Equipment door plate control method, controller, equipment and storage medium

Abstract

The invention relates to an equipment door plate control method, a controller, equipment and a storage medium. The method comprises the following steps: acquiring an initial knocking signal; performing wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to a plurality of decomposition layers; updating the initial wavelet coefficient of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to the plurality of decomposition layers; performing wavelet reconstruction based on the target wavelet coefficients corresponding to the decomposition layers to obtain a target knocking signal; and generating a target control instruction corresponding to the target knocking signal. The improved threshold function is adopted to carry out wavelet denoising processing on the knocking signal, high-frequency noise in the knocking signal can be effectively filtered out, the accuracy of recognizing the knocking signal is improved, and then the equipment door plate is accurately controlled according to the knocking signal to achieve the expected effect corresponding to the knocking action of a user.

Description

Technical Field

[0001] The present invention relates to the field of electrical technology, and in particular to a device door panel control method, a controller, a device and a storage medium. Background Art

[0002] Knocking to open the door has become a relatively new interactive method in home appliances with high recognition by consumers due to its advantages such as flexibility and ease of operation, such as knocking to open the door of a dishwasher or a disinfection cabinet. This method sets a knock sensor on the door of the home appliance to receive the user's knock command. The sensor converts the physical knock into an electrical signal (i.e., a knock signal) and sends the electrical signal to the control chip. The control chip recognizes the electrical signal and decides whether to execute the door opening action.

[0003] In order to achieve knock control of home appliances, the existing technology generally uses the traditional average value filtering method to process the knock signal, but this method cannot filter out the abnormal vibration signal introduced during sensor acquisition, which can easily lead to errors in knock signal recognition. Summary of the invention

[0004] In order to solve the above technical problems, the present invention discloses a device door panel control method, controller, device and storage medium, which uses an improved threshold function to perform wavelet denoising on the knock signal, which can effectively filter out high-frequency noise in the knock signal and improve the accuracy of identifying the knock signal, and then accurately control the device door panel according to the knock signal to achieve the expected effect corresponding to the user's knocking action.

[0005] In order to achieve the above object, the present invention provides a device door panel control method, comprising:

[0006] Acquire an initial knocking signal; the initial knocking signal represents knocking action information on a door panel of a target device;

[0007] Performing wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of a plurality of decomposition layers;

[0008] The initial wavelet coefficients of each layer are updated based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients;

[0009] Perform wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal;

[0010] A target control instruction corresponding to the target knocking signal is generated; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

[0011] In an optional embodiment, the initial wavelet coefficients include low-frequency wavelet coefficients and high-frequency wavelet coefficients, and the initial percussion signal is subjected to wavelet decomposition to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers, including:

[0012] Performing empirical mode decomposition on the initial knocking signal to obtain a low-frequency intrinsic mode function component and a high-frequency intrinsic mode function component;

[0013] The high-frequency intrinsic mode function components are discretely decomposed by using a preset low-pass filter and a preset high-pass filter according to a preset number of decomposition layers to obtain low-frequency wavelet coefficients and high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers.

[0014] In an optional embodiment, the updating of the initial wavelet coefficients of each layer based on a preset threshold function to obtain the target wavelet coefficients corresponding to each of the multiple decomposition layers includes:

[0015] Determine the preset thresholds corresponding to the high-frequency wavelet coefficients of each layer;

[0016] Based on the preset threshold and the preset threshold function, the high-frequency wavelet coefficients of each layer are updated to obtain updated high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers;

[0017] Based on the low-frequency wavelet coefficients corresponding to the multiple decomposition layers and the updated high-frequency wavelet coefficients, the target wavelet coefficients corresponding to the multiple decomposition layers are determined.

[0018] In an optional embodiment, determining the preset thresholds corresponding to the high-frequency wavelet coefficients of each layer includes:

[0019] Determining a fixed threshold based on the number of sampling points of the initial knock signal;

[0020] Based on the fixed threshold and the high-frequency wavelet coefficients of each layer, preset thresholds corresponding to the high-frequency wavelet coefficients of each layer are determined.

