Method and device for anti-interference measurement of instrument panel buzzer

Abstract

The invention relates to the field of buzzer detection, in particular to an anti-interference method and device for measuring a buzzer of an instrument panel, and the method comprises the steps: obtaining m duty ratio values of the buzzer of the instrument panel in a noiseless environment through a waveform detection circuit and a sound detection circuit, and carrying out the fitting of the m duty ratio values, and obtaining a fitting function, m being a positive integer greater than 2; when detection is carried out in any environment, a value obtained by the waveform detection circuit is substituted into a fitting function to obtain a fitting output value; if the fitting output value, the duty ratio of the output of the sound detection circuit and the wave crest interval are applied in a set threshold value, the buzzer sounds normally, otherwise, the buzzer sounds abnormally; a test system can accurately judge whether the buzzer is normal or not, and defective buzzer products can be effectively intercepted.

Description

Technical Field

[0001] The present invention relates to the field of buzzer detection, and particularly to a method and device for measuring a dashboard buzzer with anti-interference. Background Art

[0002] Currently, it is possible to detect by having a person listen to the buzzer's beep or using a sound acquisition circuit to convert external sound into a square wave. However, for manual testing of the buzzer, testers need to listen to whether the buzzer beeps normally when testing the dashboard, which easily leads to situations of missing or mishearing the beep; while using the method of collecting external sound with a sound acquisition circuit, due to various noises existing on the production line that will interfere with the detection, it causes the test system to be unable to determine whether it is the sound of the buzzer or external noise, and it is easy to judge defective products as non-defective products. Summary of the Invention

[0003] In order to be able to intercept defective buzzer products, the present invention proposes a method for measuring a dashboard buzzer with anti-interference, which specifically includes the following steps:

[0004] Using a waveform detection circuit and a sound detection circuit to obtain m duty ratios of the dashboard buzzer in a noise-free environment for fitting to obtain a fitting function, where m is a positive integer greater than 2;

[0005] When detecting in any environment, substitute the value obtained by the waveform detection circuit into the fitting function to obtain a fitting output value;

[0006] If the fitting output value, the duty ratio output by the sound detection circuit, and the peak interval are within the set threshold, the buzzer beeps normally, otherwise the beep is abnormal.

[0007] Further, the process of obtaining the fitting function includes:

[0008] Mark a set of waveform detection circuit and sound detection circuit obtained at the i-th sampling point as (x i , y i ), i = {1, 2,..., m};

[0009] Use a unary polynomial function to generate an m-th degree polynomial, substitute the x of the waveform detection circuit in all sampling points i into the polynomial and calculate the fitting values of all sampling points;

[0010] Calculate the error between the fitting value of the sampling point and the y of the sound detection circuit i to obtain a set of fitting coefficients that minimize the error value, and obtain the fitting function.

[0011] Further, the process of obtaining a set of fitting coefficients that minimize the error value includes:

[0012] Take the partial derivative of the error value with respect to each coefficient respectively to obtain m + 1 partial derivative equations;

[0013] Let each partial derivative value be zero, and substitute the m groups of waveform detection circuits and sound detection circuits into the partial derivative equations to construct a system of equations;

[0014] Solve the constructed system of equations to obtain the coefficients of the fitting function.

[0015] Furthermore, the error value is expressed as:

[0016]

[0017] where {a 0 , a 1 , …, a m} are the coefficients of the m-th degree polynomial.

[0018] Furthermore, the partial derivative equation of the j-th coefficient a j is expressed as:

[0019]

[0020] where {a 0 , a 1 , …, a m} are the coefficients of the m-th degree polynomial.

[0021] The present invention also provides a device for anti-interference measurement of a dashboard buzzer, including a waveform detection circuit, a sound detection circuit, a fitting module, and a discriminator, where:

[0022] The waveform detection circuit is used to detect the control square wave for controlling the buzzer of the vehicle dashboard;

[0023] The sound detection circuit is used to convert the sound of the buzzer into a square wave;

[0024] The fitting module is used to fit the square wave detected by the waveform detection circuit to obtain a fitted square wave value;

[0025] The discriminator is used to determine whether the difference in the duty ratio and the peak interval between the fitted square wave and the square wave of the sound detection circuit is greater than a set threshold. If it is greater, the detection result is that the buzzer is abnormal; otherwise, the detection result is that the buzzer is normal.

