System for, method of, device for detecting defect of electric capacitance touch panel

Abstract

To .provide a method, a device and a system which can detect defect in a touch panel and reduces influence of this kind of defects.SOLUTION: A method according to the present invention has a step of acquiring a plurality of measured values by using a designated integral window to scan a plurality of electrodes of a detection device, and a step of determining a plurality of dispersion values for the plurality of electrodes based on the plurality of measured values. The plurality of dispersion values is used to discriminate distribution of the plurality of measured values between detection positions adjacent to each other of the detection devices. The method further has a step of determining if a defect is present in the detection device, based at least partially on comparison between a plurality of difference values and a plurality of threshold values.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] FIELD OF THE DISCLOSURE This disclosure relates generally to touch panels, and more particularly to detecting defects in such touch panels. [Background technology]

[0002] Sensing devices can be used to detect user input. For example, the sensing device may be configured to distinguish between user touch and hover. Accordingly, one or more sensing modalities may be implemented to detect such input. In one example, capacitive sensing may be used to distinguish between such touch and hover based on capacitance measurements obtained from the sensing device. Such capacitive sensing devices may include an array of electrodes that are driven by a signal to obtain measurements and detect user input. However, conventional sensing devices remain limited because the electrodes are susceptible to damage, limiting their ability to function despite such damage. [Brief explanation of the drawings]

[0003] [Figure 1] 1 illustrates an example of a device for defect detection, configured in accordance with some embodiments. [Figure 2] 1 illustrates an example of a system for defect detection, configured in accordance with some embodiments. [Figure 3] 1 illustrates an example of a touch panel current diagram, configured in accordance with some embodiments. [Figure 4] 1 illustrates an example of a method for defect detection performed in accordance with some embodiments. [Figure 5] 10 illustrates an example of another method for defect detection, performed in accordance with some embodiments. [Figure 6] 10 illustrates an example of yet another method for defect detection, performed in accordance with some embodiments. [Figure 7]10 illustrates an example of an additional method for defect detection performed in accordance with some embodiments. [Figure 8] 1 illustrates a diagram of an example of an adaptive threshold map, configured in accordance with some embodiments. [Figure 9] 10 illustrates an example of another method for defect detection, performed in accordance with some embodiments. [Figure 10] 10 illustrates an example of an additional method for defect detection performed in accordance with some embodiments. [Figure 11] 1 illustrates an example of a method for defect mitigation performed in accordance with some embodiments. [Figure 12] 10 illustrates an example of another method for defect mitigation performed in accordance with some embodiments. [Figure 13] 1A and 1B show an example of a sensing device configured in accordance with some embodiments. [Figure 14] 1 illustrates an example of an additional method for defect mitigation performed in accordance with some embodiments. [Figure 15] 1A and 1B show an example of a sensing device configured in accordance with some embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0004] In the following description, numerous specific details are set forth to provide a thorough understanding of the presented concepts. The presented concepts may be practiced without some or all of these specific details. In other instances, well-known process operations have not been described in detail so as not to unnecessarily obscure the concepts being described. While some concepts will be described in conjunction with specific examples, it should be understood that these examples are not intended to be limiting.

[0005] The sensing device may include various arrays of electrodes. For example, transmitting electrodes may be driven by signals that may be received by receiving electrodes. One or more measurements may be taken in response to application of such signals. For example, mutual capacitance measurements may be taken and stored as measurement data. As described in more detail below, one or more electrodes included within a sensing device may be damaged over time due to, among other things, physical deformation and deflection that occurs during a user touch. Accordingly, the conductivity of an electrode may change due to defects and / or damage, and such altered conductivity may affect capacitance measurements. Therefore, conventional sensing devices remain limited because damaged electrodes may result in error indications and erroneous touch detections, and conventional sensing devices are unable to efficiently and effectively mitigate the effects of such damaged electrodes.

[0006] The embodiments disclosed herein provide a sensing device capable of detecting defects and mitigating the effects of such defects. As described in more detail below, a variable-time receiving electrode sensing current integration window used for measurements may be configured to facilitate differentiation between a reference electrode and a defective electrode. More specifically, a calculation, such as a difference calculation, may be performed, and the result may be compared to a threshold value. One or more defects may be detected based on the comparison, and one or more corrective actions may be performed to mitigate or reduce the effects of the defects. In this manner, the adverse effects of defects, such as defective or damaged electrodes, may be reduced, extending the safe operation of the sensing device including the electrodes.

[0007] FIG. 1 illustrates an example of a device for defect detection, configured in accordance with some embodiments. As shown in FIG. 1, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. Thus, a sensing device such as device 100 may include one or more row and column electrodes configured to perform measurements for a detection operation, such as capacitance measurements. As described in more detail below, one or more defects may exist in the electrodes of device 100. Accordingly, embodiments disclosed herein may be configured to detect such defects and perform one or more mitigation operations to mitigate the effects of such defects and extend the life and operation of device 100.

[0008] In various embodiments, device 100 includes a plurality of first electrodes and a plurality of second electrodes. For example, the first electrodes, which may be row electrodes, may be configured to be driven by a signal, and the second electrodes may be configured to obtain one or more measurements in response to application of the signal to the first electrodes. It should be appreciated that column electrodes may be driven by a signal and measurements may be obtained using row electrodes. In this manner, one or more measurements, e.g., impedance measurements and mutual capacitance measurements, may be obtained based on application of such signals. Additional details regarding the generation and application of such signals are detailed below.

[0009] In some embodiments, the first electrode includes a first electrode 102, and the second electrode includes a second electrode 104, which may be a column electrode. As shown in FIG. 1 , over time, electrodes can develop damage or defects that can affect their performance. For example, damage to electrodes can affect their conductance by reducing conductivity and the ability to obtain accurate measurements. Such damage and defects can be stress fractures, microscratches, or any other type of damage or defect. In various embodiments, the electrodes can be fabricated from a material such as indium tin oxide (ITO). Over time, defects can appear in the electrodes based on mechanical stresses endured by the electrodes, for example, from bending or applying pressure to a device 100 that may be included in a touch panel. Defects can also result from one or more aspects of the manufacturing process. Thus, as shown in FIG. 1 , the first electrode 102 can have a defect 106 that can affect received signals. Additionally, additional defects, such as defect 108, that affect transmitted signals can also be present. As described in more detail below, additional components coupled to device 100 can be configured to detect defects 106, perform various mitigating actions, and compensate for the effects of defects 106 on touch / hover detection operations.

