Acoustic skin device and contact signal positioning method thereof
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TONGJI UNIV
- Filing Date
- 2024-12-10
- Publication Date
- 2026-06-12
Smart Images
Figure CN122195244A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of human-computer interaction technology, and in particular to an acoustic skin device and its contact signal positioning method. Background Technology
[0002] In existing technologies, a major category of tactile interaction solutions mainly works by converting the pressure of the interactive interface into electrical signals. Examples include various tactile interaction solutions such as piezoresistive, piezoelectric, capacitive, and magnetic induction. These solutions typically require specific materials and special electronic skin structures, which not only increases manufacturing and maintenance costs but also limits their widespread adoption in applications such as flexible skins.
[0003] Haptic interaction schemes based on acoustic vibration signals utilize the property that solid-state acoustic waves are generated upon surface contact. Specific sensors are installed on the components that will function as touch panels, and the location of contact is deduced by analyzing the sensor data. This type of scheme can reduce the structural complexity of electronic skin and relax material requirements. Its principle is to use the solid-state acoustic signals generated upon contact to infer the location of the signal source. Among existing acoustic sensing-based haptic interaction technologies, commonly used approaches are those based on time-of-arrival (TOA) and those based on frequency domain analysis. TOA-based methods utilize the time difference in solid-state acoustic wave propagation to different sensors as a location clue. Frequency domain analysis methods, on the other hand, utilize the dispersion phenomenon generated during solid-state acoustic wave propagation, based on the different propagation speeds of solid-state acoustic waves in different frequency bands, as a location clue.
[0004] The aforementioned tactile interaction schemes based on acoustic vibration signals still face challenges in tactile interaction positioning on flexible materials. First, traditional sensor technologies require specific materials and complex internal structures, limiting their application in scenarios such as flexible skins. Second, time-difference-based methods typically require high sampling rates to ensure temporal resolution, which not only increases the complexity of data processing but also raises the performance requirements of hardware devices. Time-difference-based methods are susceptible to interference from reflected sound waves. When the constraint size of the tactile panel is small, the superposition of reflected waves and the original signal becomes highly complex, severely interfering with signal matching between different sensors and affecting positioning accuracy. Frequency-domain matching methods often suffer from strong dependence on patterns, which also affects positioning accuracy when the contact pattern changes. Furthermore, the aforementioned methods are usually focused on signal positioning on hard surfaces, such as glass and wood. On more flexible surfaces, signal distortion becomes more severe, limiting application scenarios. Summary of the Invention
[0005] The purpose of this invention is to solve the above-mentioned problems and provide a highly efficient and low-cost tactile sensing solution that does not rely on specific materials or complex electronic skin structures.
[0006] To achieve the above objectives, this invention proposes an acoustic skin device that realizes tactile perception through a method of locating tactile signals based on acoustic vibration. The acoustic skin device includes a panel, an acoustic sensor array, and a signal processing device: the panel has a constraint frame along its edge; the acoustic sensor array is mounted on the panel and located within the enclosure of the constraint frame; the acoustic sensor array is signal-connected to the signal processing device.
[0007] Furthermore, the panel is provided with a tactile sensing area. When the panel receives a contact signal (including but not limited to finger touch), it is approximately regarded as being subjected to a pulse impact. Elastic deformation occurs around the contact point, generating solid-state acoustic waves that propagate on the panel and are reflected by the constraint frame. Interference occurs between the reflected waves, causing the panel to form a specific vibration mode. Under the damping effect of the device itself, the panel vibration energy weakens over time until it stops, which is regarded as the end of this contact signal. The acoustic sensor is driven when the panel vibrates. The acoustic sensor array is used to detect the vibration of the solid-state acoustic waves and record the vibration data at the location of the acoustic sensor. The vibration data is then transmitted and stored in the signal processing device.
[0008] Furthermore, the shape of the panel includes a flat panel and a curved panel; the shape of the constraint frame is adapted to the panel.