[0026] The present invention can determine whether the detected sound is external noise or the sound of the buzzer. If it is noise, the buzzer can be retested. Through this method, the test system can accurately determine whether the buzzer is normal and can effectively intercept defective buzzer products. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flowchart of a preferred embodiment of a method for anti-interference measurement of a dashboard buzzer according to the present invention;

[0028] Figure 2 It is a schematic diagram of the acquisition process of the fitting function in the present invention;

[0029] Figure 3 It is a flowchart of another preferred embodiment of a method for an anti-interference measurement instrument panel buzzer according to the present invention. Specific embodiments

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] The present invention proposes a method for an anti-interference measurement instrument panel buzzer, which specifically includes the following steps:

[0032] Use a waveform detection circuit and a sound detection circuit to obtain m duty ratios of the instrument panel buzzer in a noise-free environment for fitting to obtain a fitting function, where m is a positive integer greater than 2;

[0033] When detecting in any environment, substitute the value obtained by the waveform detection circuit into the fitting function to obtain a fitting output value;

[0034] If the fitting output value, the duty ratio output by the sound detection circuit, and the peak-to-peak interval are within the set threshold, the buzzer sounds normally; otherwise, the sound is abnormal.

[0035] Such as Figure 1 , in this embodiment, the host computer software sends a CAN message to notify the vehicle instrument panel to control the buzzer. At the same time, the host computer software notifies the lower computer waveform detection circuit and the sound detection circuit to start detection to ensure that the waveform is detected at the same moment each time; the vehicle instrument panel controls the buzzer by outputting a square wave to the buzzer pin. The waveform detection circuit is connected in parallel with the buzzer pin to obtain the waveform output by the instrument panel; at the same time, the buzzer sounds, and the sound detection circuit converts the sound into a square wave; in this way, the test system obtains two square wave waveforms, compares the duty ratio data of the two waveforms and the interval time between the peaks, and if it meets the conditions, it is determined that the buzzer sounds; if it does not meet the conditions, it can be retested immediately to avoid being judged as a defective product and then retested all. Generally, if the difference in the duty ratio data of the two waveforms and the interval time between the peaks is within the set threshold, it meets the conditions; otherwise, it does not meet the conditions.

[0036] In this embodiment, a standard function is required as a criterion for determining whether it is noise. There is a certain correlation between the waveforms obtained by the waveform detection circuit and the sound detection circuit. Quantifying this relationship yields a standard function. To make the obtained standard function as accurate as possible, data needs to be obtained in a quiet environment, and then the standard function is deduced based on the obtained data. This process is the learning stage.

[0037] When a new model of car dashboard needs to test the buzzer, the test first enters the learning stage. The dashboard is tested in an environment without noise. Since the buzzing frequency of the buzzer is changing, there are multiple waveforms with inconsistent periods and duty cycles in the square waves detected by each circuit. Twenty duty ratio values x obtained by the waveform detection circuit and twenty duty ratio values y of the waveforms obtained by the sound detection circuit are subjected to fitting operation to obtain a fitting function. This process is the learning stage. As Figure 2 The learning stage includes the following processes:

[0038] The host computer software sends a CAN message to notify the car dashboard to control the buzzer, and the dashboard outputs a square wave to control the buzzer;

[0039] The detection circuit is used to detect the waveform. In the present invention, the amplitude of the detected square wave is a fixed value, but the duty cycle is constantly changing;

[0040] m sets of duty ratio data are obtained. In this embodiment, m = 20, and the collected data is denoted as X;

[0041] After the buzzer sounds, the external sound is detected by the sound detection module and converted into a square wave. Twenty sets of duty ratio data are obtained, and the collected data is denoted as Y. The coefficient values of the fitting function are obtained through the 20 sets of data.

