KR102513014B1 - Vehicle maintenance pit system equipped with maintenance equipment and condition monitoring function before and after vehicle inspection - Google Patents

Abstract

The present invention provides a pit system for vehicle maintenance, capable of rapidly and accurately checking abnormality of a vehicle. The pit system for vehicle maintenance includes: a floating plate supporting the vehicle entering an inspection area with multiple maintenance kits, wherein the height of the floating plate is controlled; a support plate positioned in one area of the upper surface of the floating plate and vertically moving to be independent from the floating plate by supporting the lower surface of the vehicle; a sound obtaining unit obtaining sound data based on sound generated by driving of the vehicle when the vehicle starts to drive while the support plate positions the vehicle in the air by supporting the lower surface of the vehicle; a code information generating unit generating failure code information by determining the kind of the failures occurring in the vehicle based on an analysis result by analyzing the sound data obtained by the sound obtaining unit based on an artificial intelligence algorithm stored in advance; and a maintenance kit recommending unit recommending at least one maintenance kit based on the identified maintenance information among the multiple maintenance kits to a mechanic by identifying the maintenance information corresponding to the failure code information among the multiple pieces of the maintenance information stored in a maintenance category stored in advance when the generation of the failure code information is completed. Also, the maintenance kit recommending unit enables the mechanic to maintain the vehicle by using the recommended maintenance kit. Other embodiments identified through the document are possible.

Description

Vehicle maintenance pit system equipped with maintenance equipment and condition monitoring function before and after vehicle inspection

The present invention relates to a pit system for vehicle maintenance equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection, and specifically, a vehicle entering an inspection area equipped with a plurality of maintenance kits is moved through a floating plate and a support plate to the vehicle. is placed in the air, when the car starts driving, sound data based on the sound generated by the driving of the car is acquired, and the acquired sound data is analyzed through a pre-stored artificial intelligence algorithm to generate sound generated in the car. A technology for generating fault code information by determining the type of fault that has occurred, recommending a maintenance kit based on maintenance information corresponding to the fault code information among a plurality of maintenance kits to a mechanic, and allowing the mechanic to repair the vehicle.

Cars have become an indispensable necessity in modern life. In order to maintain and manage such a car, a lot of maintenance costs are consumed, and when a breakdown occurs, additional repair costs are incurred in addition to the maintenance costs, and inconvenient problems exist because the vehicle cannot be used during repair. In order to solve these problems, the automobile industry conducts preventive maintenance of automobiles to replace consumables that need to be replaced at appropriate intervals or recommends repairing malfunctions that the driver is not aware of, thereby helping to extend the lifespan of automobiles and prevent accidents. are giving

However, recently there have been frequent cases in which the performance of a vehicle that has been brought to a company for preventive maintenance is degraded after it is shipped from the company. because it is carried out Accordingly, the automobile maintenance industry is developing various technologies to provide accurate maintenance services by converging AI technology and maintenance technology, which are growing rapidly.

As an example, Korean Registered Patent No. 10-2026300 (Method for detecting abnormal vehicle signals using an artificial intelligence system) receives time-series electrical signals from one or more parts of the vehicle and converts the received electrical signals through an artificial intelligence algorithm. A technology for analyzing and detecting an abnormal signal is disclosed.

However, in the prior art described above, only a technology for determining whether or not there is an abnormality in a part by simply detecting an abnormal signal through an artificial intelligence algorithm has been disclosed. and when the car starts driving in a state where the car is placed in the air through the support plate, sound data based on the sound generated by the driving of the car is acquired, and the acquired sound data is processed through a pre-stored artificial intelligence algorithm. analysis, determine the type of failure occurred in the vehicle, generate failure code information, recommend a maintenance kit based on the maintenance information corresponding to the failure code information among a plurality of repair kits to the mechanic, and allow the mechanic to repair the vehicle. Since no technology has been disclosed, the need for a technology capable of solving this problem is emerging.

Accordingly, the present invention, when the vehicle enters the inspection area equipped with a plurality of maintenance kits and the vehicle is placed in the air through the floating plate and the support plate, when the vehicle starts driving, Acquires sound data based on sound, analyzes the acquired sound data through pre-stored artificial intelligence algorithms, determines the type of fault that has occurred in the vehicle, generates fault code information, and generates fault code information among a plurality of maintenance kits. By recommending a maintenance kit based on the corresponding maintenance information to the mechanic and having the mechanic repair the car, the car's abnormality can be quickly and accurately checked through sound data, and at the same time, the mechanic can easily repair the type of failure that occurred. Its purpose is to provide mechanics with maintenance kits and repair guides where possible.

a floating plate whose height is adjusted while supporting a vehicle entering an inspection area equipped with a plurality of maintenance kits according to an embodiment of the present invention; a support plate positioned on a region of an upper surface of the floating plate and capable of moving up and down independently of the floating plate by supporting a lower surface of the vehicle; A sound acquisition unit for acquiring sound data based on a sound generated by the driving of the vehicle when the vehicle starts to drive in a state where the support plate supports the lower surface of the vehicle and places the vehicle in the air. ; a code information generation unit that analyzes the sound data obtained through the sound acquisition unit based on a pre-stored artificial intelligence algorithm, determines the type of failure that has occurred in the vehicle through the analysis result, and generates failure code information; and when the generation of the fault code information is completed, maintenance information corresponding to the fault code information is identified among a plurality of maintenance information stored in a pre-stored maintenance category, and at least one of the plurality of maintenance kits based on the identified maintenance information is identified. and a maintenance kit recommending unit for recommending a maintenance kit of the vehicle to a mechanic and having the mechanic repair the vehicle through the recommended maintenance kit.

In the inspection area, it is preferable that each of the plurality of maintenance kits is disposed in the vicinity of the area where the floating plate is located, and a lighting device is provided in each designated area.

The sound acquisition unit receives sound generated from at least one voice generating target included in the car through a sound input unit located in the inspection area as the car starts to drive, and receives sound data based on the received sound. is obtained, an inspection process for determining the type of failure of the car is started, and sound data obtained before the car is serviced is first type sound data and sound data acquired after the car is serviced is provided. Divided into two types of sound data, the voice generation target is at least one part constituting the vehicle, and it is possible to generate sound by power generated according to driving of the vehicle.

