Infrared proximity sensor ranging compensation calibration method

Abstract

The application provides an infrared proximity sensor ranging compensation calibration method and system, which comprises the following steps: taking the value of the sensor in the empty state as the noise, denoted as A; using standard test paper to shield the sensor at different distance positions to obtain the value of the sensor at each distance position, denoted as I; calculating the effective value of I at each position, denoted as Ieff; based on the discrete characteristics of the sampling data set, a mapping formula between the distance and Ieff is fitted, ln(Ieff)=ln(x)-yd; the noise of each device and the value I corresponding to different positions are measured, and the mapping formula corresponding to each device is obtained by substituting the values into the formula; the user defines the proximity distance, and the Ieff corresponding to the current device is calculated according to the mapping formula corresponding to the current device, which is used as the trigger threshold value preset by the current user. The application can improve the consistency of the trigger threshold value of the device at the same distance, and realize product standardization and accurate ranging.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and in particular to a method for ranging compensation calibration of an infrared proximity sensor. Background Technology

[0002] With the increasing popularity of smart home products, infrared sensors are widely used in near-field sensing scenarios. These sensors undergo distance testing before leaving the factory, but due to variations in device structure, hardware and material selection, assembly, and the inherent inconsistencies of the sensor components, the final product exhibits general inconsistencies. This leads to inconsistent trigger thresholds for different software applications, failing to meet precise ranging requirements. Furthermore, the non-linear relationship between infrared sensor data and actual detection distance further amplifies ranging errors and limits the product's sensing accuracy.

[0003] Therefore, it is urgent to study an infrared proximity sensor ranging compensation calibration method to improve the final sensing accuracy of the product. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide an infrared proximity sensor ranging compensation calibration method, which solves the problem that when the same trigger threshold is set in the software, the values ​​collected by sensors of different devices at the same distance are different due to differences in product structure, hardware and material selection, assembly deviation and the consistency of the components themselves, resulting in deviations in the actual trigger distance.

[0005] In a first aspect, the present invention provides a ranging compensation calibration method for an infrared proximity sensor, the method comprising: Step S1: The sensor value measured by the device in an open and unobstructed environment is taken as the noise floor and recorded as the noise floor value A. Step S2: According to the application requirements of different distance levels on the device, use standard test paper to block the sensor at different distance levels by placing it at the corresponding height of the fixture, and obtain the sensor value I at each distance level as the sampling dataset. Step S3: Calculate the effective value of I for each distance level in the sampled dataset, denoted as I effective, where I effective = numerical value I - noise floor value A; Step S4: Based on the discrete distribution of the sampled dataset, fit the mapping formula between distance and effective value I: ln(I effective) = ln(x) - yd, where d is the distance corresponding to the distance level, and x and y are parameters to be determined; Step S5: Before leaving the factory, measure the noise floor of each device and the value I corresponding to different distance levels, and record the effective value of I corresponding to different distances as a calibration data set. Step S6: Substitute the calibration data set of each device into the mapping formula, calculate the corresponding parameter x and y values ​​for each device, and obtain the one-to-one mapping formula for each device after calibration, which is used as the mapping formula for the current device. Step S7: The application calculates the effective value of I corresponding to the proximity distance by inputting the user-defined proximity distance and referencing the current device mapping formula, which is used as the trigger threshold preset by the current user.

[0006] Furthermore, the distance settings in step S2 are specifically 30cm, 60cm, 80cm and 100cm.

[0007] Furthermore, in step S6, the calibration data set includes at least two sets: when two sets of data are input for calculation, a unique solution x and y is obtained, and the mapping formula corresponding to the current device is determined; when more than two sets of data are input, the optimal x and y values ​​are obtained by least squares fitting, and the mapping formula corresponding to the current device is determined.

[0008] Furthermore, after step S6, a verification operation on the mapping formula is also included, as follows: Take at least two test point distances d0 and d2, substitute them into the formula, and calculate the corresponding effective values ​​of I, I0 and I2 respectively. Then place the paper at a test distance d1 and measure the effective value of I, I1. If the following conditions are met: d0 > d1 > d2 and I2 > I1 > I0, then the test is considered passed, that is, the mapping formula corresponding to the current device has been verified and has taken effect.

