Abnormal sound diagnosing apparatus, abnormal sound diagnosing method, and abnormal sound diagnosing program

Abstract

An abnormal sound diagnosis device includes a first reception unit that receives input of vehicle information related to a structure of a subject vehicle that is a subject of abnormal sound diagnosis, a second reception unit that receives input of at least one of an abnormal sound traveling condition and an abnormal sound environmental condition in which an abnormal sound is generated in the subject vehicle, and an extraction unit that extracts, from a sound emission map database in which a plurality of sound emission maps are stored, one or more associated sound emission maps associated with the subject vehicle based on the input vehicle information, the at least one of the abnormal sound traveling condition and the abnormal sound environmental condition. The sound emission map is a map that indicates a correlation between a protruding amount in which the abnormal sound generated in the vehicle protrudes from background noise and at least one of a traveling condition and an environmental condition. The abnormal sound diagnosis device includes a first determination unit that determines at least one of a first traveling condition and a first environmental condition in which the protruding amount of the abnormal sound in the subject vehicle becomes large based on the extracted associated sound emission map.

Description

TECHNICAL FIELD

[0001] The technology disclosed in this specification relates to an abnormal sound diagnosis device, an abnormal sound diagnosis method, and an abnormal sound diagnosis program. BACKGROUND

[0002] An abnormal sound diagnosis device is disclosed in Patent Literature 1, which is capable of collecting vehicle data indicating a running state and sound data at the time of running of a vehicle, and diagnosing by associating the sound data and the vehicle data.

[0003] PRIOR ART DOCUMENTS

[0004] PATENT LITERATURE

[0005] Patent Literature 1: Japanese Patent Application Publication No. 2019-85059 SUMMARY

[0006] PROBLEMS TO BE SOLVED BY THE INVENTION

[0007] Depending on the running conditions and environmental conditions of a vehicle, the amount by which an abnormal sound generated by the vehicle stands out from background noise is sometimes insufficient. In this case, determination of the abnormal sound and determination of the cause of generation become difficult. In this specification, a technology for determining an abnormal sound with good precision is proposed.

[0008] SOLUTION TO THE PROBLEM

[0009] The abnormal sound diagnosis device disclosed in this specification includes a first reception means that receives input of vehicle information related to a structure of a subject vehicle that is a subject of abnormal sound diagnosis. The abnormal sound diagnosis device includes a second reception means that receives input of at least one of a running condition in which an abnormal sound is generated in the subject vehicle, i.e., an abnormal sound running condition, and an environmental condition in which an abnormal sound is generated in the subject vehicle, i.e., an abnormal sound environmental condition. The abnormal sound diagnosis device includes an extraction means that extracts one or more associated sound maps associated with the subject vehicle from a sound map database in which a plurality of sound maps are stored, based on at least one of the input vehicle information, the abnormal sound running condition, and the abnormal sound environmental condition. The sound map is a map indicating a correlation between an amount by which an abnormal sound generated in a vehicle stands out from background noise and at least one of a running condition and an environmental condition. The abnormal sound diagnosis device includes a first decision means that decides at least one of a first running condition in which the amount by which an abnormal sound in the subject vehicle stands out increases, and a first environmental condition in which the amount by which an abnormal sound in the subject vehicle stands out increases, based on the extracted associated sound map.

[0010] In the abnormal sound diagnosis apparatus, in response to reception of input of vehicle information, abnormal sound running conditions, and abnormal sound environmental conditions, an associated sound emission map associated with the subject vehicle can be extracted. Then, at least one of a first running condition and a first environmental condition in which an amount of protrusion of the abnormal sound from background noise is large can be determined based on the associated sound emission map. By causing the vehicle to run in the first running condition and the first environmental condition, or the like, an abnormal sound having a sufficient amount of protrusion from background noise can be generated. Determination of the abnormal sound and its cause can be made with good accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0011] Figure 1 is a block diagram showing an outline of an abnormal sound diagnosis system 1.

[0012] Figure 2 is a diagram showing an example of an abnormal sound and background noise.

[0013] Figure 3 is a diagram showing an example of a sound emission map.

[0014] Figure 4 is a flowchart showing the content of an abnormal sound diagnosis process.

