Automobile seat quality testing method, device and equipment

Abstract

The present application is applicable to the technical field of automobile seat quality detection, and in particular, relates to an automobile seat quality detection method, device and equipment. The automobile seat quality detection method comprises: obtaining a first cushion image; analyzing the first cushion image to obtain first cushion quality detection data; obtaining first backrest information; analyzing the moving speed of the first backrest information to obtain first backrest quality detection data; obtaining pressure information and obtaining a second cushion image; analyzing the second cushion image and pressure information to obtain second cushion quality detection data; obtaining second backrest information based on a second movement signal; analyzing the second backrest information to obtain second backrest quality detection data; obtaining automobile seat quality detection data based on the first cushion quality detection data, the first backrest quality detection data, the second cushion quality detection data and the second backrest quality detection data. The method can comprehensively evaluate the actual performance of the seat.

Description

Technical Field

[0001] The present application belongs to the technical field of automobile seat quality inspection, and in particular, relates to an automobile seat quality inspection method, device and equipment. Background Art

[0002] Car seats are an important part of transportation, and their comfort and safety directly affect the experience of drivers and passengers. With the development of technology, the design of car seats is becoming more and more complex, and at the same time, consumers and users have higher and higher requirements for the quality of seats.

[0003] At present, the quality inspection of automobile seats mainly relies on static simulation experiments in the laboratory. Although this inspection method can provide basic strength and durability evaluation, it has certain limitations, especially it cannot directly reflect the dynamic performance and riding comfort of the seat in actual use. Summary of the invention

[0004] The embodiments of the present application provide a method, device and equipment for detecting the quality of automobile seats, which can solve the problem that the automobile seat detection method in the related art cannot intuitively reflect the dynamic performance and riding comfort of the seat in actual use.

[0005] In a first aspect, an embodiment of the present application provides a method for detecting the quality of a car seat, comprising:

[0006] The control device controls the pressure object of the pressure-applying device to apply pressure to the seat cushion and backrest of the car seat based on the preset pressure information, and obtains a first seat cushion image; wherein the first seat cushion image is used to reflect the state of the seat cushion after being pressed;

[0007] Analyze the first seat cushion image to obtain first seat cushion quality detection data;

[0008] Acquiring first backrest information based on the first movement signal; wherein the first movement signal is used to indicate a trigger signal for the adjustment device to adjust the backrest in the seating interval when the pressure-applying object applies pressure to the backrest, the seating interval is used to indicate the position range of the backrest when the angle between the backrest and the seat cushion is greater than a preset angle, and the first backrest information is used to reflect the movement state of the backrest in the seating interval when the pressure-applying object applies pressure to the backrest;

[0009] Analyze the moving speed of the first backrest information to obtain first backrest quality detection data; wherein the moving speed includes the speed magnitude, speed change information and speed difference information of the backrest when it moves in the seating area;

[0010] After a preset pressure application time, the pressure object is controlled to move away from the seat cushion at a preset speed and pressure information is obtained; wherein the pressure information is used to reflect the pressure of the seat cushion on the pressure object;

[0011] Acquire a second seat cushion image; wherein the second seat cushion image is used to reflect the state of the seat cushion within a preset time after the pressure-applying object is completely separated from the seat cushion;

[0012] Analyze the second cushion image and the pressure information to obtain second cushion quality detection data;

[0013] Acquiring second backrest information based on a second movement signal; wherein the second movement signal is used to indicate an adjustment signal of the adjustment device for moving the backrest from the seating interval to the retracted interval, the retracted interval is used to indicate a position range of the backrest when the angle between the backrest and the seat cushion is less than the preset angle, and the second backrest information is used to reflect a movement state of adjusting the backrest from the seating interval to the retracted interval when no pressure is applied to the backrest;

[0014] Analyze the second backrest information to obtain second backrest quality detection data;

[0015] The automobile seat quality detection data is obtained based on the first seat cushion quality detection data, the first backrest quality detection data, the second seat cushion quality detection data and the second backrest quality detection data.

[0016] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0017] The automobile seat quality detection method provided in this application more realistically reflects the performance of the seat in different usage scenarios by simulating the actual force exerted by the passengers on the seat, such as applying pressure, adjusting the backrest angle and other dynamic processes. This not only includes the test of physical load-bearing, but also covers the response speed and smoothness of the seat to the passenger's actions. By analyzing the deformation recovery of the seat after being subjected to force, it is helpful to quantify the adaptability of the seat to passengers of different body shapes and the comfort of long-term riding. At the same time, by recording detailed data of the seat in dynamic testing, such as pressure distribution, deformation recovery rate, etc., potential material fatigue or structural weaknesses can be discovered earlier, providing a scientific basis for the reliability and service life of the seat. This method can shift from static testing to dynamic and comprehensive evaluation, and more accurately reflect the actual performance of the seat.

[0018] In a possible implementation manner of the first aspect, the analyzing the first seat cushion image to obtain first seat cushion quality detection data includes:

[0019] Analyze the first cushion image to obtain depth information; wherein the depth information is used to reflect the depth of the depression of the cushion;

[0020] An analysis is performed based on the depth information to obtain first cushion quality detection data.

[0021] In a possible implementation manner of the first aspect, the analyzing according to the depth information to obtain first cushion quality detection data includes:

[0022] Analyzing the depth information of the first area of ​​the depth information to obtain the pressure quality data of the first cushion; wherein the depth information of the first area is used to reflect the concave state of the first area where the pressure object contacts the cushion;

[0023] Analyze the deformation information of the second area of ​​the depth information to obtain the first cushion support quality data; wherein the deformation information of the second area is used to reflect the deformation state of the second area adjacent to the first area;

[0024] First seat cushion mass detection data is obtained based on the first seat cushion compression mass data and the first seat cushion support mass data.

[0025] In a possible implementation of the first aspect, the analyzing the depth information of the first area of ​​the depth information to obtain the first cushion pressure mass data includes:

[0026] Analyzing the depression depth in the first region depth information of the depth information to obtain the first cushion compression mass;

[0027] Analyzing the depth difference in the first region depth information of the depth information to obtain the compressed mass of the second cushion;

[0028] First seat cushion compression mass data is obtained based on the first seat cushion compression mass and the second seat cushion compression mass.