[0009] Furthermore, step S4 also includes: when a numerical mutation occurs in the sampled dataset that exceeds the range of the preset fitting formula, fitting is performed separately according to different distance levels.

[0010] Secondly, the present invention provides an infrared proximity sensor ranging compensation calibration device, the device comprising: The noise floor data acquisition module is used to take the value of the sensor measured by the device in an open and unobstructed environment as the noise floor, and denoted as the noise floor value A. The numerical acquisition module is used to obtain the sensor's numerical value I at different distance levels by placing standard test paper at the corresponding height of the fixture to block the sensor at different distance levels according to the application requirements of different distance levels of the device, and using it as a sampling dataset. The deviation processing module is used to calculate the effective value of I at each distance level of the sampled dataset, denoted as I effective, where I effective = numerical value I - background noise value A; The formula fitting module is used to fit the mapping formula between distance and effective value I based on the discrete distribution of the sampled dataset: ln(I effective) = ln(x) - yd, where d is the distance corresponding to the distance level, and x and y are parameters to be determined; The calibration data acquisition module is used to measure the noise floor and the value I corresponding to different distance levels of each device before it leaves the factory, and record the effective value of I corresponding to different distances as a calibration data set. The formula determination module is used to substitute the calibration data set of each device into the mapping formula, calculate the corresponding parameter x and y values ​​of each device, and obtain a one-to-one mapping formula for each device after calibration, which is used as the mapping formula for the current device. The trigger threshold calculation module is used by the application to calculate the effective value of I corresponding to the proximity distance by inputting a user-defined proximity distance and referring to the current device mapping formula, which is then used as the trigger threshold preset by the current user.

[0011] Furthermore, the distance settings in the numerical acquisition module are specifically 30cm, 60cm, 80cm and 100cm.

[0012] Furthermore, the calibration data set in the formula determination module includes at least two sets: when two sets of data are input for calculation, a unique solution x and y is obtained, and the mapping formula corresponding to the current device is determined; when more than two sets of data are input, the optimal x and y values ​​are obtained by least squares fitting, and the mapping formula corresponding to the current device is determined.

[0013] Furthermore, the formula determination module is followed by a verification module, as detailed below: Take at least two test point distances d0 and d2, substitute them into the formula, and calculate the corresponding effective values ​​of I, I0 and I2 respectively. Then place the paper at a test distance d1 and measure the effective value of I, I1. If the following conditions are met: d0 > d1 > d2 and I2 > I1 > I0, then the test is considered passed, that is, the mapping formula corresponding to the current device has been verified and has taken effect.

[0014] Furthermore, the formula fitting module also includes: when a numerical mutation occurs in the sampled dataset that exceeds the range of the preset fitting formula, fitting is performed separately according to different distance levels.

[0015] The present invention provides one or more technical solutions, which have at least the following technical effects or advantages: by sampling and fitting formulas for products of the same model, and by substituting the test data of each device into the formulas to obtain the determined parameters, each device can achieve difference compensation through the fitting formula, thereby improving the sensing accuracy of the device. The compensation calibration method of the present invention can effectively eliminate the noise difference caused by components and assembly, improve the consistency of the trigger threshold of devices of the same model at the same distance, realize product standardization, improve mass production calibration efficiency, and reduce after-sales costs. Attached Figure Description

[0016] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0017] Figure 1 This is a flowchart illustrating the execution of an infrared proximity sensor ranging compensation calibration method according to Embodiment 1 of the present invention. Figure 2 This is a schematic diagram of the structure of an infrared proximity sensor ranging compensation calibration system according to the present invention. Detailed Implementation

[0018] This application provides an infrared proximity sensor ranging compensation calibration method and system, which can effectively eliminate noise floor differences, improve the consistency of trigger thresholds for smart home devices at the same distance, improve ranging accuracy, achieve product standardization, and improve mass production efficiency.

