Electric horn service life detection method and device, storage medium, vehicle machine controller and vehicle

Abstract

The invention relates to an electric horn service life detection method and device, a storage medium, a vehicle-mounted terminal and a vehicle. The electric horn service life detection method comprises the steps that a sound signal sent by a current electric horn and collected by a vehicle microphone is acquired; extracting a sound characteristic parameter value of the current klaxon from a sound signal sent by the current klaxon; and detecting the service life of the current klaxon according to the sound characteristic parameter value of the current klaxon. According to the method, the service life of the electric horn can be accurately detected.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, device, storage medium, vehicle controller and vehicle for detecting the service life of an electric horn. Background Art

[0002] With the development of the automobile industry, car audio equipment has become an important part of modern cars. Car audio equipment can not only provide entertainment for the driver, but also provide important sound prompts during driving, such as reversing alarms, turn prompts, etc. Among them, the electric horn is an important device in car audio equipment, and its service life directly affects the performance of the car audio equipment and driving safety. In traditional technology, the service life of the electric horn is usually judged by artificial hearing. Although this method is simple, it is highly subjective and cannot accurately judge the service life of the electric horn. In addition, there are some technical solutions that measure the resistance, current and other parameters of the electric horn to determine its service life. However, there are certain differences between these parameters and the actual sound characteristics of the electric horn, and they cannot accurately reflect the service life of the electric horn. The current technology has the following problems in this field:

[0003] First, due to the strong subjectivity of artificial hearing, it is impossible to accurately judge the service life of the electric horn, which will cause the actual service life of the electric horn to exceed its optimal service life, thus affecting the performance of the car audio equipment and driving safety. Secondly, the solution of judging the service life of the electric horn by measuring the resistance, current and other parameters of the electric horn cannot accurately reflect the service life of the electric horn because there is a certain difference between these parameters and the actual sound characteristics of the electric horn, which will cause the actual service life of the electric horn to be underestimated, thereby increasing the frequency of repairs and replacements and increasing maintenance costs. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, storage medium, vehicle controller and vehicle for detecting the service life of an electric horn in order to address the above technical problems, so as to accurately detect the service life of the electric horn.

[0005] A method for detecting the service life of an electric horn comprises: obtaining a sound signal emitted by a current electric horn collected by a vehicle microphone; extracting a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn.

[0006] In one embodiment, the current sound characteristic parameter value of the electric horn includes one or more of a sound pressure level, a center frequency value, and a frequency bandwidth value.

[0007] In one of the embodiments, a method for detecting the service life of an electric horn further includes: obtaining a current working state of the current electric horn in response to receiving a sound signal emitted by the current electric horn; detecting the service life of the current electric horn according to a sound characteristic parameter value of the current electric horn, including: detecting the service life of the current electric horn according to the current working state and sound characteristic parameter value of the current electric horn.

[0008] In one of the embodiments, after the step of obtaining the current working state of the current electric horn, it also includes: determining an electric horn life detection model according to the current working state of the current electric horn, the electric horn life detection model includes a relationship between the service life of the electric horn and the sound characteristic parameter; detecting the service life of the current electric horn according to the current working state of the current electric horn and the sound characteristic parameter value, including: inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model.

[0009] In one embodiment, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a normal working state, a first electric horn life detection model is determined, the first electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the normal working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, the normal working state is determined by the working voltage and / or working current of the electric horn; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model, and the service life of the current electric horn output by the electric horn life detection model is obtained, including: the sound characteristic parameter values ​​of the current electric horn are input into the first electric horn life detection model, and the service life of the current electric horn output by the first electric horn life detection model is obtained.

[0010] In one embodiment, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a faulty working state, a second electric horn life detection model is determined, the second electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the faulty working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the faulty working state is determined by the working voltage and / or working current of the electric horn; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model, including: the sound characteristic parameter values ​​of the current electric horn are input into the second electric horn life detection model to obtain the service life of the current electric horn output by the second electric horn life detection model.

[0011] In one of the embodiments, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a specific working state, a third electric horn life detection model is determined, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the specific working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, the specific working state is detected and determined by detecting the vehicle environment through a vehicle sensor; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model, and the service life of the current electric horn output by the electric horn life detection model is obtained, including: the sound characteristic parameter values ​​of the current electric horn are input into the third electric horn life detection model, and the service life of the current electric horn output by the third electric horn life detection model is obtained.

[0012] In one embodiment, the specific working state is a low temperature environment state, a high temperature environment state or a humid environment state, and the low temperature environment state and the high temperature environment state are both detected and determined by a vehicle temperature sensor, and the humid environment state is detected and determined by a vehicle air quality sensor; when the specific working state is a low temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the low temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a high temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the high temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a humid environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the humid environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn.

[0013] In one embodiment, the first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model all include a relationship between the service life of the electric horn and the basic parameter value corresponding to the service life, the sound pressure level characteristic parameter, the basic parameter value of the sound pressure level characteristic parameter, the center frequency characteristic parameter, the basic parameter value of the center frequency characteristic parameter, the bandwidth characteristic parameter, and the basic value of the bandwidth characteristic parameter; wherein the basic parameter value corresponding to the service life in the first electric horn life detection model is greater than the basic parameter value corresponding to the service life in the third electric horn life detection model, and the basic parameter value corresponding to the service life in the third electric horn life detection model is greater than the basic parameter value corresponding to the service life in the second electric horn life detection model.

[0014] In one embodiment, the relational expression of the first electric horn life detection model, the relational expression of the second electric horn life detection model and the relational expression of the third electric horn life detection model all further include the weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter; the weight of the sound pressure level characteristic parameter in the relational expression of the first electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relational expression of the third electric horn life detection model, and the weight of the sound pressure level characteristic parameter in the relational expression of the third electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relational expression of the second electric horn life detection model. In one embodiment, the electric horn life detection model is a linear regression model.