[0029] In a possible implementation manner of the first aspect, analyzing the deformation information of the second region according to the depth information to obtain the first cushion support quality data includes:

[0030] Analyze the deformation area in the deformation information of the second region of the depth information to obtain the first cushion support quality; wherein the deformation area is used to indicate the area of ​​the cushion that is deformed without contacting the pressure object;

[0031] Analyzing the deformation amount in the deformation information of the second region of the depth information to obtain the second cushion support quality; wherein the deformation amount is used to reflect the degree of bending of the second region;

[0032] First seat cushion support mass data is obtained based on the first seat cushion support mass and the second seat cushion support mass.

[0033] In a possible implementation manner of the first aspect, the analyzing according to the second seat cushion image and the pressure information to obtain the second seat cushion quality detection data includes:

[0034] Comparing the second cushion image with the preset cushion image to obtain a fatigue value; wherein the fatigue value is used to reflect the fatigue resistance of the cushion after being pressed for the preset pressing time;

[0035] Analyzing the pressure information to obtain rebound information; wherein the rebound information is used to reflect the state of the seat cushion when it rebounds;

[0036] Second seat cushion quality detection data is obtained based on the fatigue value and the rebound information.

[0037] In a possible implementation manner of the first aspect, the analyzing according to the pressure information to obtain the rebound information includes:

[0038] Analyze the pressure value of the pressure information to obtain a first rebound mass of the rebound information;

[0039] The second rebound quality of the rebound information is obtained by analyzing the pressure time of the pressure information.

[0040] In a possible implementation manner of the first aspect, the analyzing according to the second backrest information to obtain the second backrest quality detection data includes:

[0041] Analyze the backrest moving speed according to the second backrest information to obtain the first backrest storage mass in the second backrest quality detection data;

[0042] The second backrest storage mass in the second backrest quality detection data is obtained by analyzing the noise information of the second backrest information.

[0043] In a second aspect, an embodiment of the present application provides a vehicle seat quality detection device, comprising:

[0044] A first control acquisition module, configured to control the device to control the pressure object of the pressure applying device to apply pressure to the seat cushion and backrest of the vehicle seat based on preset pressure information, and to acquire a first seat cushion image; wherein the first seat cushion image is used to reflect the state of the seat cushion after being pressed;

[0045] A first analysis module, configured to analyze the first seat cushion image to obtain first seat cushion quality detection data;

[0046] A first acquisition module is used to acquire first backrest information based on a first movement signal; wherein the first movement signal is used to indicate a trigger signal when the adjustment device adjusts the backrest in a seating interval when the pressure-applying object applies pressure to the backrest, the seating interval is used to indicate a position range of the backrest when the angle between the backrest and the seat cushion is greater than a preset angle, and the first backrest information is used to reflect the movement state of the backrest in the seating interval when the pressure-applying object applies pressure to the backrest;

[0047] A second analysis module is used to analyze the moving speed of the first backrest information to obtain first backrest quality detection data; wherein the moving speed includes the speed of the backrest when it moves in the seating area, speed change information and speed difference information;

[0048] A second control acquisition module is used to control the pressure object to move away from the seat cushion at a preset speed after a preset pressure time and acquire pressure information; wherein the pressure information is used to reflect the pressure of the seat cushion on the pressure object;

[0049] A second acquisition module is used to acquire a second seat cushion image; wherein the second seat cushion image is used to reflect the state of the seat cushion within a preset time after the pressure-applying object is completely separated from the seat cushion;

[0050] a third analysis module, configured to perform analysis based on the second cushion image and the pressure information to obtain second cushion quality detection data;

[0051] a third acquisition module, configured to acquire second backrest information based on a second movement signal; wherein the second movement signal is used to indicate an adjustment signal of the adjustment device for moving the backrest from the seating interval to the retracted interval, the retracted interval is used to indicate a position range of the backrest when the angle between the backrest and the seat cushion is less than the preset angle, and the second backrest information is used to reflect a movement state of adjusting the backrest from the seating interval to the retracted interval when no pressure is applied to the backrest;

[0052] a fourth analysis module, configured to analyze the second backrest information to obtain second backrest quality detection data;

[0053] A summation module is used to obtain the automobile seat quality detection data based on the first seat cushion quality detection data, the first backrest quality detection data, the second seat cushion quality detection data and the second backrest quality detection data.

[0054] In the third aspect, an embodiment of the present application provides a car seat quality inspection device, comprising a pressure device, an adjustment device and a control device, wherein the control device is electrically connected to the pressure device and the adjustment device, and the control device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the methods described in the first aspect when executing the computer program.

[0055] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the above-mentioned first aspects is implemented.

[0056] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a car seat quality inspection device, the car seat quality inspection device executes the car seat quality inspection method described in any one of the first aspects above.

[0057] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0059] Figure 1 It is a flow chart of a method for detecting the quality of a car seat provided in an embodiment of the present application;

[0060] Figure 2 1 is a schematic diagram of the implementation process of step S200 in the automobile seat quality detection method provided in an embodiment of the present application;

[0061] Figure 3 1 is a schematic diagram of the implementation process of step S220 in the automobile seat quality detection method provided in an embodiment of the present application;

[0062] Figure 4 1 is a schematic diagram of the implementation process of step S221 in the automobile seat quality detection method provided in an embodiment of the present application;

[0063] Figure 5 It is a schematic diagram of the implementation process of step S222 in the automobile seat quality detection method provided in an embodiment of the present application;

[0064] Figure 6 It is a schematic diagram of the implementation process of step S700 in the automobile seat quality detection method provided in an embodiment of the present application;

[0065] Figure 7 It is a schematic diagram of the implementation process of step S720 in the automobile seat quality detection method provided in an embodiment of the present application;

[0066] Figure 8 It is a schematic diagram of the implementation process of step S900 in the automobile seat quality detection method provided in an embodiment of the present application;

[0067] Fig. 9 is a structural schematic diagram of a vehicle seat quality detection device provided in an embodiment of the present application;

[0068] Fig.10 It is a structural schematic diagram of a control device of an automobile seat quality inspection device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0069] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0070] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0071] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0072] As used in the specification of this application and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if it is determined" or "if the described condition or event is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce the described condition or event is detected" or "in response to detecting the described condition or event" depending on the context.

[0073] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0074] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0075] Car seats are an important part of transportation, and their comfort and safety directly affect the experience of drivers and passengers. With the development of technology, the design of car seats is becoming more and more complex, and at the same time, consumers and users have higher and higher requirements for the quality of seats.

[0076] At present, the quality inspection of automobile seats mainly relies on static simulation experiments in the laboratory. Although this inspection method can provide basic strength and durability evaluation, it has certain limitations, especially it cannot directly reflect the dynamic performance and riding comfort of the seat in actual use.