[0010] 2 illustrates an example of a system for defect detection configured in accordance with some embodiments. As described above, the systems disclosed herein are configured to obtain impedance and capacitance measurements and, based on such measurements, identify hover and touch events, such as those that may occur when a user hovers or touches a sensing device. Accordingly, systems such as system 200 may include such sensing devices implemented in the context of capacitive sensors.

[0011] Thus, system 200 includes a sensing device 202, which may be a touch panel, that includes a component, for example, an electrode, configured to detect a change in an electrical property measured within a specified distance of the sensing device. As described above, the sensing device may be a touch screen, a touch panel, a fingerprint sensor, or a button that includes one or more electrodes. In one example, the electrodes may be arranged in an array of transmit and receive electrodes, where the transmit electrodes are configured to transmit signals according to a scanning protocol or sequence and the receive electrodes are configured to receive the signals, thus obtaining sensed measurements of capacitance and / or impedance between the two.

[0012] System 200 further includes one or more sensing channels 204 configured to receive signals sensed by sensing device 202, which may be generated by receiving electrodes included within the sensing device. In various embodiments, sensing channel 204 includes various components, such as an attenuator and an integrating capacitor. In various embodiments, sensing channel 204 is configured to perform one or more operations that convert charge to code, thus allowing additional calculations to be performed later in digital format. In various embodiments, output data from sensing channel 204 is raw data. As shown in FIG. 2 , sensing channel 204 may also be coupled to components, such as a processing unit 208, also referred to herein as a processing device. Processing unit 208 is configured to perform various calculations, such as raw data multiphase deconvolution, filtering and noise removal, baseline calculation and subtraction, touch and hover object position calculation, finger identifier calculation, panel defect detection, and mitigation action execution. In various embodiments, processing unit 208 may be configured to include a controller and may be configured to include one or more processors or hardware accelerators configured to perform processing and mitigation operations. For example, processing unit 208 may be configured to identify and store measurement data in a memory device and to perform one or more calculations to identify particular events, such as hover events and touch events. Furthermore, processing unit 208 may also be configured to perform defect detection and mitigation operations, as described in more detail below. Processing unit 208 is shown coupled to sensing channel 204.

[0013] The system 200 further includes a transmit channel 210 configured to generate one or more signals provided to the sensing device 202, where the transmit channel 210 provides signals used during a scan sequence and forms the basis of subsequent measurements. Accordingly, the transmit channel 210 may include various components, such as one or more amplifiers and / or buffers and current and / or voltage sources. As shown in FIG. 2 , the transmit channel 210 may be coupled to a signal generator 212 and a charge pump 214. Accordingly, the signal generator 212 may be configured to generate signals used to drive the transmit electrodes during the scan sequence and may configure parameters of such drive signals accordingly. The charge pump 214 may be configured to provide voltage control for the transmit channel 210. Furthermore, the multiplexer 220 may be configured to selectively couple the sensing channel 204 and the transmit channel 210 to specific electrodes of the sensing device 202 according to the scan sequence. In various embodiments, the sensing device 202 has more receive electrodes than the number of parallel sensing channels 204, so that full scanning of the sensing device 202 is accomplished in more than one scan slot. In some embodiments, the multiplexer 220 may include a transmit multiplexer for the transmit electrodes and a sense multiplexer for the sensing, also referred to herein as receive electrodes. In various embodiments, the multiplexer 220 may be implemented as a single multiplexer or as multiple multiplexers that are implemented separately or combined. In one example, there may be one or more transmit multiplexers for the transmit channels 210 and one or more receive multiplexers for the receive channels 204.

[0014] FIG. 3 shows an example of a touch panel waveform diagram configured in accordance with some embodiments. As described above, electrodes may be included in a sensing device, and one or more signals may be used to drive a first electrode and obtain measurements on a second electrode. As shown in diagram 300, a TX signal 302 may be used to apply a voltage to drive a first transmitting electrode in the sensing device, as described above. Application of this type of drive signal may induce a current in a receiving electrode of the sensing device. When there is no defect in the sensing device, which may be a panel, current waveform 304 shows the current in the receiving electrode. When there is a defect (e.g., a microscratch) in the sensing device, current waveform 306 shows the current in the same receiving electrode.

[0015] In various embodiments, current waveform 304 represents the current in an electrode without a defect. Additionally, current waveform 306 represents the current in the same electrode, but with a defect such as a microscratch. Therefore, because the defective sensing electrode has a larger time constant due to the increased receiving electrode resistance caused by the defect, the time course of current decay is extended and occurs over a longer period for the defective, damaged electrode, as shown in diagram 300. As described in more detail below, these differences in time course can be used to identify damaged electrodes and to identify and implement mitigating actions.

[0016] 4 illustrates an example method for defect detection performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 400 may be performed to identify defects in such sensing devices. Accordingly, the methods disclosed herein may be performed to detect defects in the sensing device, and subsequent mitigation actions may be performed to mitigate such defects and extend the operation of the sensing device.

[0017] Method 400 may perform operation 402, in which the sensing device may be scanned using a specified integration window. Thus, similar to the above, row and column electrodes may be scanned sequentially to obtain multiple measurements. In some embodiments, row and column electrodes may be scanned simultaneously using multi-phase transmit channels or multiple transmit and receive channels. Furthermore, a specified integration window may be used for this type of scanning. In various embodiments, the specified integration window is a specified period of time over which the measured charge is integrated. Thus, the specified integration window may be a measurement window.

[0018] Method 400 may perform operation 404, in which multiple variances between adjacent rows and columns may be determined. Thus, measurements between adjacent rows and adjacent columns may be compared to obtain multiple variance values ​​representing the variances between adjacent rows and the differences between adjacent columns. As described in more detail below, the variance values ​​may be difference values ​​representing the differences, or may be data values ​​generated at least in part based on an approximation function.

[0019] Method 400 may perform operation 406, in which it may be determined whether any defects exist in the panel. Accordingly, during operation 406, the difference values ​​may be compared to multiple thresholds to determine whether any of the determined differences exceed the thresholds. If the difference values ​​exceed the thresholds, a defect may be identified, and one or more mitigation actions may be performed, as described in more detail below.

[0020] 5 illustrates an example of another method for defect detection performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 500 may be performed to identify defects in such sensing devices. As described in more detail below, a time response to sensing position may be used in combination with a threshold value to facilitate detection and identification of defects in the sensing device.