[0015] In one of the embodiments, a method for detecting the service life of an electric horn further includes: recording the service life of the current electric horn obtained each time according to the current working state and sound characteristic parameter value of the current electric horn; among the multiple recorded service lives of the current electric horn, when the cumulative value of the number of service lives of any working state that is less than a set life threshold is greater than a set number, controlling the vehicle display screen to display a prompt message to prompt the user to replace the current electric horn.

[0016] A device for detecting the service life of an electric horn comprises: an acquisition module for acquiring a sound signal emitted by a current electric horn collected by a vehicle microphone; an extraction module for extracting a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and a detection module for detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn.

[0017] A vehicle controller comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps of any one of the above methods when executing the computer program.

[0018] A vehicle is provided with the above-mentioned vehicle controller.

[0019] A computer-readable storage medium stores a computer program, which implements the steps of any of the above methods when executed by a processor.

[0020] The above-mentioned electric horn service life detection method, device, storage medium, vehicle controller and vehicle obtain the sound signal emitted by the current electric horn collected by the vehicle microphone; extract the sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and detect the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn. Since the sound signal emitted by the electric horn can directly reflect the actual sound characteristics of the electric horn, the sound characteristic parameter value is extracted from the sound signal emitted by the electric horn for analysis. Compared with the service life of the electric horn determined by parameters such as the resistance and current of the electric horn, the service life determined by the sound signal is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is an application environment diagram of a method for detecting the service life of an electric horn in one embodiment;

[0022] Figure 2 It is a schematic diagram of a flow chart of a method for detecting the service life of an electric horn in one embodiment;

[0023] Figure 3 A schematic diagram of a flow chart of model training of an electric horn life detection model in one embodiment;

[0024] Figure 4 It is a structural block diagram of a device for detecting the service life of an electric horn in one embodiment;

[0025] Figure 5 A partial structural block diagram of a vehicle in one embodiment;

[0026] Figure 6 The present invention is a flowchart of a method for detecting the service life of an electric horn of a vehicle in a specific example. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] It should be understood that in the description of the present application, unless the context clearly requires otherwise, words such as "include", "comprises", and the like throughout the specification should be interpreted as including rather than being exclusive or exhaustive; that is, as including but not limited to.

[0029] It should also be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, "plurality" means two or more.

[0030] The present application provides a method for detecting the service life of an electric horn, which is applied to Figure 1 In the application environment shown. Figure 1 As shown, the vehicle controller 100 is used to execute a method for detecting the service life of an electric horn of the present application. Specifically, Figure 1 As shown, the user triggers the electric horn button in the vehicle controller 100, and the vehicle controller 100 sends an electric horn trigger signal to the vehicle body domain controller 200, and the vehicle body domain controller 200 supplies power to the vehicle electric horn 300, driving the vehicle electric horn 300 to emit an electronic sound. The vehicle microphone 400 collects the sound signal emitted by the electric horn, and sends the collected sound signal emitted by the electric horn to the vehicle controller 100. The vehicle controller 100 receives the sound signal emitted by the electric horn, extracts the sound characteristic parameter value of the electric horn from the sound signal emitted by the electric horn, and detects the service life of the electric horn according to the sound characteristic parameter value of the electric horn. Therefore, the service life of the electric horn can be detected by the sound signal of the electric horn. Compared with the traditional judgment of the service life of the electric horn by parameters such as the resistance and current of the electric horn, the service life of the electric horn determined by the sound signal is more accurate.

[0031] In one embodiment, the present application provides a method for detecting the service life of an electric horn, which is applied to Figure 1 The vehicle machine 100 shown in FIG. Figure 2 As shown, the present application provides a method for detecting the service life of an electric horn, comprising the following steps:

[0032] S202, obtaining a sound signal currently emitted by the electric horn collected by the vehicle microphone.

[0033] In this embodiment, the current electric horn refers to the object of the current service life detection. After the vehicle microphone collects the sound signal emitted by the current electric horn, the collected sound signal is transmitted to the vehicle controller. The collected sound signal contains the sound characteristics of the current electric horn in the current working state. It can be that the vehicle microphone collects sound signals at certain time intervals, such as collecting sound signals at the 5th second, 10th second, 15th second, 30th second, 1st minute and other time points. It can also be that the sound signal is collected using a sampling frequency of 44100 Hz and a sampling accuracy of 16 bits.

[0034] S204, extracting a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn.

[0035] In this embodiment, the sound signal emitted by the electric horn directly reflects the actual sound characteristics of the electric horn, and parameter information of the sound characteristic parameters of the electric horn, specifically the sound characteristic parameter values, can be extracted from the sound signal.

[0036] In one embodiment, the sound characteristic parameters include one or more of sound pressure, center frequency of the sound signal, and bandwidth of the sound signal, and the sound characteristic parameter value of the current electric horn includes one or more of sound pressure level, center frequency value, and bandwidth value.

[0037] Specifically, the collected sound signal is processed and analyzed. The processing methods include filtering, amplification, spectrum analysis, etc., so as to extract the change information of the current electric speaker sound characteristics. The filtering adopts the Butterworth bandpass filter, and the passband frequency of the filter is 200Hz to 20000Hz. The amplification adopts the audio power amplifier, and the amplification factor is 10 times. The spectrum analysis adopts the fast Fourier transform (FFT), the analysis window length is 1024 points, and the window function adopts the Hamming window. Therefore, the sound pressure level, center frequency value and bandwidth value in the sound signal can be extracted.

[0038] S206, detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn.

[0039] In this embodiment, the sound characteristic parameter value of the current electric horn can truly reflect the current state of the current electric horn, and the service life of the current electric horn can be accurately detected through the sound characteristic parameter value of the current electric horn.

[0040] The above-mentioned electric horn service life detection method obtains the sound signal emitted by the current electric horn collected by the vehicle microphone; extracts the sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and detects the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn. Since the sound signal emitted by the electric horn can directly reflect the actual sound characteristics of the electric horn, the sound characteristic parameter value is extracted from the sound signal emitted by the electric horn for analysis. Compared with the service life of the electric horn determined by parameters such as the resistance and current of the electric horn, the service life determined by the sound signal is more accurate.