[0021] In an optional embodiment, before the initial wavelet coefficients of each layer are updated based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers, the method further includes:

[0022] Determine the function parameter corresponding to the high-frequency wavelet coefficient as the target parameter;

[0023] Determine a ratio between the absolute value of the target parameter and a preset threshold value corresponding to the target parameter as a preset ratio term, determine a difference between the absolute value of the target parameter and the preset threshold value corresponding to the target parameter as a preset difference term, determine a logarithmic function with respect to the preset ratio term as the preset logarithmic function, determine an exponential function with respect to the preset difference term as the preset exponential function, and determine a square function with respect to the preset difference term as the preset square function;

[0024] The preset threshold function is constructed based on the target parameter, a preset threshold corresponding to the target parameter, the preset logarithmic function, the preset exponential function and the preset square function.

[0025] In an optional embodiment, the updating of the high-frequency wavelet coefficients of each layer based on the preset threshold and the preset threshold function to obtain updated high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers includes:

[0026] For the high-frequency wavelet coefficient corresponding to each decomposition layer, when the absolute value of the high-frequency wavelet coefficient is less than the preset threshold value corresponding to the high-frequency wavelet coefficient, the preset value is determined as the updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient;

[0027] When the absolute value of the high-frequency wavelet coefficient is greater than or equal to a preset threshold corresponding to the high-frequency wavelet coefficient, the target parameter in the preset threshold function is replaced by the high-frequency wavelet coefficient to obtain an updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient.

[0028] In an optional embodiment, performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain the target knocking signal includes:

[0029] Performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a denoised high-frequency intrinsic mode function component;

[0030] Signal reconstruction is performed based on the low-frequency intrinsic mode function component and the denoised high-frequency intrinsic mode function component to obtain the target knocking signal.

[0031] The present invention also provides a device door panel controller, comprising:

[0032] A signal acquisition module, used to acquire an initial knocking signal; the initial knocking signal represents knocking action information on a door panel of a target device;

[0033] A wavelet decomposition module, used for performing wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers;

[0034] A wavelet coefficient updating module is used to update the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients;

[0035] A wavelet reconstruction module, used for performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal;

[0036] A control instruction generating module is used to generate a target control instruction corresponding to the target knocking signal; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

[0037] The present invention also provides a device, comprising:

[0038] A collection end, used for collecting knocking action information on a door panel of a target device, and converting the knocking action information into an initial knocking signal;

[0039] A device door panel controller is used to obtain the initial knocking signal; perform wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers; update the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients; perform wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal; generate a target control instruction corresponding to the target knocking signal; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

[0040] The present invention also provides a computer-readable storage medium, in which at least one instruction or at least one program is stored. The at least one instruction or the at least one program is loaded and executed by a processor to implement the device door panel control method as described above.

[0041] Implementing the embodiments of the present invention has the following beneficial effects:

[0042] The device door panel control method disclosed in the present invention constructs an improved threshold function based on the logarithmic function, exponential function and square function related to the function parameters corresponding to the wavelet coefficients, and uses the improved threshold function to perform wavelet denoising on the knock signal. Since the improved threshold function is not only continuous in the entire wavelet domain, but also reduces the deviation between the wavelet coefficients and the updated wavelet coefficients, it ensures that the knock signal after reconstruction will not be distorted. Under the premise of occupying the limited computing power and memory space of the single-chip microcomputer, the filtering of high-frequency noise in the knock signal is guaranteed to the greatest extent, thereby improving the accuracy of identifying the knock signal. By identifying the knock signal, the device door panel can be accurately controlled to achieve the expected effect corresponding to the user's knocking action. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the device door panel control method, controller, device and storage medium described in the present invention, the drawings required for the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 A schematic flow chart of a device door panel control method provided by an embodiment of the present invention;

[0045] Figure 2 A schematic diagram of a flow chart of a wavelet decomposition method provided by an embodiment of the present invention;

[0046] Figure 3 A comparison diagram of function images of different threshold functions provided by an embodiment of the present invention;

[0047] Figure 4 A schematic flow chart of a wavelet reconstruction method provided by an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of a knock signal denoising effect provided by an embodiment of the present invention;