[0009] Furthermore, the panel can use various types of sheet materials suitable for robot skin, including more flexible sheet materials (such as ethylene-vinyl acetate copolymer foam). The constraint frame serves to constrain the edge areas of the panel, and its shape is not fixed. The central area on the panel that is not directly constrained by the constraint frame is called the tactile sensing area, which can undergo elastic deformation under the action of normal external force.
[0010] Furthermore, the acoustic sensor array includes at least three acoustic sensors.
[0011] Furthermore, the acoustic sensor array is connected to the signal processing device via a cable.
[0012] This invention also proposes a contact signal localization method based on the aforementioned acoustic skin device. The core of this method lies in comparing the intensity difference of signals received between acoustic sensors. The method includes the following steps:
[0013] S1: The vibration of solid sound waves is detected by an acoustic sensor array, the sound intensity ratio is calculated, and a sound intensity ratio distribution surface map is obtained, so that any set of acoustic sensor combinations corresponds to a specific sound intensity ratio distribution surface map, which is stored in the signal processing device; the acoustic sensor array contains n acoustic sensors, and the acoustic sensors are paired to form n-1 mutually independent acoustic sensor combinations (referred to as sensor groups);
[0014] S2: When the sensing area of the panel receives a touch signal, a set of acoustic sensors obtains a sound intensity ratio data. The sound intensity ratio data corresponds to a set of contour lines in the sound intensity ratio distribution surface map of the set of acoustic sensors. The probability distribution of the possible location of the signal source is obtained based on the contour lines.
[0015] S3: Obtain the probability distribution map of n-1 signal sources by combining the sound intensity ratio data of n-1 independent acoustic sensor combinations. After combining all the probability distribution maps to obtain the comprehensive probability distribution, take the point where the maximum value of the comprehensive probability distribution is located as the signal source location estimation point.
[0016] Further, in step S1, the sensor assembly is the basic unit for acquiring signal intensity difference data. After the acoustic sensor receives the signal, the signal processing device uses a low-pass filter with a certain cutoff frequency to filter the original signal. The cutoff frequency is related to the material used in the panel. In the filtered signal data, a specific threshold is used as the starting point of the contact signal, and a fixed time window length is used to intercept the contact signal. The method for calculating the sound intensity ratio is as follows: after the acoustic sensor filters the received vibration signal through a low-pass filter with a certain cutoff frequency, the square root (root mean square) of the sum of the squares of the sampling points within a certain time window is used as the sound intensity value of the signal, and the ratio of the sound intensity values detected by the two acoustic sensors in the acoustic sensor assembly is calculated to obtain the sound intensity ratio. The logarithmic form of the sound intensity ratio is...
[0017]
[0018] In the formula, A1 and A2 are the sound intensity values of the signals received by the two sensors (numbered 1 and 2) in the sensor group, respectively.
[0019] Furthermore, the sound intensity ratio obtained by any group of sensors for a contact signal occurring at a fixed position can be considered fixed; that is, the sound intensity ratio is related to the position of the contact signal but not to the energy level of the signal. Therefore, any group of acoustic sensors corresponds to a sound intensity ratio for any point in the panel's sensing area.
[0020] Further, in step S1, the method for drawing the sound intensity ratio distribution surface diagram is as follows: For a set of acoustic sensor combinations, when any point on the tactile sensing area of the panel becomes a signal source, it corresponds to a sound intensity ratio value. The sound intensity ratio value is used as the z-axis, and the signal source position as the x-axis and y-axis to draw the sound intensity ratio distribution surface diagram. Specifically, when any point on the tactile sensing area of the panel becomes a signal source, the two-dimensional coordinates of that point in the panel's contact sensing area are used as the x-axis and y-axis of a binary function, and the sound intensity ratio value S corresponding to that point is... R Using the z-axis as the axis, a bivariate function graph S reflecting the change of sound intensity ratio with the position of the signal source can be obtained. R =f sir (x, y) is called the sound intensity ratio distribution map. n-1 independent sensor groups correspond to n-1 independent sound intensity ratio distribution maps. The sound intensity ratio distribution map can be calibrated experimentally, specifically as follows: a finite number of test points are selected in the sensing area of the panel. After repeated experiments, the average value of the sound intensity ratio data measured at each test point is taken as the calibrated sound intensity ratio value for that test point. Then, through interpolation, the scatter plot of the sound intensity ratio distribution is generated into a continuous sound intensity ratio distribution map. The sound intensity ratio distribution map obtained through experimental calibration is stored inside the signal processing device.