[0041] In one embodiment, before the above step S206, that is, before the step of detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn, it also includes: in response to receiving the sound signal emitted by the current electric horn, obtaining the current working state of the current electric horn. The above step of detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn includes: detecting the service life of the current electric horn according to the current working state and the sound characteristic parameter value of the current electric horn.

[0042] In this embodiment, the current working state of the electric horn can be determined by the sound signal of the current electric horn, and then the service life of the current electric horn can be detected according to the sound characteristic parameter value of the current electric horn and in combination with its current working state. The working state includes a normal working state, a faulty working state, and a special working state. The faulty working state of the electric horn is determined by detecting the abnormal working current and / or abnormal working voltage when the electric horn is in use. The faulty working state of the electric horn includes a fault that has completely become unusable, the sound of the electric horn has been continuously abnormal, and the sound of the electric horn is intermittent.

[0043] The specific manifestations are:

[0044] ① The fault is completely unusable: After the user presses the electric horn button, the electric horn does not sound at all. At this time, the working current of the electric horn is 0 and the working voltage is 12V.

[0045] ② The sound of the electric horn has been abnormal for a long time: When the user presses the electric horn button, the electric horn sounds hoarse, weak, or distorted. At this time, the working current and working voltage of the electric horn are greatly different from those in the normal working state.

[0046] ③ Intermittent horn sound failure: Sometimes the horn does not sound after the user presses the horn button, and sometimes the horn sounds after the user presses the horn button. In this case, the sound of the horn is no different from that in normal working state. In addition, when the horn does not sound, the working current of the horn is 0 and the working voltage is 12V.

[0047] The special working state includes a low temperature environment state, a high temperature environment state or a humid environment state. Among them, the low temperature working state, the high temperature working state and the humid working state are directly determined by the vehicle controller detecting the temperature of the vehicle environment or the electric horn. Under different working states, the service life of the electric horn is different for the same sound characteristic parameter value. Therefore, the accuracy of the service life detection can be improved by combining the current working state of the electric horn to detect its service life.

[0048] In one example, after the above step of obtaining the current working state of the current electric horn, it also includes: determining an electric horn life detection model according to the current working state of the current electric horn, the electric horn life detection model includes a relationship between the service life of the electric horn and the sound characteristic parameters; the above step of detecting the service life of the current electric horn according to the current working state of the current electric horn and the sound characteristic parameter value includes: inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model.

[0049] Among them, the electric horn life detection model is a linear regression model.

[0050] In this example, different working states correspond to different electric horn life detection models, and the electric horn life detection model that matches the current working state is determined according to the current working state of the electric horn. The electric horn life detection model is configured with a relationship between the service life of the electric horn and the sound characteristic parameter. After the sound characteristic parameter value is input into the electric horn life detection model, the electric horn life detection model outputs the corresponding service life. In one implementation, the electric horn life detection model is a linear regression model.

[0051] In one example, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a normal working state, a first electric horn life detection model is determined, the first electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the normal working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, the normal working state is determined by the working voltage and / or working current of the electric horn; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model, and the service life of the current electric horn output by the electric horn life detection model is obtained, including: the sound characteristic parameter values ​​of the current electric horn are input into the first electric horn life detection model, and the service life of the current electric horn output by the first electric horn life detection model is obtained.

[0052] In another example, the above-mentioned determination of the electric horn life detection model based on the current working state of the current electric horn includes: when the current working state of the current electric horn is a faulty working state, determining a second electric horn life detection model, the second electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the faulty working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the faulty working state is determined by the working voltage and / or working current of the electric horn; inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model, including: inputting the sound characteristic parameter values ​​of the current electric horn into the second electric horn life detection model to obtain the service life of the current electric horn output by the second electric horn life detection model.

[0053] In another example, the above-mentioned determination of the electric horn life detection model according to the current working state of the current electric horn includes: when the current working state of the current electric horn is a specific working state, determining a third electric horn life detection model, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the specific working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, the specific working state is detected and determined by detecting the vehicle environment through a vehicle sensor; inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model, including: inputting the sound characteristic parameter values ​​of the current electric horn into the third electric horn life detection model, and obtaining the service life of the current electric horn output by the third electric horn life detection model.

[0054] Among them, the specific working state is a low temperature environment state, a high temperature environment state or a humid environment state, the low temperature environment state and the high temperature environment state are both detected and determined by the vehicle temperature sensor, and the humid environment state is detected and determined by the vehicle air quality sensor; when the specific working state is a low temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the low temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a high temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the high temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a humid environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the humid environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn.

[0055] In one embodiment, the first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model all include a relationship between the service life of the electric horn and the basic parameter value corresponding to the service life, the sound pressure level characteristic parameter, the basic parameter value of the sound pressure level characteristic parameter, the center frequency characteristic parameter, the basic parameter value of the center frequency characteristic parameter, the bandwidth characteristic parameter, and the basic value of the bandwidth characteristic parameter; wherein the basic parameter value corresponding to the service life in the first electric horn life detection model is greater than the basic parameter value corresponding to the service life in the third electric horn life detection model, and the basic parameter value corresponding to the service life in the third electric horn life detection model is greater than the basic parameter value corresponding to the service life in the second electric horn life detection model.