[0077] To solve the above problems, the embodiments of the present application provide a method, device and equipment for detecting the quality of automobile seats. In the method, a pressure object of a pressure device is controlled by a control device to apply pressure to the cushion and backrest of the automobile seat based on preset pressure information, and a first cushion image reflecting the state of the cushion after being pressed is obtained; the first cushion image is analyzed to obtain first cushion quality detection data; then, based on a first movement signal indicating that the pressure object applies pressure to the backrest, a trigger signal when the adjustment device adjusts the backrest in a seating interval indicating the position range of the backrest when the angle between the backrest and the cushion is greater than a preset angle is obtained, which is used to reflect the movement state of the backrest in the seating interval when the pressure object applies pressure to the backrest; the first backrest quality detection data is obtained based on the movement speed of the first backrest information, wherein the movement speed includes the speed size, speed change information and speed difference information when the backrest moves in the seating interval; after the preset pressure time, the pressure object is controlled to Move away from the cushion at a preset speed and obtain pressure information for reflecting the pressure of the cushion on the pressure object; then obtain a second cushion image for reflecting the state of the cushion within a preset time after the pressure object is completely separated from the cushion; analyze the second cushion image and pressure information to obtain the second cushion quality detection data; then obtain the second backrest information for reflecting the movement state of adjusting the backrest from the sitting interval to the shrinking interval when no pressure is applied to the backrest based on the second movement signal for indicating the adjustment signal of the adjustment device for moving the backrest from the sitting interval to the shrinking interval indicating the position range of the backrest when the angle between the backrest and the cushion is less than the preset angle; analyze the second backrest information to obtain the second backrest quality detection data; finally, obtain the automobile seat quality detection data based on the first cushion quality detection data, the first backrest quality detection data, the second cushion quality detection data and the second backrest quality detection data. This method simulates the actual force exerted by the occupant on the seat, such as dynamic processes such as applying pressure and adjusting the backrest angle, and more realistically reflects the performance of the seat in different usage scenarios, which not only includes the test of physical load-bearing, but also covers the response speed and smoothness of the seat to the occupant's actions. By analyzing the deformation recovery of the seat after being stressed, it is helpful to quantify the adaptability of the seat to passengers of different body types and the comfort of long-term riding. At the same time, by recording detailed data of the seat in dynamic testing, such as pressure distribution, deformation recovery rate, etc., potential material fatigue or structural weaknesses can be discovered earlier, providing a scientific basis for the reliability and service life of the seat. This method can shift from static testing to dynamic and comprehensive evaluation, and more accurately reflect the actual performance of the seat.

[0078] The automobile seat quality inspection method provided in the embodiment of the present application can be applied to an automobile seat quality inspection device. At this time, the automobile seat quality inspection device is the executor of the automobile seat quality inspection method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of the automobile seat quality inspection device.

[0079] For example, the automobile seat quality inspection equipment may include a pressure device, an adjustment device and a control device, and the control device is electrically connected to the pressure device and the adjustment device. The pressure device is used to apply pressure to the cushion and backrest of the automobile seat. The pressure device includes a driving mechanism and a pressure object, the output end of the driving mechanism is connected to the pressure object, and the driving mechanism is used to drive the pressure object to move. The driving mechanism can be a combination of a pneumatic motor, a liquid pump or an electric motor and a driving rod; it can also be a combination of a pneumatic motor, a liquid pump or an electric motor and a mechanical arm, etc., but not limited to this. The pressure object can be a block with a regular or irregular shape with a folding and opening function; it can also be a dummy simulating a human body shape, etc., but not limited to this. The adjustment device is connected to the angle adjuster of the automobile seat, and is used to control and adjust the angle of the backrest and the cushion of the automobile seat. The adjustment device includes a driving device and a controller, and the output end of the driving device is connected to the controller, and is used to control the movement of the controller. The driving device can be a pneumatic motor, a liquid pump or an electric motor, etc., but not limited to this. The controller is connected to the angle adjuster of the automobile seat, and is used to control and adjust the angle of the backrest and the cushion of the automobile seat. The controller can be an object with regular or irregular shape that can push the angle adjuster to move, such as a push rod, a rotating disk, etc., but not limited thereto. The control device monitors and controls the entire pressure application process and the adjustment process.

[0080] The control device may be a station (STAION, ST) in a WLAN, and may be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a mobile phone, a tablet computer, a wearable device, an in-vehicle device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a desktop computer, a smart screen, a smart TV, a handheld device with a wireless communication function, a computing device or other processing device connected to a wireless modem, an in-vehicle device, an Internet of Vehicles terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a TV set top box (STB), a customer premises equipment (customer premises equipment) equipment, CPE) and / or other equipment for communicating on wireless systems and next-generation communication systems, for example, mobile terminals in 5G networks or mobile terminals in future evolved public land mobile networks (Public Land Mobile Network, PLMN), etc.

[0081] In order to better understand the automobile seat quality detection method provided in the embodiment of the present application, the specific implementation process of the automobile seat quality detection method provided in the embodiment of the present application is exemplarily introduced below.

[0082] Figure 1 A schematic flow chart of a vehicle seat quality detection method provided in an embodiment of the present application is shown, and the vehicle seat quality detection method includes:

[0083] S100, the control device controls the pressure applying object of the pressure applying device to apply pressure to the seat cushion and backrest of the car seat based on preset pressure information, and obtains a first seat cushion image; wherein the first seat cushion image is used to reflect the state of the seat cushion after being pressed.

[0084] It can be understood that the preset pressure information refers to the size, position and time of the pressure exerted by the pressure object on the seat cushion and backrest. The preset pressure information can be manually input by a person; it can also be obtained from the seat database, etc., but is not limited to this. The seat database refers to a database containing different models of seats and corresponding preset pressure information. These data can be obtained through laboratory experiments, on-site measurements and monitoring, and past experience. After acquisition, the collected data will be sorted, classified and archived, useful information and rules will be extracted, and the relevant data will be saved in the database to form a seat database. The first seat cushion image can be obtained by a camera or other imaging device. For example, a camera or other imaging device can be installed in a position directly above the front of the car seat to facilitate the acquisition of the overall image of the car seat, or it can be installed around the pressure object, etc., but is not limited to this.

[0085] S200: Analyze the first seat cushion image to obtain first seat cushion quality detection data.

[0086] It can be understood that key features (such as deformation amount, uniformity, etc.) of the first cushion image can be extracted through image analysis technology, and first cushion quality detection data with quantitative indicators (such as deformation percentage, uniformity index, etc.) can be output through these key features.

