a recording program is configured to cause a computer to perform the following steps: acquiring detection results from a sensor that detects the deterioration state of oil; diagnosing the replacement period of the oil based on the detection results; and notifying a replacement information to a notification object corresponding to the sensor, the replacement information indicating the diagnosed replacement period.

[0057] Method 19 provides a diagnostic device comprising: a storage unit for storing light reception results when light is received from oil; and a control unit for diagnosing oil deterioration based on the light reception results, wherein the control unit diagnoses oil deterioration based on light reception results of light at a wavelength corresponding to the type of oil. Furthermore, the "control unit" may be a control unit that performs prescribed computational processing, or it may not perform control processing specific to the prescribed hardware.

[0058] In method 20, according to the diagnostic device described in method 19, the control unit diagnoses the deterioration of the first oil based on the light reception result of the first wavelength when diagnosing the first oil, and diagnoses the deterioration of the second oil based on the light reception result of the second wavelength, which is different from the first oil, when diagnosing the second oil.

[0059] Method 21 provides a computer-readable recording medium, wherein a recording program is configured to cause a computer to perform the following steps: acquiring light reception results when light is received from the oil; and diagnosing the deterioration of the oil based on light reception results of light with wavelengths corresponding to the type of the oil.

[0060] Method 22 provides a diagnostic method for diagnosing oil deterioration, wherein, in diagnosing a first oil, the deterioration of the first oil is diagnosed based on the light reception results of light of a first wavelength; and in diagnosing a second oil different from the first oil, the deterioration of the second oil is diagnosed based on the light reception results of light of a second wavelength different from the first wavelength. According to this diagnostic method, oil deterioration can be appropriately diagnosed.

[0061] In method 23, according to the diagnostic method described in method 22, the result of light reception of the first wavelength of light on the first oil is more strongly correlated with the residual rate of antioxidants contained in the first oil compared to the result of light reception of the second wavelength of light on the first oil; and the result of light reception of the second wavelength of light on the second oil is more strongly correlated with the residual rate of antioxidants contained in the second oil compared to the result of light reception of the first wavelength of light on the second oil. According to this diagnostic method, it is possible to appropriately diagnose the deterioration caused by a decrease in the residual rate of antioxidants in both the first and second oils.

[0062] ===First Implementation Method===

[0063] The following is a reference to the appendix. Figure 1 Preferred embodiments of this disclosure will be described below. Identical or equivalent components and parts shown in the accompanying drawings will be labeled with the same reference numerals, and repetitive descriptions will be omitted where appropriate.

[0064] <Composition of Diagnostic Systems>

[0065] Figure 1 This is an explanatory diagram of the diagnostic system 100.

[0066] The diagnostic system 100 is a system for diagnosing oil change intervals. The diagnostic system 100 includes: a sensor unit 10 with a sensor 11; and a diagnostic device 20 with a control unit 30 and a storage unit 40. Communication between the sensor unit 10 and the diagnostic device 20 is possible via a communication network 90. ​​The communication network 90 can be, for example, a network via telephone lines (public telephone lines, mobile phone lines), wireless communication, wired communication, etc., such as the Internet, intranet, LAN, WAN, etc., with the Internet assumed here. The communication network 90 also connects to terminals of oil users (user terminals 61), terminals of authorized oil distributors / agents supplying oil to oil users (supplier terminals 71), and terminals 71' of the general oil distribution company, etc. Communication between these terminals and the diagnostic device 20 is also possible via the communication network 90.

[0067] Here, "user" means the entity that uses the oil. "Supplier" means the entity that supplies oil to the user. Suppliers include not only authorized dealers and agents, but sometimes also the general distributor of the oil (and sometimes "supplier terminal 71" means "general distributor terminal 71"). However, sometimes "supplier" does not include the general distributor. Furthermore, besides the general distributor, sometimes the supplier and user are collectively referred to as "customer." Here, it is assumed that "oil" refers to oil that needs to be replaced due to deterioration. For example, oil includes lubricating oil (processing oil, machine oil, etc.), cooling oil, rust inhibitors, etc. Oil is composed of base oil with additives such as antioxidants. Due to the decrease in the residual rate of antioxidants and other additives, the oil deteriorates.

[0068] At the user's location, there is a user terminal 61, an oil-using device 62, etc. The user terminal 61 is the terminal used by the user. Here, it is assumed that the user terminal 61 is a smartphone, but it could also be a personal computer or a tablet. At the user's location, there may be one or more oil-using devices 62. Device 62 may be, for example, a machine tool that uses lubricating oil (an example of oil), a compressor, etc. Device 62 is equipped with a tank 63 for storing oil (see reference). Figure 2A , Figure 2B The oil in each device 62 is supplied, replaced, and recycled by the supplier's operators. The device 62 that uses oil (tank 63 for storing oil) is equipped with a sensor unit 10 with a sensor 11.

[0069] Among the oil suppliers, there is a supplier terminal 71. Here, it is assumed that supplier terminal 71 is a personal computer. However, supplier terminal 71 can also be a mobile terminal such as a smartphone or tablet.

[0070] Figure 2A This is an explanatory diagram of sensor unit 10.

[0071] Sensor unit 10 constitutes a measuring device (detection device) for measuring oil. Sensor unit 10 includes sensor 11, control unit 12, and communication unit 13. Sensor 11 detects the deterioration state of the oil used in the user's device 62. Here, sensor 11 is a color sensor that detects the color of the oil in container 63 and outputs RGB data (color data with R data, G data, and B data) representing the grayscale values ​​of each of RGB (red, green, and blue). Furthermore, R data represents the grayscale value of the light received at the wavelength of red. G data represents the grayscale value of the light received at the wavelength of green. B data represents the grayscale value of the light received at the wavelength of blue. Sensor 11 does not necessarily need to be a color sensor as long as it can detect the deterioration state of the oil; for example, it can also analyze the composition of the oil and output composition data as the detection result. Control unit 12 controls sensor unit 10. Communication unit 13 communicates with diagnostic device 20 via communication network 90. For example, the control unit 12 is composed of a CPU, an MPU and other arithmetic processing devices, and RAM, ROM and other storage devices (main storage device and auxiliary storage device). The arithmetic processing device executes the program stored in the storage device, thereby receiving setting data (described later) from the diagnostic device 20 via the communication unit 13, or sending the detection results of the sensor 11 (here, RGB data) to the diagnostic device 20.

[0072] Figure 2B This is an explanatory diagram of a modified example of the sensor unit 10. The sensor unit 10 may also have multiple sensors 11. Each sensor 11 detects the deterioration state of the oil in the tank 63 of each device 62. According to the modified example of the sensor unit 10, the deterioration state of the oil in the tank 63 of multiple devices 62 can be detected by one sensor unit 10 (one control unit 12).

[0073] In the first embodiment, a diagnostic system 100 can be constructed by installing a sensor unit 10 (sensor 11) on the existing tank 63 of the oil-using device 62.

[0074] Diagnostic device 20 is a device for diagnosing oil deterioration. Figure 3 This is an explanatory diagram of the hardware configuration of the diagnostic device 20.

[0075] The diagnostic device 20 includes a processing unit 51, a storage device 52, and a communication device 53. All components in the figure are connected via a bus (not shown). The processing unit 51 is, for example, a CPU. The storage device 52 is, for example, a main storage device such as RAM, or an auxiliary storage device such as a hard disk drive or an SSD. The processing unit 51 executes the program stored in the storage device 52 to achieve… Figure 1 The various functions shown. Communication device 53 is a device for connecting to communication network 90, and is composed of a communication module for wired or wireless communication, etc. Diagnostic device 20 may also include display device 54 (e.g., a monitor) and input device 55 (e.g., a keyboard, mouse, etc.). Diagnostic device 20 may be composed of one computer or multiple computers. When using multiple computers to construct diagnostic device 20, multiple functions can be enabled ( Figure 1 The control unit 30 and storage unit 40 shown are implemented separately by different computers for each function, or the same function can be processed by multiple computers in a distributed manner.

[0076] Furthermore, the computers constituting the aforementioned user terminal 61 and supplier terminal 71 are also related to... Figure 3 The diagnostic device 20 shown is the same as the one shown, and as hardware, it includes a processing unit, a storage unit, a communication unit, an input unit, and a display unit.

[0077] like Figure 1 As shown, the diagnostic device 20 has a control unit 30 and a storage unit 40.

[0078] As described later, the control unit 30 diagnoses the oil replacement period based on the detection results (here, RGB data) of the sensor 11 stored in the storage unit 40. Furthermore, the control unit 30 notifies the user terminal 61 and the supplier terminal 71 of replacement information indicating the diagnosed replacement period. The control unit 30 includes a setting processing unit 31, a data acquisition unit 32, a diagnostic processing unit 33, a notification processing unit 34, and a history processing unit 35. The various functions of the control unit 30 will be explained later.

[0079] The storage unit 40 stores the detection results of the sensor 11. Additionally, the storage unit 40 stores various data, which will be described later. Here, the storage unit 40 includes a basic information database 41, a diagnostic setting database 42, a detection result database 43, and a replacement history database 44. The various databases of the storage unit 40 will be explained later.