[0021] Method 500 may perform operation 502, in which a peak sensitivity of the sensing device may be identified based on a short integration window width search. In various embodiments, the short integration window may be a specified period of time that is shorter than the total time for the accumulated charge in the sensing device to discharge. More specifically, a voltage may be applied to the transmitting electrode, and the accumulated charge and current may be measured at the receiving electrode, similar to that described above with reference to FIG. 3. The charge may decay over time as it discharges. T INT The integration window, also described as the .times. ...

[0022] In various embodiments, the peak sensitivity may be identified based on the application of multiple different short integration window durations. Accordingly, operation 502 may be performed as part of a calibration operation, in which a test signal is provided and measured by electrodes included in the sensing device during calibration and initial configuration of the sensing device. The different short integration windows may be a designated set of windows having different lengths of time determined by an entity such as a manufacturer. In various embodiments, the designated set of windows may be determined based on simulation data or based on previous testing using a resistor in series with the sensing electrode to mimic or simulate changes in resistance caused by defects such as microscratches. For example, one or more calibration operations compare a sensing channel reading with a calibration resistor coupled in series with a reading without the calibration resistor, e.g., by bypassing the calibration resistor with a switch. The inclusion of the calibration resistor may identify a designated integration window when the relative change in the sensing channel raw data is greatest. For example, the rate of increase or decrease of the measured mutual capacitance may be plotted against different integration windows, and the integration window resulting in the greatest rate of difference may be identified as the designated integration window. Thus, during operation 502, sensitivity indications may be obtained for the sensing device based on different short integration windows, and the short integration window that provides the peak or maximum sensitivity may be identified.

[0023] The method 500 may perform an operation 504 in which the sensing device may be scanned using a specified short integration window. Thus, a scanning operation may be performed on the sensing device based on the short integration window, and measurements may be taken and stored as measurement data. In various embodiments, the measurements include mutual capacitance measurements that measure mutual capacitance between the transmitting and receiving electrodes. As described above, the measurements may also include impedance measurements.

[0024] Method 500 may perform operation 506, in which the sensing device may be scanned using a specified full integration window. In various embodiments, the full integration window may be a specified period of time that exceeds the total time that accumulated charge transfer within the sensing device nearly fully charges or discharges. Thus, during the full integration window, transient processes in the sensing device must be completed. Such a period may be a specified period determined by an entity such as a manufacturer as part of a simulation and / or manufacturing process. Thus, a scanning operation may be performed on the sensing device based on the full integration window, and measurements may be taken and stored as measurement data. As described above, the measurements may include mutual capacitance measurements that measure mutual capacitance between the transmitting and receiving electrodes and / or may include impedance measurements.

[0025] Method 500 may perform operation 508, in which the short integration window results may be normalized based on the full integration window results. In various embodiments, normalization may be performed by cell-to-cell (or, in other terms, cross-section of the transmitting and receiving electrodes) division of the mutual capacitance measured over the short integration window relative to the mutual capacitance over the full integration window. An equation that may be used for the normalization process is shown below in equation (1):

number

[0026] As shown in equation (1),

number

number

[0027] Method 500 may perform operation 510, in which multiple differences between adjacent rows and columns of the sensing device may be determined. Accordingly, the multiple difference values ​​may be generated based on one or more distance calculations regarding the distances between sensing cells on the sensing device. More specifically, the measurements may be stored in a table of data values, with each data value representing a measurement at an intersection between a row electrode and a column electrode in the sensing device. As described in more detail below, such intersections may also be referred to as cells or sensing cells. Furthermore, the differences may be calculated based on the difference calculations. For example, a two-dimensional high-pass filter (2D HPF) may be used to generate the difference values. In various embodiments, the 2D HPF identifies non-monotonicity in mutual capacitance changes that may be caused by panel defects. In one example, the 2D HPF is implemented by calculating row-to-row and column-to-column entry differences of a mutual capacitance matrix in a first step and a second step, respectively. Any suitable 2D HPF operation may be used.

[0028] Method 500 may perform operation 512, in which multiple thresholds may be generated based at least in part on known panel characteristics. In various embodiments, the known mutual capacitance difference and the known sensing device resistance value may be stored in memory. Such known panel characteristics may have been determined by an entity, such as a manufacturer, during a simulation and / or manufacturing process. For example, a simulation tool used during the design of the sensing device may be used to determine the known mutual capacitance difference and the known sensing device resistance value, and such known panel characteristics may be stored by the manufacturer in a memory device associated with the sensing device. As described in more detail below, the known panel characteristics may be stored in a specific data structure configured to represent the threshold value for each cell. In one example, the same threshold value may be selected for all electrode intersections. In another example, individual threshold values ​​may be determined for each electrode intersection. The threshold value may be identified based on a PSPICE simulation of the effect of microscratches on the mutual capacitance reading and using an optimal integration window selected as part of a calibration procedure. In various embodiments, generating the threshold value may be performed in parallel with other operations of method 500 or as a separate and / or previously performed process. Thus, generating the threshold may be performed independently of other operations of method 500 .

[0029] In one example, in the simulation, the cell routing resistance value may be increased by a factor of two to simulate a micro-scratch. The measured mutual capacitance may be measured and, for example, decreased by 10% for the observed cells. Thus, a detection threshold of 10% of the expected panel mutual capacitance may be identified as the threshold. This type of threshold determination operation may be appropriate for sensing devices with small (less than 5%) cell-to-cell mutual capacitance tolerances. For sensing devices with larger manufacturing tolerances, one or more normalization operations, such as those described above, may be performed. Thus, the threshold may be determined by the normalized mutual capacitance (Ni,j ) can be used to identify the saturation point, see equation (1) for calculation method.

[0030] Method 500 may perform operation 514, in which it may be determined whether the determined difference is greater than a threshold value for any sensing location. Such a determination may be made based on a comparison of the difference value to a threshold value. In various embodiments, the comparison may be a cell-by-cell or entry-by-entry comparison, in which corresponding entries in a data table are compared. If it is determined that the determined difference is greater than the threshold value for the sensing location, method 500 may proceed to operation 516.

[0031] Thus, during operation 516, the presence of a defect may be identified. Thus, if the difference value exceeds a determined threshold for a particular cell, the defect may be identified. Further, based on the location of the difference in the data table, the location of the defect may be identified based on the corresponding intersection of the row and column electrodes. As described in more detail below, in response to identifying the defect, one or more mitigation actions may be performed to mitigate the effects of the defect.