[0087] In one possible implementation, see Figure 2 In step S200, the first cushion image is analyzed to obtain first cushion quality detection data, including:

[0088] S210, analyzing the first seat cushion image to obtain depth information; wherein the depth information is used to reflect the depression depth of the seat cushion.

[0089] It can be understood that the distance of each pixel point in the first cushion image can be calculated by computer vision technology, so as to construct a depth map of the cushion surface to obtain the depth of the depression at each position of the cushion in the first cushion image; the displacement difference of the same position under different viewing angles can also be calculated by the inspection principle of multiple images, and then the depth information of each position can be inferred, etc., but not limited to this.

[0090] S220, analyzing the depth information to obtain first cushion quality detection data.

[0091] It can be understood that the depression depth reflected by the depth information can be used to obtain the pressure distribution in the first cushion quality detection data and the compressive elasticity of the cushion material, thereby providing quantitative detection data for evaluating the cushion quality.

[0092] In one possible implementation, see Figure 3In step S220, the first cushion quality detection data is obtained by analyzing the depth information, including:

[0093] S221, analyzing the depth information of the first area of ​​the depth information to obtain the pressure mass data of the first cushion; wherein the first area depth information is used to reflect the concave state of the first area where the pressure object contacts the cushion.

[0094] It can be understood that the depth information of the first area can be calculated by computer vision technology, that is, the position of the end of the pressure object in the first cushion image away from the cushion, and then the fixed distance between the end of the pressure object away from the cushion and the end close to the cushion is combined to calculate the depth of the depression of each small area in the first area. The three-dimensional coordinates of the cushion surface at the pressure point and its surrounding area reflected in the first cushion image can also be directly calibrated by image processing technology (such as stereoscopic vision, structured light, ToF, etc.), so as to calculate the vertical displacement of the cushion surface in the area relative to the unpressurized state to obtain the depression depth of the first area, and so on, but not limited to this.

[0095] In one possible implementation, see Figure 4 In step S221, the first area depth information is analyzed to obtain the first cushion pressure quality data, including:

[0096] S2211, analyzing the depression depth in the first area depth information to obtain the compression mass of the first seat cushion.

[0097] It can be understood that the depression depth can be the maximum depression depth in the first area or the average depression depth in the first area. If it is the maximum depression depth, the maximum depression depth in the first area is obtained by collecting the depression depths at various positions in the first area and then comparing them, and the depression depth is determined; if it is the average depth, the depression depths at various positions in the first area are added and then divided by the position sampling points to calculate the average depression depth in the first area. The depression depth can reflect the compression performance and elasticity of the cushion. A larger depression depth may mean that the cushion is softer and has better compression performance.

[0098] S2212: Analyze the depth difference in the depth information of the first area of ​​the depth information to obtain the compression mass of the second seat cushion.

[0099] It can be understood that the depth difference can be expressed by calculating the depression depth of all sampling points in the first area, finding the maximum depression depth and the minimum depression depth, and the difference between the two is the depth difference; the first area can also be divided into multiple small sub-areas or a grid division method is used to calculate the average depression depth in each sub-area, and then calculate the average depth difference between adjacent sub-areas, etc., but not limited to this. The depth difference can reflect the uniformity of the pressure on the cushion. A smaller depth difference may mean that the cushion can evenly disperse the pressure when it is compressed, reducing the situation of local excessive pressure, which is very important for long-term riding comfort and reducing fatigue.

[0100] S2213, obtaining first seat cushion compression mass data based on the first seat cushion compression mass and the second seat cushion compression mass.

[0101] In this way, the first cushion pressure mass includes the depression depth and depth difference of the first area of ​​the cushion. These two mass data can directly reflect the direct load-bearing capacity and uniformity of pressure distribution of the cushion, and are the key to evaluating whether the cushion can provide good support and comfort in actual use.

[0102] S222, analyzing the deformation information of the second region according to the depth information to obtain the first cushion support quality data; wherein the deformation information of the second region is used to reflect the deformation state of the second region adjacent to the first region.

[0103] It can be understood that the second area refers to the area adjacent to the first area where deformation occurs, that is, the area around the area directly affected by the pressure object. Although this area does not directly bear the pressure from the pressure object, its deformation state is crucial for evaluating the overall support and structural stability of the cushion. The deformation information of the second area can be measured by computer image processing technology to measure the three-dimensional coordinates of the cushion surface area around the pressure object in the first cushion image, and then compared with the three-dimensional coordinates of the cushion before deformation. By calculating the difference between the coordinates of the same position, the area of ​​the second area of ​​the cushion that has deformed in addition to the first area and the deformation condition (such as the depth of the depression, the uniformity of the deformation distribution, etc.) can be obtained.

[0104] In one possible implementation, see Figure 5 In step S222, the deformation information of the second region of the depth information is analyzed to obtain the first cushion support quality data, including:

[0105] S2221, analyzing the deformation area in the second region deformation information of the depth information to obtain the first seat cushion support quality; wherein the deformation area is used to indicate the area of ​​the seat cushion that is deformed without contacting the pressure object.

[0106] It can be understood that the deformation area can be obtained by comparing the first cushion image with the preset image (i.e., the image before pressure is applied), using techniques such as image matching or optical flow analysis, comparing the position changes of corresponding points or areas in the image before and after pressure is applied, identifying the deformation area in the second area indirectly caused by the pressure on the first area, and calculating the total area of ​​the deformation area by accumulating the number of single deformed pixels or merging the continuously deformed pixel areas, which is the deformation area; the three-dimensional coordinates of the cushion surface area around the pressure object in the first cushion image can also be measured by computer image processing technology, and then compared with the three-dimensional coordinates of the cushion before deformation, and the area of ​​the second area of ​​the cushion that has deformed except the first area can be obtained by calculating the difference between the coordinates of the same position, which is the deformation area, and so on, but not limited to this. The first cushion support quality includes the deformation area, which is used as a quantitative indicator to measure the support performance of the cushion.

[0107] S2222: Analyze the deformation amount in the deformation information of the second region according to the depth information to obtain the second cushion support quality; wherein the deformation amount is used to reflect the degree of bending of the second region.