[0021] Furthermore, in step S2, when the touch sensing area of the panel receives a touch signal, a set of acoustic sensors measures the sound intensity ratio corresponding to the signal (denoted as S). Rt The sound intensity ratio S Rt The sound intensity ratio distribution surface corresponding to this group of sensors corresponds to a family of contour lines (using f). sir (x,y)=S Rt (This indicates that) the points on the contour lines of this family represent all possible locations of the signal source under ideal conditions.
[0022] Furthermore, the probability distribution of the possible locations of the signal source can be obtained based on the contour lines. In step S2, considering the existence of error factors, the actual measured sound intensity ratio may deviate. For a certain signal measured by a certain group of sensors, the sound intensity ratio S... Rt The actual sound intensity ratio may be related to S. Rt A value that is close to S, assuming that the value follows a certain pattern. Rt Given a normal distribution with a mean, the probability exponent P of the signal source location can be further defined and plotted. i Bivariate functions:
[0023]
[0024] In the formula, σ is the variance of the sound intensity ratio, and the formula represents the probability index P of the signal source location. iThe binary function graph plotted is a probability distribution map of the signal source location, representing the coordinates (x, y) of points within the panel's contact sensing area. Points with larger probability exponents are more likely to be signal sources.
[0025] Furthermore, step S3 specifically involves: when the touch sensing area of the panel receives a touch signal, the n-1 independent sensor groups can draw n-1 probability distribution maps of the signal source positions, respectively using P1(x,y), P2(x,y), ..., P n-1 Represented by (x, y), the combined probability distribution function of the signal source locations is obtained by directly multiplying the probability distribution functions of all signal source locations:
[0026]
[0027] The maximum value P of the comprehensive probability distribution function of the signal source location max Location As a location estimation point for the signal source.
[0028] Compared with the prior art, the advantages of the present invention are:
[0029] 1. This invention eliminates the dependence on specific materials or specific electronic skin structures, and can use any sheet material that can be used as a panel (such as robot skin) to arrange acoustic sensors to capture vibration signals, thus having versatility and wide applicability.
[0030] 2. Compared with traditional time difference-based methods, this invention is easy to operate, has no requirements for time synchronization, and has lower requirements for sampling rate, effectively solving the problem of extremely high requirements for time synchronization and sampling rate.
[0031] 3. The method of the present invention is not affected by the touch mode, which may include various different modes such as finger tapping, fingernail tapping, etc.
[0032] 4. The method of the present invention can quickly adapt to the influence of reflected waves, thereby solving the problem that the signal becomes more complex due to the superposition of reflected waves in traditional methods, which in turn affects the positioning accuracy.
[0033] 5. Compared to traditional acoustic touch panels which are rigid flat panels, the method of this invention can be applied to both flat and curved panels.
[0034] 6. The method of this invention provides new possibilities for human-computer interaction using flexible skins that can sense the impact position of robots, breaking the limitation of using only rigid shell materials, and providing a low-cost and high-efficiency solution for tactile interaction of flexible robot skins. Attached Figure Description
[0035] Figure 1 This is a schematic diagram of the device using a flat panel at an angle from which the back side can be observed.
[0036] Figure 2 A schematic diagram of a device using a flat panel at an angle from which the front can be observed;
[0037] Figure 3 This is a schematic diagram showing the angle at which the back side of the device, which uses a curved panel, can be observed.
[0038] Figure 4 A schematic diagram of a device employing a curved panel at an angle from which the front can be observed;
[0039] Figure 5 A schematic diagram showing the test area, test points, and coordinates of the acoustic sensors;
[0040] Figure 6 The diagram shows the sound intensity ratio distribution corresponding to sensor group (Ⅰ-Ⅱ) and the contour lines corresponding to the sound intensity ratio of a certain signal in the diagram.