[0015] Figure 5 is a flowchart showing the content of an abnormal sound diagnosis process.

[0016] Figure 6 is a diagram showing an example of a specific sound emission map.

[0017] REFERENCE NUMERALS

[0018] 1: Abnormal sound diagnosis system, 10: Smartphone, 11: CPU, 12: Storage unit, 16: Microphone, 17: Abnormal sound diagnosis program, 18: Recorded sound data, 20: Server, 31: Vehicle database, 32: Sound emission map database, 33: Map database, 34: Abnormal sound database. DETAILED DESCRIPTION

[0019] The abnormal sound diagnosis device according to an example of the present specification can also include a component that records the abnormal sound. The abnormal sound diagnosis device can also include a generating component that generates a specific sound mapping that indicates a correlation between a sound pressure level of the recorded abnormal sound and at least one of a driving condition and an environmental condition, the specific sound mapping extrapolating a sound pressure level of an abnormal sound outside a range of changes in the driving condition and the environmental condition at the time of recording. The abnormal sound diagnosis device can also include a second determining component that determines at least one of a second driving condition, which is a driving condition in which an abnormal sound prominence increases, and a second environmental condition, which is an environmental condition in which an abnormal sound prominence increases, based on the generated specific sound mapping. According to this configuration, the second driving condition and the second environmental condition can be determined using the actually recorded abnormal sound. As a result, the second driving condition and the second environmental condition can be made realistic conditions. The abnormal sound prominence can be reliably increased.

[0020] The abnormal sound diagnosis device according to an example of the present specification can also include a component that reflects the specific sound mapping in a plurality of sound mappings stored in a sound mapping database. The specific sound mapping is a mapping generated using the actually recorded abnormal sound, and thus has high accuracy. By feeding back the specific sound mapping to the plurality of sound mappings, the accuracy of the plurality of sound mappings can be improved.

[0021] The abnormal sound diagnosis device according to an example of the present specification can also include a road information acquisition component that acquires specific location road information indicating a road state of a specific location on a map from a map database storing road states of locations on the map, in a case where the second reception component receives an input indicating an abnormal sound environmental condition of the specific location on the map. The extraction component can also extract the associated sound mapping based on the acquired specific location road information. According to this configuration, by specifying the specific location on the map, the associated sound mapping can be extracted. The procedure for extraction can be simplified.

[0022] The abnormal sound diagnosis device according to an example of the present specification can also include an abnormal sound information acquisition component that acquires associated abnormal sound information associated with the subject vehicle from an abnormal sound database storing abnormal sound information related to abnormal sounds of vehicles. The extraction component can also extract the associated sound mapping based on the acquired associated abnormal sound information. As an example of the abnormal sound information, information related to abnormal sounds obtained when developing a vehicle, complaint information related to abnormal sounds can be cited. According to this configuration, the associated sound mapping can be extracted based on past abnormal sound information stored in the abnormal sound database. A large amount of abnormal sound information can be used for extraction, and thus the extraction accuracy can be improved.

[0023] In one example of the abnormal sound diagnostic device disclosed in this specification, the first driving condition may also include a driving condition that reduces background noise relative to the abnormal sound. According to this structure, background noise can be reduced, thus increasing the amount by which the abnormal sound stands out from the background noise.

[0024] [Example]

[0025] <Structure of Abnormal Sound Diagnosis System 1>

[0026] exist Figure 1 The diagram shows an overview of the abnormal sound diagnosis system 1 of this method. The abnormal sound diagnosis system 1 is a system that collects and analyzes various abnormal sounds at service sites and other locations, and determines the causes associated with the abnormal sounds. The abnormal sound diagnosis system 1 includes a smartphone 10 as an abnormal sound diagnosis device and a server 20. The smartphone 10 and server 20 are connected via a base station 50 and the Internet 40, enabling various data communication. It should be noted that the terminal device connected to the server 20 is not limited to the smartphone 10, but may include other devices. Figure 1 For the sake of simplicity, only the smartphone 10 is shown in the illustration.

