A method, apparatus, and medium for determining a fog voltage

Abstract

The application discloses a kind of mist state voltage determination method, equipment and medium.Therein, the determination method of mist state voltage is applied to the measuring device of mist state voltage, measuring device includes: main control circuit board, haze measuring device and driver;Main control circuit board is connected with haze measuring device and driver communication respectively.Determination method includes: output first control signal, to control driver to apply multiple different drive voltages to the sample to be measured;Based on haze measuring device, the haze measurement data corresponding to the sample to be measured under each drive voltage is acquired;According to haze measurement data, the best mist state voltage of the sample to be measured is determined.The technical scheme of the application, the best mist state voltage of the sample to be measured is determined by analyzing haze data, avoids the problem that only relying on measuring personnel visual judgment sample to be measured under the stability of drive voltage driven low accuracy, realizes the automatic acquisition analysis of haze measuring device, improves the accuracy of the best mist state voltage, reduces manpower cost.

Description

Technical Field

[0001] This invention relates to the field of smart glass technology, and more particularly to a method, apparatus and medium for determining fog voltage. Background Technology

[0002] Bistable dimming glass is a new type of fogging dimming glass. When the dimming glass is in a transparent state, it can be driven to a fogging state by applying an AC pulse with specific conditions. Therefore, a method is needed to measure the driving conditions of its fogging state.

[0003] Existing testing methods often rely on visual evaluation of the stability of glass haze. Therefore, the haze value measured by the haze meter when the dimming glass is stable is related to the subjective judgment of the measuring personnel, resulting in low accuracy of the haze driving conditions of the dimming glass. Summary of the Invention

[0004] This invention provides a method, apparatus, and medium for determining fog voltage, in order to solve the problem of low accuracy in obtaining the optimal fog voltage of dimming glass in the prior art.

[0005] According to one aspect of the present invention, a method for determining fog voltage is provided. This method is applied to a fog voltage measuring device, the measuring device comprising: a main control circuit board, a fog measuring device, and a driver; the main control circuit board is communicatively connected to the fog measuring device and the driver, respectively.

[0006] The determination methods include:

[0007] S1. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test;

[0008] S2. Obtain haze measurement data for the sample under each driving voltage based on the haze measurement device;

[0009] S3. Determine the optimal fog voltage for the sample to be tested based on the fog measurement data.

[0010] Optionally, the optimal fog voltage for the sample to be tested can be determined based on fog measurement data, including:

[0011] Acquire time-based haze data sets for the sample under each driving voltage. The time-based haze data sets include haze values ​​corresponding to each measurement time under the same driving voltage.

[0012] The haze value for each driving voltage is determined based on each set of time haze data.

[0013] Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage.

[0014] Optionally, the haze value for each drive voltage is determined based on each set of time-based haze data, including:

[0015] The stable haze range of the sample under each driving voltage is determined based on each set of time haze data.

[0016] The haze value for each driving voltage is determined based on each stable haze range.

[0017] Optionally, based on each set of time-based haze data, the stable haze range of the sample under each driving voltage is determined, including:

[0018] Determine the actual fluctuation values ​​of multiple haze values ​​in each set of time haze data within a preset time period;

[0019] When the actual fluctuation value of the i-th preset time period is within the standard fluctuation value range and the actual fluctuation value of the (i+1)-th preset time period is within the standard fluctuation value range, a stable haze interval is determined. The stable haze interval includes all haze values ​​corresponding to the time from the i-th preset time period to the time after the i-th preset time period; i is a positive integer.

[0020] Optionally, the haze value for each driving voltage is determined based on each stable haze range, including:

[0021] Determine the mean haze value for all haze values ​​in each stable haze interval;

[0022] The average haze value corresponding to different driving voltages is determined as the haze value for different driving voltages.

[0023] Optionally, determine the actual fluctuation values ​​of multiple haze values ​​in each set of time haze data within a preset time period, including:

[0024] The amount of haze change in each preset time period is determined based on the haze value within each preset time period. The amount of haze change is the difference between the maximum and minimum haze values ​​in the preset time period.

[0025] The amount of haze value change in each preset time period is determined as the actual fluctuation value for each preset time period.

[0026] Optionally, a first control signal is output to control the driver to apply multiple different drive voltages to the sample under test, including:

[0027] Output the first temperature control signal to adjust the ambient temperature of the sample to the first temperature.

[0028] After determining the optimal fog voltage of the sample to be tested based on each fog measurement data, the method also includes: outputting a second temperature control signal to adjust the ambient temperature of the sample to the second temperature, wherein the first temperature is not equal to the second temperature;

[0029] Repeat steps S1-S3 to determine the optimal fog voltage corresponding to the second temperature.