[0080] <Various Processing Methods>

[0081] (Settings and processing)

[0082] Figure 4 This is a flowchart for setting up the process.

[0083] The diagnostic device 20 processes shown in the figure are implemented by executing the program stored in the storage device 52 using the arithmetic processing unit 51. Similarly, the sensor unit 10 processes are implemented by executing the program stored in the storage device using the arithmetic processing unit of the sensor unit 10. The same applies to the processes described later.

[0084] The setting processing unit 31 of the diagnostic device 20 sets a basic information database 41 (S001 to S004) in the storage unit 40. The basic information database 41 is a database that stores basic information. Here, 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.

[0085] 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 when a new oil product is released, information related to the oil (oil information) is set in the oil database 411 and the profile database 412.

[0086] Figure 5 This is an illustrative diagram of an example from oil database 411.

[0087] Oil Database 411 is a database that stores oil-related data (oil data). Oil data is data that establishes a correspondence between oil IDs and oil information. An oil ID is information used to identify the type of oil (identification number). Oil information is information related to the oil, such as the oil name (trade name), composition (base oil, additives), etc. In addition, as additives, it may also include antioxidants.

[0088] Figure 6 This is an illustrative diagram of an example from the brief database 412.

[0089] Profile database 412 is a database storing profile data related to the characteristics of oil. Here, profile data establishes a correspondence between profile IDs and profile information. The profile ID is information (identification number) used to identify the profile. The profile information represents the characteristics of the oil. In the profile data, as profile information, the oil ID, information representing the relationship between time and grayscale values ​​(curve graph information), diagnostic color, and the initial value of the replacement threshold are established as corresponding information. The oil IDs in profile database 412 correspond to the oil IDs in oil database 411. In other words, the oil IDs in profile database 412 are used to identify the corresponding oil for each profile.

[0090] Figures 7A to 7CThis is an example of a curve graph showing the relationship between time and grayscale value. In Figures 7A to 7C The figures represent brief information for different oils (Oil A to Oil C). The horizontal axis in each figure represents time. Additionally, the left vertical axis represents the grayscale values ​​of RGB (red, green, and blue), indicating the detection result of sensor 11 when the oil's color is detected. For illustration, the curve showing the residual rate of additives contained in the oil is represented by a dashed line. The right vertical axis represents the residual rate of additives (%). Furthermore, the curve showing the residual rate of additives (dashed line) is used to illustrate the correlation between RGB data and the residual rate of additives; this information may not be included in the brief information.

[0091] exist Figures 7A to 7C In any of the graphs, under arbitrary conditions, as shown by the dashed curve, the residual rate of additives in the oil decreases over time. Furthermore, in... Figures 7A to 7C In any of the graphs shown, as the solid line curve illustrates, the detection result of sensor 11 changes with the change in the residual rate of the additive. For example, in the case of oil A, as... Figure 7A As shown, with the decrease in the residual rate of the additive, the B data (representing the blue grayscale value) output by sensor 11 decreases, while the R data and G data (representing the red and green grayscale values) hardly decrease. In the cases of oils B and C, as... Figure 7B as well as Figure 7C As shown, with the decrease in additive residue, not only the B data, but also the R and G data decrease. Furthermore, in the case of oil B, as... Figure 7B As shown, compared to the R and G data, the B data is more strongly correlated with the additive residue rate. On the other hand, in the case of oil C, as... Figure 7C As shown, it is not the B data, but the G data, that is more strongly correlated with the residual rate of additives compared to other colors (R data and B data).

[0092] Thus, the detection results of sensor 11 vary depending on the type of oil. Therefore, when developing or releasing a new oil product, the profile information related to that oil is set in the profile database 412.

[0093] Diagnostic colors included in the profile information (see reference) Figure 6This refers to the information used for oil diagnosis, which is determined from the detection result of sensor 11, i.e., the RGB data. When the diagnostic color is set to "blue (B)," the "B data" from the RGB data is used for oil diagnosis. Similarly, when the diagnostic color is set to "green (G)," the "G data" from the RGB data is used for oil diagnosis. Here, B data is used for diagnosing oil A and oil B, and G data is used for diagnosing oil C.

[0094] Furthermore, while a single diagnostic color is used here, two or more colors can also be set as diagnostic colors. For example, when impurities are mixed into the oil, all colors of the RGB data change; therefore, all colors can be set as diagnostic colors for oil with impurities. When two or more colors are set as diagnostic colors, a replacement threshold can be set for each color. In this case, the oil replacement period can be determined based on whether all colors in the data corresponding to the two or more colors set as diagnostic colors reach the replacement threshold, or it can be determined based on whether any one color reaches the replacement threshold. For example, when all colors are set as diagnostic colors for oil with impurities, the oil replacement period can be determined based on whether each color of the RGB data reaches the replacement threshold individually.

[0095] In the cases of oil A and oil B, the data for B, compared to the data for R and G, showed a stronger correlation with the residual rate of the additive (see reference). Figure 7A as well as Figure 7B Therefore, the diagnostic color corresponding to oils A and B is set to "blue (B)". On the other hand, in the case of oil C, as... Figure 7C As shown, the G data correlates more strongly with the residue rate of additives compared to the R and B data. Therefore, the diagnostic color corresponding to oil C is set as "green (G)".

[0096] The replacement thresholds included in the profile information (refer to) Figure 6The threshold value is used to diagnose whether an oil change is needed. A "grayscale value" is set as the replacement threshold. For example, in the case of oil A, the grayscale value "50" is set as the replacement threshold. Therefore, when diagnosing whether an oil A needs to be replaced, the grayscale value represented by the "B data" in the RGB data output by sensor 11 is compared with the threshold "50". An initial value for the replacement threshold is set in the profile database 412. When the detection result of sensor 11 reaches the replacement threshold, it indicates that the oil has deteriorated to the point where an oil change is necessary. That is, the replacement threshold is a reference value used to determine whether the oil has reached the replacement period (in other words, the replacement threshold is a reference value used to diagnose the life of the oil). Furthermore, as described later, the setting of the replacement threshold for diagnosing whether an oil change is needed can be changed by setting the replacement threshold (adjustment value) in the diagnostic setting database 42.

[0097] Furthermore, here, a "grayscale value" is set as the replacement threshold, but the replacement threshold is not limited to grayscale values; for example, it could also be a "slope (the proportion of grayscale value change relative to time)." In this case, the oil replacement period is determined based on whether the slope (the proportion of grayscale value change relative to time) of the data corresponding to the diagnostic color reaches (or does not reach) the replacement threshold.

[0098] Alternatively, the profile information (graph information, diagnostic colors, and replacement thresholds) can be directly set in the oil database 411 as part of the oil information, thereby merging the profile database 412 into the oil database 411. In this way, the basic information database 41 may not contain a portion of other types of databases. Alternatively, the basic information database 41 may also contain other types of databases. The same applies to the other types of databases described later.

[0099] 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 signed between an oil distributor and an authorized dealer (an example of a supplier), the supplier uses the supplier terminal 71 to register its own information (supplier information) in the diagnostic device 20 (S011), or the person in charge of the distributor uses the terminal 71' to register supplier-related information in the diagnostic device 20 (S011), thereby setting the supplier-related information in the supplier database 413 (S002). Similarly, when a contract is signed between a supplier and a user, the user uses the user terminal 61 to register its own information (user information) in the diagnostic device 20 (S012), or the supplier uses the supplier terminal 71 to register user-related information in the diagnostic device 20 (S012), thereby setting the user-related information (user information) in the user database 414 (S003).

[0100] Figure 8A This is an illustrative diagram of an example of a supplier database 413 and a user database 414.

[0101] Supplier database 413 is a database that stores data related to suppliers (supplier data). Supplier data is data that establishes a correspondence between supplier IDs and supplier information. Supplier ID is information (identification number) used to identify a supplier. Supplier information is information related to the supplier, such as the supplier's name, address, and contact information (e.g., email address).

[0102] User database 414 is a database that stores user-related data (user data). User data is data that establishes a correspondence between user IDs and user information. User ID is information (identification number) used to identify a user. User information is information related to the user, such as the user's name, address, and contact information (e.g., email address). In user data, user information is associated with supplier IDs. The supplier ID included in the user data represents the supplier that supplies oil to that user and corresponds to the supplier ID in supplier database 413.

[0103] Figure 8B This is an illustrative diagram of an example of customer database 414. (As shown...) Figure 8B As shown, Figure 8A The supplier database 413 and user database 414 shown can also be aggregated into a single database (customer database 414').

[0104] Customer database 414' is a database that stores data (customer data) related to customers, including suppliers and users, and serves as an alternative to the aforementioned supplier database 413 and user database 414. Customer data is data that establishes a correspondence between customer IDs and customer information. A customer ID is information (identification number) used to identify a customer (supplier or user). Customer information is information related to the 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 diagram, "Customer ID; X" is shown as the supplier, and "Customer ID; AAA" as the user. Here, in the supplier information for "Customer ID; X," a customer ID representing the supplier is not specified, but an ID representing the general distributor could be specified. As described above, basic information database 41 can also replace supplier database 413 and user database 414, and customer database 414' can be provided instead.