[0027] The smartphone 10 mainly includes a CPU 11, a storage unit 12, a communication unit 13, an operation panel 14, a speaker 15, and a microphone 16. The CPU 11 controls the various components of the smartphone 10. The storage unit 12 includes, for example, an EEPROM. The storage unit 12 stores various programs such as an abnormal sound diagnosis program 17 and recorded data 18. When the CPU 11 executes the abnormal sound diagnosis program 17 stored in the storage unit 12, the smartphone 10 functions as a first receiving unit, a second receiving unit, an extraction unit, a first decision unit, a generation unit, and a second decision unit.

[0028] The communication unit 13 is a component that conducts wireless communication 51 with the base station 50 via an antenna unit (not shown) in a manner similar to mobile phone communication. The speaker 15 is a component for outputting sound, such as during a call. The microphone 16 is a component for inputting sound. The sound recorded by the microphone 16 is stored as recording data 18 in the storage unit 12. The operation panel 14 has various buttons for accepting user operations and a touchpad screen for displaying character information, buttons, etc.

[0029] Server 20 includes CPU 21, storage unit 22, and external connection interface 23. CPU 21 controls the various components of server 20. External connection interface 23 is an interface that enables data communication with external devices via Internet 40.

[0030] Storage unit 22 stores a vehicle database 31, a pronunciation mapping database 32, a map database 33, and an abnormal sound database 34. Vehicle database 31 stores vehicle specifications (e.g., vehicle dimensions, engine type, suspension type, etc.) for various vehicle models. Pronunciation mapping database 32 stores multiple pronunciation mappings. The content of the pronunciation mappings will be described later.

[0031] Map database 33 is a database that stores the road conditions of various locations on the map. Road conditions can include parameters such as slope, curvature of curves, surface roughness, and the presence or absence of steps.

[0032] The Abnormal Sound Database 34 is a database of information related to abnormal sounds from vehicles, i.e., abnormal sound information. Abnormal sound information is stored for each vehicle model. This information includes the driving and environmental conditions that caused the abnormal sound, the content of the abnormal sound (e.g., sound altitude, sound type), and the location of the abnormal sound (e.g., engine compartment, front wheels, air conditioning vents). Abnormal sound information can be obtained during vehicle development or based on complaint information.

[0033] (Pronunciation mapping content)

[0034] A sound mapping is a mapping that represents the correlation between the amount of prominence of an abnormal sound generated in a vehicle from the background noise and at least one of the driving conditions and environmental conditions. Sound mappings can take various forms, such as two-dimensional graphs, three-dimensional graphs using contour lines, or mathematical expressions. Furthermore, the variables used in sound mapping are not limited to two or three; they can be four or more. Background noise refers to all noise other than the abnormal sound from its source. Examples include road noise and wind noise.

[0035] Driving conditions are those controlled by the driver's actions. Examples of driving conditions include speed, acceleration, torque, accelerator opening, driving state (initial driving, constant speed cruising, etc.), and gear selection. Environmental conditions are the environment surrounding the vehicle. Examples of environmental conditions include external air temperature, internal air temperature, humidity, air pressure, road conditions (e.g., slope, radius of curvature), and driving location (e.g., parking lot exit).

[0036] exist Figure 2An example of abnormal sound and background noise is shown in FIG. 6. The horizontal axis is frequency, and the vertical axis is sound pressure level. Abnormal sounds AN1 and AN2 are sounds generated under different driving conditions. The abnormal sound AN1 is at or below the same level as the background noise BN throughout the frequency band. Therefore, the abnormal sound AN1 is buried by the background noise BN, and thus it is difficult to determine. On the other hand, the abnormal sound AN2 is more prominent than the abnormal sound AN1 in terms of the amount of prominence from the background noise. That is, the abnormal sound AN2 is sufficiently greater than the background noise BN in terms of sound pressure level throughout the frequency band. Therefore, the abnormal sound AN2 can be distinguished from the background noise BN, and thus it can be determined. In the technology of the present specification, as described later, by appropriately determining the driving condition, the abnormal sound AN1 can be changed to the abnormal sound AN2 (refer to arrow Y1). Thereby, determination of the abnormal sound and determination of the cause can be performed with good accuracy.