When the inspection process starts as the sound acquisition unit acquires the first type sound data, the code information generation unit starts inspection and analysis of the first type sound data through the pre-stored artificial intelligence algorithm. wealth; a first waveform comparator which compares a waveform of the first type sound data with a waveform of each of a plurality of pre-stored comparison sound data when the analysis of the first type sound data starts; When there exists comparison sound data whose similarity rate with the waveform of the first type sound data exceeds the specified range due to the performance of the function of the first waveform comparator, the similarity rate exceeds the specified range through comparison sound data. a fault code generating unit that checks the type of fault that has occurred in the vehicle and generates fault code information based on the type of the identified fault; and when there exists at least one comparison sound data whose similarity rate with the waveform of the first type is within a specified range due to the performance of the function of the first waveform comparator, at least one whose similarity rate is within a specified range. It is possible to include; a candidate code generation unit that identifies a candidate group for the type of failure occurring in the vehicle through one comparison sound data and generates candidate code information based on the identified candidate group.

The plurality of comparison sound data is sound data based on the sound generated by the voice generating target according to the type of breakdown of the vehicle, and is compared with sound data based on the sound generated by the voice generating target when the vehicle is idling. an idle category containing a plurality of comparison sound data to be; and a rotation category including a plurality of comparison sound data to be compared with sound data based on the sound generated by the voice generation target when the tires of the vehicle rotate.

When the generation of the fault code information is completed, the kit recommendation unit identifies maintenance information corresponding to the fault code information among the plurality of maintenance information, and selects a maintenance kit based on the identified maintenance information among the plurality of maintenance kits. a maintenance request unit requesting the mechanic to repair the car through a maintenance kit disposed in the designated area by driving a lighting device in the designated area; and when the generation of the candidate code information is completed, at least one maintenance information corresponding to the candidate code information among the plurality of maintenance information is identified, and maintenance based on the identified at least one maintenance information among the plurality of maintenance kits is performed. Driving the lighting devices in the designated area where the kit is placed, driving the lighting devices in the designated area in order so as to correspond to the order of comparison sound data with a high similarity included in the designated range to recommend the maintenance order of the car to the mechanic It is possible to include; a maintenance sequence recommendation unit to do.

The sound acquisition unit obtains a sound generated by driving the maintained vehicle through the sound input unit in a state in which the mechanic has completed the maintenance of the vehicle by performing the function of the kit recommendation unit, and In the case of obtaining type sound data, it is possible to start a maintenance completion check process for checking whether or not there is an abnormality in the serviced vehicle.

The code information generation unit may include: a maintenance completion analysis start unit that starts analyzing the second type sound data through the pre-stored artificial intelligence algorithm when the maintenance completion inspection process starts; When the analysis of the second type sound data starts, normal sound data corresponding to a type of failure based on at least one of the failure code information and the candidate code information is identified among a plurality of pre-stored normal sound data, a second waveform comparator which compares the waveform of the normal sound data with the waveform of the second type sound data; When the similarity rate of the waveform of the second type sound data to the waveform of the normal sound data exceeds a specified reference value due to the performance of the function of the second waveform comparator, the maintenance of the vehicle is performed through an output unit located in the inspection area. Check completion confirmation unit for outputting a message indicating that the was completed normally; and when the similarity rate of the waveform of the second type sound data to the waveform of the normal sound data is less than a specified reference value due to the performance of the function of the second waveform comparator, the similarity rate among the waveforms of the second type sound data is specified. It is possible to further include; a recheck code generation unit that identifies a portion determined to be less than the reference value, checks the type of failure corresponding to the identified portion through the pre-stored artificial intelligence algorithm, and generates recheck code information.

When the generation of the recheck code information is completed, the kit recommendation unit identifies maintenance information corresponding to the generated recheck code information among the plurality of pieces of maintenance information, and arranges a maintenance kit based on the identified maintenance information. By driving a lighting device in a designated area, it is possible to request the mechanic to recondition the car.

The pre-stored artificial intelligence algorithm is an algorithm for analyzing the sound data to identify the type of failure that has occurred in the vehicle, and performs machine learning on the sound data received through the sound input means to obtain the pre-stored plurality of It is possible to update a comparison relationship between the waveforms of two comparison sound data or the waveforms of a plurality of pre-stored normal sound data and the waveforms of the sound data.

The vehicle maintenance pit system equipped with the condition monitoring function and maintenance equipment before and after the vehicle inspection according to the present invention analyzes the sound data based on the sound generated in the vehicle through a pre-stored artificial intelligence algorithm to identify the type of failure that occurred in the vehicle, It is possible to quickly and accurately check whether there is an abnormality in the vehicle.

In addition, it recommends a plurality of maintenance kits placed in each designated area of the inspection area based on the type of confirmed failure and at the same time provides guide information on maintenance and requests maintenance, reducing the work time required for maintenance. At the same time, it is possible to provide a high-quality maintenance service to the car owner.

1 is a block diagram of a pit system for vehicle maintenance equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.
2 is a block diagram of a sound acquisition unit included in a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.
3 is a block diagram of a code information generation unit included in a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.
4 is a block diagram of a maintenance kit recommendation unit included in a vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.
5 is another block diagram of a code information generation unit included in a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.
6 is a diagram for explaining an example of an internal configuration of a computing device according to an embodiment of the present invention.

In the following, various embodiments and/or aspects are disclosed with reference now to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth in order to facilitate a general understanding of one or more aspects. However, it will also be appreciated by those skilled in the art that such aspect(s) may be practiced without these specific details. The following description and accompanying drawings describe in detail certain illustrative aspects of one or more aspects. However, these aspects are exemplary and some of the various methods in principle of the various aspects may be used, and the described descriptions are intended to include all such aspects and their equivalents.

References to “embodiment,” “example,” “aspect,” “example,” etc., used in this specification should not be construed as indicating that any aspect or design described is preferable to or advantageous over other aspects or designs. .

Also, the terms "comprises" and/or "comprising" mean that the feature and/or element is present, but excludes the presence or addition of one or more other features, elements and/or groups thereof. It should be understood that it does not.

In addition, terms including ordinal numbers such as first and second may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element, without departing from the scope of the present invention. The terms and/or include any combination of a plurality of related recited items or any of a plurality of related recited items.

In addition, in the embodiments of the present invention, unless otherwise defined, all terms used herein, including technical or scientific terms, are those commonly understood by those of ordinary skill in the art to which the present invention belongs. have the same meaning. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in the embodiments of the present invention, an ideal or excessively formal meaning not be interpreted as

1 is a block diagram of a pit system for vehicle maintenance equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.

Referring to FIG. 1, a vehicle maintenance pit system 100 (hereinafter referred to as a maintenance pit system) equipped with a condition monitoring function before and after vehicle inspection and maintenance equipment is equipped with a sound acquisition unit 101 and a code information generation unit ( 103), a maintenance kit recommendation unit 105, a floating plate 111, and a support plate 113.