[0019] The technical solution in this application embodiment follows the following general approach: First, by collecting distance measurement data from several devices of the same model, including distance and corresponding sensor data, a parameter formula for the distance corresponding to the sensor value is fitted. Then, during the in-plant functional testing phase after the equipment assembly is completed, multiple distances and near-valid values ​​measured at the production end are substituted into the factory test (software used for production testing) to derive the parameter determination formula, obtaining a one-to-one correspondence between distance d and the effective sensor value I. Next, a distance d is substituted into the parameter determination formula to obtain I effective. Then, I effective is compared with I effective measured at two distances before and after. For example, if d is substituted into the formula to obtain I effective, and the factory test obtains I effective 1 at (d-10) cm and I effective 2 at (d+10) cm, when I effective 2 < I effective < I effective 1, it is determined that the parameter determination formula has passed verification. Finally, the application end references the verified formula, substitutes the corresponding distance according to the actual distance requirements at the installation site, and obtains the corresponding distance's I effective as a trigger threshold. The distance sensor numerical formula (i.e., mapping formula) derived from the fitting of the distance measurement data of the above-mentioned devices of the same model can be applied to all devices of the same model. Each device is tested again before leaving the factory to determine the parameter values ​​in the formula, realize device-side difference compensation, and obtain the formula determined by each device, thereby improving the sensing accuracy of the device.

[0020] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods. Example 1

[0021] like Figure 1 As shown, this embodiment provides a ranging compensation calibration method for an infrared proximity sensor, the method comprising: Step S1: The sensor values ​​measured by the device in an open and unobstructed environment are taken as the noise floor, and recorded as the noise floor value A; deviations caused by inconsistencies in structural assembly, hardware, materials, and components are reflected in the noise floor at the device end. Step S2: According to the application requirements of different distance levels on the device (or product), use standard test paper to block the sensor at different distance levels by placing it at the corresponding height of the fixture, and obtain the sensor value I at each distance level as the sampling dataset; for infrared sensors, the relationship between the collected value and the distance from the blocking object to the sensor should be: the closer the distance, the larger the collected value. Step S3: Calculate the effective value of I for each distance level in the sampled dataset, denoted as I effective, I effective = numerical value I - background noise value A, and remove consistency deviation; Step S4: Combining the exponential decay characteristic of infrared light intensity with distance, and based on the discrete distribution of the sampled dataset, fit the mapping formula between distance and effective value I: ln(I effective) = ln(x) - yd, where d is the distance corresponding to the distance level, and x and y are parameters to be determined; Step S5: Before leaving the factory, measure the noise floor of each device and the value I corresponding to different distance levels, and record the effective value of I corresponding to different distances as a calibration data set. The calibration data set is based on the distance requirements of different products. The production end records the equipment noise floor A one by one, and places test cards at the corresponding distances of the tooling to block the noise. The software records and writes the effective values ​​of I corresponding to different distances d. Step S6: Substitute the calibration data set of each device into the mapping formula, calculate the corresponding parameter x and y values ​​for each device, and obtain the one-to-one mapping formula for each device after calibration, which is used as the mapping formula for the current device. Step S7: On the current device application side (device application stage), by inputting the user-defined proximity distance and referencing the current device mapping formula, calculate the effective value of I corresponding to the proximity distance, which is used as the trigger threshold preset by the current user.

[0022] Preferably, the distance settings in step S2 are specifically 30cm, 60cm, 80cm, and 100cm. Based on the application requirements of different distance settings on the product side, such as very close / near / standard / far corresponding to distances d=30 / 60 / 80 / 100cm, standard test cards are placed at the corresponding heights of the fixture at 30 / 60 / 80 / 100cm from the sensor to provide coverage. The values ​​of I measured at different distances are recorded as IB / IC / ID / IE, respectively. To remove consistency deviations: calculate the effective I at different distances = numerical I - noise floor value A, thus obtaining the effective IB / IC / ID / IE values.

[0023] Preferably, the calibration data set in step S6 includes at least two sets: when two sets of data are input for calculation, a unique solution x and y is obtained, and the mapping formula corresponding to the current device is determined; when more than two sets of data are input, the optimal x and y values ​​are obtained by least squares fitting, and the mapping formula corresponding to the current device is determined.