[0032] Returning to operation 514, if it is determined that no determined difference is greater than the threshold for any sensing location, method 500 may proceed to operation 518 where it may be determined that no fault is detected. If it is determined that no fault is detected, normal operation of the sensing device may continue. It should be appreciated that the next iteration of method 500 may be performed periodically as part of a maintenance / diagnostic operation, or may be performed dynamically in response to a diagnostic operation triggering an event or input.

[0033] 6 illustrates an example of yet another method for defect detection performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 600 may be performed to identify defects based at least in part on a time response of sensing position and an associated threshold. As described in more detail below, various different types of calculations may be used to identify defects.

[0034] Method 600 may perform operation 602, in which a peak sensitivity of the sensing device may be identified based on a short integration window width search. Similar to what was described above, the peak sensitivity may be identified based on application of a plurality of different short integration window durations. Thus, operation 602 may be performed as part of a calibration operation, in which a test signal may be provided and measured by electrodes included within the sensing device during calibration and initial configuration of the sensing device. Thus, similar to what was described above with reference to operation 502 of FIG. 5 , during operation 602, sensitivity indications may be obtained for the sensing device based on different short integration windows, and a short integration window providing a peak or maximum sensitivity may be identified.

[0035] The method 600 may perform operation 504, in which the sensing device may be scanned using a specified short integration window. Thus, a scanning operation may be performed on the sensing device based on the short integration window, and measurements may be taken and stored as measurement data. In various embodiments, the measurements include mutual capacitance measurements that measure mutual capacitance between the transmitting electrode and the receiving electrode.

[0036] Method 600 may perform operation 606, in which the sensing device may be scanned using a specified full integration window. As described above, the full integration window may be a specified period of time that exceeds the total time for accumulated charge in the sensing device to discharge. Thus, a scanning operation may be performed on the sensing device based on the full integration window, and measurements, which may be mutual capacitance measurements and / or impedance measurements, may be taken and stored as measurement data.

[0037] Method 600 may perform operation 608, in which the short integration window results may be normalized based on the full integration window results. Thus, as described above, additional variance in the measurements may be reduced. In various embodiments, operations 606 and 608 are performed optionally. For example, in some embodiments, method 600 does not include operations 606 and 608. Thus, in various embodiments, full integration window measurements are not performed, and no normalization operation is performed. The normalization procedure is similar to normalization procedure 508 of FIG. 5.

[0038] Method 600 may perform operation 610, in which an approximation function may be generated based at least in part on least-squares regression. In various embodiments, application of least-squares regression, also referred to herein as least-squares fitting, may be used to identify steps or transitions in the measurement data. For example, similar to that described above, the measurements may be stored in a table of data values, with each data value representing a measurement at an intersection between a row electrode and a column electrode in the sensing device. Thus, a one-dimensional least-squares approximation function may be used to approximate the mutual capacitance dependence for each electrode included in the sensing device. In this manner, the least-squares fitting may be used to generate an approximate representation of the sensing device behavior, which may include one or more transitions, e.g., steps defined by step parameters.

[0039] In some embodiments, the least-squares fitting technique calculates the sum of squared differences between the fitting function and the experimental data. Therefore, fitting approximation methods (e.g., the Levenberg-Marquardt algorithm) attempt to determine the coefficients of the fitting function that minimize the sum of squared differences. The fitting function is defined to have a step parameter. For example, the fitting function is the sum of a Heaviside step function with an index offset and a step amplitude and a second-order polynomial function. The fitting function calculates the polynomial coefficients along with the Heaviside step function offset and step amplitude during the least-squares fitting optimization operation. The polynomial function represents the natural mutual capacitance decay approaching the center of the sensing device. A defect is considered to be detected when the Heaviside step function amplitude is higher than a threshold and the offset index identifies the defect location. An example of this type of mutual capacitance fitting function for one dimension is shown below in Equation (2). y(x)=A·(xx c )2+B·(xx c )+C+D·H(xx d ) (2)

[0040] As shown in equation (2) above, A, B, and C may be coefficients that represent the polynomial portion of the approximation function. In some embodiments, B is the coefficient of the cell center x c It can be set to zero for high quality panels with perfectly symmetrical mutual capacitance display with respect to position. c may be the index of the center of the sensing device. For example, if the sensing device has 25 electrodes, the index of the center x c is 13. Furthermore, H(x) may be a Heaviside step function, D may be a step amplitude, and x d may be the defective electrode index. If the D coefficient is higher than a specified threshold, a defect may be identified.

[0041] In some embodiments, the approximation function may be generated based on multiple sets of measurement data from different scans and therefore may have reduced variance. As described in more detail below, the step parameters identified by the approximation function may be compared to thresholds to identify defects. It should be appreciated that two-dimensional approximation functions or any other suitable approximation functions may also be used. Method 600 may perform operation 612, in which multiple thresholds may be generated based at least in part on known panel characteristics. As described above, the known panel characteristics may be stored in a specific data structure configured to represent the threshold values ​​for each cell.

[0042] Thus, the specified threshold mapping may be read from memory during operation 612. As mentioned above, the thresholds may be generated independently and / or asynchronously from other operations of method 600.

[0043] Method 600 may perform operation 614, where it may be determined whether the determined step parameter is greater than a threshold value for any sensed location. Such a determination may be made based on a comparison of the step parameter to a threshold value. In various embodiments, the comparison may be a cell-by-cell or entry-by-entry comparison, where corresponding entries in a data table are compared. If it is determined that the determined difference is greater than a threshold value for the sensed location, method 600 may proceed to operation 616.

[0044] Thus, during operation 616, the presence of a defect may be identified. Thus, if the step parameter value exceeds a determined threshold for a particular cell, the defect may be identified. Further, based on the location of the difference in the data table, the location of the defect may be identified based on the corresponding intersection of the row and column electrodes. As described in more detail below, in response to identifying the defect, one or more mitigation actions may be performed to mitigate the effects of the defect.

[0045] Returning to operation 614, if it is determined that no determined step parameter values ​​are greater than the threshold for any sensing location, method 600 may proceed to operation 618 where it may be determined that no fault is detected. If it is determined that no fault is detected, normal operation of the sensing device may continue. It should be appreciated that the next iteration of method 600 may be performed periodically as part of a maintenance / diagnostic operation, or may be performed dynamically in response to a diagnostic operation triggering an event or input.