[0105] 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 sets the sensor unit 10 in the device 62 (the oil-using device 62) located at the user's location, the user registers information related to the sensor 11 in the diagnostic device 20 using the user terminal 61 (S013), or the supplier registers information related to the sensor 11 in the diagnostic device 20 using the supplier terminal 71 (S013), thereby setting the information related to the sensor 11 (sensor information) in the sensor database 415 (S004).

[0106] Figure 9 This is an illustrative diagram of an example from Sensor Database 415.

[0107] Sensor database 415 is a database that stores data (sensor data) related to sensor 11. Sensor data is data that establishes a correspondence between sensor IDs and sensor information. Sensor ID is information (identification number) used to identify sensor 11. Here, sensor ID is a pre-set serial number for sensor 11. However, sensor ID can also be a number assigned each time a new sensor 11 is added to sensor database 415. Sensor information is information related to sensor 11. Sensor information includes device information, oil ID, and user ID. Device information is information related to device 62 where sensor 11 is installed. Device information includes the name, manufacturer, model, and tank capacity (or, the amount of oil stored in tank 63) of device 62 where sensor 11 is installed. The oil ID in sensor database 415 corresponds to the oil ID in oil database 411, and is used to identify the oil that is being detected by sensor 11. The user ID in sensor database 415 corresponds to the user ID in user database 414, and is used to identify the user of device 62 where sensor 11 is installed. As sensor information, it can also be mapped to other information. For example, if the sensor ID and the serial number of sensor 11 are different, the serial number of sensor 11 can be mapped to the sensor ID as sensor information. Alternatively, a separate device database can be prepared, mapping device IDs to device information, with the device information in the sensor data mapped to the device ID. In this case, the device database will map the device name, manufacturer, model, tank capacity, and other device information to the device ID.

[0108] Through the above-described processes (S001 to S004), a 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 description, 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 oil database 411, profile database 412, supplier database 413, user database 414, and sensor database 415, but the order in which the databases are registered is not limited to this.

[0109] 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 the supplier sets the sensor unit 10 in the device 62 (the oil-using device 62) located at the user's location, the diagnostic device 20 sets the setting information (diagnostic setting information) for the diagnostic processing using the sensor 11. In addition, the user registers information related to the sensor 11 in the diagnostic device 20 using the user terminal 61 (S014), or the supplier registers information related to the sensor 11 in the diagnostic device 20 using the supplier terminal 71 (S014), thereby setting the diagnostic setting information in the diagnostic setting database 42 (S005).

[0110] Figure 10 This is an illustrative diagram of an example of a diagnostic settings database 42.

[0111] The diagnostic setting database 42 is a database that stores data (diagnostic setting data) related to the settings of diagnostic processing using sensor 11. The diagnostic setting data establishes a correspondence between sensor IDs and diagnostic setting information. The sensor ID is information used to identify sensor 11 (identification number), and it corresponds to the sensor IDs in the sensor database 415. The diagnostic setting information is information related to the settings of diagnostic processing using sensor 11. Here, the diagnostic setting data, as diagnostic setting information, includes information related to detection timing, thresholds (replacement thresholds and period thresholds), and notification targets.

[0112] The detection timing information in the diagnostic settings is information that sets the timing for the oil detection by sensor 11. Here, the detection timing is set to a time interval such as "every 1 hour" or "every 24 hours", but the time can also be set as the detection timing, such as "8:00 AM".

[0113] As already explained, the replacement threshold for diagnostic settings is information used to set a reference value (a reference value used to diagnose the lifespan of the oil; the replacement threshold Tc described later) that is used to determine when the oil has reached its replacement period. Here, in the diagnostic setting database 42, an adjustment value is set as the replacement threshold to adjust the replacement threshold (initial value) of the profile database 412. The replacement threshold (initial value) of the profile database 412 is added to the replacement threshold (adjustment value) of the diagnostic setting database 42, thereby determining the reference value (replacement threshold Tc described later) used to determine when the oil has reached its replacement period. Alternatively, in the diagnostic setting database 42, instead of directly setting the adjustment value, a grayscale value equivalent to the replacement threshold Tc described later can be directly set.

[0114] The period threshold for diagnostic setting information is a set value used to set the timing of notification warnings (described later). Furthermore, a timing warning (described later) is issued when the period threshold is reached during the period until the oil reaches its replacement period. Here, the period threshold is set corresponding to the sensor (sensor ID), but it can also be set corresponding to the replacement threshold in the profile database 412 and the profile ID. In this case, for example, for the diagnosis of impurity contamination, the period threshold is arbitrarily set corresponding to the profile ID that sets all colors as diagnostic colors, thereby enabling a warning to be issued even when impurities are detected in the oil. Furthermore, the period threshold can be set to any value, either positive or negative. Since the period threshold can be set to any value, the timing of the notification warning (described later) can be set to meet various requirements.

[0115] The notification object for diagnostic setting information refers to the object to which a warning (described later) is sent. Here, the notification object is configured in correspondence with sensor 11 as "supplier," "user," or "both parties (supplier and user)." Furthermore, the supplier ID and user ID (or customer ID) mentioned above can also be configured as the notification object for diagnostic setting information.

[0116] However, in the first embodiment, at least one of the users and suppliers can be set as the notification recipients in the diagnostic setting database 42. This allows for the setting of the warning notification recipients, as described later, to be tailored to the specific circumstances of each oil transaction.

[0117] Furthermore, even with the same type of oil, the oil's lifespan can vary depending on the device 62 using the oil (or, on the user of that device 62). For example, the allowable degree of oil degradation differs between devices 62 requiring high precision and those that can operate even with relatively degraded oil, thus affecting the oil's lifespan. Therefore, in the first embodiment, a replacement threshold can be set separately in the diagnostic setting database 42, corresponding to the sensor 11 (sensor ID). This allows for setting the oil's lifespan period to meet different requirements.

[0118] Furthermore, for each device 62 using oil (or for each user or supplier using the device 62), there are requirements for issuing warnings at different time intervals. For example, in the case of a device 62 requiring high precision and where the use of oil nearing the end of its lifespan is not permitted, it is preferable to issue an oil change notification (the warning notification described later) at an earlier time interval, considering the oil change operation period. On the other hand, in the case where the use of oil nearing the end of its lifespan is permitted, it is desirable to issue an oil change notification at a time as close to the end of its lifespan as possible, rather than issuing a notification at an earlier stage. Therefore, in the first embodiment, a corresponding setting period threshold can be established in the diagnostic setting database 42 for the sensor 11 (sensor ID). Thus, warnings can be issued at time intervals that meet different requirements (described later).

[0119] When 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 sends setting data containing detection timing information 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 described later, the sensor unit 10 uses the sensor 11 to detect oil according to the set detection timing and sends the detection result to the diagnostic device 20. Furthermore, if the sensor unit 10 has a detection timing preset, the detection timing may not be set in the diagnostic setting database 42, and the setting signal containing detection timing information may not be sent from the diagnostic device 20 to the sensor unit 10.

[0120] (Data acquisition and processing)

[0121] Figure 11 This is a flowchart of data acquisition and processing.

[0122] When the set detection timing is reached (yes in S101), sensor unit 10 acquires RGB data from sensor 11 (S102) and sends the RGB data to diagnostic device 20 (S103). Preferably, sensor unit 10 appends the sensor ID (here, the serial number of sensor 11) to the RGB data and sends the RGB data to diagnostic device 20. Alternatively, if the sensor ID and serial number are different, and the sensor database 415 establishes a correspondence between the serial number and sensor ID as sensor information, sensor unit 10 may append the serial number to the RGB data and send it to diagnostic device 20, whereby diagnostic device 20 determines the sensor ID based on the serial number. Additionally, sensor unit 10 may append information indicating the detection time (detection date and time) to the RGB data and send the RGB data to diagnostic device 20. Data acquisition unit 32 of diagnostic device 20 receives RGB data from sensor unit 10 and accumulates the RGB data in detection result database 43 (S111).

[0123] Figure 12 This is an illustrative diagram of an example from the detection results database 43.

[0124] The detection result database 43 is a database that stores the detection results of sensor 11. In the detection result database 43, for each sensor ID, the detection time (detection date and time) is mapped to the detection result (RGB data) of sensor 11 at that detection time (in the figure, although each column is empty, it stores information such as time and grayscale value). The sensor IDs in the detection result database 43 are mapped to the sensor IDs in the sensor database 415. The diagnostic device 20 registers the received RGB data in the detection result database 43, mapping it to the sensor ID appended to the received RGB data. Furthermore, the diagnostic device 20 registers the RGB data in the detection result database 43, mapping it to the information indicating the detection time appended to the RGB data, or using the time when the RGB data is received from sensor unit 10 as the detection time (S111), mapping it to the detection time. The detection result database 43 accumulates RGB data corresponding to multiple detection times. That is, the detection result database 43 accumulates the history of the detection results (RGB data) of sensor 11.