[0024] Preferably, after step S6, a verification operation on the mapping formula is further included, as follows: Take at least two test points at distances d0 and d2, substitute them into the formula, and calculate the corresponding valid values ​​of I as I0 and I2, respectively. Then place the card at a test distance d1 and measure the valid value of I as I1. If the following conditions are met: d0 > d1 > d2 and I2 > I1 > I0, then the test is considered passed, meaning the mapping formula corresponding to the current device has been verified and is effective. The test points can be selected from commonly used distances based on the product application scenario.

[0025] For example, substituting d=60 and d=80 into the formula, the corresponding effective I is calculated and used as the software verification threshold. During production verification, the paper jam is placed 70cm away from the equipment, and the effective I is measured. Simultaneously, if the effective I measured at d=80cm < the effective I measured at d=70cm < the effective I measured at d=60cm, the test passes, meaning the formula has taken effect and verification is complete. Then, on the application side, the factory-verified formula is used as the standard, and the required distance d is substituted to obtain the corresponding effective I, which can then be used as the preset trigger threshold at the required distance on the application side.

[0026] As mentioned above, each device is calibrated to generate a one-to-one formula, and reverse verification can be performed at the production end to ensure the formula's validity.

[0027] Specifically, step S4 further includes: when a numerical mutation occurs in the sampled dataset that exceeds the range of the preset fitting formula, fitting is performed separately according to different distance levels, or the effective value of I collected corresponding to the mutation distance d is directly used as the trigger threshold for applying the corresponding distance level. Example 2

[0028] like Figure 2 As shown, this embodiment provides an infrared proximity sensor ranging compensation calibration device, the device comprising: The noise floor data acquisition module is used to take the values ​​of the sensor measured by the device in an open and unobstructed environment as the noise floor, denoted as the noise floor value A; deviations caused by inconsistencies in structural assembly, hardware, materials, and components are reflected as noise floor at the device end. The numerical acquisition module is used to obtain the sensor's numerical value I at different distance levels by placing standard test cards at the corresponding height of the fixture to block the sensor at different distance levels according to the application requirements of different distance levels on the device (or product) side. This value is used as the sampling dataset. For infrared sensors, the relationship between the acquired value and the distance from the blocking object to the sensor should be: the closer the distance, the larger the acquired value. The deviation processing module is used to calculate the effective value of I at each distance level of the sampled dataset, denoted as I effective, where I effective = numerical value I - background noise value A, and removes consistency deviation. The formula fitting module is used to combine the exponential decay characteristics of infrared light intensity with distance and, based on the discrete distribution of the sampled dataset, fit the mapping formula between distance and effective value I: ln(I effective) = ln(x) - yd, where d is the distance corresponding to the distance level, and x and y are parameters to be determined. The calibration data acquisition module is used to measure the noise floor and the corresponding values ​​I for different distance levels of each device before it leaves the factory, and record the effective values ​​of I for different distances as calibration data sets. The calibration data sets are generated by recording the noise floor A of each device at the production end according to the distance requirements of different products, and placing test cards at the corresponding distances of the tooling to block the noise. The software records and writes the effective values ​​of I corresponding to different distances d.

[0029] The formula determination module is used to substitute the calibration data set of each device into the mapping formula, calculate the corresponding parameter x and y values ​​of each device, and obtain a one-to-one mapping formula for each device after calibration, which is used as the mapping formula for the current device. The trigger threshold calculation module is used to calculate the effective value of I corresponding to the current proximity distance by inputting a user-defined proximity distance and referencing the current device mapping formula at the current device application end (device application stage), and use it as the trigger threshold preset by the current user.

[0030] Preferably, the distance settings in the numerical acquisition module are specifically 30cm, 60cm, 80cm, and 100cm. Based on the application requirements of different distance settings on the product side, such as very close / near / standard / far corresponding to distances d=30 / 60 / 80 / 100cm, standard test cards are placed at the corresponding heights of the fixture at 30 / 60 / 80 / 100cm from the sensor to provide coverage. The values ​​of I measured at different distances are recorded as IB / IC / ID / IE, respectively. To remove consistency deviations: calculate the effective value of I at different distances as I = numerical value I - noise floor value A, thus obtaining the effective values ​​of IB / IC / ID / IE.