[0037] In Figure 3 An example of the sound emission map is shown in FIG. 7. In Figure 3 In FIG. 7, the amount of prominence of the abnormal sound from the background noise is represented by a three-dimensional graph using contour lines. The horizontal axis represents the speed of the vehicle. The vertical axis represents the acceleration in the positive direction when accelerating and the acceleration in the negative direction when decelerating. The contour lines represent that the deeper the color, the greater the amount of prominence of the abnormal sound from the background noise. In Figure 3 In the example of FIG. 7, it is known that the amount of prominence of the abnormal sound is the greatest at the maximum points Pa and Pb.

[0038] A plurality of labels are assigned to a plurality of sound emission maps, respectively. The label is information indicating the attribute or feature of the sound emission map. As an example of the label, a vehicle model, a place where the abnormal sound is generated, the content of the abnormal sound, an environmental condition (example: uphill), and the like can be listed. By adding the label, each of a large number of sound emission maps can be classified for each vehicle model and each place where the abnormal sound is generated.

[0039] (Content of Abnormal Sound Diagnosis Process)

[0040] The flow of Figure 4 and Figure 5 explains the content of the abnormal sound diagnosis process performed by the smartphone 10. Figure 4 and Figure 5 The flow of FIGS. 10A and 10B is started by the CPU 11 executing the abnormal sound diagnosis program 17.

[0041] In step S10, the smartphone 10 receives input of vehicle information. The vehicle information is information related to the structure of the subject vehicle that is the diagnosis target. As an example of the vehicle information, there can be cited the vehicle model, the platform, the power train, the constituent components of each part, and the like. The input method of the vehicle information can be various. For example, there can be a method of downloading the vehicle information by accessing the vehicle database 31 of the server 20 via the Internet 40 when the vehicle identification number of the subject vehicle is input to the smartphone 10. Further, for example, there can be a method of acquiring the vehicle information by performing CAN (Controller Area Network) communication between the subject vehicle and the smartphone 10.

[0042] In step S20, the smartphone 10 receives input of at least one of an abnormal sound running condition and an abnormal sound environment condition. The abnormal sound running condition is a running condition in which an abnormal sound is generated in the subject vehicle. The abnormal sound environment condition is an environment condition in which an abnormal sound is generated in the subject vehicle. The input method of the abnormal sound running condition and the abnormal sound environment condition can be various. For example, it is also possible to input the contents of the interrogation of the user via the operation panel 14. Further, for example, there can be a method of acquiring the vehicle speed and the accelerator opening degree at the time of generation of an abnormal sound by performing CAN communication between the subject vehicle and the smartphone 10.

[0043] Further, in step S20, input of an abnormal sound content can also be received. The abnormal sound content is information related to an abnormal sound obtained by interrogating the user. As an example of the abnormal sound content, there can be cited the place of generation of an abnormal sound, the timing of generation of an abnormal sound, the height of an abnormal sound, the kind of an abnormal sound (for example, a periodic sound such as "clank clank", a continuous sound such as "beep").

[0044] In step S30, the smartphone 10 acquires abnormal sound information from the abnormal sound database 34. The acquisition method of the abnormal sound information can be various. For example, there can be a method of returning the abnormal sound information associated with the vehicle model when the vehicle model of the subject vehicle is sent to the abnormal sound database 34.

[0045] In step S40, the smartphone 10 accesses the pronunciation mapping database 32. Then, based on at least one of the vehicle information, the abnormal sound running condition, the abnormal sound environment condition, and the abnormal sound information, one or more associated pronunciation mappings associated with the subject vehicle are extracted.

[0046] The manner of the extraction method can be various. For example, a filter function can also be used. An example of the extraction method is listed below. In a case where extraction is performed using vehicle information (vehicle model), a pronunciation map having a label corresponding to the vehicle model can also be extracted. In a case where extraction is performed using abnormal sound traveling condition (speed), a pronunciation map using speed as a variable can also be extracted. In a case where extraction is performed using abnormal sound environment condition (specific place on a map), a map database 33 can also be accessed to acquire specific place road information (example: uphill) indicating a road state of the specific place. Also, a pronunciation map having a label corresponding to the specific place road information can also be extracted. In a case where extraction is performed using abnormal sound information (abnormal sound content: periodic sound), a pronunciation map having a label corresponding to the abnormal sound content can also be extracted. By performing a plurality of these extraction processes, an associated pronunciation map associated with the subject vehicle can be appropriately extracted from a large number of pronunciation maps.