[0049] Figure 6 A schematic structural diagram of a device door panel controller provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0051] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0052] Please refer to Figure 1 , which shows a flow chart of a device door panel control method provided by an embodiment of the present invention. This specification provides method operation steps as described in the embodiment or flow chart, but based on conventional or non-creative labor, more or fewer operation steps may be included. The order of steps listed in the embodiment is only one way of executing the order of many steps, and does not represent the only execution order. When the actual system or server product is executed, it can be executed in the order of the method shown in the embodiment or the accompanying drawings. Specifically, Figure 1 As shown, the device door panel control method is applied to a device door panel controller, and the method includes:

[0053] S101, obtaining an initial knocking signal; the initial knocking signal represents knocking action information on a door panel of a target device;

[0054] In the embodiments of this specification, the target device is a smart home appliance with a door panel, such as a washing machine, a refrigerator, an oven, a dishwasher, a disinfection cabinet, and other appliances;

[0055] In the embodiment of the present specification, the door panel of the target device has a built-in knock sensor. When the user knocks on the door panel, the knock sensor converts the physical knock into an initial knock signal, and sends the initial knock signal to the device door panel controller. The device door panel controller performs denoising on the initial knock signal to obtain a target knock signal, and then identifies the target knock signal, and generates a target control instruction based on the target knock signal, so that the door panel of the target device achieves the expected effect corresponding to the knock action information;

[0056] In the embodiments of the present specification, the knocking action information may include the number of knocks, the knocking position, etc. Different knocking action information corresponds to different expected effects. For example, knocking once displays data, knocking twice automatically opens the door, knocking on the left side starts working, and knocking on the right side stops working.

[0057] S103, performing wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of a plurality of decomposition layers;

[0058] In the embodiment of the present specification, the initial wavelet coefficients include low-frequency wavelet coefficients and high-frequency wavelet coefficients, and the initial percussion signal is subjected to wavelet decomposition to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers, including:

[0059] Performing empirical mode decomposition on the initial knocking signal to obtain a low-frequency intrinsic mode function component and a high-frequency intrinsic mode function component;

[0060] The high-frequency intrinsic mode function components are discretely decomposed by using a preset low-pass filter and a preset high-pass filter according to a preset number of decomposition layers to obtain low-frequency wavelet coefficients and high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers.

[0061] In the embodiments of the present specification, Empirical Mode Decomposition (EMD) is an adaptive signal processing method for decomposing complex nonlinear and non-stationary signals into a finite number of Intrinsic Mode Functions (IMFs) with different frequency characteristics; by performing Empirical Mode Decomposition on the initial knocking signal containing noise, low-frequency Intrinsic Mode Function components and high-frequency Intrinsic Mode Function components can be obtained;

[0062] In the embodiment of the present specification, since the noise mainly exists in the high-frequency intrinsic mode function component, it is necessary to perform denoising on the high-frequency intrinsic mode function component. Specifically, the high-frequency intrinsic mode function component is sequentially subjected to wavelet decomposition, wavelet coefficient update and wavelet reconstruction;

[0063] In the embodiment of the present specification, in the wavelet decomposition stage of the high-frequency intrinsic mode function component, since the continuous wavelet transform (CWT) is too redundant and is not applicable in an environment such as a single-chip microcomputer where the memory and computing power resources are relatively limited, it is necessary to use the discrete wavelet transform (DWT) to process the high-frequency intrinsic mode function component;

[0064] In the embodiments of this specification, Figure 2A flow chart of a wavelet decomposition method provided by an embodiment of the present invention, for a high-frequency intrinsic mode function component x[n], it is convolved with a low-pass decomposition coefficient g[n] (preset low-pass filter) and a high-pass decomposition coefficient h[n] (preset high-pass filter) defined by a preset discrete wavelet function, respectively, and then the first convolution result is downsampled with a step size of 2, so that the low-frequency wavelet coefficient A of the first layer can be obtained. 1 [n] and high frequency wavelet coefficient D 1 [n], continue to convert the low-frequency wavelet coefficients A of the first layer 1 [n] is convolved with the low-pass decomposition coefficient g[n] and the high-pass decomposition coefficient h[n] respectively, and the second convolution result is downsampled with a step size of 2 to obtain the low-frequency wavelet coefficient A of the second layer. 2 [n] and high frequency wavelet coefficient D 2 [n], repeat the above steps until the required preset decomposition layer number, the low-frequency wavelet coefficient A corresponding to the jth layer j [n] and high frequency wavelet coefficient D j [n] can be expressed as follows:

[0065] A j [n] = ∑A j-1 [k]×g[nk](j≥2)

[0066] D j [n] = ∑A j-1 [k]×h[nk](j≥2)

[0067] In the embodiments of this specification, the preset discrete wavelet function (i.e., the preset low-pass filter and the preset high-pass filter) and the preset number of decomposition layers can be set according to actual conditions;

[0068] In the embodiments of this specification, the low-frequency wavelet coefficients are also called approximation coefficients, which contain the overall shape and trend of the signal; the high-frequency wavelet coefficients are also called detail coefficients, which contain the specific details in the signal;

[0069] The embodiment of this specification decomposes the knock signal to obtain a low-frequency component and a high-frequency component. Since the noise mainly exists in the high-frequency component, the high-frequency component is subjected to wavelet denoising. By decomposing the knock signal and selecting the high-frequency component obtained after the decomposition for denoising, the denoising efficiency of the knock signal can be improved and the denoising effect of the knock signal can be enhanced.

[0070] S105, updating the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function, and a preset square function, and the preset logarithmic function, the preset exponential function, and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients;

[0071] In the embodiment of this specification, the initial knock signal is a time domain signal. After wavelet decomposition, the initial knock signal is transformed from the time domain to the wavelet domain. In the wavelet domain, the wavelet coefficient corresponding to the effective signal is large, and the wavelet coefficient corresponding to the noise is small. It is generally believed that the wavelet coefficient corresponding to the noise in the sensor in the wavelet domain satisfies the Gaussian white noise distribution and has the characteristics of Gaussian distribution. The wavelet coefficients of most noises are within the interval of [-3σ, 3σ]. By processing this part of the wavelet coefficients, the noise in the initial knock signal can be effectively filtered out;

[0072] In the embodiments of this specification, wavelet transform usually transforms noise to concentrate in the high-frequency area, that is, the wavelet coefficients corresponding to the noise are mainly high-frequency wavelet coefficients. Therefore, an improved threshold function (that is, a preset threshold function) can be used to update the high-frequency wavelet coefficients in the initial wavelet coefficients.

[0073] In the embodiment of the present specification, the updating of the initial wavelet coefficients of each layer based on the preset threshold function to obtain the target wavelet coefficients corresponding to each of the multiple decomposition layers includes:

[0074] Determine the preset thresholds corresponding to the high-frequency wavelet coefficients of each layer;

[0075] Based on the preset threshold and the preset threshold function, the high-frequency wavelet coefficients of each layer are updated to obtain updated high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers;

[0076] Based on the low-frequency wavelet coefficients corresponding to the multiple decomposition layers and the updated high-frequency wavelet coefficients, the target wavelet coefficients corresponding to the multiple decomposition layers are determined.

[0077] In the embodiment of this specification, the preset threshold corresponding to each layer can be determined based on the high-frequency wavelet coefficient corresponding to the layer;

[0078] In the embodiment of the present specification, the high-frequency wavelet coefficients corresponding to each layer can be updated based on the improved threshold function and the preset threshold corresponding to each layer, so as to obtain the updated high-frequency wavelet coefficients corresponding to each layer;

[0079] The embodiment of this specification uses an improved threshold function to perform wavelet denoising on the knock signal, which can effectively filter out high-frequency noise in the knock signal, improve the accuracy of identifying the knock signal, and then accurately control the device door panel according to the knock signal to achieve the expected effect corresponding to the user's knocking action.

[0080] In the embodiment of this specification, determining the preset thresholds corresponding to the high-frequency wavelet coefficients of each layer includes:

[0081] Determining a fixed threshold based on the number of sampling points of the initial knock signal;

[0082] Based on the fixed threshold and the high-frequency wavelet coefficients of each layer, preset thresholds corresponding to the high-frequency wavelet coefficients of each layer are determined.

[0083] In the embodiment of the present specification, a fixed threshold (sqtwolog) is selected for noise filtering, and its expression is as follows, where N represents the number of sampling points of the initial knocking signal.