[0031] Preferably, the calibration data set in the formula determination module includes at least two sets: when two sets of data are input for calculation, a unique solution x and y is obtained, and the mapping formula corresponding to the current device is determined; when more than two sets of data are input, the optimal x and y values ​​are obtained by least squares fitting, and the mapping formula corresponding to the current device is determined.

[0032] Preferably, the formula determination module further includes a verification module, as follows: Take at least two test point distances d0 and d2, substitute them into the formula, and calculate the corresponding effective values ​​of I, I0 and I2 respectively. Then place the paper at a test distance d1 and measure the effective value of I, I1. If the following conditions are met: d0 > d1 > d2 and I2 > I1 > I0, then the test is considered passed, that is, the mapping formula corresponding to the current device has been verified and has taken effect.

[0033] For example, substituting d=60 and d=80 into the formula, the corresponding effective I is calculated and used as the software verification threshold. During production verification, the paper jam is placed 70cm away from the equipment, and the effective I is measured. Simultaneously, if the effective I measured at d=80cm < the effective I measured at d=70cm < the effective I measured at d=60cm, the test passes, meaning the formula has taken effect and verification is complete. Then, on the application side, the factory-verified formula is used as the standard, and the required distance d is substituted to obtain the corresponding effective I, which can then be used as the preset trigger threshold at the required distance on the application side.

[0034] As mentioned above, each device is calibrated to generate a one-to-one formula, and reverse verification can be performed at the production end to ensure the formula's validity.

[0035] Preferably, the formula fitting module further includes: when a numerical mutation occurs in the sampled dataset that exceeds the range of the preset fitting formula, fitting is performed separately according to different distance levels, or the effective value of I collected corresponding to the distance d of the mutation is directly used as the trigger threshold for applying the corresponding distance level.

[0036] The technical solution provided in this application embodiment has at least the following technical effects or advantages: it effectively solves the problem that, due to differences in product structure, hardware and material selection, assembly deviations, and the consistency of components themselves, when a unified trigger threshold is set in the software, the values ​​collected by sensors of different devices at the same distance deviate, resulting in deviations in the actual trigger distance. The application of this invention's technical solution allows product applications to perform distance calibration according to actual product needs, achieving accurate distance measurement, while simultaneously improving the consistency of product thresholds at the same distance.

[0037] While specific embodiments of the present invention have been described above, those skilled in the art should understand that the specific embodiments described are merely illustrative and not intended to limit the scope of the invention. Equivalent modifications and variations made by those skilled in the art in accordance with the spirit of the invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A ranging compensation calibration method for an infrared proximity sensor, characterized in that: The method includes: Step S1: The sensor value measured by the device in an open and unobstructed environment is taken as the noise floor and recorded as the noise floor value A. Step S2: According to the application requirements of different distance levels on the device, use standard test paper to block the sensor at different distance levels by placing it at the corresponding height of the fixture, and obtain the sensor value I at each distance level as the sampling dataset. Step S3: Calculate the effective value of I for each distance level in the sampled dataset, denoted as I effective, where I effective = numerical value I - noise floor value A; Step S4: Based on the discrete distribution of the sampled dataset, fit the mapping formula between distance and effective value I: ln(I effective) = ln(x) - yd, where d is the distance corresponding to the distance level, and x and y are parameters to be determined; Step S5: Before leaving the factory, measure the noise floor of each device and the value I corresponding to different distance levels, and record the effective value of I corresponding to different distances as a calibration data set. Step S6: Substitute the calibration data set of each device into the mapping formula, calculate the corresponding parameter x and y values ​​for each device, and obtain the one-to-one mapping formula for each device after calibration, which is used as the mapping formula for the current device. Step S7: The application calculates the effective value of I corresponding to the proximity distance by inputting the user-defined proximity distance and referencing the current device mapping formula, which is used as the trigger threshold preset by the current user.