[0108] It can be understood that the deformation variable can be calculated by the deformation variables of each sampling area in the second area, and the average deformation variable can be used as the quantitative data of the deformation variable; the maximum deformation variable of each sampling area in the second area can also be used as the quantitative data of the deformation variable, and so on, but not limited to this. The deformation variable of each sampling area can be calculated by the curvature of the surface reflected in the first cushion image to characterize the bending degree of the deformation; the position coordinates of the sampling area that fit the edge of the pressure object and the position coordinates between the deformation and the non-deformation under the same horizontal coordinate can also be obtained by computer image processing technology for comparison and calculation, and the bending degree is calculated by the change values ​​of the horizontal coordinate and the vertical coordinate of these two position coordinates, and so on, but not limited to this. The size of the deformation variable reflects the elastic support and wrapping support capabilities of the cushion. The larger the deformation variable, the better the elastic support and wrapping support capabilities of the cushion.

[0109] S2223: Obtain first seat cushion support mass data based on the first seat cushion support mass and the second seat cushion support mass.

[0110] With this arrangement, the first cushion support quality data includes the deformation area and deformation amount of the second region. Through multi-dimensional and refined considerations, the support performance of the cushion can be comprehensively quantified.

[0111] S223: Obtain first seat cushion quality detection data based on the first seat cushion compression quality data and the first seat cushion support quality data.

[0112] With this arrangement, the first cushion quality test data includes the depression depth and depth difference of the first area of ​​the cushion, and the deformation area and deformation amount of the second area. These measurement test data can reflect the direct pressure bearing performance of the cushion, the compression elasticity of the material, and the uniformity of pressure distribution, as well as the stress transmission and structural stability of the cushion material, as well as the support and comfort of the cushion. This provides more comprehensive and quantitative data for evaluating the overall quality of the cushion.

[0113] S300, obtaining first backrest information based on the first movement signal; wherein the first movement signal is used to indicate a trigger signal for the adjustment device to adjust the backrest in the seating interval when a pressure object applies pressure to the backrest, the seating interval is used to indicate the position range of the backrest when the angle between the backrest and the seat cushion is greater than a preset angle, and the first backrest information is used to reflect the movement state of the backrest in the seating interval when a pressure object applies pressure to the backrest.

[0114] It is understood that the first movement signal can be manually input or obtained from a seat database, etc., but not limited thereto. The first backrest information can be obtained by monitoring the movement of the backrest through a sensor (such as a velocity sensor, an acceleration sensor or a position sensor); or by using a high-speed camera or video analysis technology to record the dynamic process of backrest adjustment, and analyzing the backrest posture change, the smoothness of the motion trajectory, etc. through an image processing algorithm, etc., but not limited thereto.

[0115] S400, analyzing the moving speed of the first backrest information to obtain first backrest quality detection data; wherein the moving speed includes the speed of the backrest when it moves in the seating area, speed change information and speed difference information.

[0116] It can be understood that the movement speed can reflect the movement state of the backrest under pressure, that is, simulate the movement of the backrest when the backrest angle is adjusted when the passenger sits on the car seat, so as to reflect the adjustment comfort of the backrest. The riding range can be set by many factors such as ergonomics, design specifications, simulation tests, market feedback and biomechanics. For example, the angle between the backrest and the seat cushion can be set to 100°~150° as the riding range, and the movement speed can be obtained by adjusting the backrest to move within the riding range.

[0117] S500, after a preset pressure time, the pressure object is controlled to move away from the seat cushion at a preset speed and pressure information is obtained; wherein the pressure information is used to reflect the pressure of the seat cushion on the pressure object.

[0118] It can be understood that the preset pressure time is part of the preset pressure information. The preset speed is a preset value, and the preset speed is used to indicate the moving speed of the pressure object when it moves away from the seat cushion. The preset speed can be manually input by a person; it can also be obtained in the seat database, etc., but not limited to this. The seat database refers to a database containing different models of seats and corresponding preset speeds. These data can be obtained through laboratory experiments, on-site measurements and monitoring, and past experience. After obtaining, the collected data will be sorted, classified and archived, and useful information and rules will be extracted. The relevant data will then be saved in the database to form a seat database. The pressure information can be obtained through a pressure sensor installed at the bottom of the pressure object.

[0119] S600, acquiring a second seat cushion image; wherein the second seat cushion image is used to reflect the state of the seat cushion within a preset time after the pressure-applying object is completely separated from the seat cushion.

[0120] It is understood that the preset time is a preset value used to indicate the time from when the pressure object is completely separated from the seat cushion to when the second seat cushion image is obtained. The preset time can be manually input; it can also be obtained from the seat database, etc., but is not limited thereto. The second seat cushion image can be obtained by a camera or other imaging device.

[0121] S700: Analyze the second seat cushion image and pressure information to obtain second seat cushion quality detection data.

[0122] It is understood that the second cushion image can be analyzed by computer vision technology to obtain the shape of the cushion, and then the shape of the cushion can be quantitatively analyzed to obtain quantitative data. The second cushion quality detection data can be obtained by combining the obtained pressure value with the quantified shape of the cushion.

[0123] In one possible implementation, see Figure 6 In step S700, the second cushion image and pressure information are analyzed to obtain the second cushion quality detection data, including:

[0124] S710, comparing the second cushion image with the preset cushion image to obtain a fatigue value; wherein the fatigue value is used to reflect the fatigue resistance of the cushion after being pressed for a preset pressing time.

[0125] It can be understood that the preset cushion image refers to the cushion image before pressure is applied, which can be obtained through a camera or other imaging device, or in a seat database, etc., but is not limited thereto. The second cushion image can be compared with the preset cushion image, and the difference measure between the two images can be calculated using image comparison technology (such as cross-correlation analysis, structural similarity index SSIM, etc.) to obtain a difference value. This may include pixel-level difference analysis or global similarity evaluation based on feature point matching. The smaller the difference value, the better the cushion recovery and the lower the fatigue level. The corresponding fatigue value is then obtained through the mapping relationship between the difference value and the fatigue value. For example, the functional relationship between the difference value and the fatigue value can be obtained through historical data, experimental calibration and other methods (for example, P=kC+b, where P is used to represent the fatigue value, C is used to represent the difference value, and k and b are coefficients determined by experimental calibration or historical data analysis). After obtaining the difference value, the difference value is brought into the mapping formula to obtain the corresponding fatigue value; the second cushion image and the preset cushion image can also be input into the mathematical model to output the corresponding fatigue value, and so on, but not limited to this. The mathematical model is trained by multiple sets of training data, and each set of training data in the multiple sets of training data includes the second cushion image, the preset cushion image and the corresponding fatigue value. The larger the fatigue value, the lower the fatigue resistance. For example, a range of 0-100 can be defined, where 0 means that the cushion has no deformation or damage, and 100 means extreme fatigue (which may include severe deformation, cracks or irreversible damage). By obtaining a specific fatigue value, it can be used to evaluate the fatigue resistance of the cushion.