[0125] (Notification processing)

[0126] Figure 13 This is a flowchart of the notification processing. Figure 14 This is an explanatory diagram of the replacement period t1 and the remaining period Pr. Figure 14 The horizontal axis represents time, and the vertical axis represents grayscale values. Time t0 represents the current time. Figure 14The solid line represents the progression of the detection results (e.g., B data) of sensor 11. The dashed line in the figure represents the progression of the prediction of future detection results. Before time t0, the graph is a solid line representing the past detection results of sensor 11, and after time t0, the graph is a dashed line representing the progression of the prediction of the detection results of sensor 11.

[0127] First, the diagnostic processing unit 33 of the diagnostic device 20 performs diagnostic processing for the oil change period (S201 to S204).

[0128] During the diagnostic process, the diagnostic processing unit 33 obtains the information required for diagnosis during the oil change period from the storage unit 40 (S201). Here, the diagnostic processing unit 33 obtains the detection results, profile information, and thresholds of the sensor 11.

[0129] At this time, the diagnostic processing unit 33 determines the diagnostic color set for the oil corresponding to the sensor ID. When diagnosing the oil detected by "Sensor ID; Sensor 001", since the oil ID corresponding to "Sensor ID; Sensor 001" in the sensor database 415 is "Oil A", the diagnostic processing unit 33 determines the diagnostic color to be "Blue (B)" based on the profile database 412. When diagnosing the oil detected by "Sensor ID; Sensor 003", since the oil ID corresponding to "Sensor ID; Sensor 003" in the sensor database 415 is "Oil C", the diagnostic processing unit 33 determines the diagnostic color to be "Green (G)" based on the profile database 412.

[0130] After determining the diagnostic color, the diagnostic processing unit 33 retrieves the detection result of the sensor 11 from the detection result database 43. At this time, the diagnostic processing unit 33 retrieves the data corresponding to the diagnostic color from the RGB data in the detection result database 43. For example, when the diagnostic processing unit 33 retrieves the detection result corresponding to "Sensor ID; Sensor 001", since the diagnostic color corresponding to "Sensor ID; Sensor 001" is "Blue (B)" (see reference...) Figure 6 , Figure 9 Therefore, the B data is extracted from the RGB data of "Sensor ID; Sensor 001" in the detection result database 43. Additionally, when the diagnostic processing unit 33 obtains the detection result corresponding to "Sensor ID; Sensor 003", it extracts the G data from the RGB data of "Sensor ID; Sensor 003" in the detection result database 43. In this way, the diagnostic processing unit 33 can extract the light reception results of different wavelengths of light according to the type of oil (resulting in the diagnostic processing unit 33 diagnosing oil deterioration based on the light reception results of different wavelengths of light according to the type of oil).

[0131] Additionally, the diagnostic processing unit 33 retrieves profile information (a graph showing the relationship between time and grayscale value) corresponding to the sensor 11 from the profile database 412. At this time, the diagnostic processing unit 33 retrieves graph information corresponding to the diagnostic color from the RGB graph information in the profile database 412 (for example, retrieving the graph information of the grayscale value of blue (B) from the graphs of the grayscale values ​​of each of the RGB values). The diagnostic processing unit 33 may extract graph information of different wavelengths of light based on the type of oil (resulting in the diagnostic processing unit 33 diagnosing oil degradation based on graph information of different wavelengths of light according to the type of oil).

[0132] Additionally, the diagnostic processing unit 33 adds the replacement threshold (initial value) from the profile database 412 to the replacement threshold (adjustment value) from the diagnostic setting database 42 to obtain the replacement threshold Tc corresponding to the sensor 11. Furthermore, the diagnostic processing unit 33 obtains the period threshold Tp corresponding to the sensor 11 from the diagnostic setting database 42.

[0133] Next, the diagnostic processing unit 33 calculates the predicted shift of the sensor 11's detection result based on the detection result and the profile information (S202). For example, the diagnostic processing unit 33 displays a graph of the profile information (refer to...). Figures 7A to 7C The time axis is scaled up or down to match the progression of the detection results of sensor 11 so far (see reference). Figure 14 (The solid line curve). Furthermore, the diagnostic processing unit 33 makes the curve of the modified time axis profile information match the progression of the sensor 11's detection results (see reference). Figure 14 (The solid line curve) (by changing the time axis and the curve) Figure 14 (Fitting the curve of the solid line) to obtain Figure 14 The dashed line represents the predicted shift of the detection result (the future shift of the detection result). Furthermore, the method for determining the predicted shift of the detection result of sensor 11 is not limited to this. For example, if the detection result of sensor 11 changes linearly (where the slope of the curve is constant), the predicted shift of the detection result of sensor 11 can be determined by finding the extension line of the curve showing the detection result of sensor 11 up to this point.

[0134] However, it is considered that the rate of oil degradation changes depending on the usage of device 62. For example, if the frequency of use of device 62 increases, the oil degradation accelerates, and therefore the change in the detection result of sensor 11 is considered to be faster. Conversely, if the frequency of use of device 62 decreases, the oil degradation is suppressed, and therefore the change in the detection result of sensor 11 is considered to be slower. In this way, since the rate of oil degradation changes, the prediction accuracy is improved when predicting the future trend of detection results based on the recent rate of oil degradation. Therefore, in the first embodiment, new detection results stored in the detection result database 43 (in other words, old detection results are not used) are used to determine the oil degradation rate. Figure 14 The dashed line indicates the predicted shift of the detection results. Therefore, it is possible to predict the future shift of detection results with high accuracy, and to diagnose the oil change interval with high precision. However, it is also possible to use the detection results from sensor 11 since the beginning of oil use to determine... Figure 14 The dashed line indicates the predicted shift of the detection results.

[0135] Next, the diagnostic processing unit 33 calculates the replacement period t1 when the detection result of sensor 11 reaches the replacement threshold Tc (S203). For example, the diagnostic processing unit 33 calculates... Figure 14 The intersection of the dashed line curve with the replacement threshold Tc is defined as the replacement period t1. The replacement period t1, when the sensor 11's detection result reaches the replacement threshold Tc, corresponds to the period when the oil deteriorates to the point where it needs to be replaced, or the period when the oil reaches the end of its lifespan. Therefore, in the following description, the period when the sensor 11's detection result reaches the replacement threshold Tc is sometimes referred to as the oil's "lifespan end date".

[0136] Additionally, the diagnostic processing unit 33 calculates the remaining period Pr up to the replacement period t1 (S204). For example, as... Figure 14 As shown, the diagnostic processing unit 33 calculates the residual period Pr by calculating the difference between the replacement period t1 and the current time t0. The residual period Pr is the period (number of days) until the oil's lifespan is reached, and is therefore equivalent to the oil's "remaining lifespan". If the detection result of sensor 11 is already below the replacement threshold Tc, the residual period Pr is expressed as a negative number.

[0137] In addition, the diagnostic processing unit 33 performs the diagnostic processing shown in S201 to S204 according to each sensor 11, and calculates the oil replacement period t1 and the residual period Pr according to each sensor 11 (in other words, according to the oil detected by each sensor 11).

[0138] After the diagnostic processing unit 33 performs diagnostic processing (S201-S204), the notification processing unit 34 of the diagnostic device 20 performs notification processing (S205-S207).

[0139] First, the notification processing unit 34 determines the sensor ID that has reached the notification timing (S205). At this time, the notification processing unit 34 processes the residual period Pr calculated in S204 (refer to...). Figure 14 ) and the period threshold Tp (refer to Figure 10 The comparison is performed. If the remaining period Pr is less than the period threshold Tp, the notification processing unit 34 determines that the notification timing has been reached. That is, the notification processing unit 34 determines the sensor ID that satisfies the condition that the remaining period Pr is less than the period threshold Tp based on the remaining period Pr calculated for each sensor 11 (according to each sensor ID) and the period threshold Tp set in the diagnostic setting database 42 for each sensor 11.

[0140] Next, the notification processing unit 34 determines the notification object corresponding to the sensor ID determined in S205 (S206).

[0141] For example, if the sensor ID determined in S205 is "sensor 001", the notification processing unit 34 determines that the notification recipient corresponding to "sensor 001" in the diagnostic setting database 42 is "user" (see reference). Figure 10 ), and determine that the user ID corresponding to "sensor 001" in sensor database 415 is "AAA" (refer to Figure 9 The contact information (e.g., email address) corresponding to "AAA" in user database 414 will be used to identify the "user" corresponding to the sensor ID as the notification recipient (see [reference]). Figure 8A Furthermore, when a supplier ID and user ID (or customer ID) are established as corresponding recipients of diagnostic setting information in the diagnostic setting database 42, the notification processing unit 34 determines the supplier ID and other contact information corresponding to "sensor 001" in the diagnostic setting database 42.

[0142] Additionally, for example, if the sensor ID determined in S206 is "sensor 002", the notification processing unit 34 determines that the notification recipient corresponding to "sensor 002" in the diagnostic setting database 42 is "supplier", and determines that the user ID corresponding to "sensor 002" in the sensor database 415 is "AAA" (see reference). Figure 9 ), and determine the supplier ID corresponding to "AAA" in user database 414 as "X" (refer to Figure 8AThe contact information (e.g., email address) corresponding to "X" in supplier database 413 will be used to identify the "supplier" corresponding to the sensor ID as the notification recipient (see [reference]). Figure 8A ).