2. The infrared proximity sensor ranging compensation calibration method according to claim 1, characterized in that: The distance settings in step S2 are specifically 30cm, 60cm, 80cm and 100cm.

3. The infrared proximity sensor ranging compensation calibration method according to claim 1, characterized in that: In step S6, the calibration data set includes at least two sets: when two sets of data are input for calculation, a unique solution x and y is obtained, and the mapping formula corresponding to the current device is determined; when more than two sets of data are input, the least squares fitting is used to find the optimal x and y values, and the mapping formula corresponding to the current device is determined.

4. The infrared proximity sensor ranging compensation calibration method according to claim 1, characterized in that: Following step S6, a verification operation is performed on the mapping formula, as follows: Take at least two test point distances d0 and d2, substitute them into the formula, and calculate the corresponding effective values ​​of I, I0 and I2 respectively. Then place the paper at a test distance d1 and measure the effective value of I, I1. If the following conditions are met: d0 > d1 > d2 and I2 > I1 > I0, then the test is considered passed, that is, the mapping formula corresponding to the current device has been verified and has taken effect.

5. The infrared proximity sensor ranging compensation calibration method according to claim 1, characterized in that: Step S4 further includes: when a numerical mutation occurs in the sampled dataset that exceeds the range of the preset fitting formula, fitting is performed separately according to different distance levels.

6. An infrared proximity sensor ranging compensation calibration device, characterized in that: The device includes: The noise floor data acquisition module is used to take the value of the sensor measured by the device in an open and unobstructed environment as the noise floor, and denoted as the noise floor value A. The numerical acquisition module is used to obtain the sensor's numerical value I at different distance levels by placing standard test paper at the corresponding height of the fixture to block the sensor at different distance levels according to the application requirements of different distance levels of the device, and using it as a sampling dataset. The deviation processing module is used to calculate the effective value of I at each distance level of the sampled dataset, denoted as I effective, where I effective = numerical value I - background noise value A; The formula fitting module is used to fit the mapping formula between distance and effective value I based on the discrete distribution of the sampled dataset: ln(I effective) = ln(x) - yd, where d is the distance corresponding to the distance level, and x and y are parameters to be determined; The calibration data acquisition module is used to measure the noise floor and the value I corresponding to different distance levels of each device before it leaves the factory, and record the effective value of I corresponding to different distances as a calibration data set. The formula determination module is used to substitute the calibration data set of each device into the mapping formula, calculate the corresponding parameter x and y values ​​of each device, and obtain a one-to-one mapping formula for each device after calibration, which is used as the mapping formula for the current device. The trigger threshold calculation module is used by the application to calculate the effective value of I corresponding to the proximity distance by inputting a user-defined proximity distance and referring to the current device mapping formula, which is then used as the trigger threshold preset by the current user.

7. The infrared proximity sensor ranging compensation calibration device according to claim 6, characterized in that: The distance settings in the numerical acquisition module are specifically 30cm, 60cm, 80cm and 100cm.

8. The infrared proximity sensor ranging compensation calibration device according to claim 6, characterized in that: The calibration data set in the formula determination module includes at least two sets: when two sets of data are input for calculation, a unique solution x and y is obtained, and the mapping formula corresponding to the current device is determined; when more than two sets of data are input, the optimal x and y values ​​are obtained by least squares fitting, and the mapping formula corresponding to the current device is determined.

9. The infrared proximity sensor ranging compensation calibration device according to claim 6, characterized in that: The formula determination module is followed by a verification module, as detailed below: Take at least two test point distances d0 and d2, substitute them into the formula, and calculate the corresponding effective values ​​of I, I0 and I2 respectively. Then place the paper at a test distance d1 and measure the effective value of I, I1. If the following conditions are met: d0 > d1 > d2 and I2 > I1 > I0, then the test is considered passed, that is, the mapping formula corresponding to the current device has been verified and has taken effect.

10. The infrared proximity sensor ranging compensation calibration device according to claim 6, characterized in that: The formula fitting module also includes: when a numerical mutation occurs in the sampled dataset that exceeds the range of the preset fitting formula, fitting is performed separately according to different distance levels.

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