According to one embodiment, the floating plate 111 supports a vehicle entering the inspection area 110 equipped with a plurality of maintenance kits 115 and can be adjusted in height. More precisely, the floating plate 111 is a flat (plate) structure in which a vehicle to be tested is raised and its height is adjusted, and may include, for example, a configuration that distributes and supports the weight of the vehicle according to the weight of the vehicle. there is. A vehicle referred to in the present invention may be understood to mean a large vehicle, for example, a truck, a van, etc. other than all vehicles classified as passenger cars (including vans with 12 seats or less), and accordingly, the support plate 113 described later ) may be configured to receive the load, and a configuration may be included in the floating plate 111 to distribute and support some of the load. That is, the floating plate 111 may be configured to cover a portion of the lower surface of the vehicle except for the wheel, or may be configured to have a frame structure having only an external shape.

According to one embodiment, the plurality of maintenance kits 115 may include tools and equipment required for vehicle maintenance disposed in each designated area of the inspection area 110 . The inspection area 110 may be an area in which a plurality of maintenance kits 115 are disposed in each designated area near the area where the floating plate 111 is located, and a lighting device is provided in each designated area.

According to another embodiment, in the inspection area 110, the plurality of maintenance kits 115 are located on a frame constituting the floating plate 111 and the support plate 113 as well as the designated area. Alternatively, by being installed, the convenience of a mechanic who maintains a vehicle within the inspection area 110 may be improved. That is, the inspection area 110 may include a maintenance pit for a vehicle in which a plurality of maintenance kits 115 are configured.

According to an embodiment, the support plate 113 may be located on one area of the upper surface of the floating plate 111 to support the lower surface of the vehicle and move up and down independently of the floating plate 113. . That is, the support plate 113 may be an elevating means formed on one area of the upper surface of the floating plate 111, or at least one may be formed on one area of the upper surface.

According to an embodiment, the sound acquisition unit 101 is configured to support the lower surface of the car by supporting the lower surface of the car and place the car in the air when the car starts driving. It is possible to obtain sound data based on the sound generated by the driving of the .

According to one embodiment, the sound acquisition unit 101 is a sound input unit located in the inspection area 110 (eg : A sound generated by the vehicle may be received through a microphone), and the sound data may be obtained based on the received sound.

According to an embodiment, the code information generation unit 103 analyzes the sound data obtained through the sound acquisition unit 101 based on a pre-stored artificial intelligence algorithm, and the breakdown occurred in the vehicle through the analysis result. Fault code information can be generated by determining the type of

According to an embodiment, the fault code information is information for identifying the type of fault that has occurred in the vehicle, and may be generated according to a preset condition. For example, when the powertrain is out of order, the code information generation unit 103 starts with P and may generate code information in which a preset number is combined according to a detailed failure part of the powertrain.

According to an embodiment, the code information generation unit 103 may analyze the waveform of the sound data based on the pre-stored artificial intelligence algorithm. More accurately, the code information generation unit may identify the type of failure occurring in the vehicle by comparing the waveform of the sound data with the waveform of each of a plurality of pre-stored comparison sound data.

According to an embodiment, when the generation of the fault code information is completed, the maintenance kit recommendation unit 105 may identify maintenance information corresponding to the fault code information from among a plurality of pieces of maintenance information stored in a pre-stored maintenance category. . When the maintenance kit recommendation unit 105 completes identification of the maintenance information, it recommends at least one maintenance kit based on the identified maintenance information among the plurality of maintenance kits to the mechanic, so that the mechanic can select the recommended maintenance kit. You can have your car serviced.

According to one embodiment, the pre-stored maintenance category may be a database in which a plurality of maintenance information is stored. At this time, each of the plurality of maintenance information may include guide information for guiding a mechanic to repair the type of failure occurring in the vehicle, and a code corresponding to a code number included in the failure code information. may contain a number.

Accordingly, the maintenance kit recommendation unit 105 can identify maintenance information corresponding to the fault code information through the code number, and recommend at least one maintenance kit based on the maintenance information to a mechanic. At this time, each of the plurality of maintenance kits is disposed in each designated area of the inspection area 110, and a lighting device may be formed in the designated area.

According to an embodiment, when recommending at least one maintenance kit based on the maintenance information to a mechanic, the maintenance kit recommendation unit 105 may identify a lighting device corresponding to a code number included in the maintenance information. The maintenance kit recommendation unit 105 may drive a lighting device in a designated area where a maintenance kit corresponding to tool information (eg, tool and facility information used to repair a malfunction) included in the maintenance information is disposed. . That is, the maintenance kit recommendation unit 105 may identify a code number assigned to a lighting device in a designated area in order to recommend a maintenance kit disposed in the designated area to a mechanic through the tool information.

According to an exemplary embodiment, the maintenance kit recommending unit 105 drives the lighting device when the identification of the lighting device is completed, so that the maintenance kit for repairing the type of failure occurring in the vehicle is located. area can be identified. In addition, when recommending the maintenance kit to a mechanic, the maintenance kit recommendation unit 105 may also output guide information for repairing the type of failure occurring in the vehicle through an output means located in the inspection area 110. there is.

2 is a block diagram of a sound acquisition unit included in a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.

Referring to FIG. 2, a vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection (e.g., a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection in FIG. 1 (100 )) (hereinafter referred to as a pit system for maintenance) may include a sound acquisition unit 201 (eg, the sound acquisition unit 101 of FIG. 1 ).

According to one embodiment, the sound acquisition unit 201 is in a state in which the support plate (eg, the support plate 113 of FIG. 1 ) supports the lower surface of the vehicle to position the vehicle 203 in the air, the vehicle ( When the vehicle 203 starts driving, sound data 205 based on a sound generated by driving the vehicle 203 may be acquired.

More specifically, as the vehicle 203 starts to drive, the sound acquisition unit 201 uses the sound input means 201a located in an inspection area (eg, the inspection area 110 of FIG. 1 ) to detect the vehicle 203. ), sound data 205 based on the received sound may be obtained. At this time, the sound acquisition unit 201 may start an inspection process upon obtaining the sound data.

According to an embodiment, the voice generating target is at least one component constituting the vehicle 203 and may be a component that generates sound by power generated according to driving of the vehicle 203 . More precisely, when the power energy is generated as the vehicle 203 is driven (eg, the engine is running), the sound generated by the vibration, the sound generated when each part is fastened, and the power Sound can be produced from functions performed through energy. Accordingly, the sound obtaining unit 201 may obtain the sound data by receiving sound (eg, sound) generated through the sound input means 201a.