[0126] S720, analyzing the pressure information to obtain rebound information; wherein the rebound information is used to reflect the state of the seat cushion when it rebounds.

[0127] It can be understood that the rebound information can be used to quantitatively evaluate the rebound performance of the seat cushion and provide data support.

[0128] In one possible implementation, see Figure 7 In step S720, the rebound information is obtained by analyzing the pressure information, including:

[0129] S721, analyzing the pressure value of the pressure information to obtain a first rebound mass of the rebound information.

[0130] It can be understood that the pressure value is constantly changing, and it first slowly increases, then slowly decreases, and finally approaches 0. Each pressure value obtained is recorded and formed into a data sequence. By analyzing the pressure value data sequence, the initial moment when the cushion starts to rebound after the pressure is released, as well as the first pressure peak during the rebound process, are identified. This peak usually corresponds to the maximum counterpressure generated when the cushion material recovers rapidly, reflecting the instantaneous rebound ability of the material. Then the difference between the pressure peak at the first rebound and the lowest pressure value at the moment of pressure release is calculated, which can quantify the instantaneous rebound force of the cushion, that is, the first rebound quality.

[0131] S722, analyzing the pressure time of the pressure information to obtain a second rebound quality of the rebound information.

[0132] It can be understood that the pressure time is used to reflect the time the cushion acts on the pressure object when it rebounds. When the moving speed of the pressure object is constant and the moving speed is less than the theoretical rebound speed of the cushion, the longer the pressure time is, the faster the rebound speed is. On the contrary, if the rebound speed of the cushion is slow, the cushion will separate from the pressure object within a certain period of time or at a certain time point, so the pressure time is short.

[0133] S730: Obtain second seat cushion quality detection data based on the fatigue value and the rebound information.

[0134] It can be understood that the second cushion quality test data includes fatigue value, first rebound quality and second rebound quality. It not only takes into account the durability of the cushion and the elastic recovery ability of the material, but also takes into account the instant response and long-term comfort maintenance of the cushion in dynamic use scenarios.

[0135] S800, obtaining second backrest information based on the second movement signal; wherein the second movement signal is used to indicate an adjustment signal of the adjustment device for moving the backrest from the sitting interval to the retracted interval, the retracted interval is used to indicate the position range of the backrest when the angle between the backrest and the seat cushion is less than a preset angle, and the second backrest information is used to reflect the movement state of the backrest when no pressure is applied to the backrest.

[0136] It can be understood that the second mobility signal and the second backrest information can be obtained by adopting a similar method to the method of obtaining the first mobility signal and the first backrest information in step S300.

[0137] S900: Analyze the second backrest information to obtain second backrest quality detection data.

[0138] It can be understood that the second backrest quality inspection data is quantitative data used to evaluate the storage performance of the backrest (storage efficiency, smoothness, etc.).

[0139] In one possible implementation, see Figure 8 In step S900, the second backrest information is analyzed to obtain the second backrest quality detection data, including:

[0140] S910, analyzing the backrest moving speed of the second backrest information to obtain the first backrest storage quality in the second backrest quality detection data.

[0141] It is understood that the backrest movement speed can be obtained by monitoring the movement of the backrest through a sensor (such as a speed sensor, an acceleration sensor or a position sensor); the dynamic process of backrest adjustment can also be recorded by using a high-speed camera or video analysis technology, and the backrest posture change, the smoothness of the motion trajectory, etc. can be analyzed by an image processing algorithm, but it is not limited to this. The speed change curve and the maximum speed of the backrest movement speed are used as quantitative data in the first backrest storage quality.

[0142] S920, analyzing the noise information of the second backrest information to obtain the second backrest storage quality in the second backrest quality detection data.

[0143] It is understood that noise information can be obtained through sound sensors, vibration sensors, etc., and the collected noise data is analyzed and processed to identify specific noises related to the storage process, including but not limited to mechanical friction noise, impact noise, abnormal vibration noise, etc. Through spectrum analysis, the noise can be decomposed into different frequency components, and the main source and characteristic frequency of the noise can be identified. The decibel size of the noise, the duration of the noise, and the frequency distribution are used as quantitative data of the storage quality of the second backrest.

[0144] S1000, obtaining automobile seat quality detection data based on first seat cushion quality detection data, first backrest quality detection data, second seat cushion quality detection data and second backrest quality detection data.

[0145] It can be understood that the automobile seat quality inspection data is the sum of the first cushion quality inspection data, the first backrest quality inspection data, the second cushion quality inspection data and the second backrest quality inspection data, forming a comprehensive automobile seat quality inspection data set. Combining the support performance of the cushion (such as depression depth, deformation area) and the adjustment performance of the backrest (such as movement speed, noise level), the riding comfort provided by the seat can be comprehensively evaluated, including immediate response, pressure distribution, and long-term comfort continuity; through the analysis of fatigue value and rebound quality, the durability of the seat material can be evaluated, as well as the ability to maintain good support and shape recovery under long-term use, which is crucial to ensure the performance stability and extend the service life of the seat under long-term use; the storage performance data of the backrest, including the storage speed and noise control during the storage process, directly reflects the quality of the seat in terms of space utilization and operational convenience. These data provide a scientific basis for the overall performance evaluation of the seat, the identification of potential problems, and the guidance of future design and production through multi-dimensional quantification.

[0146] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0147] Corresponding to the automobile seat quality detection method described in the above embodiment, the embodiment of the present application also provides an automobile seat quality detection device, and each module of the device can implement each step of the automobile seat quality detection method. Fig. 9 A structural block diagram of a vehicle seat quality detection device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0148] Reference Fig. 9 , the automobile seat quality detection device comprises:

[0149] The first control acquisition module is used to control the pressure device to apply pressure to the seat cushion and backrest of the car seat based on preset pressure information, and obtain a first seat cushion image; wherein the first seat cushion image is used to reflect the state of the seat cushion after being pressurized.

[0150] The first analysis module is used to analyze the first seat cushion image to obtain first seat cushion quality detection data.

[0151] The first acquisition module is used to obtain first backrest information based on the first movement signal; wherein the first movement signal is used to indicate a trigger signal for the adjustment device to adjust the backrest in the seating interval when a pressure-applying object applies pressure to the backrest, and the seating interval is used to indicate the position range of the backrest when the angle between the backrest and the seat cushion is greater than a preset angle, and the first backrest information is used to reflect the movement state of the backrest in the seating interval when a pressure-applying object applies pressure to the backrest.