[0047] In step S50, the smartphone 10 decides at least one of the 1st traveling condition and the 1st environment condition based on the extracted associated pronunciation map. The 1st traveling condition and the 1st environment condition are conditions in which the prominence of the abnormal sound becomes large.

[0048] Note that, in a case where a plurality of candidates exist in the 1st traveling condition, a condition in which it is easier to travel (example: low vehicle speed side) can be adopted. The 1st environment condition can be decided using a pronunciation map in which the 1st traveling condition is used as a variable. Figure 3 A specific example of a case where the 1st traveling condition is decided using a pronunciation map is described. It is known that, at the maximum points Pa and Pb, the prominence of the abnormal sound from the background noise is the largest. Also, the traveling speed S1a of the maximum point Pa is lower than the traveling speed S1b of the maximum point Pb. Thus, the traveling speed S1a and the acceleration A1a of the maximum point Pa are decided as the 1st traveling condition.

[0049] A place suitable for traveling in the 1st traveling condition can also be suggested together with the 1st traveling condition. The suggestion of the place can also be achieved by accessing the map database 33. For example, in a case where the traveling speed prompted in the 1st traveling condition is 80 km / h, the nearest expressway can also be suggested.

[0050] A place suitable for achieving the 1st environment condition can also be suggested together with the 1st environment condition. The suggestion of the place can also be achieved by acquiring weather information such as wind direction, rain, and the like from a server not illustrated. For example, in a case where the 1st environment condition is "wet road surface", an area in which it is currently raining can also be suggested.

[0051] The first travel condition can also be determined in a manner that can reduce the background noise. For example, it can be set as the first travel condition in which the gear ratio is set to the high range. Thereby, the engine speed can be reduced, and thus the background noise of the engine noise can be reduced. In addition, in the hybrid vehicle, it can be set as the first travel condition in which the SOC of the battery is increased. Thereby, the motor travel can be performed, and thus the background noise of the engine noise can be eliminated. In addition, in the hybrid vehicle, it can be set as the first travel condition in which sudden acceleration is prohibited. Thereby, the sharp current flow can be prevented, and thus the background noise of the battery cooling blower can be reduced. In addition, in the fuel cell vehicle, it can be set as the first travel condition in which the accelerator operation is moderated. Thereby, the background noise of the compressor of the FC stack can be reduced.

[0052] The first environmental condition can also be determined in a manner that can reduce the background noise. For example, by being set as the first environmental condition in which the travel resistance is small (example: flat land, downhill, tailwind), the background noise of the engine, the compressor, the road noise, and the like can be reduced.

[0053] In step S60, the smartphone 10 outputs the determined first travel condition and / or first environmental condition. The output method can be various. For example, it can be displayed on the operation panel 14, or a sound can be output to the speaker 15. In addition, for example, the first travel condition can be transmitted to the subject vehicle through CAN communication. In this case, the subject vehicle can travel in the first travel condition by automatic driving.

[0054] In step S70, the recording of the data and the travel data are performed. Specifically, as long as the subject vehicle is caused to travel in the first travel condition and / or first environmental condition, the abnormal sound is recorded using the microphone 16 of the smartphone 10. In addition, the travel condition and the environmental condition at the time of recording the sound can be recorded.

[0055] In step S80, it is determined whether the amount of protrusion of the recorded abnormal sound from the background noise is sufficient for the abnormal sound analysis. For example, the background noise component can be removed from the recorded data by a publicly known abnormal sound analysis program. Also, it can be determined whether the sound pressure level of the abnormal sound exceeds a predetermined threshold value. In the case of affirmative determination, step S180 is reached, and in the case of negative determination, step S90 is reached.

[0056] In step S90, the smartphone 10 determines whether there is a sensitivity of the abnormal sound with respect to the change in the travel condition. In the case where there is a sensitivity of the abnormal sound, the sound pressure level of the abnormal sound greatly changes according to the change in the travel condition. The determination method can be various.