According to an embodiment, the sound data 205 is data generated based on the sound generated by the voice generating target, and may be divided into first type sound data 205a and second type sound data 205b. there is.

In relation to the above, the first type sound data 205a may refer to sound data obtained by the sound acquisition unit 201 before the vehicle 203 is maintained through the sound input means 201a. there is. The second type sound data 205b may refer to sound data obtained by the sound acquisition unit 201 after the vehicle 203 is maintained through the sound input means 201a.

That is, the first type data 205a may be data used to identify the type of failure that occurred in the vehicle prior to maintenance. In addition, the second type data 205b may be data used to inspect the vehicle 203 after maintenance to determine whether or not there is an abnormality in the vehicle 203 after maintenance. Accordingly, the pit system for maintenance according to the present invention can monitor the state before and after inspection of the vehicle 203 through sound data based on the sound generated by driving the vehicle 203 .

3 is a block diagram of a code information generation unit included in a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.

Referring to FIG. 3, a vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection (e.g., a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection of FIG. 1 (100) )) (hereinafter referred to as a pit system for maintenance) may include a code information generating unit 300 (eg, the code information generating unit 103 of FIG. 1 ).

According to an embodiment, the code information generation unit 301 analyzes sound data obtained through a sound acquisition unit (eg, the sound acquisition unit 101 of FIG. 1) based on a pre-stored artificial intelligence algorithm, and analyzes the sound data. Based on the result, it is possible to determine the type of failure in the vehicle and generate failure code information.

According to an embodiment, the code information generation unit 301 is a detailed configuration for performing the above-described functions, and includes a check analysis start unit 301, a first waveform comparison unit 303, and a fault code generation unit 305. and a candidate code generator 307 .

According to an embodiment, when the inspection process starts as the sound acquisition unit acquires the first type sound data 301a, the inspection analysis start unit 301 uses a pre-stored artificial intelligence algorithm 309. Analysis of the first type sound data 301a may be started.

According to an embodiment, when the inspection and analysis start unit 301 acquires the first type sound data 301a based on the sound generated by the vehicle before maintenance through the sound acquisition unit, the pre-stored artificial intelligence algorithm ( By analyzing the first type sound data 301a through 309), it is possible to start an inspection process to identify the type of failure that occurred in the vehicle before maintenance.

According to an embodiment, when the analysis of the first type sound data 301a starts, the first waveform comparator 303 compares the waveform of the first type sound data 301a with a plurality of previously stored comparison sound data. Each waveform can be compared.

According to an embodiment, the first waveform comparator 303 compares the waveform of the first type sound data 301a with the waveform of each of a plurality of pre-stored comparison sound data through the pre-stored artificial intelligence algorithm 309. can be compared At this time, the first waveform comparator 303 compares the waveform of the first type sound data 301a with the waveform of a plurality of comparison sound data, so as to compare the frequency 305a of the first type sound data 301a. ) can be checked.

In relation to the above, the first waveform comparator 303 determines the frequency 305b based on each of the plurality of comparison sound data when the confirmation of the frequency 305a based on the first type sound data 301a is completed. You can check.

At this time, the first waveform comparator 303 compares the frequency 305a based on the first type sound data 301a with the frequency 305b based on each of the plurality of comparison sound data, each frequency can be divided into a plurality of sections. In relation to the above, when comparing the frequency 305a based on the first type sound data 301a and the frequency 305b based on each of the plurality of comparison sound data, the first waveform comparator 303 determines the same interval. standards can be compared. For example, the first period of the frequency 305a based on the first type sound data 301a and the first period of the frequency 305b based on each of the plurality of comparison sound data may correspond to each other and be compared. .

According to an embodiment, the first waveform comparator 303 is configured to generate a first section of the frequency 305a based on the first type sound data 301a and a second frequency 305b based on each of a plurality of comparison sound data. In order to compare 1 section correspondingly to each other, the lowest similarity rate with the frequency 305a based on the first type sound data 301a among the frequencies 305b based on each of the plurality of comparison sound data is the lowest value (eg, 50%) ) may be identified as frequencies to be compared with the frequency 305a based on the first type sound data 301a. That is, there may be a plurality of comparison sound data having frequencies to be compared with the frequency 305a based on the first type sound data 301a.

According to an embodiment, the first waveform comparator 303 completes identifying the frequency based on the comparison sound data to be compared with the frequency 305a based on the first type sound data 301a, the first waveform. The comparator 303 lists the frequencies included in the first interval of the frequency 305a based on the first type sound data 301a in a 3D space and places the first frequency range based on the identified comparison sound data. The similarity rate can be measured by listing the included frequencies in a three-dimensional space.

According to an embodiment, the fault code generation unit 305 compares sound data whose similarity rate with the waveform of the first type sound data exceeds a specified range due to the performance of the function of the first waveform comparison unit 303. When there exists, the type of failure occurring in the vehicle may be identified through comparison sound data having the similarity rate exceeding a specified range, and fault code information based on the identified type of failure may be generated.

In more detail, the fault code generation unit 305 has a frequency 305a based on the first type sound data 301a and a frequency 305b based on comparison sound data whose similarity exceeds a specified range, The type of failure occurring in the vehicle may be confirmed through comparison sound data having a similarity rate exceeding a designated range. The designated range (eg, 80% to 90%) is a reference value for a similarity rate for identifying the type of vehicle failure through sound data, and the failure code generator 305 is configured to generate the first type sound data 301a. ) If there is comparison sound data whose similarity rate with the frequency 305a based on the specified range exceeds a specified range, the type of vehicle failure based on the comparison sound data can be identified through the pre-stored artificial intelligence algorithm 309. .

For example, when the fault code generation unit 305 has a frequency 305a based on the first type sound data 301a and a frequency 305b based on comparison sound data whose similarity exceeds a specified range, there exist , It can be confirmed that the type of vehicle failure based on the comparison sound data is “engine oil leakage” through the pre-stored artificial intelligence algorithm 309. That is, the comparison sound data whose similarity rate with the frequency 305a based on the first type sound data 301a exceeds the designated range is the sound generated by the voice generation target when “engine oil leakage” occurs while driving the vehicle. It may be data corresponding to .

Accordingly, the fault code generating unit 305 may generate fault code information based on the "engine oil leakage" through a pre-stored artificial intelligence algorithm 309 . The fault code information may be information for identifying the type of fault occurring in the vehicle and may include a code number corresponding to the type of fault.