[0152] The second analysis module is used to analyze the moving speed of the first backrest information to obtain the first backrest quality detection data; wherein the moving speed includes the speed of the backrest when it moves in the seating area, speed change information and speed difference information.

[0153] The second control acquisition module is used to control the pressure object to move away from the seat cushion at a preset speed after a preset pressure time and obtain pressure information; wherein the pressure information is used to reflect the pressure of the seat cushion on the pressure object.

[0154] The second acquisition module is used to acquire a second seat cushion image; wherein the second seat cushion image is used to reflect the state of the seat cushion within a preset time after the pressure-applying object is completely separated from the seat cushion.

[0155] The third analysis module is used to analyze the second seat cushion image and pressure information to obtain the second seat cushion quality detection data.

[0156] The third acquisition module is used to obtain second backrest information based on the second movement signal; wherein the second movement signal is used to indicate the adjustment signal of the adjustment device for moving the backrest from the sitting interval to the retraction interval, the retraction interval is used to indicate the position range of the backrest when the angle between the backrest and the seat cushion is less than a preset angle, and the second backrest information is used to reflect the movement state of the backrest adjusted from the sitting interval to the retraction interval when no pressure is applied to the backrest.

[0157] The fourth analysis module is used to analyze the second backrest information to obtain the second backrest quality detection data.

[0158] The summation module is used to obtain the automobile seat quality detection data based on the first seat cushion quality detection data, the first backrest quality detection data, the second seat cushion quality detection data and the second backrest quality detection data.

[0159] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0160] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above modules is used as an example for illustration. In actual applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the device can be divided into different modules to complete all or part of the functions described above. The modules in the embodiment can be integrated into a processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the modules in the above device can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0161] The embodiment of the present application also provides a car seat quality inspection device, including a pressure device, an adjustment device and a control device, wherein the control device is electrically connected to the pressure device and the adjustment device. Fig.10 This is a schematic diagram of the structure of a control device 6 provided in an embodiment of the present application. Fig.10 As shown, the control device 6 of this embodiment includes: at least one processor 60 ( Fig.10 Only one is shown), at least one memory 61 ( Fig.10 Only one is shown in the figure) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, the control device 6 implements the steps in any of the above-mentioned embodiments of the automobile seat quality detection method, or implements the functions of the modules in the above-mentioned device embodiments.

[0162] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 62 in the control device 6.

[0163] The control device 6 can be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The automobile seat quality detection device can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Fig.10 It is only an example of the control device 6 and does not constitute a limitation on the control device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, buses, etc.

[0164] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0165] In some embodiments, the memory 61 may be an internal storage unit of the control device 6, such as a hard disk or memory of the control device 6. In other embodiments, the memory 61 may also be an external storage device of the control device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the control device 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the control device 6. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0166] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0167] An embodiment of the present application provides a computer program product. When the computer program product is run on a car seat quality testing device, the car seat quality testing device implements the steps in any of the above method embodiments.

[0168] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the automobile seat quality detection equipment, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0169] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0170] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0171] In the embodiments provided in the present application, it should be understood that the disclosed automobile seat quality detection device, equipment and method can be implemented in other ways. For example, the above-described automobile seat quality detection device and equipment embodiments are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0172] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0173] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for detecting the quality of a car seat, characterized in that: include: The control device controls the pressure object of the pressure-applying device to apply pressure to the seat cushion and backrest of the car seat based on the preset pressure information, and obtains a first seat cushion image; wherein the first seat cushion image is used to reflect the state of the seat cushion after being pressed; Analyze the first seat cushion image to obtain first seat cushion quality detection data; Acquiring first backrest information based on the first movement signal; wherein the first movement signal is used to indicate a trigger signal for the adjustment device to adjust the backrest in the seating interval when the pressure-applying object applies pressure to the backrest, the seating interval is used to indicate the position range of the backrest when the angle between the backrest and the seat cushion is greater than a preset angle, and the first backrest information is used to reflect the movement state of the backrest in the seating interval when the pressure-applying object applies pressure to the backrest; Analyze the moving speed of the first backrest information to obtain first backrest quality detection data; wherein the moving speed includes the speed magnitude, speed change information and speed difference information of the backrest when it moves in the seating area; After a preset pressure application time, the pressure object is controlled to move away from the seat cushion at a preset speed and pressure information is obtained; wherein the pressure information is used to reflect the pressure of the seat cushion on the pressure object; Acquire a second seat cushion image; wherein the second seat cushion image is used to reflect the state of the seat cushion within a preset time after the pressure-applying object is completely separated from the seat cushion; Analyze the second cushion image and the pressure information to obtain second cushion quality detection data; Acquiring second backrest information based on a second movement signal; wherein the second movement signal is used to indicate an adjustment signal of the adjustment device for moving the backrest from the seating interval to the retracted interval, the retracted interval is used to indicate a position range of the backrest when the angle between the backrest and the seat cushion is less than the preset angle, and the second backrest information is used to reflect a movement state of adjusting the backrest from the seating interval to the retracted interval when no pressure is applied to the backrest; Analyze the second backrest information to obtain second backrest quality detection data; Obtaining automobile seat quality detection data based on the first seat cushion quality detection data, the first backrest quality detection data, the second seat cushion quality detection data and the second backrest quality detection data; The step of analyzing the first cushion image to obtain first cushion quality detection data includes: Analyze the first cushion image to obtain depth information; wherein the depth information is used to reflect the depth of the depression of the cushion; Analyze the depth information to obtain first cushion quality detection data; The analyzing according to the depth information to obtain first cushion quality detection data includes: Analyzing the depth information of the first area of ​​the depth information to obtain the pressure quality data of the first cushion; wherein the depth information of the first area is used to reflect the concave state of the first area where the pressure object contacts the cushion; Analyze the deformation information of the second area of ​​the depth information to obtain the first cushion support quality data; wherein the deformation information of the second area is used to reflect the deformation state of the second area adjacent to the first area; Obtaining first seat cushion quality detection data based on the first seat cushion pressure quality data and the first seat cushion support quality data; The analyzing the depth information of the first area of ​​the depth information to obtain the first cushion pressure mass data includes: Analyzing the depression depth in the first region depth information of the depth information to obtain the first cushion compression mass; Analyzing the depth difference in the first region depth information of the depth information to obtain the compressed mass of the second cushion; Obtaining first seat cushion compression mass data based on the first seat cushion compression mass and the second seat cushion compression mass; The analyzing the deformation information of the second region according to the depth information to obtain the first cushion support quality data includes: Analyze the deformation area in the deformation information of the second region of the depth information to obtain the first cushion support quality; wherein the deformation area is used to indicate the area of ​​the cushion that is deformed without contacting the pressure object; Analyzing the deformation amount in the deformation information of the second region of the depth information to obtain the second cushion support quality; wherein the deformation amount is used to reflect the degree of bending of the second region; Obtaining first seat cushion support mass data based on the first seat cushion support mass and the second seat cushion support mass; The step of analyzing the second cushion image and the pressure information to obtain second cushion quality detection data includes: Comparing the second cushion image with the preset cushion image to obtain a fatigue value; wherein the fatigue value is used to reflect the fatigue resistance of the cushion after being pressed for the preset pressing time; Analyzing the pressure information to obtain rebound information; wherein the rebound information is used to reflect the state of the seat cushion when it rebounds; Obtaining second cushion quality detection data based on the fatigue value and the rebound information; The step of analyzing the pressure information to obtain the rebound information includes: Analyze the pressure value of the pressure information to obtain a first rebound mass of the rebound information; Analyze the pressure time of the pressure information to obtain a second rebound quality of the rebound information; The step of analyzing the second backrest information to obtain the second backrest quality detection data includes: Analyze the backrest moving speed according to the second backrest information to obtain the first backrest storage mass in the second backrest quality detection data; The second backrest storage mass in the second backrest quality detection data is obtained by analyzing the noise information of the second backrest information.