[0056] In this embodiment, the basic parameter values ​​corresponding to the service life in the electric horn life detection model, the basic parameter values ​​of the sound pressure level characteristic parameters, the basic parameter values ​​of the center frequency characteristic parameters, and the basic value of the bandwidth characteristic parameters are all determined by collecting the actual test data of the sample electric horn under the corresponding working state. Specifically, after collecting a large amount of test data, the basic parameter values ​​of each sound characteristic parameter of the sample electric horn under different working states and different working times can be calculated, and each basic parameter value is obtained by taking the average. Among them, the basic parameter value corresponding to the service life of the electric horn in the normal working state is greater than the basic parameter value corresponding to the service life of the electric horn in the special working state, and the basic parameter value corresponding to the service life of the electric horn in the special working state is greater than the basic parameter value corresponding to the service life of the electric horn in the faulty working state. For example, the basic parameter value corresponding to the service life of the electric horn under the normal working state is 10, and the basic parameter value corresponding to the service life of the electric horn under the faulty working state is 2. The basic parameter values ​​corresponding to the service life of the electric horn in the special working state are: the basic parameter value is 3 in a high temperature environment, the basic parameter value is 6 in a low temperature environment, and the basic parameter value is 5 in a humid environment.

[0057] In one embodiment, the relationship formula of the first electric horn life detection model, the relationship formula of the second electric horn life detection model and the relationship formula of the third electric horn life detection model all further include the weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter; the weight of the sound pressure level characteristic parameter in the relationship formula of the first electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model, and the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the second electric horn life detection model.

[0058] In this embodiment, the weight represents the proportion of the corresponding sound characteristic parameter in the relationship. The weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter under each working state are all calculated and set based on actual test data and combined with the usage data fed back by users. Among them, for the sound pressure level characteristic parameter, the weight of the sound pressure level characteristic parameter under normal working state is less than the weight of the sound pressure level characteristic parameter under special working state, and the weight of the sound pressure level characteristic parameter under special working state is less than the weight of the sound pressure level characteristic parameter under faulty working state. In the above three examples, specific methods for performing service life detection using the corresponding electric horn life detection model when the current electric horn is in normal working state, faulty working state and special working state are given. Among them, the model training process of the first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model is as follows:

[0059] like Figure 3As shown, the model training of the electric horn life detection model includes the following steps:

[0060] ① Collection of basic sound characteristic parameter values ​​of the sound signal of the electric horn:

[0061] 1000 sample electric horns were measured in normal working state, fault working state and special working state, and the corresponding sound pressure, center frequency of sound spectrum, bandwidth of sound spectrum and other sound characteristic parameter values ​​when they worked continuously for 5s, 10s, 15s, 30s and 1min. Special working state is further divided into low temperature environment state, high temperature environment state and humid environment state.

[0062] ② Establish the standard of basic sound characteristic parameter values:

[0063] After collecting a large amount of data, we obtained the basic parameter library of the electric horn under different working conditions and different working times. The basic parameter values ​​of each sound characteristic parameter type are obtained by taking the average method. For example, a is the basic parameter value of sound pressure, b is the basic parameter value of center frequency, and c is the basic parameter value of bandwidth. The basic parameter value of the service life of the electric horn under normal working conditions is A, the basic parameter value of the service life under faulty working conditions is B, and the basic parameter values ​​of the service life under special working conditions are C1, C2, and C3 respectively. The weights of sound pressure, center frequency, and bandwidth in the service life under normal working conditions are: 0.3, 0.4, and 0.3 respectively, the weights of the service life under faulty working conditions are: 0.5, 0.3, and 0.2 respectively, and the weights of the service life under special working conditions are: 0.4, 0.3, and 0.3.

[0064] ③Establish a linear calculation formula:

[0065] The input variables of the linear calculation formula are the sound characteristic parameters of the electric horn: a1 represents the sound pressure, b1 represents the center frequency, and c1 represents the bandwidth. The output variable of the linear calculation formula is the service life of the electric horn. For example, the calculation formula for the service life of the electric horn under normal working conditions is:

[0066]

[0067] Wherein, Y represents the service life of the electric horn. When the sound pressure level, center frequency value and bandwidth value of the current electric horn are detected, the above linear calculation formula is input to output the service life of the electric horn under normal working conditions.

[0068] In one embodiment, after the above step S206, it also includes: recording the service life of the current electric horn obtained each time according to the current working state of the current electric horn and the sound characteristic parameter value detection; among the multiple recorded service lives of the current electric horn, when the cumulative value of the number of service lives of any working state that is less than the set life threshold is greater than the set number, controlling the vehicle display screen to display a prompt message to prompt the user to replace the current electric horn.

[0069] Specifically, after the vehicle controller performs a detection of the service life of the current electric horn each time, the detected service life of the current electric horn is stored in the vehicle database of the vehicle. Each time the vehicle controller updates the vehicle database of the service life of the current electric horn, it is necessary to record the service life under each working state. When the service life of the electric horn is less than 20h for 10 times in the corresponding working state, the vehicle controller controls the vehicle display screen to pop up a 10s alarm message to remind the user to replace the electric horn. Therefore, according to the predicted service life of the electric horn, the electric horn can be maintained and replaced within its optimal service life to ensure the performance of the car audio equipment and driving safety.

[0070] In summary, the beneficial effects of the technical solution of this application are as follows:

[0071] 1. Accuracy: This application continuously collects the sound signals emitted by the electric horn through the microphone in the car, and analyzes these signals, which can accurately monitor the changes in the performance of the electric horn and then infer its service life. This solves the problem in the prior art that the service life of the electric horn cannot be accurately judged due to the strong subjectivity of artificial hearing, and avoids the actual service life of the electric horn exceeding its optimal service life, thereby affecting the performance of the car audio equipment and driving safety.

[0072] 2. Accuracy: This application uses a microphone inside the car to collect the sound emitted by the electric horn, which can directly reflect the actual sound characteristics of the electric horn. This is more accurate than the method of judging the service life of the electric horn by measuring the resistance, current and other parameters of the electric horn in the prior art. Because there are certain differences between the resistance, current and other parameters and the actual sound characteristics of the electric horn, it is impossible to accurately reflect the service life of the electric horn.

[0073] 3. Reduce maintenance costs: This application can accurately determine the service life of the electric horn, avoiding the actual service life of the electric horn being underestimated, thereby reducing the frequency of repair and replacement and reducing maintenance costs. It solves the problem in the prior art that the actual service life of the electric horn is underestimated due to the difference between the measurement parameters and the actual sound characteristics, thereby increasing the frequency of repair and replacement and increasing maintenance costs.