[0046] 7 illustrates an example of an additional method for defect detection performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 700 may be performed to identify defects based at least in part on an adaptive threshold map. As described in more detail below, the use of such an adaptive threshold map may account for non-uniformities in the sensing device.

[0047] The method 700 may perform an operation 702 in which the sensing device may be scanned based on a specified integration window. Similar to the above, a scanning operation may be performed on the sensing device based on an integration window having a specified duration, and measurements may be taken and stored as measurement data. In various embodiments, the measurements include mutual capacitance measurements that measure mutual capacitance between a transmitting electrode and a receiving electrode.

[0048] Method 700 may perform operation 704, in which multiple differences between adjacent rows and columns of the sensing device may be determined. Similar to what has been described above, the multiple difference values ​​may be generated based on one or more calculations. In one example, the measurements may be stored in a table of data values, with each data value representing a measurement at an intersection between a row electrode and a column electrode in the sensing device. Furthermore, the differences may be calculated based on a difference calculation. For example, a two-dimensional high-pass filter (2D HPF) may be used to generate the difference values. In some embodiments, a least-squares calculation may be performed, similar to what has been described above.

[0049] Method 700 may perform operation 706, in which an adaptive threshold map may be identified based at least in part on the specified panel characteristics. In various embodiments, the adaptive threshold map is generated by an entity such as a manufacturer. As described in more detail below, the adaptive threshold map is configured to have varying thresholds based on one or more sensing device parameters. When adaptive thresholds are implemented in this manner, false positive defect detections can be reduced because the adaptive threshold map may be configured to compensate for non-uniformity in the sensing device. More specifically, the thresholds may be varied based on known non-uniform performance characteristics of the sensing device. For example, the thresholds of the adaptive threshold map may be increased near the edges of the sensing device and / or near the electrode connectors. As described above, the adaptive threshold map may be generated based on simulation data or other data obtained from testing during sensing of the device and / or structure.

[0050] Method 700 may perform operation 708, in which it may be determined whether a defect exists based at least in part on the plurality of differences and the adaptive threshold map. Similar to the above, this type of determination may be made based on a comparison of the difference values ​​to an adaptive threshold. In various embodiments, the comparison may be a cell-by-cell or entry-by-entry comparison, where corresponding entries in a data table are compared. Thus, during operation 708, the difference values ​​may be compared to thresholds contained within the threshold map, and a defect may be identified based on whether any of the difference values ​​exceed the corresponding threshold.

[0051] FIG. 8 illustrates an example of an adaptive threshold map configured in accordance with some embodiments. As described above, the use of an adaptive threshold map may account for non-uniformity in a sensing device. Thus, the thresholds included within the adaptive threshold map may vary according to the performance characteristics of the sensing device. As shown in FIG. 8, image 800 illustrates an example of various thresholds that may be applied based on distance from the center of the sensing device. For example, a first adaptive threshold 802 may be used for sensing cells positioned at a first distance range from the center of the sensing device. Additionally, a second adaptive threshold 804 may be used for a second distance range from the center of the sensing device. Additionally, a third adaptive threshold 806 may be used for a third distance range from the center of the sensing device. In this manner, the adaptive threshold map may be configured to map different thresholds to different sensing locations on the sensing device.

[0052] 9 illustrates an example of another method for defect detection performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 900 may be performed to identify defects based at least in part on different types of capacitance measurements. As described in more detail below, capacitance measurements of self-capacitance may be used to identify defects.

[0053] Method 900 may perform operation 902, in which a plurality of electrodes may be grounded. In various embodiments, the plurality of electrodes may be non-scanned electrodes. In one example, the plurality of electrodes may include one or more of the receiving electrodes included in the sensing device. Accordingly, the receiving electrodes included in the sensing device may be coupled to a ground circuit. As described in more detail below, electrode grounding may be performed to facilitate obtaining self-capacitance measurements.

[0054] Method 900 may perform operation 904, in which the sensing device may be scanned and a peak sensitivity of the sensing device may be identified. Similar to the above, the peak sensitivity may be identified based on application of a plurality of different short integration window periods. Thus, operation 904 may be performed as part of a calibration operation, in which a test signal may be provided and measured by electrodes included within the sensing device during calibration and initial configuration of the sensing device. Thus, during operation 904, sensitivity indications may be obtained based on different short integration windows using self-capacitance measurements, and a short integration window providing a peak or maximum sensitivity may be identified.

[0055] The method 900 may perform operation 906, in which the sensing device may be scanned using a specified integration window. Similar to the above, the specified integration window may be a specified period of time during which accumulated charge in the sensing device is discharged. Thus, a scanning operation may be performed on the sensing device based on the integration window, and measurements, which may be self-capacitance measurements, may be taken and stored as measurement data.

[0056] Method 900 may perform operation 908, in which multiple differences between adjacent rows and columns of the sensing device may be determined. Similar to the above, the multiple difference values ​​may be generated based on one or more calculations. Further, the differences may be calculated based on a difference calculation.

[0057] Method 900 may perform operation 910, in which a plurality of thresholds may be generated based at least in part on known panel characteristics. As described above, the known panel characteristics may be stored in a specific data structure configured to represent the thresholds for each cell. Thus, during operation 910, the specified threshold mapping may be read from memory. As described above, the thresholds may be generated independently and / or asynchronously from other operations of method 900.

[0058] Method 900 may perform operation 912, in which it may be determined whether the determined difference is greater than a threshold value for any sensed location. Such a determination may be made based on a comparison of the difference value to a threshold value. In various embodiments, the comparison may be a row-by-row or column-by-column comparison, in which corresponding entries in a data table are compared. If it is determined that the determined difference is greater than the threshold value for the sensed location, method 900 may proceed to operation 914.

[0059] Thus, the presence of a defect may be identified during operation 914. Thus, if the difference value exceeds a determined threshold for a particular cell, the defect may be identified. In response to identifying the defect, one or more mitigation actions may be performed to mitigate the effects of the defect, as described in more detail below.

[0060] Returning to operation 912, if it is determined that no determined difference is greater than the threshold for any sensing location, method 900 may proceed to operation 916 where it may be determined that no fault is detected. If it is determined that no fault is detected, normal operation of the sensing device may continue. It should be appreciated that the next iteration of method 900 may be performed periodically as part of a maintenance / diagnostic operation, or may be performed dynamically in response to a diagnostic operation triggering an event or input.

[0061] 10 illustrates an example of an additional method for defect detection performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 1000 may be performed to identify defects based at least in part on a time response of sensing location and an associated threshold. As described in more detail below, different scanning frequencies may be used to identify defects.