[0143] Next, the notification processing unit 34 notifies the notification recipients identified in S206 of the warning (S207). The warning notified by the notification processing unit 34 includes information indicating the replacement period diagnosed by the diagnostic processing unit 33 (replacement information). Furthermore, the replacement information notified by the notification processing unit 34 is only required to indicate the replacement period diagnosed by the diagnostic processing unit 33, and is not limited to information indicating the date of the replacement period t1. For example, the replacement information may also include "information related to the remaining period indicating the number of days until the replacement period" and "information about the content close to the replacement period".

[0144] In the first embodiment, by performing notification processing (S205-S207) by the notification processing unit 34, a warning can be notified to the notification recipient at a predetermined time when the remaining period Pr reaches the period threshold Tp. Thus, a warning can be issued at a predetermined time. Furthermore, if the period threshold Tp is set to a positive value, a warning can be issued before the oil reaches the end of its lifespan (before the oil's lifespan ends). On the other hand, a warning can also be issued after the oil reaches its lifespan by setting the period threshold Tp to a negative value.

[0145] Furthermore, in the first embodiment, the diagnostic setting database 42 described above allows for the establishment of corresponding time thresholds for each sensor 11 (sensor ID). This enables the issuance of warnings at specific time points that meet different requirements.

[0146] Figures 15A-15C This is an explanatory diagram of a warning screen. A warning is issued by the notification processing unit 34 (S207), thereby displaying a warning screen indicating a change in information on the user terminal 61 and the supplier terminal 71 that received the warning. Figures 15A-15C The middle part represents the warning screen displayed on the user terminal 61.

[0147] The warning screen is displayed on the user terminal 61 and supplier terminal 71 that receive the warning. The warning screen displays information indicating the oil change period diagnosed by the diagnostic processing unit 33.

[0148] exist Figure 15A The warning screen displays the target device, end-of-life date, remaining lifespan, and contact information. The "Target Device" section of the warning screen displays information related to device 62, which is currently using oil that should be replaced (device information). Additionally, the "End-of-Life Date" and "Remaining Lifespan" sections of the warning screen indicate the period t1 corresponding to the replacement date (refer to...). Figure 14 The warning screen displays information about the remaining Pr (presumably a unit of measurement) and the oil supplier's contact information in the "Contact Information" section. Additionally, the contact information of the oil user can also be displayed on the screen shown on the supplier's terminal 71. Figure 15A In the warning screen shown, as replacement information (indicating the replacement period diagnosed by the diagnostic processing unit 33), the period corresponding to replacement period t1 is directly displayed (refer to...). Figure 14 ), the remaining period of Pr, including the date, number of days, and other values.

[0149] exist Figure 15B The warning screen shown displays information related to device 62, which is using oil that should be changed, and the corresponding change period t1 (see reference). Figure 14 Information such as the end of lifespan. Thus, in the warning screen, as replacement information, only one of the information corresponding to the replacement period t1 and the remaining period Pr can be displayed.

[0150] exist Figure 15C The warning screen displays information related to the device 62 that is using oil that should be replaced, as well as information indicating that the oil replacement period is approaching. Thus, the replacement information displayed on the warning screen may not be a specific date or number of days, but rather information indicating that the replacement period diagnosed by the diagnostic processing unit 33 is approaching.

[0151] By displaying a warning screen on the user terminal 61, the user can be aware of the oil replacement period for the equipment and replace the oil as needed. Similarly, by displaying a warning screen on the supplier terminal 71, the supplier can be aware of the oil replacement period for the equipment 62 located at the user's location and urge the user to replace the oil as needed. Thus, by issuing a warning in S207 to the notification processing unit 34, both the user and the supplier can be urged to replace the oil.

[0152] (List notification processing)

[0153] In the above Figure 13 In the notification processing, a warning about oil level is issued to a device 62 (S207). However, when a user uses multiple devices 62, it would be convenient to simultaneously obtain information about other oils supplied to the user when notifying a device 62 about its oil level. Therefore, a process for notifying a list containing information about the oil levels of the multiple devices 62 used by the user will be described.

[0154] Figure 16 This is a flowchart of the list notification process. S207 in the diagram (and the processes performed before S207) and... Figure 13 Since they are the same, the explanation is omitted here.

[0155] The notification processing unit 34 determines the user ID of the object that has been added to the list (S301). Here, the notification processing unit 34 determines the user ID corresponding to the sensor ID that has reached the notification timing. For example, if the sensor ID determined in S205 above is "sensor 001", the notification processing unit 34 determines the user ID based on the sensor database 415 (see reference). Figure 9 The user ID of the object in the list is determined to be "AAA".

[0156] Next, the notification processing unit 34 determines the sensor ID corresponding to the user ID determined in S301 (S302). For example, if the user ID determined in S301 is "AAA", the notification processing unit 34 determines the sensor ID based on the sensor database 415 (see reference). Figure 9 The sensor IDs that become objects in the list are identified as "sensor 001" and "sensor 002". Furthermore, the notification processing unit 34 extracts the oil information corresponding to the sensor IDs identified in S302 and creates a list (S303).

[0157] Figure 17A This is an illustrative diagram of an example of a list created in S303. Furthermore, Figure 17A This is also an illustrative diagram of an example of a list sent to the supplier terminal 71 in S304.

[0158] The list represents information about the oil used by device 62 corresponding to a user ID. If a user uses multiple devices 62, the list includes information about the oil used by each of the user's devices 62. Figure 17A The list shown includes not only information about the oil corresponding to "sensor 001" that notifies the user of a warning, but also information about other oils (the oil corresponding to "sensor 002").

[0159] The list in the diagram includes sensor ID, oil ID, device information, end-of-life date, remaining life, and notification status. Sensor ID is information (identification number) associated with sensor 11 installed on device 62 used by the user. Oil ID is information used to identify the oil that is being detected by sensor 11. Device information is information associated with device 62 using the oil. End-of-life date corresponds to replacement period t1 (see reference). Figure 14 The remaining lifetime is equivalent to the remaining period Pr (refer to...). Figure 14The presence or absence of a notification indicates whether the aforementioned warning has been issued. In the list shown in the diagram, replacement information (indicating the replacement period diagnosed by the diagnostic processing unit 33) includes information such as the lifespan end date (replacement period t1 calculated by the diagnostic processing unit 33) and remaining lifespan (residual lifespan Pr calculated by the diagnostic processing unit 33). However, the replacement information included in the list can be either the lifespan end date or the remaining lifespan, or other information. Additionally, the list may also include user ID information corresponding to the sensor ID.

[0160] After the list is created, the notification processing unit 34 notifies the supplier terminal 71 of the list (S304). 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 using the notification list. The supplier can grasp the oil change information for each of the multiple devices 62 used by the user based on the list. Therefore, for example, the supplier can make a comprehensive suggestion to the user that includes not only the oil change for which a warning has been issued, but also the change of other oils. That is, the supplier can easily diagnose the oil change schedule for the multiple oils used by the user. Thus, when a warning is issued for the oil of a certain device 62, it is effective to notify the supplier terminal 71 of a list containing information on other oils supplied to that user.

[0161] (Handling of list notifications corresponding to the request)

[0162] In the list notification process described above, when a warning is issued regarding oil for a specific device 62, the list is notified to the supplier terminal 71. However, the list can also be notified upon request from a user (or supplier), as explained below.

[0163] Figure 18 This is a flowchart of other list notification processing. The diagram shows a flowchart for the case where a list is notified based on a request from user terminal 61.

[0164] If the notification processing unit 34 receives a list request from the user terminal 61, it determines the user ID of the user who is included in the list (S301). As shown in the flowchart, if the terminal requesting the list is user terminal 61, the notification processing unit 34 determines the user ID corresponding to user terminal 61 in S301. Furthermore, if the terminal requesting the list is supplier terminal 71, the supplier ID corresponding to supplier terminal 71 is determined in S301, and a corresponding user ID is established with the determined supplier ID (if the supplier supplies oil to multiple users, multiple user IDs are determined in S301).

[0165] Next, notify the processing department 34 and Figure 16 Similar to the notification processing, the sensor ID corresponding to the user ID determined in S301 is determined (S302), and the oil information corresponding to the sensor ID determined in S302 is extracted and a list is created (S303). In addition, when the list is created in S303, the diagnostic processing unit 33 calculates the replacement information required for the list (for example, calculating the replacement period t1 corresponding to the end of the service life and the remaining period Pr corresponding to the remaining service life).

[0166] After the list is created, the notification processing unit 34 notifies the terminal that requested the list (here, user terminal 61) of the list (S304). Furthermore, while S304 in the figure notifies user terminal 61 of the list, if a list request is received from supplier terminal 71, the notification processing unit 34 notifies supplier terminal 71 of the list. That is, if a list request is received from supplier terminal 71, the notification processing unit 34 determines the supplier ID (S301), determines multiple sensor IDs corresponding to the determined supplier ID (S302), creates a list containing replacement information corresponding to each of the determined multiple sensor IDs (S303), and notifies supplier terminal 71 of the list (S304). Thus, the supplier can easily diagnose the oil replacement period. Additionally, when the supplier supplies oil to multiple users, the notification processing unit 34 notifies supplier terminals 71 of the lists for multiple users (S304).