According to one embodiment, the candidate code generation unit 307 is configured such that the similarity rate with the waveform of the first type sound data 301a is within a specified range due to the function performance of the first waveform comparison unit 303. When there is at least one comparison sound data, a candidate group for the type of failure occurring in the vehicle may be identified through the at least one comparison sound data having the similarity rate within a designated range. Accordingly, the candidate code generation unit 307 may generate candidate code information based on the confirmed candidate group.

According to an embodiment, the candidate code generation unit 307 may include a frequency 305a based on the first type sound data 301a and a frequency 305b based on at least one comparison sound data whose similarity rate is within a designated range. ) exists, it is possible to identify a candidate for the type of failure occurring in the vehicle through at least one comparison sound data whose similarity rate is within a designated range.

For example, the candidate code generation unit 307 may, when there exists at least one comparison sound data whose similarity rate with the frequency 305a based on the first type sound data 301a is within a designated range, the pre-stored sound data 301a. The artificial intelligence algorithm 309 checks the type of vehicle failure based on the at least one comparison sound data, and classifies “engine oil leak”, “transmission oil leak”, and “fly wheel wear” as failures occurring in the vehicle. It can be identified as a candidate group for the type. That is, at least one comparison sound data included in a range in which the similarity rate with the frequency 305a based on the first type sound data 301a is specified is “engine oil leakage”, “transmission oil leakage” and “fly It may be data corresponding to the sound generated by the voice generation target when "wheel wear" occurs.

Accordingly, the candidate code generating unit 305 includes candidate code information including code information based on the “engine oil leakage”, “transmission oil leakage” and “fly wheel wear” through the pre-stored artificial intelligence algorithm 309. can create That is, the candidate code information may be information for identifying a candidate group for the type of failure occurring in the vehicle, and may include a code number corresponding to the candidate group for the type of failure.

According to an embodiment, the plurality of comparison sound data is sound data based on the sound generated by the voice generating target according to the type of breakdown of the vehicle, and the sound generated by the voice generating target when the vehicle is idling. An idling category containing a plurality of comparison sound data for comparison with the based sound data and a plurality of comparison sound data for comparison with sound data based on the sound generated from the voice generation target when the vehicle tire rotates. Can be included in rotation category.

In a car, even if the same part has a failure, the sound generated during idling and the sound generated as the tire rotates may be different. This is because the sound varies according to the number of parts operated during tire rotation greater than the number of parts operated during idling.

Therefore, since the pit system for maintenance of the present invention stores comparison sound data during idling and comparison sound data during tire rotation according to the same type of failure in the idling category and the rotation category, the pre-stored artificial intelligence algorithm 309 It is possible to accurately identify the type of vehicle failure by limiting and identifying comparison sound data comparable to the first type sound data among a plurality of comparison sound data within a narrow range.

4 is a block diagram of a maintenance kit recommendation unit included in a vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.

Referring to FIG. 4, a vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection (e.g., a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection in FIG. 1 (100) )) (hereinafter, referred to as a maintenance pit system) may include a maintenance kit recommendation unit 400 (eg, the maintenance kit recommendation unit 105 of FIG. 1 ).

According to an embodiment, when the generation of the fault code information 401a is completed, the maintenance kit recommendation unit 400, among a plurality of maintenance information stored in a pre-stored maintenance category, the maintenance information corresponding to the fault code information 401a. is identified, recommending at least one maintenance kit based on the identified maintenance information among a plurality of maintenance kits 405 to the mechanic, and having the mechanic repair the car through the recommended maintenance kit.

According to an embodiment, the maintenance kit recommendation unit 400 may include a maintenance request unit 401 and a maintenance sequence recommendation unit 403 as detailed components for performing the above-described functions.

According to an embodiment, the maintenance request unit 401, when generation of the failure code information by the failure code generation unit (eg, the failure code generation unit 303 of FIG. 3) is completed, the failure among a plurality of maintenance information. By identifying maintenance information corresponding to code information and driving a lighting device in a designated area in which a maintenance kit based on the identified maintenance information is disposed among the plurality of maintenance kits, through a maintenance kit disposed in an area designated for the mechanic. You can request that your car be serviced.

According to an embodiment, each of the plurality of pieces of maintenance information is information corresponding to a type of vehicle breakdown and may be guide information for servicing the type of vehicle breakdown. Accordingly, it is natural that the guide information includes information on tools and facilities used to repair vehicle breakdowns, and includes repair guide information for servicing the types of vehicle breakdowns through the tools and facilities. It would be natural to do that.

For example, the maintenance request unit 401 may check the generated fault code information 401a and check a code number included in the fault code information for identifying a fault of the vehicle. The maintenance request unit 401 can check the code number and confirm that the type of failure occurred in the vehicle is “engine oil leakage”. When the confirmation of the fault code information 401a is completed, the maintenance request unit 401 may identify maintenance information including a code number corresponding to a code number of “engine oil leakage” among a plurality of pieces of maintenance information. The maintenance information including the code number corresponding to the code number of the “engine oil leak” is guide information for repairing the “engine oil leak” failure of the vehicle, and is a tool used to repair the “engine oil leak” failure. and equipment information and repair guide information to repair the failure of “engine oil leakage”.

Accordingly, the maintenance request unit 401 drives the lighting device including the code number corresponding to the code number of the “leakage of engine oil” and repairs the maintenance kits 405a and 405b disposed in the designated area where the lighting device is installed. , 405e) can be recommended to a mechanic to repair an “engine oil leak” fault that has occurred in a car.

According to an embodiment, the maintenance sequence recommendation unit 403, when generation of the candidate code information 403a by the candidate code generator (eg, the candidate code generator 305 of FIG. 3) is completed, the plurality of Among the maintenance information, at least one maintenance information corresponding to the candidate code information 403a is identified to drive the lighting device in the designated area where the maintenance kit based on the identified at least one maintenance information among the plurality of maintenance kits is disposed. However, it is possible to recommend the maintenance order of the car to the mechanic by sequentially driving the lighting devices in the designated area so as to correspond to the order of comparison sound data included in the designated range and having a high similarity rate.

For example, the maintenance sequence recommendation unit 403 may check the candidate code information 403a and check code numbers included in the candidate code information 403a for identifying a vehicle failure. At this time, the code numbers included in the candidate code information 403a may be information for identifying a candidate group for the type of failure occurring in the vehicle. The maintenance order recommending unit 403 checks the code numbers included in the candidate code information 403a, and identifies candidates for the types of failures occurring in the vehicle as “engine oil leakage”, “brake oil leakage” and “brake oil leakage”. Flywheel wear” can be confirmed.