[0084]

[0085] The fixed threshold λ obtained from the above formula * Multiplying the noise variance of each layer after wavelet decomposition to obtain the threshold λ corresponding to the layer, the noise variance σ of the jth layer j It can be calculated by the following formula:

[0086] σ j =median(|D j [k]|) / 0.6745 k=1,2,3…

[0087] In the above formula, D j [k] is the high-frequency wavelet coefficient of the jth layer. Therefore, the preset threshold corresponding to the jth layer, that is, the preset threshold λ corresponding to the high-frequency wavelet coefficient of the jth layer j for:

[0088] λ j =λ * ×σ j .

[0089] The embodiments of this specification use fixed thresholds and improved threshold functions to perform wavelet denoising on the knock signals, which can effectively filter out high-frequency noise in the knock signals, improve the accuracy of identifying knock signals, and then accurately control the device door panel according to the knock signals to achieve the expected effect corresponding to the user's knocking action.

[0090] In the embodiment of the present specification, before the initial wavelet coefficients of each layer are updated based on the preset threshold function to obtain the target wavelet coefficients corresponding to each of the multiple decomposition layers, the method further includes:

[0091] Determine the function parameter corresponding to the high-frequency wavelet coefficient as the target parameter;

[0092] Determine a ratio between the absolute value of the target parameter and a preset threshold value corresponding to the target parameter as a preset ratio term, determine a difference between the absolute value of the target parameter and the preset threshold value corresponding to the target parameter as a preset difference term, determine a logarithmic function with respect to the preset ratio term as the preset logarithmic function, determine an exponential function with respect to the preset difference term as the preset exponential function, and determine a square function with respect to the preset difference term as the preset square function;

[0093] The preset threshold function is constructed based on the target parameter, a preset threshold corresponding to the target parameter, the preset logarithmic function, the preset exponential function and the preset square function.

[0094] In the embodiments of this specification, in the prior art, the high-frequency wavelet coefficient update generally uses a hard threshold update function or a soft threshold update function, and their function expressions are as follows, where D j [k] is the high-frequency wavelet coefficient of the jth layer, is the updated high-frequency wavelet coefficient of the j-th layer, and λ is the preset threshold corresponding to the high-frequency wavelet coefficient of the j-th layer.

[0095] Hard threshold update function:

[0096]

[0097] Soft threshold update function:

[0098]

[0099] Based on this, there are some new threshold update functions, such as the following formula:

[0100]

[0101] It can be seen from the above formula that the processing of the hard threshold update function is relatively rough, which will cause additional oscillations in the reconstructed signal; the processing of the soft threshold update function is relatively smooth, and the updated high-frequency wavelet coefficients obtained after threshold processing have better continuity, but there is a constant deviation problem between the high-frequency wavelet coefficients and the updated high-frequency wavelet coefficients, resulting in signal loss; the new threshold update function converges to y=x slowly, which easily leads to distortion of the reconstructed signal.

[0102] The preset threshold function provided in the embodiment of this specification is shown in the following formula, where D j [k] is the function parameter (i.e., target parameter) corresponding to the high-frequency wavelet coefficient, is the preset ratio term, |Dj [k]|-λ is the preset difference term, is the default logarithmic function, exp(|D j [k]|-λ) is the preset exponential function, (|D j [k]|-λ) 2 is the preset square function.

[0103]

[0104] Figure 3 A comparison diagram of function images of different threshold functions provided by the embodiment of the present invention, Figure 3 It can be seen that the preset threshold function provided in the embodiment of this specification is not only continuous in the entire wavelet domain, but also makes the constant deviation between the high-frequency wavelet coefficient and the updated high-frequency wavelet coefficient further reduced, and can converge to y=x faster, ensuring that the reconstructed signal will not be distorted, and under the premise of occupying the limited computing power and memory space of the single-chip computer, it guarantees the filtering of high-frequency noise to the greatest extent, thereby improving the noise reduction effect of the knock signal, and further improving the accuracy of identifying the knock signal;

[0105] The embodiment of this specification uses an improved threshold function to perform wavelet denoising on the knock signal, which can effectively filter out high-frequency noise in the knock signal, improve the accuracy of identifying the knock signal, and then accurately control the device door panel according to the knock signal to achieve the expected effect corresponding to the user's knocking action.