[0041] Figure 7 According to the appendix Figure 6 The probability distribution map of signal source locations generated by contour lines in the image;
[0042] Figure 8 The diagram shows the sound intensity ratio distribution corresponding to sensor group (Ⅲ-Ⅳ) and the contour lines corresponding to the sound intensity ratio of a certain signal in the diagram.
[0043] Figure 9 According to the appendix Figure 8 The probability distribution map of signal source locations generated by contour lines in the image;
[0044] Figure 10 The diagram shows the sound intensity ratio distribution corresponding to sensor group (Ⅲ-Ⅰ) and the contour lines corresponding to the sound intensity ratio of a certain signal in the diagram.
[0045] Figure 11 According to the appendix Figure 10 The probability distribution map of signal source locations generated by contour lines in the image;
[0046] Figure 12 According to the appendix Figure 7 , 9 The comprehensive probability distribution map of the signal source location generated by 11 for final positioning. Detailed Implementation
[0047] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be further described below.
[0048] Example 1 proposes an acoustic skin device that achieves tactile perception through a method of locating tactile signals based on acoustic vibration. For example... Figure 1-2 As shown, the acoustic skin device includes a panel 1, an acoustic sensor array, and a signal processing device 4. The panel 1 is a planar panel made of ethylene-vinyl acetate copolymer foam material. A constraint frame 2 is fixedly provided along the edge of the back of the panel 1. The shape of the constraint frame 2 is adapted to the planar panel 1 to constrain the edge area of the panel 1. The acoustic sensor array is mounted on the back of the panel 1 and is located within the enclosure of the constraint frame 2.
[0049] In Example 1, the acoustic sensor array includes four acoustic sensors: a first acoustic sensor 31, a second acoustic sensor 32, a third acoustic sensor 33, and a fourth acoustic sensor 34. These four acoustic sensors are fixed at different positions on the back of panel 1 and are paired to form three independent acoustic sensor combinations (referred to as sensor groups). The combination methods are as follows: the first acoustic sensor 31 and the second acoustic sensor 32, the third acoustic sensor 33 and the fourth acoustic sensor 34, and the third acoustic sensor 33 and the first acoustic sensor 31, respectively referred to as sensor group (I-II), sensor group (III-IV), and sensor group (III-I). The four acoustic sensors are respectively connected to the signal processing device signal 4 via cables 35.
[0050] like Figure 2 As shown, the central area of the front of panel 1 that is not directly constrained by the constraint frame 2 is designated as the tactile sensing area. The tactile sensing area can undergo elastic deformation under the action of normal external force. When the tactile sensing area on the front of panel 1 receives a contact signal (including but not limited to finger touch), it is approximately regarded as being subjected to a pulse impact. Elastic deformation occurs around the contact point, and solid sound waves are generated and propagate on panel 1. They are then reflected through the constraint frame 2, and interference occurs between the reflected waves, causing panel 1 to form a specific vibration mode. Under the damping effect of the device itself, the vibration energy of the panel weakens over time until it stops, which is regarded as the end of this contact signal. Among them, the first acoustic sensor 31, the second acoustic sensor 32, the third acoustic sensor 33 and the fourth acoustic sensor 34 are driven when panel 1 vibrates, detect the vibration of solid sound waves, record the vibration data at the location of the acoustic sensors, and then transmit the vibration data to the signal processing device 4.
[0051] Example 2 proposes an acoustic skin device, such as Figure 3-4 As shown, the difference between this device and Embodiment 1 is that the panel 1 is a curved panel, and the shape of the constraint frame 2 is adapted to the curved panel 1.
[0052] The experimental method for contact signal localization of the acoustic skin device of Embodiment 1 is as follows. The core of this method lies in comparing the intensity difference of the signals received between the acoustic sensors. The steps include:
[0053] S1: The vibration of solid sound waves is detected by an acoustic sensor array, the sound intensity ratio is calculated, and a sound intensity ratio distribution surface map is obtained, so that any combination of acoustic sensors corresponds to a specific sound intensity ratio distribution surface map, which is stored in the signal processing device 4.