[0074] 4. Intelligence: This application uses sound signal processing technology and vehicle electronic control technology to achieve intelligent management of the service life of the electric horn. This is more intelligent than the existing method that requires manual judgment of the service life of the electric horn.

[0075] It should be understood that, although the steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0076] The present application also provides a device for detecting the service life of an electric horn. Figure 4 The present invention shows a device for detecting the service life of an electric horn, comprising an acquisition module 402, an extraction module 404 and a detection module 406. The acquisition module 402 is used to acquire a sound signal emitted by a current electric horn collected by a vehicle microphone; the extraction module 404 is used to extract a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and the detection module 406 is used to detect the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn.

[0077] In one embodiment, the current sound characteristic parameter value of the electric horn includes one or more of a sound pressure level, a center frequency value, and a frequency bandwidth value.

[0078] In one embodiment, an electric horn service life detection device also includes an acquisition module for obtaining a current working state of the current electric horn in response to receiving a sound signal emitted by the current electric horn; detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn, including: detecting the service life of the current electric horn according to the current working state and sound characteristic parameter value of the current electric horn.

[0079] In one of the embodiments, after the step of obtaining the current working state of the current electric horn, it also includes: determining an electric horn life detection model according to the current working state of the current electric horn, the electric horn life detection model includes a relationship between the service life of the electric horn and the sound characteristic parameter; detecting the service life of the current electric horn according to the current working state of the current electric horn and the sound characteristic parameter value, including: inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model.

[0080] In one embodiment, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a normal working state, a first electric horn life detection model is determined, the first electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the normal working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, the normal working state is determined by the working voltage and / or working current of the electric horn; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model, and the service life of the current electric horn output by the electric horn life detection model is obtained, including: the sound characteristic parameter values ​​of the current electric horn are input into the first electric horn life detection model, and the service life of the current electric horn output by the first electric horn life detection model is obtained.

[0081] In one embodiment, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a faulty working state, a second electric horn life detection model is determined, the second electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the faulty working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the faulty working state is determined by the working voltage and / or working current of the electric horn; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model, including: the sound characteristic parameter values ​​of the current electric horn are input into the second electric horn life detection model to obtain the service life of the current electric horn output by the second electric horn life detection model.

[0082] In one of the embodiments, an electric horn life detection model is determined according to the current working state of the current electric horn, including: when the current working state of the current electric horn is a specific working state, a third electric horn life detection model is determined, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the specific working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, the specific working state is detected and determined by detecting the vehicle environment through a vehicle sensor; the sound characteristic parameter values ​​of the current electric horn are input into the electric horn life detection model, and the service life of the current electric horn output by the electric horn life detection model is obtained, including: the sound characteristic parameter values ​​of the current electric horn are input into the third electric horn life detection model, and the service life of the current electric horn output by the third electric horn life detection model is obtained.

[0083] In one embodiment, the specific working state is a low temperature environment state, a high temperature environment state or a humid environment state, and the low temperature environment state and the high temperature environment state are both detected and determined by a vehicle temperature sensor, and the humid environment state is detected and determined by a vehicle air quality sensor; when the specific working state is a low temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the low temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a high temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the high temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a humid environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the humid environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn.

[0084] In one embodiment, the first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model all include a relationship between the service life of the electric horn and the basic parameter value corresponding to the service life, the sound pressure level characteristic parameter, the basic parameter value of the sound pressure level characteristic parameter, the center frequency characteristic parameter, the basic parameter value of the center frequency characteristic parameter, the bandwidth characteristic parameter, and the basic value of the bandwidth characteristic parameter; wherein the basic parameter value corresponding to the service life in the first electric horn life detection model is greater than the basic parameter value corresponding to the service life in the third electric horn life detection model, and the basic parameter value corresponding to the service life in the third electric horn life detection model is greater than the basic parameter value corresponding to the service life in the second electric horn life detection model.

[0085] In one embodiment, the relationship formula of the first electric horn life detection model, the relationship formula of the second electric horn life detection model and the relationship formula of the third electric horn life detection model all further include the weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter; the weight of the sound pressure level characteristic parameter in the relationship formula of the first electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model, and the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the second electric horn life detection model.

[0086] In one embodiment, the electric horn life detection model is a linear regression model.

[0087] In one embodiment, an electric horn service life detection device also includes a prompt module, which is used to record the service life of the current electric horn obtained each time according to the current working state and sound characteristic parameter value of the current electric horn; among the multiple recorded service lives of the current electric horn, when the cumulative value of the number of service lives in any working state that is less than a set life threshold is greater than a set number, the vehicle display screen is controlled to display a prompt message to prompt the user to replace the current electric horn.

[0088] For the specific definition of an electric horn service life detection device, please refer to the definition of an electric horn service life detection method mentioned above, which will not be repeated here. Each module in the above-mentioned electric horn service life detection device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the vehicle controller in the form of hardware, or can be stored in the memory of the vehicle controller in the form of software, so that the processor can call and execute the corresponding operations of the above modules.

[0089] In one embodiment, a vehicle controller is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented: obtaining a sound signal emitted by a current electric horn collected by a vehicle microphone; extracting a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn.

[0090] In one embodiment, the current sound characteristic parameter value of the electric horn includes one or more of a sound pressure level, a center frequency value, and a frequency bandwidth value.

[0091] In one of the embodiments, when the processor executes the computer program, the following steps are also implemented: in response to receiving a sound signal emitted by the current electric horn, the current working state of the current electric horn is obtained; when the processor executes the computer program to implement the above-mentioned step of detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn, the following steps are specifically implemented: detecting the service life of the current electric horn according to the current working state and the sound characteristic parameter value of the current electric horn.