[0167] The list notified by the notification processing unit 34 contains replacement information corresponding to each of the multiple sensors 11. This allows for a simple diagnosis of the replacement periods for multiple oils. Furthermore, it is preferable that the notification processing unit 34 notifies a list that arranges the replacement information according to the remaining time. This arranges the information for multiple oils in the list in order of perceived necessity for oil replacement, thus facilitating supplier confirmation.

[0168] However, if a request for a list or replacement information is received from the user terminal 61, it can be inferred that the user is concerned about oil replacement. 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 of the content of the request (S401). Thus, the supplier can understand the user's concern about oil replacement. When a request for a list is received from the user terminal 61, as notification of this content, the notification processing unit 34 can also send the list sent to the user terminal 61 to the supplier terminal 71. Thus, the supplier can easily make a comprehensive suggestion to the user regarding oil replacement, including the oil listed.

[0169] (Used list notification processing for changing resumes)

[0170] The history processing unit 35 of the control unit 30 sets information related to past oil changes (actual change information) in the replacement history database 44. For example, after an oil change, the user registers the information related to the oil change (actual change information) with the diagnostic device 20 using the user terminal 61, or the supplier registers the information related to the oil change (actual change information) with the diagnostic device 20 using the supplier terminal 71, thereby setting the information related to the actual oil change (actual change information) in the replacement history database 44.

[0171] Figure 19 This is an illustration of changing the resume database 44.

[0172] The replacement history database 44 is a database that stores information related to past oil changes (actual replacement information). In the replacement history database 44, actual replacement information is accumulated for each sensor ID. This actual replacement information includes the date of the oil change, the oil ID, and the remaining period. The remaining period of the actual replacement information represents the remaining lifespan of the oil at the time of the actual oil change. Specifically, the remaining period of the actual replacement information represents the difference between the replacement period t1 (the period when the detection result of sensor 11 is diagnosed as reaching the replacement threshold Tc, or the period when the detection result of sensor 11 reaches the replacement threshold Tc) and the actual oil change period. If the oil change was performed at a time earlier than the diagnosed replacement period t1, the remaining period is positive. Conversely, if the oil change was performed at a time later than the replacement period t1, the remaining period is negative. The remaining period in the replacement history database 44 represents information indicating the user's tendency to schedule oil changes.

[0173] Figure 17B This is another illustrative diagram of a list sent to supplier terminal 71. Furthermore, in Figure 17B The list shown can also include information corresponding to the sensor ID, including the user ID.

[0174] As already explained, in Figure 18 In step S40, the notification processing unit 34 can also send a list to the supplier terminal 71. In this case, the list sent to the supplier terminal 71 may also include information related to the user's past oil changes. Preferably, as follows... Figure 17B As shown, the information related to past oil changes includes information related to the remaining life of the oil at the time of the past oil change (the residual period of the actual change information in the change history database 44). Therefore, the supplier can understand the user's preferred oil change timing and can propose oil changes to the user based on this preference. For example, upon receiving... Figure 17BThe supplier on the list, knowing that the user's oil change time is relatively late, can suggest an oil change for the user. Here, the notification processing unit 34 notifies the supplier terminal 71 of information related to the remaining life of the oil at the time of the previous oil change, but the actual replacement information notified to the supplier terminal 71 is not limited to the remaining life of the oil, and may also be other actual replacement information.

[0175] <Summary>

[0176] As described above, the diagnostic system 100 of the first embodiment includes a sensor 11, a storage unit 40 for storing the detection results of the sensor 11, and a control unit 30. The control unit 30 of the first embodiment is based on the detection results stored in the storage unit 40 (refer to...). Figure 12 The database of test results (43) diagnoses the oil replacement period (refer to...). Figure 13 (S203), and notifies the corresponding notification object of sensor 11 of the replacement information indicating the diagnosed replacement period (see S203). Figure 13 (S207). According to the diagnostic system 100 configured in this way, replacement information is notified to the notification object corresponding to the sensor 11, so the oil replacement period detected by the sensor 11 can be easily determined, and the oil replacement period can be diagnosed in a simple way.

[0177] Furthermore, in the diagnostic method of the first embodiment, the detection result is obtained from the sensor 11 (see reference). Figure 11 The oil change interval is diagnosed based on the detection results of sensor 11 (refer to...). Figure 13 (S203), notify the corresponding notification object of the sensor of the replacement information indicating the diagnosed replacement period (refer to S203). Figure 13 (S207). According to this diagnostic method, the replacement information is notified to the notification object corresponding to the sensor 11, so the oil replacement period detected by the sensor 11 can be easily determined, and the oil replacement period can be diagnosed in a simple way.

[0178] Furthermore, in the above description, sensor 11, which detects the deterioration state of the oil, is a color sensor. The color change of the oil is based on the residual rate of additives (see...). Figures 7A to 7C Therefore, a color sensor can be used to detect the deterioration state of the oil. However, sensor 11 may not be a color sensor. For example, sensor 11 may also analyze the composition of the oil and output composition data as a detection result. Furthermore, in this case, the replacement threshold mentioned above is not a grayscale value, but rather a value equivalent to the composition data when the oil reaches the end of its lifespan. Thus, the replacement threshold is not limited to a grayscale value. In addition, sensor 11 may also analyze impurities contained in the oil, such as the amount of iron powder, to detect the deterioration state of the oil.

[0179] ===Second Implementation Method===

[0180] Next, the second embodiment of this disclosure will be described.

[0181] Patent Document 1 describes the inclusion of various additives in lubricating oils, including oiliness agents, anti-wear agents, extreme pressure additives (extreme pressure agents) and other load-bearing additives, antioxidants, and defoamers. Furthermore, Patent Document 1 describes the inference of the concentration of additives in the lubricating oil based on the value of B in colorimetric data.

[0182] In cases where the residual rate of one of the diagnostic additives, namely antioxidants, is low, the accuracy of inferences based on the value of B may decrease.

[0183] In the second embodiment, the purpose is to diagnose the deterioration of the oil appropriately.

[0184] <Diagnostic Methods>

[0185] Figures 7A to 7C This is a graph showing the time-varying changes in the color sensor's detection results versus the time-varying changes in the residual rate of antioxidants in oil used under arbitrary conditions. The horizontal axis in each graph represents time. Additionally, the left vertical axis represents the grayscale values ​​of each of the RGB (red, green, blue) colors. The right vertical axis represents the residual rate (%) of the additive (here, antioxidant). The solid line graph represents the time-varying changes in the color sensor's detection results (RGB data) when the oil's color is detected. The dashed line graph represents the time-varying changes in the residual rate of antioxidants. Figures 7A to 7C The graph in the middle represents the curves of different oils (oil A to oil C).

[0186] A color sensor is a sensor (color detector) used to detect the color of oil. A color sensor has a light-emitting part and a light-receiving part. Light is shone from the light-emitting part towards the oil, and the light-receiving part receives the light from the oil. Based on the amount of each color of light received by the light-receiving part, the color sensor outputs RGB data (color data with R data, G data, and B data), representing the grayscale values ​​of each of the RGB (red, green, and blue) colors. Specifically, R data represents the grayscale value of the received light at the wavelength of red, G data represents the grayscale value of the received light at the wavelength of green, and B data represents the grayscale value of the received light at the wavelength of blue.

[0187] exist Figures 7A to 7C In any of the graphs shown, as indicated by the dashed line, the residual rate of antioxidants contained in the oil decreases over time. Furthermore, as shown by the solid line, the color sensor's detection results change along with the change in the residual rate of antioxidants.

[0188] like Figures 7A to 7C As shown, the relationship between changes in the residual antioxidant rate and changes in the color sensor's detection results varies depending on the type of oil. For example, in the case of oil A, such as Figure 7A As shown, with the decrease in antioxidant residue, the B data (representing the blue grayscale values) decreases, but the R and G data (representing the red and green grayscale values) hardly decrease. In the cases of oils B and C, as... Figure 7B as well as Figure 7C As shown, with the decrease in the residual rate of antioxidants, not only the B data, but also the R data and G data also decrease.

[0189] Figure 20 This is a table showing the correlation between the residual rate of antioxidants and RGB data.

[0190] The values ​​in the table represent correlation coefficients. The closer the absolute value of the correlation coefficient is to 1, the stronger the correlation. Furthermore, the closer the correlation coefficient is to 1, the stronger the positive correlation; the closer the correlation coefficient is to -1, the stronger the negative correlation. Figure 1 As shown, in oils A and B, data B is more strongly correlated with the antioxidant residue rate compared to other colors (data R and data G). Conversely, in oil C, data G is more strongly correlated with the antioxidant residue rate compared to other colors (data R and data B). When the antioxidant residue rate is more strongly correlated with data B, as in oils A and B, it is preferable to diagnose the antioxidant residue rate based on data B. On the other hand, when the antioxidant residue rate is more strongly correlated with data G, as in oil C, diagnosing the antioxidant residue rate based on data G provides a higher accuracy than diagnosing it based on data B.