[0054] 1.1) After receiving the contact signal, the acoustic sensor records data at a sampling rate of 44100Hz. The acquired raw data is filtered by a Butterworth low-pass filter. In this experimental method, the cutoff frequency of the low-pass filter is set to 700Hz. The filtered signal exceeds the threshold T. h When the signal is received, it is considered the start of the contact signal, and a fixed-length time window of data is extracted from it. This data segment is used as the contact signal data for this time.
[0055] 1.2) The number of sampling points contained within the time window is w, and the data of each sampling point of the intercepted signal is labeled a1, a2, ..., a w This means that the sound intensity A of the signal at the end of this segment is the root mean square value of that data segment, that is:
[0056]
[0057] 1.3) Calculation of the sound intensity ratio: The sound intensity ratio of a single contact signal is the ratio of the sound intensities measured by the two sensors within the sensor group. To ensure numerical symmetry, a logarithmic definition is used, with the unit being decibels (dB). Taking sensor group (Ⅰ-Ⅱ) as an example, if the first acoustic sensor 31 and the second acoustic sensor 32 measure the sound intensities of a certain contact signal as A1 and A2 respectively, then the sound intensity ratio S of this signal is... 12 for:
[0058]
[0059] 1.4) Obtain the sound intensity ratio distribution surface diagram: When any point on the tactile sensing area of panel 1 becomes the signal source, the two-dimensional coordinates of that point in the tactile sensing area of panel 1 are used as the x-axis and y-axis of a binary function. The sound intensity ratio S corresponding to that point is... R Using the z-axis as the axis, a bivariate function graph S reflecting the change of sound intensity ratio with the position of the signal source can be obtained. Rt =f sir (x, y) is called the sound intensity ratio distribution map. Using n-1 independent sensor groups corresponds to n-1 independent sound intensity ratio distribution maps.
[0060] The sound intensity ratio distribution map can be calibrated experimentally, as follows: A two-dimensional coordinate system is established on the front of panel 1 with the center of the contact sensing area as the origin, as shown below. Figure 5 As shown in the figure, the thick solid-line square box represents the constraint boundary, and the panel outside the boundary is considered to be non-deformable; the dashed square box represents the test area of this embodiment; the four "+" symbols represent the positions of the sensors (i.e., the projection points of the sensors on the back of panel 1 on the front), where the left and right "+" symbols represent the first acoustic sensor 31 and the second acoustic sensor 32, respectively, and the top and bottom "+" symbols represent the third acoustic sensor 33 and the fourth acoustic sensor 34, respectively. The evenly distributed dots "·" represent the test points (49 in the figure) used to calibrate the sound intensity ratio distribution map. Since the device in Embodiment 1 uses four acoustic sensors, it can form up to three independent sensor groups. The selected sensor combinations are: the combination of the first acoustic sensor 31 and the second acoustic sensor 32, the combination of the third acoustic sensor 33 and the fourth acoustic sensor 34, and the combination of the third acoustic sensor 33 and the first acoustic sensor 31, respectively denoted as sensor group (Ⅰ-Ⅱ), sensor group (Ⅲ-Ⅳ), and sensor group (Ⅲ-Ⅰ). It is worth noting that the acoustic sensor arrangement shown in the figure in the positioning experiment method of this embodiment 1 is only one implementation of the present invention, and therefore should not be construed as limiting the use of this arrangement array. Similarly, the test point arrangement shown in the figure is only one implementation of the present invention, and does not mean that the number and arrangement of test points must be limited to those shown in the figure. Figure 5 Each test point was touched once and data was recorded, and the experiment was repeated m times. Each sensor group obtained m sound intensity ratio data points for each test point. Due to errors, these sound intensity ratio data points would fluctuate slightly; the average of these data points was used as the calibration value for the sound intensity ratio at that test point. After the sound intensity ratios of all test points were calibrated, the following was used: Figure 5 Using the planar coordinate system as the x-axis and y-axis of the three-dimensional coordinate system, and the sound intensity ratio after the test point is calibrated as the z-axis, a discrete scatter plot of the sound intensity ratio distribution can be obtained. Then, a continuous sound intensity ratio distribution plot can be obtained by cubic interpolation. Figure 6 , 8 Figures 1 and 10 show the sound intensity ratio distribution maps corresponding to sensor groups (I-II), (III-IV), and (III-I), respectively. The calibrated sound intensity ratio distribution maps are stored in signal processing device 4 for subsequent tactile signal localization.