[0057] Use Figure 6This example illustrates how to determine the presence or absence of sensitivity to abnormal sounds. The horizontal axis represents driving speed, and the vertical axis represents sound pressure level. The solid measured curve CL0 is a graph representing the variation in sound pressure level of abnormal sounds in actual recordings. The measured curve CL0 is generated within the range FR from driving speed Sa to Sb. The range FR is the range of driving speed variation during recording. This is because, in actual driving, driving resistance and operation vary, resulting in frequent variations in driving speed. Alternatively, if the rate of change of sound pressure level of abnormal sounds within this range FR exceeds a predetermined threshold, it can be determined that abnormal sound sensitivity exists.

[0058] If a negative judgment is made (step S90: NO), proceed to step S170, and an error is displayed on the operation panel 14. Then, the process ends. On the other hand, if a positive judgment is made (step S90: YES), proceed to step S110.

[0059] In step S110, the smartphone 10 generates a specific pronunciation map. The specific pronunciation map is a map representing the correlation between the sound pressure level of the recorded abnormal sound and at least one of the driving conditions and / or environmental conditions. Additionally, the specific pronunciation map is a map extrapolating the sound pressure level of abnormal sounds outside the range of variations in driving conditions and environmental conditions at the time of recording.

[0060] use Figure 6 The example illustrates the method for generating a specific pronunciation map. The extrapolated curves CL1 and CL2, represented by dashed lines, are graphs obtained by extrapolating from the measured curve CL0. That is, the extrapolated curves CL1 and CL2 are graphs predicted based on the measured curve CL0. The extrapolation method can be varied. For example, a first-order or n-order extrapolation can be used. Additionally, multiple approximation lines can be defined.

[0061] In step S120, the smartphone 10 determines at least one of a second driving condition and a second environmental condition based on the generated specific pronunciation map. The second driving condition and the second environmental condition are conditions where the prominence of the abnormal sound increases. (Explanation of usage) Figure 6 The specific pronunciation mapping determines the specific instance of the second driving condition. Figure 6 As shown by the extrapolated curve CL1, it can be seen that the higher the driving speed, the higher the sound pressure level of the abnormal sound. Therefore, as the second driving condition, the driving speed S2, which is the maximum speed within the legal speed range, is determined. This allows the sound pressure level of the abnormal sound to increase from SPL1 to SPL2.

[0062] In step S130, the smartphone 10 outputs the determined second driving conditions and / or second environmental conditions. The content of step S130 is the same as that of the aforementioned step S60, therefore, the description is omitted.

[0063] In step S140, the smartphone 10 reflects the generated specific sound emission map in the plurality of sound emission maps stored in the sound emission map database 32. The manner of reflection can be various. For example, the smartphone 10 can also transmit the specific sound emission map to the server 20. Also, the server 20 can extract the sound emission map associated with the specific sound emission map and correct the content. The effect is described. The data of the sound emission map is sometimes a predicted value based on extrapolation. In this case, by using the data of the specific sound emission map generated based on the actual running data, it is possible to correct the predicted value to the measured value. It is possible to improve the accuracy of the sound emission map.

[0064] In step S150, the acquisition of the recording data and the running data is performed. Specifically, it is only necessary to record the sound with the microphone 16 of the smartphone 10 while making the subject vehicle run in the 2nd running condition and / or the 2nd environmental condition. In addition, it is only necessary to record the running condition, the environmental condition at the time of recording the sound.

[0065] In step S160, it is determined whether the protruding amount of the recorded abnormal sound from the background noise is sufficient for the abnormal sound analysis. The content of step S160 is the same as that of step S80, and thus the description is omitted. In the case of negative determination, the flow proceeds to step S170, and in the case of affirmative determination, the flow proceeds to step S180. In step S180, the abnormal sound analysis is performed based on the recorded abnormal sound. Various methods known in the art can be used in the abnormal sound analysis, and thus the description is omitted. Then, the flow ends.