[0092] In one of the embodiments, when the processor executes the computer program, the following steps are also implemented: determining an electric horn life detection model according to the current working state of the current electric horn, the electric horn life detection model including a relationship between the service life of the electric horn and the sound characteristic parameters; when the processor executes the computer program to implement the above-mentioned step of detecting the service life of the current electric horn according to the current working state of the current electric horn and the sound characteristic parameter value, the following steps are specifically implemented: inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model.

[0093] In one embodiment, when the processor executes a computer program to implement the above-mentioned step of determining the electric horn life detection model according to the current working state of the current electric horn, the following steps are specifically implemented: when the current working state of the current electric horn is a normal working state, a first electric horn life detection model is determined, and the first electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the normal working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the normal working state is determined by the working voltage and / or working current of the electric horn; when the processor executes a computer program to implement the above-mentioned step of inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model, the following steps are specifically implemented: inputting the sound characteristic parameter values ​​of the current electric horn into the first electric horn life detection model, and obtaining the service life of the current electric horn output by the first electric horn life detection model.

[0094] In one embodiment, when the processor executes a computer program to implement the above-mentioned step of determining the electric horn life detection model according to the current working state of the current electric horn, the following steps are specifically implemented: when the current working state of the current electric horn is a faulty working state, a second electric horn life detection model is determined, and the second electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the faulty working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the faulty working state is determined by the working voltage and / or working current of the electric horn; when the processor executes a computer program to implement the above-mentioned step of inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model, the following steps are specifically implemented: inputting the sound characteristic parameter values ​​of the current electric horn into the second electric horn life detection model to obtain the service life of the current electric horn output by the second electric horn life detection model.

[0095] In one of the embodiments, when the processor executes a computer program to implement the above-mentioned step of determining the electric horn life detection model according to the current working state of the current electric horn, the following steps are specifically implemented: when the current working state of the current electric horn is a specific working state, a third electric horn life detection model is determined, and the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the specific working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the specific working state is detected and determined by the vehicle sensor detecting the vehicle environment; when the processor executes a computer program to implement the above-mentioned step of inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model, the following steps are specifically implemented: inputting the sound characteristic parameter values ​​of the current electric horn into the third electric horn life detection model, and obtaining the service life of the current electric horn output by the third electric horn life detection model.

[0096] In one embodiment, the specific working state is a low temperature environment state, a high temperature environment state or a humid environment state, and the low temperature environment state and the high temperature environment state are both detected and determined by a vehicle temperature sensor, and the humid environment state is detected and determined by a vehicle air quality sensor; when the specific working state is a low temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the low temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a high temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the high temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a humid environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the humid environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn.

[0097] In one embodiment, the first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model all include a relationship between the service life of the electric horn and the basic parameter value corresponding to the service life, the sound pressure level characteristic parameter, the basic parameter value of the sound pressure level characteristic parameter, the center frequency characteristic parameter, the basic parameter value of the center frequency characteristic parameter, the bandwidth characteristic parameter, and the basic value of the bandwidth characteristic parameter; wherein the basic parameter value corresponding to the service life in the first electric horn life detection model is greater than the basic parameter value corresponding to the service life in the third electric horn life detection model, and the basic parameter value corresponding to the service life in the third electric horn life detection model is greater than the basic parameter value corresponding to the service life in the second electric horn life detection model.

[0098] In one embodiment, the relationship formula of the first electric horn life detection model, the relationship formula of the second electric horn life detection model and the relationship formula of the third electric horn life detection model all further include the weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter; the weight of the sound pressure level characteristic parameter in the relationship formula of the first electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model, and the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the second electric horn life detection model.

[0099] In one embodiment, the electric horn life detection model is a linear regression model.

[0100] In one of the embodiments, the processor further implements the following steps when executing the computer program: recording the service life of the current electric horn obtained each time according to the current working state of the current electric horn and the sound characteristic parameter value detection; among the multiple recorded service lives of the current electric horn, when the cumulative value of the number of service lives of any working state that is less than a set life threshold is greater than a set number, controlling the vehicle display screen to display a prompt message to prompt the user to replace the current electric horn.

[0101] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining a sound signal emitted by a current electric horn collected by a vehicle microphone; extracting a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; and detecting the service life of the current electric horn based on the sound characteristic parameter value of the current electric horn.

[0102] In one embodiment, the sound characteristic parameter value of the current electric horn includes one or more of a sound pressure level, a center frequency value, and a frequency bandwidth value.

[0103] In one of the embodiments, when the computer program is executed by the processor, the following steps are also implemented: in response to receiving a sound signal emitted by the current electric horn, the current working state of the current electric horn is obtained; when the computer program is executed by the processor to implement the above-mentioned step of detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn, the following steps are specifically implemented: detecting the service life of the current electric horn according to the current working state and the sound characteristic parameter value of the current electric horn.

[0104] In one of the embodiments, when the computer program is executed by the processor, the following steps are also implemented: an electric horn life detection model is determined according to the current working state of the current electric horn, and the electric horn life detection model includes a relationship between the service life of the electric horn and the sound characteristic parameters; when the computer program is executed by the processor to implement the above-mentioned step of detecting the service life of the current electric horn according to the current working state of the current electric horn and the sound characteristic parameter value, the following steps are specifically implemented: the sound characteristic parameter value of the current electric horn is input into the electric horn life detection model, and the service life of the current electric horn output by the electric horn life detection model is obtained.

[0105] In one embodiment, when a computer program is executed by a processor to implement the above-mentioned step of determining an electric horn life detection model according to the current working state of the current electric horn, the following steps are specifically implemented: when the current working state of the current electric horn is a normal working state, a first electric horn life detection model is determined, and the first electric horn life detection model is obtained by training the sound characteristic parameter values ​​of a sample electric horn under a normal working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the normal working state is determined by the working voltage and / or working current of the electric horn; when a computer program is executed by a processor to implement the above-mentioned step of inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model, the following steps are specifically implemented: inputting the sound characteristic parameter values ​​of the current electric horn into the first electric horn life detection model, and obtaining the service life of the current electric horn output by the first electric horn life detection model.