[0062] Method 1000 may perform operation 1002, in which the sensing device may be scanned at a high operating frequency. Accordingly, during operation 1002, the sensing device may be scanned at a first frequency, and a first plurality of measurements may be obtained. In various embodiments, the first frequency is a higher operating frequency that may be used for a particular sensing operation or mode. In various embodiments, performance characteristics may vary based on the operating frequency due to frequency-dependent characteristics of the sensing device. In one example, at the high operating frequency, the transient process does not complete because the sensing device was not fully recharged. The sensing device is fully recharged (stable) during a second scan having a lower operating frequency. In one example, the first frequency is 300 kHz and the second frequency is 100 kHz.

[0063] Method 1000 may perform operation 1004, in which the sensing device may be scanned at a lower operating frequency. Accordingly, during operation 1004, the sensing device may be scanned at a second frequency, and a second plurality of measurements may be obtained. In various embodiments, the second frequency is a normal operating frequency that may be used during normal operation of the sensing device. Furthermore, the second frequency may be lower than the first frequency. As discussed above, performance characteristics of the sensing device may differ between the first frequency and the second frequency due to frequency-dependent characteristics of the sensing device.

[0064] Method 1000 may perform operation 1006, in which the scan data may be normalized. Thus, similar to the above, additional variance in the measurements may be reduced through one or more normalization operations. More specifically, measurement data acquired during a high operating frequency may be normalized based on measurement data acquired during a low operating frequency. In various embodiments, operations 1004 and 1006 are optionally performed. For example, in some embodiments, method 1000 does not include operations 1004 and 1006. In various embodiments, high-frequency scan results may be normalized based on low-frequency scan results. For example, for each panel intersection, a new matrix of coefficients can be calculated based on the relationship between the scan results at the high operating frequency and the scan results at the low operating frequency. Thus, in various embodiments, low-frequency measurements are not performed, and no normalization operation is performed.

[0065] Method 1000 may perform operation 1008, in which multiple differences between adjacent rows and columns of the sensing device may be determined. Similar to the above, the multiple difference values ​​may be generated based on one or more calculations. In one example, the measurements may be stored in a table of data values, with each data value representing a measurement at an intersection between a row electrode and a column electrode in the sensing device. Furthermore, the differences may be calculated based on a difference calculation. For example, a two-dimensional high-pass filter may be used to generate the difference values. In some embodiments, a least-squares calculation may be performed, similar to the above.

[0066] Method 1000 may perform operation 1010, in which a plurality of thresholds may be generated based at least in part on known panel characteristics. As described above, the known panel characteristics may be stored in a specific data structure configured to represent the thresholds for each cell. Thus, during operation 1010, the specified threshold mapping may be read from memory. As described above, the thresholds may be generated independently and / or asynchronously from other operations of method 1000.

[0067] Method 1000 may perform operation 1012, in which it may be determined whether the determined difference is greater than a threshold value for any sensed location. Such a determination may be made based on a comparison of the difference value to a threshold value. In various embodiments, the comparison may be cell-by-cell (cross-section-by-cross-section) or entry-by-entry, where corresponding entries in a data table are compared. If it is determined that the determined difference is greater than the threshold value for the sensed location, method 1000 may proceed to operation 1014.

[0068] Thus, during operation 1014, the presence of a defect may be identified. Thus, if the difference value exceeds a determined threshold for a particular cell, the defect may be identified. Further, based on the location of the difference in the data table, the location of the defect may be identified based on the corresponding intersection of the row and column electrodes. As described in more detail below, in response to identifying the defect, one or more mitigation operations may be performed to mitigate the effects of the defect.

[0069] Returning to operation 1012, if it is determined that no determined difference is greater than the threshold for any sensing location, method 1000 may proceed to operation 1016 where it may be determined that no fault is detected. If it is determined that no fault is detected, normal operation of the sensing device may continue. It should be appreciated that subsequent iterations of method 1000 may be performed periodically as part of a maintenance / diagnostic operation, or may be performed dynamically in response to a diagnostic operation triggering an event or input.

[0070] 11 illustrates an example of a method for defect mitigation performed in accordance with some embodiments. As described above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 1100 may be performed to identify defects based at least in part on a time response of sensing location and an associated threshold. As described in more detail below, different scanning frequencies may be used to identify defects.

[0071] Method 1100 may perform operation 1102, in which one or more defect detection operations may be performed. As described above, the defect detection operations may include scanning a sensing device to obtain multiple measurements, as well as performing one or more calculations, such as determining a difference value. In various embodiments, the defect detection operations may also include determining one or more thresholds for the sensing device.

[0072] Method 1100 may perform operation 1104, where it may be determined whether a defect is detected. Thus, as described above, the measurement data may be compared to a threshold to identify the presence of one or more defects. For example, the difference value may be compared to a threshold to determine whether the difference value exceeds the threshold for any sensing cell. If it is determined that a defect is detected, method 1100 may proceed to operation 1106.

[0073] Thus, during operation 1106, one or more corrective actions may be performed based at least in part on the detected defect. In various embodiments, the corrective actions may be selected and configured to reduce the impact of the detected defect on the effectiveness of the sensing device. For example, in response to identifying a defect, a scanning operation may skip scanning the damaged electrode, thus avoiding false positives that would otherwise be detected by the panel. In another example, the operating frequency of the sensing device may be reduced. Additionally, the performance of the defective sensor may be normalized by the surrounding system. Other corrective actions may include scanning the defective electrode longer, using a higher transmit signal, and / or applying a gain value to the receive signal. Thus, an increase in the transmit signal and / or receive gain may be localized to the defective sensor. In another example, the scanning frequency may be reduced, or a particular scanning operation identified as important or high priority may be moved away from the location of the defect. In some embodiments, the user may be provided with options for selecting a corrective action. Thus, the user may identify which corrective action to perform, for example, during a configuration operation.

[0074] In various embodiments, the corrective action may include generating a notification or message. Thus, a notification may be generated and sent to other system components or other systems to indicate that a defect has been detected. For example, the notification may be a message indicating that a repair is recommended or may include a flag indicating that the panel should be replaced during the next service. Furthermore, such notification messages may also include instructions for completing the repair.