In relation to the above, the maintenance sequence recommendation unit 403, when it is confirmed that the candidate group for the type of failure occurring in the vehicle is “engine oil leakage”, “brake oil leakage”, and “fly wheel wear” is completed, the designated Comparative sound data based on each of “engine oil leak”, “brake oil leak” and “fly wheel wear” in order to sequentially drive the lighting devices in the designated area to correspond to the comparison sound data sequence with a high similarity included in the range By checking the similarity rate within the specified range of sound data for , comparative sound data based on “fly wheel wear” with a similar rate of 89%, and comparative sound data based on “engine oil leakage” with a similar rate of 82% and comparative sound data based on “brake oil leakage” having a similarity rate of 80%. In this case, a high similarity rate may mean that measurement accuracy for the type of failure occurring in the vehicle is high.

Accordingly, the maintenance sequence recommendation unit 403 sets the lighting devices in the designated area in order (405b, 405f, 405a in order) to correspond to the order of “fly wheel wear,” “engine oil leak,” and “brake oil leak.” ), it is possible to increase the efficiency of work by recommending that the mechanic preferentially repair the type of failure that occurred in the vehicle with high measurement accuracy.

5 is another block diagram of a code information generation unit included in a vehicle maintenance pit system equipped with a state monitoring function and maintenance equipment before and after vehicle inspection according to an embodiment of the present invention.

Referring to FIG. 5, a pit system for vehicle maintenance equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection (e.g., a pit system for vehicle maintenance equipped with a state monitoring function and maintenance equipment before and after vehicle inspection in FIG. 1 (100) )) (hereinafter referred to as a pit system for maintenance) may include a code information generating unit 500 (eg, the code information generating unit 103 of FIG. 1 ).

According to an embodiment, the sound acquisition unit (eg, the sound acquisition unit 101 of FIG. 1 ) performs the function of the kit recommendation unit (eg, the kit recommendation unit 105 of FIG. 1 ) so that the mechanic repairs the car. In the finished state, when the second type sound data 501a is acquired by acquiring the sound generated by the driving of the maintained vehicle through the sound input means, the maintenance completion check is performed to check whether or not there is an abnormality in the maintained vehicle. process can be started.

According to an embodiment, the code information generating unit 500 may start analyzing the second type sound data 501a through a pre-stored artificial intelligence algorithm 509 when a maintenance completion inspection process starts. That is, the code information generation unit 500 can determine whether there is an abnormality in the maintained car by analyzing the second type sound data 501a through the pre-stored artificial intelligence algorithm 509.

According to an embodiment, when the analysis of the second type sound data 501a starts, the second waveform comparator 503 performs at least one of the fault code information and the candidate code information among a plurality of pre-stored normal sound data. It is possible to identify normal sound data corresponding to the type of failure based on . When the identification of the normal sound data is completed, the second waveform comparator 503 may compare the identified waveform of the normal sound data with the waveform of the second type sound data 501a.

In more detail, the second waveform comparator 503 may check the type of failure occurring in the vehicle before maintenance through at least one of the obtained failure code information and the candidate code information during the inspection process. The second waveform comparator 503, when the confirmation of the type of breakdown in the vehicle before maintenance is completed, normal sound based on the normal sound generated from the voice generating target as the type of breakdown in the vehicle is repaired by the mechanic. Data may be identified through a code number included in the fault code information and the candidate code information. That is, the plurality of pre-stored normal sound data is data based on sound generated when there is no abnormality in the vehicle from a voice generating target, and may be pre-stored reference data for comparison with the second type sound data 501a.

According to an embodiment, the second waveform comparator 503 may compare the waveform of the second type sound data 501a and the identified normal sound data through the pre-stored artificial intelligence algorithm 509. there is. At this time, the second waveform comparator 503 checks the frequency of the second type sound data 501a in order to compare the waveform of the second type sound data 501a with the waveforms of a plurality of comparison sound data. can

In relation to the above, the second waveform comparator 503 may check the frequency based on the identified normal sound data when the checking of the frequency based on the second type sound data 501a is completed.

At this time, the second waveform comparator 503 divides each frequency into a plurality of sections in order to compare the frequency based on the second type sound data 501a with the frequency based on each of the identified normal sound data. can In relation to the above, the second waveform comparator 503 may compare the frequency based on the second type sound data and the frequency based on the identified normal sound data based on the same interval. For example, the first interval of frequency based on the second type sound data 501a and the first interval of frequency based on the identified normal sound data may correspond to each other and be compared.

According to an embodiment, the similarity rate of the waveform of the second type sound data 501a with respect to the waveform of the normal sound data is designated due to the performance of the function of the second waveform comparator 503 in the check completion confirmation unit 505. When the reference value is exceeded, a message informing that maintenance of the vehicle has been normally completed may be output through an output unit 505a (eg, a speaker, a display, etc.) located in the inspection area.

In more detail, the inspection completion confirming unit 505 lists the frequencies included in the first section of the frequency based on the second type sound data 501a in a 3D space, and controls the frequencies based on the identified normal sound data. The similarity rate can be measured by listing the frequencies included in one section in a 3-dimensional space. At this time, if the similarity rate between the frequency based on the second type sound data 501a and the frequency based on the identified normal sound data exceeds a specified reference value (eg, 95%), it means that there is no abnormality in the repaired vehicle. Upon confirmation, a message indicating that the maintenance of the vehicle has been normally completed may be output through the output means 505a located in the inspection area.

According to an embodiment, the recheck code generation unit 507 determines the similarity rate of the waveform of the second type sound data with respect to the waveform of the normal sound data due to the performance of the function of the second waveform comparison unit 503. If it is less than the reference value, a portion of the waveforms of the second type sound data for which the similarity rate is determined to be less than the specified reference value is identified, and the type of failure corresponding to the identified portion is checked through the pre-stored artificial intelligence algorithm to check the recheck code. information can be generated.

More specifically, the recheck code generation unit 507 lists the frequencies included in the first section of the frequency based on the second type sound data 501a in a 3D space, and lists the frequencies based on the identified normal sound data. The similarity rate can be measured by listing the frequencies included in the first section in a 3D space. At this time, if the similarity rate between the frequency based on the second type sound data 501a and the frequency based on the identified normal sound data is less than a specified reference value (eg, 95%), it is determined that there is an abnormality in the repaired vehicle. You can check. At this time, the recheck code generation unit 507 analyzes the frequency based on the second type sound data 501a through the pre-stored artificial intelligence algorithm 509, and analyzes the frequency based on the normal sound data whose frequency is identified. It is possible to identify a section in which the similarity rate with does not satisfy a specified reference value.