[0191] However, when developing a new oil product, the components it contains (base oil, antioxidants) and the combination of these components are determined. Therefore, at that time, the relationship between changes in the residual antioxidant rate in the oil and changes in the detection results of the color sensor is determined. Therefore, under arbitrary usage conditions, the time-varying change in the residual antioxidant rate of the developed oil is measured, and the time-varying change in the detection results (RGB data output from the color sensor) when detecting the oil is also measured, thereby obtaining... Figures 7A to 7C The dashed and solid lines represent the measurement results (graph information). Furthermore, based on these measurement results, such as... Figure 20As shown, the correlation coefficients of each color in the R, G, and B data relative to the antioxidant residue rate are calculated, and the data with a strong correlation to the antioxidant residue rate are identified from the RGB data. Thus, for each type of oil, the wavelengths (colors) with a strong correlation to the antioxidant residue rate can be determined.

[0192] In the second embodiment, oil degradation is diagnosed based on the light reception results of different wavelengths of light, depending on the type of oil. Specifically, when diagnosing a first oil (e.g., oil A, oil B), the degradation is diagnosed based on the light reception results of a first wavelength of light (e.g., data B); when diagnosing a second oil (e.g., oil C), the degradation is diagnosed based on the light reception results of a second wavelength of light (e.g., data G). Thus, oil degradation can be diagnosed appropriately according to the type of oil.

[0193] Furthermore, preferably in diagnosing oil degradation in this way, the light reception result of a first wavelength (e.g., data B) for the first oil (e.g., oil A, oil B) is more strongly correlated with the residual antioxidant content of the first oil compared to the light reception result of a second wavelength (e.g., data G). This allows for appropriate diagnosis of oil degradation caused by a decrease in the residual antioxidant content. Similarly, preferably, the light reception result of a second wavelength (e.g., data G) for the second oil (e.g., oil C) is more strongly correlated with the residual antioxidant content of the second oil compared to the light reception result of the first wavelength (e.g., data B). This allows for appropriate diagnosis of oil degradation caused by a decrease in the residual antioxidant content.

[0194] Furthermore, the diagnostic apparatus for diagnosing oil deterioration in the second embodiment diagnoses the deterioration of a first oil (e.g., oil A, oil B) based on the light reception results of a first wavelength (e.g., data B), and diagnoses the deterioration of a second oil (e.g., oil C) based on the light reception results of a second wavelength (e.g., data G). For example, the diagnostic apparatus 20 described later diagnoses oil deterioration based on data B when diagnosing oil A and oil B (equivalent to the first oil), and based on data G when diagnosing oil C. Thus, oil deterioration can be diagnosed appropriately according to the type of oil.

[0195] <Examples of the use of diagnostic methods>

[0196] The diagnostic system in the second embodiment is configured similarly to that described in the first embodiment. Figure 1 The diagnostic system 100 shown has the same configuration, so its description is omitted.

[0197] like Figure 2A as well as Figure 2BAs shown, the sensor unit 10 includes a color sensor 11, a control unit 12, and a communication unit 13. The color sensor 11, as already described, 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 sends the detection results (here, RGB data) of the color sensor 11 to the diagnostic device 20 via the communication unit 13.

[0198] The control unit 30 of the diagnostic device 20 diagnoses the oil change period based on the detection results (here, RGB data) of the color sensor 11 stored in the storage unit 40.

[0199] like Figure 6 As shown, the diagnostic color included in the profile information is information used to determine the detection result of the color sensor 11, i.e., the data in the RGB data used for oil diagnosis. When the diagnostic color is set to "blue (B)," "B data" from the RGB data is used for oil diagnosis. Similarly, when the diagnostic color is set to "green (G)," "G data" from the RGB data is used for oil diagnosis. Furthermore, when the diagnostic color is set to "red (R)," "R data" from the RGB data is used for oil diagnosis. Here, B data is used for diagnosing oil A and oil B, and G data is used for diagnosing oil C. Moreover, as described later, the diagnostic color in the profile information is information used to switch whether the diagnostic processing unit 33 functions as a first diagnostic unit or a second diagnostic unit.

[0200] The replacement threshold included in the information is a threshold used to diagnose whether an oil change is necessary. A "grayscale value" is set as the replacement threshold. For example, in the case of oil A, a grayscale value of "50" is set as the replacement threshold. Therefore, during the diagnosis of oil A, the grayscale value shown in the "B data" of the RGB data output by the color sensor 11 is compared with the threshold "50". If the detection result of the color sensor 11 reaches the replacement threshold, it indicates that the oil has deteriorated to the point where an oil change is necessary. In other words, the replacement threshold is a reference value used to determine when the oil has reached the replacement period (in other words, the replacement threshold is a reference value used to diagnose the lifespan of the oil).

[0201] The diagnostic processing unit 33 of the control unit 30 diagnoses oil deterioration based on the light reception results of the color sensor 11 (the light reception results when light from the oil is received; here, RGB data). As described later, the diagnostic processing unit 33 is configured to diagnose oil deterioration based on B data (the light reception results of light of the first wavelength) when diagnosing oil A and oil B (equivalent to the first oil), and based on G data (the light reception results of light of the second wavelength) when diagnosing oil C (equivalent to the second oil). In other words, the diagnostic processing unit 33 has the function of diagnosing oil deterioration based on B data as a first diagnostic unit and diagnosing oil deterioration based on G data as a second diagnostic unit. Furthermore, the diagnostic processing unit can also be configured to diagnose oil deterioration based on R data. The various processes of the control unit 30 (diagnostic processing unit 33) described below are implemented by executing the program stored in the storage device by the arithmetic processing unit of the diagnostic device 20.

[0202] The diagnostic processing unit 33 determines the diagnostic color (refer to) for the oil setting corresponding to the sensor ID. Figure 6 For example, in the case of diagnosing oil detected by "sensor ID; sensor 001", due to the sensor database 415 (refer to...). Figure 9 The sensor ID; sensor 001 is used to establish the corresponding oil ID as "oil A". Therefore, the diagnostic processing unit 33 establishes the corresponding oil ID as "oil A" based on the profile database 412. Figure 6 The diagnostic color is determined to be "blue (B)". On the other hand, when diagnosing oil detected by "sensor ID; sensor 003", due to the relationship with sensor database 415 (see reference...) Figure 9 The sensor ID for sensor 003 is set to "oil C". Therefore, the diagnostic processing unit 33 establishes the corresponding oil ID as "oil C" based on the profile database 412. Figure 6 The diagnostic color was determined to be "green (G)".

[0203] If the diagnostic color is determined to be "blue (B)", the diagnostic processing unit 33 (first diagnostic unit) extracts the B data from the RGB data in the detection result database 43. Therefore, when diagnosing oil (here, oil A) detected by "sensor ID; sensor 001", the B data is extracted from the RGB data of "sensor ID; sensor 001" in the detection result database 43. Additionally, the diagnostic processing unit 33 extracts the grayscale value curve information of the RGB values ​​from the profile database 412 (see...). Figure 7A The diagnostic processing unit 33 obtains the grayscale value curve information of blue (B) from the test result database 43 and the grayscale value curve information of blue (B) obtained from the profile database 412, and uses this information to diagnose oil deterioration, and determines the oil replacement period and remaining life.

[0204] The diagnostic processing unit 33 scales the time axis of the grayscale value curve of blue (B) obtained from the profile database 412 to match the progression of the detection results of the color sensor 11 up to this point (see reference). Figure 14 (The solid line curve). Furthermore, the diagnostic processing unit 33 makes the curve with the changed time axis match the progress of the detection results of the color sensor 11 up to this point (see reference). Figure 14 (The solid line curve) (by changing the time axis and the curve) Figure 14 (Fitting the curve of the solid line) to obtain Figure 14 The dashed line indicates the predicted shift of the detection results (the shift of future detection results).

[0205] Next, the diagnostic processing unit 33 calculates the replacement period t1 when the detection result of the color sensor 11 reaches the specified threshold Tc. The replacement period t1 is equivalent to the period when the oil deteriorates to the point where it needs to be replaced, and is equivalent to the "lifespan end date" of the oil.

[0206] In addition, such as Figure 14 As shown, the diagnostic processing unit 33 calculates the residual period Pr by calculating the difference between the replacement period t1 and the current time t0. The residual period Pr is the period (number of days) until the oil's lifespan ends, and is therefore equivalent to the oil's "remaining lifespan".

[0207] However, the rate of oil degradation varies depending on the usage of the equipment using the oil. For example, if the equipment is used more frequently, the oil deteriorates faster, thus the change in the detection result of the color sensor 11 is considered to be faster. Conversely, if the equipment is used less frequently, the change in the detection result of the color sensor 11 is considered to be slower because oil degradation is suppressed. Since the rate of oil degradation changes, it is considered to predict the future trend of detection results based on the most recent rate of oil degradation (see reference). Figure 14 In the case of the dashed line, the prediction accuracy becomes higher. Therefore, it is preferable to use the new detection results stored in the detection result database 43 (in other words, not to use the old detection results) to obtain the result. Figure 14 The dashed line indicates the predicted shift of the detection results. Therefore, it is possible to predict the future shift of detection results with high accuracy, and to diagnose the oil change period t1 with high precision. However, it is also possible to use the detection results from the initial color sensor 11 used for the oil to determine... Figure 14 The dashed line indicates the predicted shift of the detection results.