[0061] S2: When the sensing area of panel 1 receives a touch signal, a set of acoustic sensors obtains a sound intensity ratio data. This sound intensity ratio data corresponds to a set of contour lines in the sound intensity ratio distribution surface diagram of the set of acoustic sensors. The probability distribution of the possible location of the signal source can be obtained based on the contour lines.
[0062] like Figure 6 As shown, in the positioning experiment method of this embodiment 1, taking sensor group (Ⅰ-Ⅱ) as an example, the sensor group detects a tactile signal and measures the sound intensity ratio as S. 12t The sound intensity ratio distribution function corresponding to sensor group (Ⅰ-Ⅱ) is represented by S. 12 =f sir12 If we represent the signal as (x,y), then the ratio of the sound intensity S is... 12t A contour line on the corresponding sound intensity ratio distribution map is represented by S. 12 (x,y)=S 12t It means that, in Figure 6 The contour lines are dashed, representing all possible locations of the signal source under ideal conditions. However, due to errors, the actual measured sound intensity ratio may deviate from the ideal. Therefore, the possible locations of the signal source should be extended to the adjacent areas on both sides of the contour line. Assume the measured signal intensity ratio is S... 12t In this case, the ratio of the true sound intensity of the signal follows a formula based on S. 12t For a normal distribution with mean, define a probability exponent P. 12i This is used to indicate the relationship between the possible location of a signal source and its probability.
[0063]
[0064] In the formula) 12 The variance of the sound intensity ratio data when measuring the sensor group (Ⅰ-Ⅱ) is determined using the data used during calibration.
[0065] Formula 3 is the position probability exponent P. 12i A bivariate function of position coordinates (x, y). Figure 7 That is, according to Figure 6 The graph plotted using contour lines represents a bivariate function of the signal source location probability exponent. Points with higher probability exponents are more likely to be the source of the signal. Correspondingly, Figure 8 , 10 The contour lines corresponding to the sound intensity ratio of the signal for sensor group (Ⅲ-Ⅳ) and sensor group (Ⅲ-Ⅰ) are drawn with dashed lines respectively. Figure 9 , 11 Then, the position probability exponential distribution diagrams P for the signal of sensor group (Ⅲ-Ⅳ) and sensor group (Ⅲ-Ⅰ) were plotted respectively. 34i (x,y) and P 31i (x,y).
[0066] S3: In the positioning method of this embodiment 1, three sets of independent acoustic sensors are combined to obtain a probability exponential distribution P of three signal sources for the same signal. 12i (x,y), P 34i(x,y) and P 31i (x,y). The combined probability distribution function of the signal source locations, P(x,y), is obtained by directly multiplying all the probability distribution functions of the signal source locations:
[0067] P(x,y)=P 12i (x,y)P 34i (x,y)·P 31i (x,y) Formula 4
[0068] Will Figure 7 , 9 After integrating formula 4, we get the following: Figure 12 The graph shown represents the combined probability distribution P(x,y) of the signal source location. Its maximum value is P. imax Take P imax Location This serves as the location estimation point for the signal source, thus completing the localization of the tactile signal.
[0069] The above are merely preferred embodiments of the present invention and do not constitute any limitation on the present invention. Any equivalent substitutions or modifications made by those skilled in the art to the technical solutions and content disclosed in the present invention without departing from the scope of the present invention shall be deemed to have remained within the protection scope of the present invention.
Claims
1. An acoustic skin device, characterized in that, Includes panels, acoustic sensor arrays, and signal processing equipment: The panel has a constraint frame along its edge, and the acoustic sensor array is mounted on the panel and located within the enclosure of the constraint frame; the acoustic sensor array is signal-connected to the signal processing device.