[0106] In the embodiment of the present specification, the updating of the high-frequency wavelet coefficients of each layer based on the preset threshold and the preset threshold function to obtain the updated high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers includes:

[0107] For the high-frequency wavelet coefficient corresponding to each decomposition layer, when the absolute value of the high-frequency wavelet coefficient is less than the preset threshold value corresponding to the high-frequency wavelet coefficient, the preset value is determined as the updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient;

[0108] When the absolute value of the high-frequency wavelet coefficient is greater than or equal to a preset threshold corresponding to the high-frequency wavelet coefficient, the target parameter in the preset threshold function is replaced by the high-frequency wavelet coefficient to obtain an updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient.

[0109] In the embodiment of the present specification, after obtaining the high-frequency wavelet coefficients corresponding to each layer through wavelet decomposition, the high-frequency wavelet coefficients corresponding to each layer are substituted into the preset threshold function, that is, the target parameter D in the preset threshold function is j [k] is replaced by the high-frequency wavelet coefficients corresponding to each layer, and the updated high-frequency wavelet coefficients corresponding to each layer are obtained;

[0110] In the embodiment of the present specification, for a high-frequency wavelet coefficient corresponding to a certain layer, if the absolute value of the high-frequency wavelet coefficient is less than the preset threshold value corresponding to the high-frequency wavelet coefficient, the preset value is determined as the updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient, and the preset value is 0 here; if the absolute value of the high-frequency wavelet coefficient is greater than or equal to the preset threshold value corresponding to the high-frequency wavelet coefficient, the target parameter in the preset threshold function is replaced with the high-frequency wavelet coefficient to obtain the updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient;

[0111] The embodiment of this specification uses an improved threshold function to perform wavelet denoising on the knock signal, which can effectively filter out high-frequency noise in the knock signal, improve the accuracy of identifying the knock signal, and then accurately control the device door panel according to the knock signal to achieve the expected effect corresponding to the user's knocking action.

[0112] S107, performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal;

[0113] In the embodiment of the present specification, the wavelet reconstruction is performed based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain the target knocking signal, including:

[0114] Performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a denoised high-frequency intrinsic mode function component;

[0115] Signal reconstruction is performed based on the low-frequency intrinsic mode function component and the denoised high-frequency intrinsic mode function component to obtain the target knocking signal.

[0116] In the embodiment of this specification, the target wavelet coefficients include the low-frequency wavelet coefficients corresponding to each layer and the updated high-frequency wavelet coefficients;

[0117] In the embodiments of this specification, Figure 4 A schematic diagram of a flow chart of a wavelet reconstruction method provided by an embodiment of the present invention, Figure 4 Take the three-layer wavelet transform as an example. After updating the high-frequency wavelet coefficients corresponding to each layer, the high-frequency intrinsic mode function components can be reconstructed. The reconstruction formula is as follows:

[0118]

[0119] In the above formula, A j is the low-frequency wavelet coefficient corresponding to the jth layer after wavelet decomposition, is the updated high-frequency wavelet coefficient corresponding to the jth layer, g * 、h *are low-pass reconstruction coefficient and high-pass reconstruction coefficient respectively, x * [n] is the reconstructed time domain signal, that is, the high-frequency intrinsic mode function component after denoising. Since each layer is downsampled during discrete wavelet decomposition, in order to meet the Nyquist sampling condition, 0 must be padded between adjacent coefficients during reconstruction (that is, upsampling). After wavelet reconstruction, the denoised high-frequency intrinsic mode function component can be obtained. Then, the low-frequency intrinsic mode function component and the denoised high-frequency intrinsic mode function component are reconstructed to obtain the denoised knocking signal, that is, the target knocking signal.

[0120] The embodiment of this specification uses an improved threshold function to perform wavelet denoising on the knock signal, which can effectively filter out high-frequency noise in the knock signal, improve the accuracy of identifying the knock signal, and then accurately control the device door panel according to the knock signal to achieve the expected effect corresponding to the user's knocking action.