[0066] (EFFECT)

[0067] In the technology of the present specification, it is possible to extract the associated sound emission map associated with the subject vehicle in response to the input of the vehicle information, the abnormal sound running condition, and the abnormal sound environmental condition (step S40). Then, it is possible to determine at least one of the 1st running condition and the 1st environmental condition in which the protruding amount of the abnormal sound from the background noise is large based on the associated sound emission map (step S50). By making the vehicle run in accordance with the 1st running condition and the 1st environmental condition, it is possible to generate the abnormal sound in which the protruding amount from the background noise is sufficiently large (step S70). It is possible to improve the recording accuracy of the recording data, and thus it is possible to determine the abnormal sound and the cause with good accuracy in the abnormal sound analysis (step S180).

[0068] In the technology of the present specification, a specific sound production map of an abnormal sound whose sound pressure level is extrapolated to an outer side of a range of changes in a driving condition and an environmental condition at the time of recording can be generated (step S110). Then, at least one of a second driving condition and a second environmental condition in which an amount of prominence of the abnormal sound from the background noise is large can be determined based on the specific sound production map (step S120). Since the second driving condition and the second environmental condition can be determined using data of the abnormal sound of the actual recording, the amount of prominence of the abnormal sound can be reliably increased.

[0069] The microphone 16 built in the smartphone 10 has lower performance such as sensitivity and directivity than a dedicated microphone used in vehicle development. Thus, even an abnormal sound that can be definitely recognized by human ears cannot be recognized in the recording data in some cases. In the technology of the present specification, an abnormal sound whose amount of prominence from the background noise is large enough can be produced, and thus even a microphone with low performance can generate recording data in which the abnormal sound can be recognized. Since the abnormal sound measurement and analysis can be performed using the smartphone 10, a dedicated device for abnormal sound analysis and a professional technician can not be needed. The abnormal sound analysis can be widely and generally performed.

[0070] The embodiments are described in detail above, but they are merely examples and do not limit the claims. In the technology recited in the claims, technologies obtained by various modifications and changes of the above-described specific examples are included. The technical elements described in the present specification or the drawings exhibit technical usefulness alone or through various combinations, and are not limited to the combinations recited in the claims at the time of filing. In addition, the technology exemplified in the present specification or the drawings simultaneously achieves multiple objects, and achieving one of them itself has technical usefulness.

[0071] (Modified example)

[0072] Figure 4 And Figure 5 The flowchart is an example, and is not limited to this way. For example, the order of the input of the vehicle information (step S10), the input of the abnormal sound driving condition and the abnormal sound environmental condition (step S20), and the acquisition of the abnormal sound information (S30) can be freely changed, and any step can be omitted.

[0073] The case where the service site is the utilization subject of the abnormal sound diagnosis system 1 is described, but is not limited to this way, and can be utilized by various subjects. For example, automobile manufacturers, automobile dealers, repair shops, leasing companies, automobile sharing companies, company automobile management departments, automobile parts suppliers, acoustic analysis tool industries, communication service industries, data science industries, portable application development industries, and the like can also be the subjects.

[0074] The case where the smartphone 10 is used as the abnormal sound diagnosis device is explained, but is not limited to this. Various devices such as a tablet terminal, a PC, and the like can be used.

[0075] The case where the vehicle database 31 to the abnormal sound database 34 are stored in the server 20 is explained, but is not limited to this. For example, these databases can be stored in the abnormal sound diagnosis device itself.

Claims

1. An abnormal sound diagnosis device, comprising: a first reception means that receives input of vehicle information related to a structure of a subject vehicle that is a subject of abnormal sound diagnosis; a second reception means that receives input of at least one of a driving condition in which an abnormal sound is generated in the subject vehicle, i.e., an abnormal sound driving condition, and an environmental condition in which the abnormal sound is generated in the subject vehicle, i.e., an abnormal sound environmental condition; an extraction means that extracts, from a sound emission map database in which a plurality of sound emission maps are stored, one or more associated sound emission maps associated with the subject vehicle, based on at least one of the input vehicle information, the abnormal sound driving condition, and the abnormal sound environmental condition, the sound emission map being a map that represents a correlation between a protruding amount in which an abnormal sound generated in a vehicle protrudes from background noise and at least one of a driving condition and an environmental condition; and a first decision means that decides at least one of a first driving condition that is a driving condition in which the protruding amount of the abnormal sound in the subject vehicle becomes large and a first environmental condition that is an environmental condition in which the protruding amount of the abnormal sound in the subject vehicle becomes large, based on the extracted associated sound emission map. The abnormal sound diagnosis device further comprises: a sound recording means that records the abnormal sound; a generation means that generates a specific sound emission map that represents a correlation between a sound pressure level of the recorded abnormal sound and at least one of a driving condition and an environmental condition, the specific sound emission map extrapolating a sound pressure level of the abnormal sound outside a range of changes in the driving condition and the environmental condition at the time of recording; and a second decision means that decides at least one of a second driving condition that is a driving condition in which the protruding amount of the abnormal sound becomes large and a second environmental condition that is an environmental condition in which the protruding amount of the abnormal sound becomes large, based on the generated specific sound emission map.