[0042] During normal testing, the x value is obtained through the detection circuit, and y' is calculated by substituting it into the fitting formula. The absolute value is taken by subtracting the duty ratio value y obtained by the sound detection module from y'. Those with the absolute value within the specified range are qualified. At the same time, the interval time between the two wave peaks is compared. If both the duty cycle and the wave peak interval time are within the specified range, it is determined that the buzzer is buzzing normally; otherwise, it is determined as noise. When it is determined as noise, repeated testing is immediately carried out. If the number of retests reaches the upper limit, the test fails (indicating that there is continuous noise interference during the test).

[0043] When there is no noise interference, the square waves obtained by the sound detection circuit and the waveform detection circuit have a certain correlation, which can be expressed by a function; when testing the buzzer normally, external sounds need to be detected. To distinguish between external noise and the sound of the buzzer, it is necessary to determine the square wave obtained by the sound detection circuit. Since there is no external interference in the waveform detection circuit, if these two square waves conform to the expression after being substituted into the function, they are determined to be qualified; if they do not conform to the expression, they are determined to be noise. To obtain an accurate function, the system needs to learn in a noise-free environment and fit the function after obtaining the data.

[0044] The polynomial fitting model is a commonly used machine learning method for fitting non-linear relationships in a dataset. It constructs a polynomial function on the input variables and uses the least squares method to fit the data. This model can adapt to various datasets. The duty cycle data ranges from 0 to 100 and belongs to non-linear data, so polynomial fitting is adopted. The specific fitting process includes the following steps:

[0045] In the learning stage, a set of data is obtained as {(x 1 ,y 1 )(x 2 ,y 2 )…(x m ,y m )} (in this application, m = 20). A certain point in the array can be represented as (x i ,y i ), where i = 1, 2, 3, …, m;

[0046] A unary polynomial function is used to generate a polynomial of degree m, which is expressed as:

[0047] z = a 0 x m + a 1 x m-1 + a 2 x m-2 +... + a m-1 x + a m

[0048] Among them, a 0 , a 1 ......a m are the coefficients of the polynomial. In this embodiment, the ordinate corresponding to the abscissa x 1 of the given sample point of the polynomial of degree m is:

[0049]

[0050] To compare all z i with y i in the sample pointsHow much difference there is is characterized by the sum of the squares of the errors / residuals (the sum of squared residuals is a quantity that measures the goodness of fit of a model in a linear model. It is a data processing method that approximately depicts or analogizes discrete point groups on a plane with a continuous curve to represent the functional relationship between coordinates). For the i-th sample point x i the fitted value and its corresponding true value, that is, the sample point y i The error between the values is expressed as:

[0051]

[0052] where ε i is the error value between the fitted value and the true value of the i-th sample x i .

[0053] The coefficient values of the fitting function are obtained by minimizing the error values, which specifically include the following steps:

[0054] Take the partial derivatives of the error values with respect to each coefficient to obtain m + 1 partial derivative equations; the obtained partial derivative equations are expressed as:

[0055] Let each partial derivative value be zero, that is and substitute m groups of waveform detection circuits and sound detection circuits into the partial derivative equations to construct a system of equations; the expanded partial derivative equation of the j-th coefficient a j is expressed as:

[0056]

[0057] Substitute m groups of waveform detection circuits and sound detection circuits into the above equations, and solve the constructed system of equations to obtain the coefficients of the fitting function.

[0058] In the test stage, substitute the value obtained by the waveform detection circuit as x into the formula to obtain the corresponding y' value. Compare y' as the theoretical value with the duty cycle y obtained by the actual sound detection circuit. Subtract y from y' and take the absolute value. Those with the absolute value within the specified range are qualified.

[0059] Normally, the buzzer will beep at a fixed frequency once and then pause for a while and then beep again. However, when the buzzer has a dry joint (i.e., poor soldering), the pause time of the buzzer will become irregular. In this abnormal situation, the interval time between two wave peaks will be different. Because the dashboard normally outputs a square wave, and the abnormal beeping of the buzzer causes the square wave of the sound detection module to be abnormal, so it can be judged by relying on the wave peak interval time.