[0075] In this way, the impact of defects on operation can be mitigated and reduced, thus allowing the sensing device to be used longer and delaying the time when the sensing device will fail and must be replaced. As described above, sensing devices may be included within systems, such as automobiles and security control panels, and thus may be incorporated into system components that make replacing such sensing devices expensive and impractical. The embodiments disclosed herein extend the functionality of such sensing devices, thus improving the useful life of such systems. Furthermore, the embodiments disclosed herein improve the operational safety of such systems by extending the safe operation of such sensing devices. More particularly, touch panels configured as disclosed herein may be incorporated in contexts such as automobiles, extending the safe operation of such touch panels and ensuring that safe operation and control of automobile components can be maintained despite the presence of defects or failures in portions of the touch panel.

[0076] Returning to operation 1104, if it is determined that no defects are present, method 1100 may perform operation 1108, in which normal operation of the sensing device may be performed. Thus, a normal scanning frequency may be used for the scanning operation, and normal operation of the sensing device may continue. It should be appreciated that additional iterations of method 1100 may be performed periodically or dynamically. For example, additional iterations of the defect detection operation may be performed after a specified period of time has elapsed. In other examples, additional iterations of the defect detection operation may be performed in response to a particular event, such as the occurrence of a message or notification from another system component, or the detection of one or more patterns of activity.

[0077] 12 illustrates an example of another method for defect mitigation performed in accordance with some embodiments. Similar to the above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 1200 may be performed to identify a defect in the sensing device or an associated sensor and perform one or more signal generation operations to compensate for the identified defective electrode.

[0078] Method 1200 may perform operation 1202, in which the sensing device may be scanned in a mutual capacitance mode. Similar to the above, one or more scanning operations may be performed to obtain multiple mutual capacitance measurements using electrodes included within the sensing device. As described above, such mutual capacitance measurements may be stored as measurement data.

[0079] Method 1200 may perform operation 1204, in which one or more diagnostic operations associated with at least some of the plurality of sensors may be performed. Thus, in some embodiments, the sensing device may be included within one or more sensors, such as a touch sensor. During operation 1204, one or more diagnostic operations may be performed to determine whether the sensor is operating properly or whether a problem with the operation of the sensor has been detected.

[0080] Method 1200 may perform operation 1206, in which it may be determined whether a defective electrode is present. Accordingly, during operation 1206, one or more of the defect detection techniques described above may be performed to determine whether a defective electrode is present in the sensing device.

[0081] If a defective electrode is determined to be present, method 1200 may perform operation 1208, which may generate one or more simulation signals based on one or more interpolation operations. In various embodiments, the simulation signals may be generated based on electrodes adjacent to the identified defective electrode. Thus, the adjacent electrodes may be used to approximate or simulate the signal that would be generated by the defective electrode if it were operating properly. In some embodiments, the simulation signals are generated based on one or more interpolation operations. In various embodiments, one or more linear interpolation techniques may be used to generate a signal for the damaged i-th column by averaging signals from adjacent i-1, i+1-th columns using an equation such as Equation (3) below: C i,j =1 / 2(C i-1,j +C i+1,j ) (3)

[0082] Various embodiments may determine that if the damaged column i is located at the end of the sensing device (e.g., the column with the highest or lowest possible index number), the signal for the damaged column may be determined based on a linear extrapolation technique using mutual capacitance values ​​from columns adjacent to the column i, e.g., columns i-1 and i-2, as shown in equation (4). C i,j =2 C i-1,j -C i-2,j (4)

[0083] This type of calculation may be performed for all rows by sweeping the index j in equations (3) and (4). In various embodiments, if the defect is located on a row electrode of the sensing device, a similar interpolation or extrapolation technique may be performed. Thus, a linear interpolation technique may be used to determine a replacement signal for the damaged row line.

[0084] Method 1200 may perform operation 1210, in which signals generated by one or more defective electrodes may be replaced with one or more simulated signals. Thus, the simulated signals may be used to generate an approximated measurement data set, and the approximated measurement data may be included in the measurement data in place of the output of the defective electrodes.

[0085] Method 1200 may perform operation 1212, in which one or more input position calculations may be performed. Thus, the measurement data, which may include approximate measurement data, may be used to determine whether an input, such as a touch or hover, is present on the sensing device. Such a determination may be made based on a comparison of the measurement data to a predetermined threshold, or may be made based on any suitable touch detection calculation.

[0086] 13A illustrates an example of a sensing device configured in accordance with some embodiments. As shown in FIG. 13A, a sensing device such as sensing device 1300 may have one or more rows and columns of electrodes with intersections used for measurements. In some embodiments, one or more of the electrodes may be defective. For example, electrode 1304 may be defective and not function properly. More specifically, electrode 1304 may be damaged, preventing accurate capacitance measurements from being taken.

[0087] 13B shows an example of another sensing device configured in accordance with some embodiments. As shown in FIG. 13B, a sensing device such as sensing device 1310 may have one or more defective electrodes, e.g., electrode 1312. In various embodiments, adjacent electrodes, e.g., electrode 1314 and electrode 1316, may be used to generate a signal to approximate the output of electrode 1312. Thus, an interpolation operation may be performed on measurements associated with electrodes 1314 and 1316 to generate a simulated signal, as described above.

[0088] 14 illustrates an example of an additional method for defect mitigation performed in accordance with some embodiments. Similar to the above, a sensing device may include various electrodes configured to obtain one or more measurements for touch and / or hover detection. In various embodiments, a method such as method 1400 may be performed to identify defects in the sensing device or an associated fingerprint sensor and perform one or more matching operations to compensate for the identified defective electrodes.

[0089] The method 1400 may perform operation 1402, in which the fingerprint sensor may be scanned in a mutual capacitance mode. Similar to the above, one or more scanning operations may be performed to obtain multiple mutual capacitance measurements using electrodes included in a sensing device that may be included in the fingerprint sensor.

[0090] Method 1400 may perform operation 1404, in which one or more diagnostic operations associated with the fingerprint sensor may be performed. Thus, in some embodiments, the sensing device may be included within the fingerprint sensor. During operation 1404, one or more diagnostic operations may be performed to determine whether the fingerprint sensor is operating properly or whether a problem has been detected.

[0091] Method 1400 may perform operation 1406, in which it may be determined whether a defective electrode is present. Accordingly, during operation 1406, one or more of the defect detection techniques described above may be performed to determine whether a defective electrode is present in the sensing device.

[0092] If a defective electrode is determined to be present, method 1400 may perform operation 1408, in which one or more fingerprint image regions may be generated. Accordingly, the sensing device may be divided into one or more regions based on the identified active electrodes. For example, first and second regions may be identified on either side of the defective electrode, and the defective electrode may be excluded. Additional details are detailed below with reference to Figures 15A and 15B.