[0121] S109, generating a target control instruction corresponding to the target knocking signal; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

[0122] In the embodiment of the present specification, after obtaining the target knocking signal, the device door panel controller generates a target control instruction corresponding to the target knocking signal, and the target control instruction is used to control the door panel of the target device to be in a target control state corresponding to the user's knocking action;

[0123] In the embodiment of this specification, the target control state can be opening a door, displaying data, etc. For example, the target control state corresponding to knocking once is displaying data, and the target control state corresponding to knocking twice is opening a door;

[0124] In the embodiments of this specification, Figure 5 This is a schematic diagram of a knock signal denoising effect provided in an embodiment of the present invention. It can be seen from the figure that the wavelet denoising method provided in the embodiment of this specification can effectively filter out abnormal vibration signals in the initial knock signal.

[0125] It can be seen from the embodiments of the device door panel control method provided by the present invention that the embodiment of the present invention obtains an initial knocking signal; the initial knocking signal represents the knocking action information for the door panel of the target device; the initial knocking signal is subjected to wavelet decomposition to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers; the initial wavelet coefficients of each layer are updated based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients; wavelet reconstruction is performed based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal; a target control instruction corresponding to the target knocking signal is generated; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information. The technical solution provided in the embodiments of this specification uses an improved threshold function to perform wavelet denoising on the knock signal, which can effectively filter out high-frequency noise in the knock signal, improve the accuracy of identifying the knock signal, and then accurately control the device door panel according to the knock signal to achieve the expected effect corresponding to the user's knocking action.

[0126] The embodiment of the present invention also provides a device door panel controller, such as Figure 6 As shown, it is a structural schematic diagram of a device door panel controller provided by an embodiment of the present invention; specifically, the device includes:

[0127] The signal acquisition module 610 is used to acquire an initial knocking signal; the initial knocking signal represents the knocking action information on the door panel of the target device;

[0128] The wavelet decomposition module 620 is used to perform wavelet decomposition on the initial percussion signal to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers;

[0129] The wavelet coefficient updating module 630 is used to update the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients;

[0130] A wavelet reconstruction module 640 is used to perform wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal;

[0131] The control instruction generation module 650 is used to generate a target control instruction corresponding to the target knocking signal; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

[0132] An embodiment of the present invention further provides a device, comprising:

[0133] A collection end, used for collecting knocking action information on a door panel of a target device, and converting the knocking action information into an initial knocking signal;

[0134] A device door panel controller is used to obtain the initial knocking signal; perform wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers; update the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; the preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients; perform wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal; generate a target control instruction corresponding to the target knocking signal; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

[0135] An embodiment of the present invention also provides a computer-readable storage medium, which can be set in a device door panel controller to store at least one instruction, at least one program, code set or instruction set related to a device door panel control method in an implementation method embodiment. The at least one instruction, the at least one program, the code set or instruction set can be loaded and executed by the processor of the device door panel controller to implement the device door panel control method provided in the above method embodiment.

[0136] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store program codes.

[0137] It should be noted that the sequence of the embodiments of the present invention described above is for description only and does not represent the advantages and disadvantages of the embodiments. The above describes specific embodiments of this specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0138] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the controller embodiment and the device embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0139] Those skilled in the art will appreciate that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk, or an optical disk, etc.

[0140] The above disclosure is only a preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A device door panel control method, characterized in that: include: Get the initial knock signal; The initial knocking signal represents knocking action information on the door panel of the target device; Performing wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of a plurality of decomposition layers; The initial wavelet coefficients of each layer are updated based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; The preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, wherein the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients; Perform wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal; A target control instruction corresponding to the target knocking signal is generated; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

2. The device door panel control method according to claim 1, characterized in that: The initial wavelet coefficients include low-frequency wavelet coefficients and high-frequency wavelet coefficients. The initial percussion signal is subjected to wavelet decomposition to obtain initial wavelet coefficients corresponding to multiple decomposition layers, including: Performing empirical mode decomposition on the initial knocking signal to obtain a low-frequency intrinsic mode function component and a high-frequency intrinsic mode function component; The high-frequency intrinsic mode function components are discretely decomposed by using a preset low-pass filter and a preset high-pass filter according to a preset number of decomposition layers to obtain low-frequency wavelet coefficients and high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers.