[0106] In one embodiment, when the computer program is executed by the processor to implement the above-mentioned step of determining the electric horn life detection model according to the current working state of the current electric horn, the following steps are specifically implemented: when the current working state of the current electric horn is a faulty working state, a second electric horn life detection model is determined, and the second electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the faulty working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the faulty working state is determined by the working voltage and / or working current of the electric horn; when the computer program is executed by the processor to implement the above-mentioned step of inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model, the following steps are specifically implemented: inputting the sound characteristic parameter values ​​of the current electric horn into the second electric horn life detection model to obtain the service life of the current electric horn output by the second electric horn life detection model.

[0107] In one embodiment, when the computer program is executed by the processor to implement the above-mentioned step of determining the electric horn life detection model according to the current working state of the current electric horn, the following steps are specifically implemented: when the current working state of the current electric horn is a specific working state, a third electric horn life detection model is determined, and the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn under the specific working state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn, and the specific working state is detected and determined by the vehicle sensor detecting the vehicle environment; when the computer program is executed by the processor to implement the above-mentioned step of inputting the sound characteristic parameter values ​​of the current electric horn into the electric horn life detection model, and obtaining the service life of the current electric horn output by the electric horn life detection model, the following steps are specifically implemented: inputting the sound characteristic parameter values ​​of the current electric horn into the third electric horn life detection model, and obtaining the service life of the current electric horn output by the third electric horn life detection model.

[0108] In one embodiment, the specific working state is a low temperature environment state, a high temperature environment state or a humid environment state, and the low temperature environment state and the high temperature environment state are both detected and determined by a vehicle temperature sensor, and the humid environment state is detected and determined by a vehicle air quality sensor; when the specific working state is a low temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the low temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a high temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the high temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; when the specific working state is a humid environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the humid environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn.

[0109] In one embodiment, the first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model all include a relationship between the service life of the electric horn and the basic parameter value corresponding to the service life, the sound pressure level characteristic parameter, the basic parameter value of the sound pressure level characteristic parameter, the center frequency characteristic parameter, the basic parameter value of the center frequency characteristic parameter, the bandwidth characteristic parameter, and the basic value of the bandwidth characteristic parameter; wherein the basic parameter value corresponding to the service life in the first electric horn life detection model is greater than the basic parameter value corresponding to the service life in the third electric horn life detection model, and the basic parameter value corresponding to the service life in the third electric horn life detection model is greater than the basic parameter value corresponding to the service life in the second electric horn life detection model.

[0110] In one embodiment, the relationship formula of the first electric horn life detection model, the relationship formula of the second electric horn life detection model and the relationship formula of the third electric horn life detection model all further include the weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter; the weight of the sound pressure level characteristic parameter in the relationship formula of the first electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model, and the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the second electric horn life detection model.

[0111] In one embodiment, the electric horn life detection model is a linear regression model.

[0112] In one of the embodiments, when the computer program is executed by the processor, the following steps are also implemented: recording the service life of the current electric horn obtained each time according to the current working state of the current electric horn and the sound characteristic parameter value detection; among the multiple recorded service lives of the current electric horn, when the cumulative value of the number of service lives of any working state that is less than a set life threshold is greater than a set number, controlling the vehicle display screen to display a prompt message to prompt the user to replace the current electric horn.

[0113] The present application also provides a vehicle, in which the vehicle controller of the above embodiment is configured. In other embodiments, the vehicle controller is configured with a vehicle. Figure 5 As shown, the vehicle may also include the system solution which mainly consists of a vehicle electric horn 300, a vehicle microphone 400, a vehicle controller, a vehicle display screen 500, a body domain controller 200, a vehicle temperature sensor 600 and a vehicle air quality sensor 700.

[0114] Specifically, the vehicle implements a method for detecting the service life of an electric horn in the above embodiment, see Figure 6 As shown:

[0115] 1. The user presses the electric horn button on the steering wheel;

[0116] 2. The vehicle body domain controller detects that the electric horn button is pressed and starts to provide current to drive the electric horn;

[0117] 3. The vehicle electric horn emits a sound with a frequency of 420+35HZ and a sound pressure within the range of 105-118db;

[0118] 4. The microphone in the car collects the sound signal from the electric horn, converts it into a digital signal and transmits it to the car computer;

[0119] 5. After receiving the sound characteristic parameters of the electric horn fed back by the microphone, the vehicle computer starts to call the vehicle temperature sensor, vehicle air quality sensor, working current and working voltage of the electric horn to determine the working status of the electric horn;

[0120] 6. After the vehicle computer determines the working status of the electric horn, the collected electric horn sound characteristic parameter values ​​and working status are input into the electric horn life detection model module;

[0121] 7. The electric horn life detection model calculates the remaining service life of the electric horn in the current working state and stores it in the vehicle database of the vehicle computer;

[0122] 8. Before updating the on-board database of the electric horn's service life each time, the vehicle computer needs to record the service life under each working state. When the service life of the electric horn is less than 20 hours for 10 times in total under the corresponding working state, the vehicle computer controls the vehicle display screen to pop up a 10s alarm message to remind the user to replace the electric horn.

[0123] The electric horn service life detection method of the above embodiment is integrated into the electronic control system of the vehicle to realize automatic monitoring and prediction of the service life of the electric horn, thereby improving the intelligence level of the system. At the same time, the collected sound signals and prediction results are stored in the vehicle database for data query and analysis, providing data support for subsequent maintenance and replacement.

[0124] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0125] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0126] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A method for detecting the service life of an electric horn, characterized in that: The method comprises: Acquire the sound signal emitted by the current electric horn collected by the vehicle microphone; Extracting a sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; The service life of the current electric horn is detected according to the sound characteristic parameter value of the current electric horn.

2. The method according to claim 1, characterized in that The current sound characteristic parameter value of the electric horn includes one or more of a sound pressure level, a center frequency value, and a frequency bandwidth value.