3. The abnormal sound diagnosis device according to claim 2, further comprising a means that reflects the specific sound emission map in a plurality of the sound emission maps stored in the sound emission map database.

4. The abnormal sound diagnosis device according to any one of claims 1 to 3, further comprising a road information acquisition means that acquires specific point road information that represents a road state of a specific point on a map, from a map database in which a road state of each point on a map is stored, in a case where the second reception means receives input of the abnormal sound environmental condition that represents the specific point on the map, wherein the extraction means extracts the associated sound emission map based on the acquired specific point road information.

5. The abnormal sound diagnosis device according to any one of claims 1 to 3, wherein the abnormal sound diagnosis device further comprises an abnormal sound information acquisition means that acquires associated abnormal sound information associated with the subject vehicle, from an abnormal sound database in which information related to an abnormal sound of a vehicle, i.e., abnormal sound information, is stored, ​ ​ 2. The abnormal sound diagnosis apparatus according to claim 1, wherein ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ The extraction section extracts the associated sound production map based on the acquired associated abnormal sound information.

6. The abnormal sound diagnosis device according to any one of claims 1 to 3, wherein The first driving condition includes a driving condition in which the background noise can be reduced with respect to the abnormal sound.

7. An abnormal sound diagnosis method, the abnormal sound diagnosis method comprising: a first reception step of receiving input of vehicle information related to a structure of a subject vehicle that is a subject of abnormal sound diagnosis; a second reception step of receiving input of at least one of a driving condition in which an abnormal sound is generated in the subject vehicle, that is, an abnormal sound driving condition, and an environmental condition in which the abnormal sound is generated in the subject vehicle, that is, an abnormal sound environmental condition; an extraction step of extracting, from a sound production map database in which a plurality of sound production maps are stored, one or more associated sound production maps associated with the subject vehicle, based on at least one of the input vehicle information, the abnormal sound driving condition, and the abnormal sound environmental condition, the sound production map being a map that indicates a correlation between a protruding amount in which an abnormal sound generated in a vehicle protrudes from background noise and at least one of a driving condition and an environmental condition; and a first decision step of deciding at least one of a first driving condition in which the protruding amount of the abnormal sound in the subject vehicle becomes larger and a first environmental condition in which the protruding amount of the abnormal sound in the subject vehicle becomes larger, based on the extracted associated sound production map.

8. An abnormal sound diagnosis program product that is read into an abnormal sound diagnosis device, wherein the abnormal sound diagnosis program product causes the abnormal sound diagnosis device to function as: a first reception section that receives input of vehicle information related to a structure of a subject vehicle that is a subject of abnormal sound diagnosis; a second reception section that receives input of at least one of a driving condition in which an abnormal sound is generated in the subject vehicle, that is, an abnormal sound driving condition, and an environmental condition in which the abnormal sound is generated in the subject vehicle, that is, an abnormal sound environmental condition; an extraction section that extracts, from a sound production map database in which a plurality of sound production maps are stored, one or more associated sound production maps associated with the subject vehicle, based on at least one of the input vehicle information, the abnormal sound driving condition, and the abnormal sound environmental condition, the sound production map being a map that indicates a correlation between a protruding amount in which an abnormal sound generated in a vehicle protrudes from background noise and at least one of a driving condition and an environmental condition; and a first decision section that decides at least one of a first driving condition in which the protruding amount of the abnormal sound in the subject vehicle becomes larger and a first environmental condition in which the protruding amount of the abnormal sound in the subject vehicle becomes larger, based on the extracted associated sound production map.

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