According to an embodiment, the recheck code generation unit 507 analyzes the frequency included in the identified section through the pre-stored artificial intelligence algorithm 509, and the failure corresponding to the abnormality existing in the repaired vehicle. You can generate recheck fault code information by checking the type of The recheck fault code information is the same as the fault code information, but may be generated when there is an abnormality in the vehicle maintained in the maintenance completion inspection process.

In relation to the above, the recheck code generator 507 analyzes the frequency included in the identified section through the pre-stored artificial intelligence algorithm 509 to determine the type of failure occurring in the repaired vehicle before repair. It is possible to check whether the type of failure is identical to that of the fault, and whether the type of fault occurring in the repaired vehicle is a newly occurring fault type.

According to one embodiment, the pre-stored artificial intelligence algorithm 509 is an algorithm for analyzing sound data (first type sound data and second type sound data) to identify the type of failure that has occurred in the vehicle, and is a sound input unit. By performing machine learning on the sound data received through, the waveform of a plurality of pre-stored comparison sound data (sound data compared with the waveform of the first type sound data) or the waveform of a plurality of pre-stored normal sound data (the second type sound data) A comparison relationship between the type sound data compared with the waveform of the sound data) and the waveform of the sound data may be updated.

That is, the pre-stored artificial intelligence algorithm 509 analyzes and learns the sound data obtained through the sound input unit to determine a comparison relationship between a plurality of pre-stored waveforms of comparison sound data or a plurality of pre-stored normal sound data waveforms. can be updated

According to an embodiment, the pre-stored artificial intelligence algorithm 509 may include at least one of a supervised learning algorithm, a semi-supervised learning algorithm, and an unsupervised unsupervised learning algorithm, but is not limited thereto. The pre-stored artificial intelligence algorithm 509 correlates sound data with pre-stored comparison sound data (or pre-stored normal sound data) in order to confirm the type of failure (or abnormality) occurring in the vehicle through the sound data. It can be an algorithm that analyzes and learns relationships.

In addition, the pre-stored artificial intelligence algorithm 509 may include an artificial neural network model (ANN model), a convolution neural network model (CNN model), and a recurrent neural network model (RNN model). can include

According to an embodiment, when the generation of the recheck code information is completed, the kit recommendation unit identifies maintenance information corresponding to the generated recheck code information among a plurality of pieces of maintenance information, and a maintenance kit based on the identified maintenance information is provided. It is possible to request the mechanic to recondition the car by driving the lighting device in the designated area.

6 is a diagram for explaining an example of an internal configuration of a computing device according to an embodiment of the present invention.

6 illustrates an example of an internal configuration of a computing device according to an embodiment of the present invention, and in the following description, descriptions of unnecessary embodiments overlapping with those of FIGS. 1 to 5 will be omitted. do it with

As shown in FIG. 6, a computing device 10000 includes at least one processor 11100, a memory 11200, a peripheral interface 11300, an input/output subsystem ( It may include at least an I/O subsystem (11400), a power circuit (11500), and a communication circuit (11600). In this case, the computing device 10000 may correspond to a user terminal connected to the tactile interface device (A) or the aforementioned computing device (B).

The memory 11200 may include, for example, high-speed random access memory, magnetic disk, SRAM, DRAM, ROM, flash memory, or non-volatile memory. there is. The memory 11200 may include a software module, a command set, or other various data necessary for the operation of the computing device 10000.

In this case, access to the memory 11200 from other components, such as the processor 11100 or the peripheral device interface 11300, may be controlled by the processor 11100.

Peripheral interface 11300 may couple input and/or output peripherals of computing device 10000 to processor 11100 and memory 11200 . The processor 11100 may execute various functions for the computing device 10000 and process data by executing software modules or command sets stored in the memory 11200 .

Input/output subsystem 11400 can couple various input/output peripherals to peripheral interface 11300. For example, the input/output subsystem 11400 may include a controller for coupling a peripheral device such as a monitor, keyboard, mouse, printer, or touch screen or sensor to the peripheral interface 11300 as needed. According to another aspect, input/output peripherals may be coupled to the peripheral interface 11300 without going through the input/output subsystem 11400.

The power circuit 11500 may supply power to all or some of the terminal's components. For example, power circuit 11500 may include a power management system, one or more power sources such as a battery or alternating current (AC), a charging system, a power failure detection circuit, a power converter or inverter, a power status indicator or power It may contain any other components for creation, management and distribution.

The communication circuit 11600 may enable communication with another computing device using at least one external port.

Alternatively, as described above, the communication circuit 11600 may include an RF circuit and transmit/receive an RF signal, also known as an electromagnetic signal, to enable communication with another computing device.

The embodiment of FIG. 6 is only an example of the computing device 10000, and the computing device 11000 may omit some components shown in FIG. 6, further include additional components not shown in FIG. 6, or 2 It may have a configuration or arrangement combining two or more components. For example, a computing device for a communication terminal in a mobile environment may further include a touch screen or a sensor in addition to the components shown in FIG. , Bluetooth, NFC, Zigbee, etc.) may include a circuit for RF communication. Components that may be included in the computing device 10000 may be implemented as hardware including one or more signal processing or application-specific integrated circuits, software, or a combination of both hardware and software.

Methods according to embodiments of the present invention may be implemented in the form of program instructions that can be executed through various computing devices and recorded in computer readable media. In particular, the program according to the present embodiment may be configured as a PC-based program or a mobile terminal-only application. An application to which the present invention is applied may be installed in a user terminal through a file provided by a file distribution system. For example, the file distribution system may include a file transmission unit (not shown) that transmits the file according to a request of a user terminal.

The device described above may be implemented as a hardware component, a software component, and/or a combination of hardware components and software components. For example, devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may run an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of software. For convenience of understanding, there are cases in which one processing device is used, but those skilled in the art will understand that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it can include. For example, a processing device may include a plurality of processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

Software may include a computer program, code, instructions, or a combination of one or more of the foregoing, which configures a processing device to operate as desired or processes independently or collectively. The device can be commanded. Software and/or data may be any tangible machine, component, physical device, virtual equipment, computer storage medium or device, intended to be interpreted by or to provide instructions or data to a processing device. may be permanently or temporarily embodied in Software may be distributed on networked computing devices and stored or executed in a distributed manner. Software and data may be stored on one or more computer readable media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with limited examples and drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques may be performed in an order different from the method described, and/or components of the described system, structure, device, circuit, etc. may be combined or combined in a different form than the method described, or other components may be used. Or even if it is replaced or substituted by equivalents, appropriate results can be achieved. Therefore, other implementations, other embodiments, and equivalents of the claims are within the scope of the following claims.