3. The method according to claim 2, characterized in that The method further comprises: In response to receiving the sound signal emitted by the current electric horn, obtaining the current working state of the current electric horn; The detecting the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn comprises: The service life of the current electric horn is detected according to the current working state and the sound characteristic parameter value of the current electric horn.

4. The method according to claim 3, characterized in that After the step of obtaining the current working state of the current electric horn, the method further includes: Determining an electric horn life detection model according to the current working state of the current electric horn, wherein the electric horn life detection model includes a relationship between the service life of the electric horn and the sound characteristic parameters; The detecting the service life of the current electric horn according to the current working state and the sound characteristic parameter value of the current electric horn comprises: The sound characteristic parameter value of the current electric horn is input into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model.

5. The method according to claim 4, characterized in that The step of determining the electric horn life detection model according to the current working state of the current electric horn includes: When the current working state of the current electric horn is a normal working state, determining a first electric horn life detection model, wherein the first electric horn life detection model is obtained by training the sound characteristic parameter value of a sample electric horn under a normal working state and the sample service life corresponding to the sound characteristic parameter value of the sample electric horn, wherein the normal working state is determined by the working voltage and / or working current of the electric horn; The step of inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model comprises: The sound characteristic parameter value of the current electric horn is input into the first electric horn life detection model to obtain the service life of the current electric horn output by the first electric horn life detection model.

6. The method according to claim 5, characterized in that The step of determining the electric horn life detection model according to the current working state of the current electric horn includes: When the current working state of the current electric horn is a faulty working state, determining a second electric horn life detection model, the second electric horn life detection model is obtained by training the sound characteristic parameter value of the sample electric horn in the faulty working state and the sample service life corresponding to the sound characteristic parameter value of the sample electric horn, the faulty working state is determined by the working voltage and / or working current of the electric horn; The step of inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model comprises: The sound characteristic parameter value of the current electric horn is input into the second electric horn life detection model to obtain the service life of the current electric horn output by the second electric horn life detection model.

7. The method according to claim 6, characterized in that The step of determining the electric horn life detection model according to the current working state of the current electric horn includes: When the current working state of the current electric horn is a specific working state, determining a third electric horn life detection model, wherein the third electric horn life detection model is obtained by training the sound characteristic parameter value of the sample electric horn under the specific working state and the sample service life corresponding to the sound characteristic parameter value of the sample electric horn, wherein the specific working state is detected and determined by detecting the vehicle environment through a vehicle sensor; The step of inputting the sound characteristic parameter value of the current electric horn into the electric horn life detection model to obtain the service life of the current electric horn output by the electric horn life detection model comprises: The sound characteristic parameter value of the current electric horn is input into the third electric horn life detection model to obtain the service life of the current electric horn output by the third electric horn life detection model.

8. The method according to claim 7, characterized in that The specific working state is a low temperature environment state, a high temperature environment state or a humid environment state, the low temperature environment state and the high temperature environment state are both detected and determined by a vehicle temperature sensor, and the humid environment state is detected and determined by a vehicle air quality sensor; When the specific working state is a low temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the low temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; When the specific working state is a high temperature environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of the sample electric horn in the high temperature environment state and the sample service life corresponding to the sound characteristic parameter values ​​of the sample electric horn; When the specific working state is a humid environment state, the third electric horn life detection model is obtained by training the sound characteristic parameter values ​​of sample electric horns in a humid environment state and the sample service lives corresponding to the sound characteristic parameter values ​​of the sample electric horns.

9. The method according to claim 7, characterized in that: The first electric horn life detection model, the second electric horn life detection model and the third electric horn life detection model all include a relationship between the service life of the electric horn and a basic parameter value corresponding to the service life, a sound pressure level characteristic parameter, a basic parameter value of the sound pressure level characteristic parameter, a center frequency characteristic parameter, a basic parameter value of the center frequency characteristic parameter, a bandwidth characteristic parameter, and a basic value of the bandwidth characteristic parameter; Among them, the basic parameter value corresponding to the service life in the first electric horn life detection model is greater than the basic parameter value corresponding to the service life in the third electric horn life detection model, and the basic parameter value corresponding to the service life in the third electric horn life detection model is greater than the basic parameter value corresponding to the service life in the second electric horn life detection model.

10. The method according to claim 9, characterized in that The relationship formula of the first electric horn life detection model, the relationship formula of the second electric horn life detection model and the relationship formula of the third electric horn life detection model all further include the weight of the sound pressure level characteristic parameter, the weight of the center frequency characteristic parameter and the weight of the bandwidth characteristic parameter; The weight of the sound pressure level characteristic parameter in the relationship formula of the first electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model, and the weight of the sound pressure level characteristic parameter in the relationship formula of the third electric horn life detection model is less than the weight of the sound pressure level characteristic parameter in the relationship formula of the second electric horn life detection model.

11. The method according to claim 4, characterized in that The electric horn life detection model is a linear regression model.

12. The method according to claim 3, characterized in that The method further comprises: Recording the service life of the current electric horn obtained each time according to the current working state and the sound characteristic parameter value of the current electric horn; Among the multiple recorded service lives of the current electric horn, when the cumulative value of the number of service lives in any working state that is less than the set life threshold is greater than the set number, the vehicle display screen is controlled to display a prompt message to prompt the user to replace the current electric horn.

13. A device for detecting the service life of an electric horn, characterized in that: The device comprises: An acquisition module, used to acquire a sound signal emitted by a current electric horn collected by a vehicle microphone; An extraction module, used to extract the sound characteristic parameter value of the current electric horn from the sound signal emitted by the current electric horn; The detection module is used to detect the service life of the current electric horn according to the sound characteristic parameter value of the current electric horn.

14. A vehicle controller, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1 to 12 when executing the computer program.

15. A vehicle, characterized in that: The vehicle is equipped with the vehicle controller according to claim 14.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.

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