[0208] 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 oil (here, oil C) detected by "sensor ID; sensor 003," G data is extracted from the RGB data of "sensor ID; sensor 003" in the detection result database 43. Additionally, the diagnostic processing unit 33 extracts the grayscale value curve information of the RGB values ​​from the profile database 412 (see...). Figure 7C The grayscale value curve information of green (G) is obtained from the database 412. Based on the G data extracted from the test result database 43 and the grayscale value curve information of green (G) obtained from the profile database 412, the diagnostic processing unit 33 calculates the oil replacement period t1 and the remaining oil lifespan Pr as an oil deterioration diagnosis. Furthermore, the calculation methods for the replacement period t1 and the remaining oil lifespan are as follows: Figure 14 As shown, the explanation is omitted here.

[0209] Notification processing unit 34 of control unit 30 (see reference) Figure 1 If Pr is less than a specified threshold (e.g., 14 days) during the remaining period, a warning is sent to user terminal 61 and supplier terminal 71.

[0210] As described above, the control unit 30 (diagnostic processing unit 33) diagnoses the deterioration of a first oil (e.g., oil A, oil B) based on the light reception results of a first wavelength (e.g., data B), and diagnoses the deterioration of a second oil (e.g., oil C) based on the light reception results of a second wavelength (e.g., data G). Thus, it is possible to appropriately diagnose oil deterioration according to the type of oil.

[0211] Furthermore, the diagnostic device is not limited to the diagnostic device 20 described above. For example, it could also be a device constructed by means of... Figure 2B The control unit 12 of the sensor unit 10 shown has 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 for oil deterioration. Furthermore, the diagnostic device for oil deterioration may not need to notify the user terminal 61 or the supplier terminal 71 of any warnings. That is, the diagnostic device 20 may not need to have a notification processing unit 34.

[0212] Furthermore, the diagnosis of oil deterioration is not limited to diagnosing the oil replacement period t1 and the remaining period Pr. For example, as a diagnosis of oil deterioration, the residual rate of antioxidants contained in the oil can also be diagnosed. In the case of diagnosing the residual rate of antioxidants contained in the oil, it is preferable that the aforementioned profile database 412 also includes data showing the relationship between the time and grayscale value of the residual rate of antioxidants. Figures 7A to 7C(Data from the dashed curve graph). Furthermore, the diagnostic processing unit 33 (first diagnostic unit) calculates the antioxidant retention rate corresponding to the grayscale value shown in the B data based on the B data (equivalent to the light reception result of the first wavelength) from the color sensor 11. Additionally, the diagnostic processing unit 33 (second diagnostic unit) calculates the antioxidant retention rate corresponding to the grayscale value shown in the G data based on the G data (equivalent to the light reception result of the second wavelength) from the color sensor 11. In this case, it is also possible to appropriately diagnose oil degradation based on the type of oil.

[0213] ===Transformation Examples===

[0214] The above-described embodiments are provided for easy understanding of this disclosure and are not intended to limit or interpret this disclosure. Furthermore, this disclosure can be modified and improved without departing from its spirit, and its equivalents are naturally included within this disclosure.

[0215] For example, in the first embodiment, the case where sensor 11 is a color sensor was described, but it can also be a contact sensor or a non-contact sensor. Furthermore, as a non-contact sensor, in addition to the color sensor described above, examples include image sensors and chemical sensors. Additionally, sensor 11 can also be a light sensor, an ultrasonic sensor, a temperature sensor, etc. Examples of light sensors include visible light sensors, infrared sensors, and ultraviolet sensors.

[0216] Furthermore, in the first embodiment, the case where the control unit 30 notifies the replacement information to the notification object corresponding to the sensor 11 has been described. However, it may also notify the replacement information to the notification object corresponding to the sensor unit 10, the device 62, or the tank 63. In this case, since the sensor unit 10, the device 62, or the tank 63 has the sensor 11, "the notification object corresponding to the sensor 11" includes "the notification object corresponding to the sensor unit 10, the device 62, or the tank 63". Alternatively, the control unit 30 may not notify the replacement information to the notification object corresponding to the sensor 11, but only to the notification object selected by the administrator or the notification object selected by the user.

[0217] Furthermore, in the first and second embodiments, storage device 52 is described as the recording medium for recording programs, but the recording medium is not limited to this. The recording medium may also be a storage device built into a computer system, such as a hard disk drive (HDD), a solid-state drive (SSD), an optical disk, a ROM (Read-Only Memory), a CD (Compact Disc)-ROM, flash memory, or other removable recording media.

[0218] Explanation of reference numerals in the attached figures

[0219] 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…Record processing unit; 40…Storage unit; 41…Basic information database; 411…Oil database; 412…Brief profile database; 413…Supplier database; 414…User database; 414'…Customer database; 415…Sensor database; 42…Diagnostic setting database; 43…Detection result database; 44…Replacement record database; 51…Arithmetic processing unit; 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, wherein, Possessing: a storage section that stores a detection result of a sensor that indicates a deterioration state of oil; and a control section that diagnoses a replacement timing of the oil based on the detection result stored in the storage section, and notifies a notification target that corresponds to the sensor of replacement information that indicates the diagnosed replacement timing.

2. The diagnosis device according to claim 1, wherein as the notification target, at least one of a user of the oil and a supplier that supplies the oil to the user can be set.

3. The diagnosis device according to claim 1, wherein as the replacement timing, the control section calculates a timing at which the detection result reaches a replacement threshold value.

4. The diagnosis device according to claim 3, wherein the replacement threshold value can be set in correspondence with the sensor.

5. The diagnosis device according to claim 1, wherein the control section diagnoses the replacement timing using a new detection result among the detection results stored in the storage section.

6. The diagnosis device according to claim 1, wherein the control section notifies the notification target of the replacement information when a remaining period reaches a period threshold value.

7. The diagnosis device according to claim 6, wherein the period threshold value can be set in correspondence with the sensor.

8. The diagnosis device according to claim 6 or 7, wherein the control section, when notifying the notification target of the replacement information, notifies the notification target of a list of suppliers of the oil to the user, the list including the replacement information of other oil supplied to the user of the oil.

9. The diagnosis device according to claim 1, wherein the control section notifies the notification target of a list including the replacement information corresponding to a plurality of the sensors respectively.

10. The diagnosis device according to claim 9, wherein the control section notifies the list in which a plurality of the replacement information is arranged in order of the remaining period.

11. The diagnosis device according to claim 9 or 10, wherein the control section determines a plurality of the sensors that correspond to the user of the oil supplied by the supplier of the oil, and notifies the supplier of the list including the replacement information corresponding to the determined plurality of the sensors respectively.

12. The diagnosis device according to claim 9, wherein the control section, when the list is requested by the user of the oil, notifies the supplier that supplies the oil to the user that the list is requested by the user.

13. The diagnosis device according to claim 1, wherein the control section, when the replacement information is requested by the user of the oil, notifies the supplier that supplies the oil to the user that the replacement information is requested by the user.

14. The diagnosis device according to claim 12 or 13, wherein the control section notifies the supplier of information related to past oil replacement of the user.

15. The diagnosis device according to claim 1, wherein The above sensor is a color sensor.

16. The diagnostic device according to claim 1, wherein The above control section diagnoses the deterioration of the oil based on a detection result of light of a wavelength corresponding to the kind of the oil among the detection results of the sensor.

17. A diagnostic method, wherein a detection result is acquired from a sensor that detects a deterioration state of oil, a replacement timing of the oil is diagnosed based on the detection result, replacement information indicating the diagnosed replacement timing is notified to a notification target that corresponds to the sensor.

18. A computer-readable recording medium, wherein, A program is recorded, the program causing a computer to execute the steps of: a detection result is acquired from a sensor that detects a deterioration state of oil; a replacement timing of the oil is diagnosed based on the detection result, and replacement information indicating the diagnosed replacement timing is notified to a notification target that corresponds to the sensor.

19. A diagnostic device, wherein, provided with: a storage section that stores a light reception result when light from oil is received; and a control section that diagnoses deterioration of the oil based on the light reception result, The above control section diagnoses the deterioration of the oil based on a light reception result of light of a wavelength corresponding to the kind of the oil.

20. The diagnostic device according to claim 19, wherein The above control section diagnoses the deterioration of the first oil based on a light reception result of light of a first wavelength when the first oil is diagnosed, and diagnoses the deterioration of a second oil different from the first oil based on a light reception result of light of a second wavelength different from the first wavelength when the second oil is diagnosed.

21. A computer-readable recording medium, wherein, A program is recorded, the program causing a computer to execute the steps of: a light reception result when light from oil is received is acquired, and deterioration of the oil is diagnosed based on a light reception result of light of a wavelength corresponding to the kind of the oil among the light reception result.

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