2. A vehicle seat quality inspection device, characterized in that: include: A first control acquisition module, configured to control the device to control the pressure object of the pressure applying device to apply pressure to the seat cushion and backrest of the vehicle seat based on preset pressure information, and to acquire a first seat cushion image; wherein the first seat cushion image is used to reflect the state of the seat cushion after being pressed; A first analysis module, configured to analyze the first seat cushion image to obtain first seat cushion quality detection data; A first acquisition module is used to acquire first backrest information based on a first movement signal; wherein the first movement signal is used to indicate a trigger signal when the adjustment device adjusts the backrest in a seating interval when the pressure-applying object applies pressure to the backrest, the seating interval is used to indicate a position range of the backrest when the angle between the backrest and the seat cushion is greater than a preset angle, and the first backrest information is used to reflect the movement state of the backrest in the seating interval when the pressure-applying object applies pressure to the backrest; A second analysis module is used to analyze the moving speed of the first backrest information to obtain first backrest quality detection data; wherein the moving speed includes the speed of the backrest when it moves in the seating area, speed change information and speed difference information; A second control acquisition module is used to control the pressure object to move away from the seat cushion at a preset speed after a preset pressure time and acquire pressure information; wherein the pressure information is used to reflect the pressure of the seat cushion on the pressure object; A second acquisition module is used to acquire a second seat cushion image; wherein the second seat cushion image is used to reflect the state of the seat cushion within a preset time after the pressure-applying object is completely separated from the seat cushion; a third analysis module, configured to perform analysis based on the second cushion image and the pressure information to obtain second cushion quality detection data; a third acquisition module, configured to acquire second backrest information based on a second movement signal; wherein the second movement signal is used to indicate an adjustment signal of the adjustment device for moving the backrest from the seating interval to the retracted interval, the retracted interval is used to indicate a position range of the backrest when the angle between the backrest and the seat cushion is less than the preset angle, and the second backrest information is used to reflect a movement state of adjusting the backrest from the seating interval to the retracted interval when no pressure is applied to the backrest; a fourth analysis module, configured to analyze the second backrest information to obtain second backrest quality detection data; a summing module, configured to obtain automobile seat quality detection data based on the first seat cushion quality detection data, the first backrest quality detection data, the second seat cushion quality detection data and the second backrest quality detection data; Wherein, the first analysis module is further used for: Analyze the first cushion image to obtain depth information; wherein the depth information is used to reflect the depth of the depression of the cushion; Analyze the depth information to obtain first cushion quality detection data; The analyzing according to the depth information to obtain first cushion quality detection data includes: Analyzing the depth information of the first area of ​​the depth information to obtain the pressure quality data of the first cushion; wherein the depth information of the first area is used to reflect the concave state of the first area where the pressure object contacts the cushion; Analyze the deformation information of the second area of ​​the depth information to obtain the first cushion support quality data; wherein the deformation information of the second area is used to reflect the deformation state of the second area adjacent to the first area; Obtaining first seat cushion quality detection data based on the first seat cushion pressure quality data and the first seat cushion support quality data; The analyzing the depth information of the first area of ​​the depth information to obtain the first cushion pressure mass data includes: Analyzing the depression depth in the first region depth information of the depth information to obtain the first cushion compression mass; Analyzing the depth difference in the first region depth information of the depth information to obtain the compressed mass of the second cushion; Obtaining first seat cushion compression mass data based on the first seat cushion compression mass and the second seat cushion compression mass; The analyzing the deformation information of the second region according to the depth information to obtain the first cushion support quality data includes: Analyze the deformation area in the deformation information of the second region of the depth information to obtain the first cushion support quality; wherein the deformation area is used to indicate the area of ​​the cushion that is deformed without contacting the pressure object; Analyzing the deformation amount in the deformation information of the second region of the depth information to obtain the second cushion support quality; wherein the deformation amount is used to reflect the degree of bending of the second region; Obtaining first seat cushion support mass data based on the first seat cushion support mass and the second seat cushion support mass; The third analysis module is also used for: Comparing the second cushion image with the preset cushion image to obtain a fatigue value; wherein the fatigue value is used to reflect the fatigue resistance of the cushion after being pressed for the preset pressing time; Analyzing the pressure information to obtain rebound information; wherein the rebound information is used to reflect the state of the seat cushion when it rebounds; Obtaining second cushion quality detection data based on the fatigue value and the rebound information; The step of analyzing the pressure information to obtain the rebound information includes: Analyze the pressure value of the pressure information to obtain a first rebound mass of the rebound information; Analyze the pressure time of the pressure information to obtain a second rebound quality of the rebound information; The fourth analysis module is also used for: Analyze the backrest moving speed according to the second backrest information to obtain the first backrest storage mass in the second backrest quality detection data; The second backrest storage mass in the second backrest quality detection data is obtained by analyzing the noise information of the second backrest information.

3. A car seat quality inspection device, characterized in that: The method comprises a pressure-applying device, an adjusting device and a control device, wherein the control device is electrically connected to the pressure-applying device and the adjusting device, and the control device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the method as claimed in claim 1 is implemented when the processor executes the computer program.

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