[0093] Method 1400 may perform operation 1410, which may generate match data based on one or more fingerprint image regions. Thus, measurement data may be generated for each of the identified fingerprint regions, and the data may be stored as match data.

[0094] Method 1400 may perform operation 1412, in which one or more matching operations may be performed. Thus, the match data may be compared to the reference data on a region-by-region basis to determine if a fingerprint match occurs. In this manner, measurements associated with generated fingerprint regions may be compared to corresponding regions of the reference data to determine if a match occurs, and the impact of defective electrodes on such matching operations may be mitigated.

[0095] FIG. 15A shows an example of a sensing device configured in accordance with some embodiments. As shown in FIG. 15A, sensing device 1502 has various electrodes, such as electrode 1504. When electrode 1504 functions properly, a single fingerprint image region, such as fingerprint image region 1506, may be identified. As shown in FIG. 15B, when an electrode does not function properly, that electrode may be excluded and only electrodes, such as the group of electrodes 1508 and 1510, may be used. Thus, when electrode 1504 does not function properly, multiple fingerprint image regions, such as fingerprint image regions 1512 and 1514, may be identified.

[0096] Although the above concepts have been described in some detail for clarity of understanding, it will be apparent that certain changes and modifications may be practiced within the scope of the appended claims. It should be noted that there are many alternative ways of implementing the processes, systems, and devices. Accordingly, the present examples should be considered illustrative and not limiting.

Claims

1. scanning a plurality of electrodes of a sensing device using a specified integration window to obtain a plurality of measurements; determining a plurality of variance values ​​for the plurality of electrodes based on the plurality of measurements and based on distance calculations associated with adjacent sensing locations, the plurality of variance values ​​identifying a variance of the plurality of measurements between the adjacent sensing locations of the sensing device; determining whether a defect exists in the sensing device based at least in part on a comparison of the plurality of variance values ​​to a plurality of thresholds; performing one or more corrective actions in response to determining that a defect exists; A method comprising:

2. The method of claim 1, wherein the one or more corrective actions include generating a notification identifying the defect.

3. The method described in claim 1, wherein the one or more corrective actions include modifying the operating frequency of the sensing device.

4. 2. The method of claim 1, wherein the sensing device is a capacitive sensing device comprising a plurality of first electrodes and a plurality of second electrodes, the plurality of first electrodes and the plurality of second electrodes being orthogonal to one another, and each of a plurality of sensing locations being an intersection between one of the plurality of first electrodes and one of the plurality of second electrodes.

5. The step of determining the plurality of variance values ​​comprises: determining a plurality of difference values ​​for the plurality of electrodes based on the plurality of measurements, the plurality of difference values ​​identifying differences in the plurality of measurements between adjacent sensing locations of the sensing device; identifying a plurality of thresholds for the sensing locations of the sensing device, the plurality of thresholds identifying a designated threshold for each sensing location; Including, The method of claim 4.

6. The method of claim 5 , wherein the plurality of difference values ​​are determined based at least in part on the distance calculation associated with a distance between sensed locations, the distance calculation being a two-dimensional high-pass filter calculation.

7. The method of claim 5 , wherein at least one of the plurality of difference values ​​is determined based at least in part on a least squares regression.

8. The method of claim 5 , wherein the plurality of thresholds are identified based on a plurality of specified panel characteristics.

9. 1. A device comprising one or more processors, the one or more processors: receiving a plurality of measurements obtained from a plurality of first electrodes and a plurality of second electrodes using a specified integration window, the plurality of first electrodes and the plurality of second electrodes being orthogonal to one another; determining a plurality of variance values ​​based on the plurality of measurements and based on distance calculations associated with adjacent sensing locations, the plurality of variance values ​​identifying a variance of the plurality of measurements between the adjacent sensing locations defined by the plurality of first electrodes and the plurality of second electrodes; determining whether a defect exists based at least in part on a comparison of the plurality of variance values ​​to a plurality of thresholds; performing one or more corrective actions in response to determining that a defect exists; configured to: device.

10. the one or more processors: determining a plurality of difference values ​​for the plurality of electrodes based on the plurality of measurements, the plurality of difference values ​​identifying differences in the plurality of measurements between adjacent sensing locations of a sensing device; identifying a plurality of thresholds for the sensing locations of the sensing device, the plurality of thresholds identifying a designated threshold for each sensing location; further configured to: the plurality of difference values ​​are determined based at least in part on a distance calculation associated with a distance between the sensed locations.

10. The device of claim 9.

11. The device of claim 9 , wherein at least one of the plurality of difference values ​​is determined based at least in part on a least squares regression.

12. The device of claim 9 , wherein the one or more corrective actions include generating a notification identifying the defect.

13. The device of claim 9 , wherein the one or more corrective actions include modifying an operating frequency of a sensing device.

14. 1. A system comprising a plurality of first electrodes, a plurality of second electrodes, and a processing device, the plurality of first electrodes and the plurality of second electrodes are orthogonal to each other; intersections between the plurality of first electrodes and the plurality of second electrodes form a plurality of sensing locations; the processing device receiving a plurality of measurements taken from the plurality of first electrodes and the plurality of second electrodes using a specified integration window; determining a plurality of variance values ​​based on the plurality of measurements and based on distance calculations associated with adjacent sensing locations, the plurality of variance values ​​identifying a variance of measurements between the adjacent sensing locations defined by the plurality of first electrodes and the plurality of second electrodes; determining whether a defect exists based at least in part on a comparison of the plurality of variance values ​​to a plurality of thresholds; performing one or more corrective actions in response to determining that a defect exists; configured to: system.

15. the processing device determining a plurality of difference values ​​for the plurality of electrodes based on the plurality of measurements, the plurality of difference values ​​identifying differences in the plurality of measurements between adjacent sensing locations of a sensing device; identifying a plurality of thresholds for the sensing locations of the sensing device, the plurality of thresholds identifying a designated threshold for each sensing location; further configured to: the plurality of difference values ​​are determined based at least in part on a distance calculation associated with a distance between the sensed locations. The system of claim 14.

16. The system of claim 14 , wherein at least one of the plurality of difference values ​​is determined based at least in part on a least squares regression.

17. The system of claim 14 , wherein the processing device is further configured to modify an operating frequency of a sensing device in response to determining that the defect is present.

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