2. The acoustic skin device according to claim 1, characterized in that, The panel is provided with a tactile sensing area. When the tactile sensing area of the panel receives a contact signal, it undergoes elastic deformation and generates solid-state acoustic waves that propagate on the panel. The waves are then reflected by the constraint frame, causing the panel to form a specific vibration mode. The acoustic sensor array detects the vibration of the solid-state acoustic waves and stores the vibration data in the signal processing device.
3. The acoustic skin device according to claim 1, characterized in that, The panel has shapes including flat panels and curved panels; the shape of the constraint frame is adapted to the panel.
4. The acoustic skin device according to claim 1, characterized in that, The acoustic sensor array includes at least three acoustic sensors.
5. The acoustic skin device according to claim 1, characterized in that, The acoustic sensor array is connected to the signal processing device via a cable.
6. A contact signal localization method, based on the acoustic skin device as described in any one of claims 1-5, characterized in that, Includes the following steps: S1: The vibration of solid sound waves is detected by an acoustic sensor array, the sound intensity ratio is calculated, and a sound intensity ratio distribution surface map is obtained, so that any set of acoustic sensor combinations corresponds to a specific sound intensity ratio distribution surface map, which is stored in the signal processing device; the acoustic sensor array contains n acoustic sensors, and the acoustic sensors are paired to form n-1 sets of mutually independent acoustic sensor combinations. S2: When the sensing area of the panel receives a touch signal, a set of acoustic sensors obtains a sound intensity ratio data. The sound intensity ratio data corresponds to a set of contour lines in the sound intensity ratio distribution surface map of the set of acoustic sensors. The probability distribution of the possible location of the signal source is obtained based on the contour lines. S3: Obtain the probability distribution map of n-1 signal sources by combining the sound intensity ratio data of n-1 independent acoustic sensor combinations. After combining all the probability distribution maps to obtain the comprehensive probability distribution, take the point where the maximum value of the comprehensive probability distribution is located as the signal source location estimation point.
7. The contact signal positioning method according to claim 6, characterized in that, In step S1, the method for calculating the sound intensity ratio is as follows: the acoustic sensor filters the received vibration signal through a low-pass filter with a certain cutoff frequency, and uses the root mean square of the sampling point data within a certain time window as the sound intensity value of the signal, and calculates the ratio of the sound intensity values detected by the two acoustic sensors in the acoustic sensor combination to obtain the sound intensity ratio.
8. The contact signal positioning method according to claim 6, characterized in that, In step S1, the method for drawing the sound intensity ratio distribution surface diagram is as follows: For a group of acoustic sensors, when any point on the tactile sensing area of the panel becomes a signal source, it corresponds to a sound intensity ratio value. The sound intensity ratio value is used as the z-axis, and the signal source position is used as the x-axis and y-axis to draw the sound intensity ratio distribution surface diagram.
9. The contact signal positioning method according to claim 6, characterized in that, Based on the probability distribution of the possible locations of the signal source obtained from the contour lines, in step S2, considering the existence of error factors, the actual measured sound intensity ratio may deviate; for a certain signal measured by a certain group of sensors, the sound intensity ratio S Rt The actual sound intensity ratio may be related to S. Rt A value that is close to S, assuming that the value follows a certain pattern. Rt Given a normal distribution with mean, we further define and plot the probability exponent P of the signal source location. i Bivariate functions: In the formula, σ is the variance of the sound intensity ratio. A point with a larger probability exponent indicates that the point is more likely to be a signal source.
10. The contact signal positioning method according to claim 6, characterized in that, Step S3 specifically involves: when the touch sensing area of the panel receives a touch signal, the n-1 independent sensor groups can draw n-1 probability distribution maps of the signal source positions, using P1(x,y), P2(x,y), ..., P... n-1 Represented by (x, y), the combined probability distribution function of the signal source locations is obtained by directly multiplying the probability distribution functions of all signal source locations: The maximum value P of the comprehensive probability distribution function of the signal source location max Location As a location estimation point for the signal source.