Claims (10)

a floating plate whose height is adjustable and supports a vehicle entering an inspection area equipped with a plurality of maintenance kits;
a support plate positioned on a region of an upper surface of the floating plate and capable of moving up and down independently of the floating plate by supporting a lower surface of the vehicle;
A sound acquisition unit for acquiring sound data based on a sound generated by the driving of the vehicle when the vehicle starts to drive in a state where the support plate supports the lower surface of the vehicle and places the vehicle in the air. ;
a code information generation unit that analyzes the sound data obtained through the sound acquisition unit based on a pre-stored artificial intelligence algorithm, determines the type of failure that has occurred in the vehicle through the analysis result, and generates failure code information; and
When the generation of the fault code information is completed, maintenance information corresponding to the fault code information is identified among a plurality of pieces of maintenance information stored in a pre-stored maintenance category, and at least one of the plurality of maintenance kits based on the identified maintenance information is identified. A maintenance kit recommending unit for recommending a maintenance kit to a mechanic and allowing the mechanic to repair the vehicle through the recommended maintenance kit;
The inspection area is
Each of the plurality of maintenance kits is disposed in a designated area near the area where the floating plate is located, and a lighting device is provided for each designated area. pit system.
delete According to claim 1,
The sound acquisition unit,
When the vehicle starts to drive, sound generated by at least one voice generating target included in the vehicle is received through a sound input unit located in the inspection area, and sound data based on the received sound is obtained. Initiate an inspection process to determine the type of failure of the vehicle;
Dividing sound data obtained before the car is maintained into first type sound data and sound data obtained after the car is maintained into second type sound data,
The voice generation target,
A pit system for vehicle maintenance equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection, characterized in that at least one part constituting the vehicle generates a sound by power generated according to driving of the vehicle.
According to claim 3,
The code information generation unit,
an inspection analysis start unit that starts analysis of the first type sound data through the pre-stored artificial intelligence algorithm when the inspection process starts as the sound acquisition unit acquires the first type sound data;
a first waveform comparator which compares a waveform of the first type sound data with a waveform of each of a plurality of pre-stored comparison sound data when the analysis of the first type sound data starts;
When there exists comparison sound data whose similarity rate with the waveform of the first type sound data exceeds the specified range due to the performance of the function of the first waveform comparator, the similarity rate exceeds the specified range through comparison sound data. a fault code generating unit that checks the type of fault that has occurred in the vehicle and generates fault code information based on the type of the identified fault; and
When at least one comparison sound data having a similarity rate with the waveform of the first type within a specified range exists due to the performance of the function of the first waveform comparator, at least one comparison sound data having a similarity rate within a specified range and a candidate code generation unit that identifies a candidate group for the type of failure that has occurred in the vehicle through comparison sound data of and generates candidate code information based on the identified candidate group. Pit system for vehicle maintenance with monitoring function and maintenance equipment.
According to claim 4,
The plurality of comparison sound data,
As sound data based on the sound generated by the voice generating target according to the type of breakdown of the vehicle,
an idle category including a plurality of comparison sound data to be compared with sound data based on sound generated by the voice generating target when the vehicle is idling; and
A state monitoring function before and after vehicle inspection, characterized in that included in a rotation category including a plurality of comparison sound data for comparison with sound data based on the sound generated by the voice generating target when the tire of the vehicle rotates; Pit system for vehicle maintenance with maintenance equipment.
According to claim 5,
The kit recommendation unit,
When the generation of the fault code information is completed, maintenance information corresponding to the fault code information is identified among the plurality of maintenance information, and the maintenance information of the plurality of maintenance kits is located in a designated area based on the identified maintenance information. a maintenance request unit requesting the mechanic to repair the car through a maintenance kit disposed in a designated area by driving a lighting device; and
When the generation of the candidate code information is completed, at least one maintenance information corresponding to the candidate code information is identified from among the plurality of maintenance information, and a maintenance kit based on the identified at least one maintenance information among the plurality of maintenance kits. Driving the lighting devices in the designated area where the is arranged, driving the lighting devices in the designated area in order so as to correspond to the order of comparison sound data with a high similarity included in the designated range to recommend the maintenance sequence of the car to the mechanic. A maintenance sequence recommendation unit; A vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection, comprising:
According to claim 6,
The sound acquisition unit,
In a state in which the mechanic has completed the maintenance of the car by performing the function of the kit recommendation unit, the second type sound data is obtained by acquiring the sound generated by the driving of the car through the sound input unit. In the case of, a vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection, characterized in that it initiates a maintenance completion inspection process to check for abnormalities in the repaired vehicle.
According to claim 7,
The code information generation unit,
a maintenance completion analysis start unit that starts analysis of the second type sound data through the pre-stored artificial intelligence algorithm when the maintenance completion inspection process starts;
When the analysis of the second type sound data starts, normal sound data corresponding to a type of failure based on at least one of the failure code information and the candidate code information is identified among a plurality of pre-stored normal sound data, a second waveform comparator which compares the waveform of the normal sound data with the waveform of the second type sound data;
When the similarity rate of the waveform of the second type sound data to the waveform of the normal sound data exceeds a specified reference value due to the performance of the function of the second waveform comparator, the maintenance of the vehicle is performed through an output unit located in the inspection area. Check completion confirmation unit for outputting a message indicating that the was completed normally; and
When the similarity rate of the waveform of the second type sound data to the waveform of the normal sound data is less than the specified reference value due to the performance of the function of the second waveform comparator, the similarity rate among the waveforms of the second type sound data is the specified reference value and a re-inspection code generation unit that identifies a portion determined to be less than the specified number and generates re-inspection code information by identifying a type of failure corresponding to the identified portion through the pre-stored artificial intelligence algorithm. Pit system for vehicle maintenance with pre- and post-inspection condition monitoring function and maintenance equipment.
According to claim 8,
The kit recommendation unit,
When the generation of the re-inspection code information is completed, maintenance information corresponding to the generated re-inspection code information is identified among the plurality of maintenance information, and a lighting device in a designated area where a maintenance kit based on the identified maintenance information is disposed. A vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after vehicle inspection, characterized in that requesting the mechanic to recondition the vehicle by driving.
According to claim 9,
The pre-stored artificial intelligence algorithm,
As an algorithm for analyzing the sound data and identifying the type of failure that has occurred in the vehicle, machine learning is performed on the sound data received through the sound input means to obtain waveforms or other previously stored comparison sound data. A vehicle maintenance pit system equipped with a condition monitoring function and maintenance equipment before and after automobile inspection, characterized in that for updating a comparison relationship between waveforms of a plurality of stored normal sound data and waveforms of the sound data.

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