[0060] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art will appreciate that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for anti-interference measurement of instrument panel buzzer, characterized in that: The specific steps include: The waveform detection circuit and the sound detection circuit are used to obtain m duty cycle values ​​of the instrument panel buzzer in a noise-free environment for fitting, and a fitting function is obtained, where m is a positive integer greater than 2; When testing in any environment, the value obtained by the waveform detection circuit is substituted into the fitting function to obtain the fitting output value; If the duty cycle of the fitted output value and the output of the sound detection circuit and the peak interval are within the set threshold, the buzzer will sound normally, otherwise it will sound abnormally.

2. The method for anti-interference measurement of instrument panel buzzer according to claim 1, characterized in that: The process of obtaining the fitting function includes: A set of waveform detection circuits and sound detection circuits obtained at the i-th sampling point is marked as (x i ,y i ),i={1,2,…,m}; A univariate polynomial function is used to generate an m-order polynomial, and all sampling points in the waveform detection circuit x i Substitute into the polynomial and calculate the fitting values ​​of all sampling points; Calculate the sampling point fitting value and the sound detection circuit y i The error between them is obtained, and a set of fitting coefficients that minimize the error value is obtained to obtain the fitting function.

3. The method for anti-interference measurement of instrument panel buzzer according to claim 2, characterized in that: The process of obtaining a set of fitting coefficients that minimizes the error value includes: Calculate the partial derivative of each coefficient for the error value and obtain m+1 partial derivative equations; Set each partial derivative value to zero, and substitute m groups of waveform detection circuits and sound detection circuits into the partial derivative equations to construct an equation group; Solving the constructed system of equations yields the coefficients of the fitted function.

4. A method for anti-interference measurement of instrument panel buzzer according to claim 2 or 3, characterized in that: The error value is expressed as: Among them, {a0,a1,…,a m } are the coefficients of the m-degree polynomial.

5. The method for anti-interference measurement of instrument panel buzzer according to claim 3, characterized in that: The jth coefficient a j The partial derivative equation is expressed as: Among them, {a0,a1,…,a m } are the coefficients of the m-degree polynomial.

6. A device for anti-interference measurement of instrument panel buzzer, characterized in that: It includes a waveform detection circuit, a sound detection circuit, a fitting module and a decision device, wherein: Waveform detection circuit, used to detect the control square wave used to control the buzzer on the car dashboard; A sound detection circuit is used to convert the buzzing sound of the buzzer into a square wave; A fitting module, used for fitting the square wave detected by the waveform detection circuit to obtain a fitting square wave value; The decision device is used to determine whether the difference in duty cycle and peak interval between the fitted square wave and the square wave of the sound detection circuit is greater than a set threshold. If so, the detection result is that the buzzer is abnormal; otherwise, the detection result is that the buzzer is normal.

7. The device for anti-interference measurement of instrument panel buzzer according to claim 6, characterized in that: The fitting module obtains the fitting square wave value through the fitting function, and the fitting function is expressed as: A set of waveform detection circuits and sound detection circuits obtained at the i-th sampling point is marked as (x i ,y i ),i={}1,2,…,m}; A univariate polynomial function is used to generate an m-order polynomial, and all sampling points in the waveform detection circuit x i Substitute into the polynomial and calculate the fitting values ​​of all sampling points; Calculate the sampling point fitting value and the sound detection circuit y i The error between them is obtained, and a set of fitting coefficients that minimize the error value is obtained to obtain the fitting function.

8. The device for anti-interference measurement of instrument panel buzzer according to claim 7, characterized in that: The process of obtaining a set of fitting coefficients that minimizes the error value includes: Calculate the partial derivative of each coefficient for the error value and obtain m+1 partial derivative equations; Set each partial derivative value to zero, and substitute m groups of waveform detection circuits and sound detection circuits into the partial derivative equations to construct an equation group; Solving the constructed system of equations yields the coefficients of the fitted function.

9. The device for anti-interference measurement of instrument panel buzzer according to claim 7 or 8, characterized in that: The error value is expressed as: Among them, {a0,a1,…,a m } are the coefficients of the m-degree polynomial.

10. The device for anti-interference measurement of instrument panel buzzer according to claim 7, characterized in that: The jth coefficient a j The partial derivative equation is expressed as: Among them, {a0,a1,…,a m } are the coefficients of the m-degree polynomial.

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