3. The device door panel control method according to claim 2, characterized in that: The updating of the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers includes: Determine the preset thresholds corresponding to the high-frequency wavelet coefficients of each layer; Based on the preset threshold and the preset threshold function, the high-frequency wavelet coefficients of each layer are updated to obtain updated high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers; Based on the low-frequency wavelet coefficients corresponding to the multiple decomposition layers and the updated high-frequency wavelet coefficients, the target wavelet coefficients corresponding to the multiple decomposition layers are determined.

4. The device door panel control method according to claim 3, characterized in that: The step of determining the preset thresholds corresponding to the high-frequency wavelet coefficients of each layer includes: Determining a fixed threshold based on the number of sampling points of the initial knock signal; Based on the fixed threshold and the high-frequency wavelet coefficients of each layer, preset thresholds corresponding to the high-frequency wavelet coefficients of each layer are determined.

5. The device door panel control method according to claim 3, characterized in that: Before updating the initial wavelet coefficients of each layer based on the preset threshold function to obtain the target wavelet coefficients corresponding to each of the multiple decomposition layers, the method further includes: Determine the function parameter corresponding to the high-frequency wavelet coefficient as the target parameter; Determine a ratio between the absolute value of the target parameter and a preset threshold value corresponding to the target parameter as a preset ratio term, determine a difference between the absolute value of the target parameter and the preset threshold value corresponding to the target parameter as a preset difference term, determine a logarithmic function with respect to the preset ratio term as the preset logarithmic function, determine an exponential function with respect to the preset difference term as the preset exponential function, and determine a square function with respect to the preset difference term as the preset square function; The preset threshold function is constructed based on the target parameter, a preset threshold corresponding to the target parameter, the preset logarithmic function, the preset exponential function and the preset square function.

6. The device door panel control method according to claim 5, characterized in that: The updating of the high-frequency wavelet coefficients of each layer based on the preset threshold and the preset threshold function to obtain updated high-frequency wavelet coefficients corresponding to each of the multiple decomposition layers includes: For the high-frequency wavelet coefficient corresponding to each decomposition layer, when the absolute value of the high-frequency wavelet coefficient is less than the preset threshold value corresponding to the high-frequency wavelet coefficient, the preset value is determined as the updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient; When the absolute value of the high-frequency wavelet coefficient is greater than or equal to a preset threshold corresponding to the high-frequency wavelet coefficient, the target parameter in the preset threshold function is replaced by the high-frequency wavelet coefficient to obtain an updated high-frequency wavelet coefficient corresponding to the high-frequency wavelet coefficient.

7. The device door panel control method according to claim 2, characterized in that: The step of performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal includes: Performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a denoised high-frequency intrinsic mode function component; Signal reconstruction is performed based on the low-frequency intrinsic mode function component and the denoised high-frequency intrinsic mode function component to obtain the target knocking signal.

8. A device door panel controller, characterized in that: include: A signal acquisition module, used to acquire an initial knocking signal; The initial knocking signal represents knocking action information on the door panel of the target device; A wavelet decomposition module, used for performing wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to each of the multiple decomposition layers; A wavelet coefficient updating module, used to update the initial wavelet coefficients of each layer based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; The preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, wherein the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients; A wavelet reconstruction module, used for performing wavelet reconstruction based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal; A control instruction generating module is used to generate a target control instruction corresponding to the target knocking signal; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

9. A device, characterized in that: include: A collection end, used for collecting knocking action information on a door panel of a target device, and converting the knocking action information into an initial knocking signal; The device door panel controller is used to obtain the initial knocking signal; perform wavelet decomposition on the initial knocking signal to obtain initial wavelet coefficients corresponding to multiple decomposition layers; The initial wavelet coefficients of each layer are updated based on a preset threshold function to obtain target wavelet coefficients corresponding to each of the multiple decomposition layers; The preset threshold function is determined based on a preset logarithmic function, a preset exponential function and a preset square function, and the preset logarithmic function, the preset exponential function and the preset square function represent functions related to function parameters corresponding to the initial wavelet coefficients; wavelet reconstruction is performed based on the target wavelet coefficients corresponding to each of the multiple decomposition layers to obtain a target knocking signal; a target control instruction corresponding to the target knocking signal is generated; the target control instruction is used to control the door panel to be in a target control state corresponding to the knocking action information.

10. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the device door panel control method as described in claims 1-7.

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