[0030] Optionally, before acquiring the haze measurement data corresponding to the sample under each driving voltage based on the haze measurement device, the following steps are included:

[0031] Output a haze measurement signal to control the haze measurement device to measure the haze of the sample to be tested.

[0032] According to another aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for determining fog voltage.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements a method for determining fog voltage.

[0034] The technical solution of this invention utilizes a main control circuit board to control a driver to apply different driving voltages to the sample under test and automatically acquires haze data measured by a haze measuring device. By analyzing the haze data, the optimal haze voltage of the sample under test is determined. This avoids the problem of low accuracy in relying solely on visual judgment by the measuring personnel to determine the stability of the sample under driving voltage. This invention achieves automatic acquisition and analysis of haze measuring devices by automatically analyzing haze measurement data to determine the stability of the sample under test, thereby improving the accuracy of the optimal haze voltage and reducing labor costs.

[0035] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart of a first method for determining fog voltage according to an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of a fog voltage measuring device according to an embodiment of the present invention;

[0039] Figure 3This is a flowchart of a second method for determining fog voltage according to an embodiment of the present invention;

[0040] Figure 4 This is a graph showing the relationship between measurement time and haze value under the same driving voltage, according to an embodiment of the present invention.

[0041] Figure 5 This is a graph showing the relationship between driving voltage and haze value at the same temperature, provided by an embodiment of the present invention.

[0042] Figure 6 This is a flowchart of a third method for determining fog voltage according to an embodiment of the present invention;

[0043] Figure 7 This is a flowchart of a fourth method for determining fog voltage according to an embodiment of the present invention;

[0044] Figure 8 This is a flowchart of a fifth method for determining fog voltage according to an embodiment of the present invention;

[0045] Figure 9 This is a flowchart of a sixth method for determining fog voltage according to an embodiment of the present invention;

[0046] Figure 10 This is a flowchart of a method for determining the seventh fog voltage according to an embodiment of the present invention;

[0047] Figure 11 This is a schematic diagram of the structure of an electronic device applied to a method for determining fog voltage according to an embodiment of the present invention. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0049] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0050] Figure 1 This is a flowchart of a first method for determining fog voltage according to an embodiment of the present invention. Figure 2 This is a schematic diagram of a fog voltage measuring device according to an embodiment of the present invention. The fog voltage determination method is applied to the fog voltage measuring device, combined with... Figure 1 and Figure 2 As shown, the measuring device includes: a main control circuit board 1, a haze measuring device 2, and a driver 3; the main control circuit board 1 is communicatively connected to the haze measuring device 2 and the driver 3 respectively.

[0051] The determination methods include:

[0052] S1. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0053] The first control signal is output by the main control circuit board 1. The first control signal can be the drive signal of the driver 3. The main control circuit board 1 outputs the first control signal to the driver 3 to control the driver 3 to apply multiple different drive voltages to the sample 4 to be tested, so as to drive the sample 4 to the corresponding fog state.

[0054] Specifically, the first control signal can control the driver 3 to output multiple different driving voltages. The haze value of the test sample 4 is different depending on the magnitude of the driving voltage applied. The interval time of the different driving voltage outputs is set according to the properties of the dimming glass itself. This embodiment of the invention does not limit this. It is sufficient to ensure that the haze value of the test sample 4 tends to stabilize after a certain period of time when each driving voltage is applied.

[0055] S2. Obtain the haze measurement data of the sample under each driving voltage based on the haze measurement device.

[0056] The sample 4 to be tested is placed on the haze measuring device 2. The haze measuring device 2 can measure the haze of the sample 4 to be tested according to the haze measurement principle and output the haze measurement data. Since the main control circuit board 1 is connected to the haze measuring device 2, the haze measurement data measured in the haze measuring device 2 can be input to the main control circuit board 1. The haze measurement data includes the haze value of the sample 4 to be tested under each driving voltage.

[0057] In some embodiments, the main control circuit board 1 also outputs a haze measurement signal to control the haze measuring device 2 to measure the haze of the sample 4 under test. The main control circuit board 1 may output multiple haze measurement signals, and it outputs a haze measurement signal once every set time interval, causing the haze measuring device 2 to collect the haze value of the sample 4 under test and input it to the main control circuit board 1. Alternatively, the main control circuit board 1 may output a single haze measurement signal to the haze measuring device 2, and the haze measuring device 2 collects the haze value of the sample 4 under test once every set time interval and inputs it to the main control circuit board 1.

[0058] S3. Determine the optimal fog voltage for the sample to be tested based on the fog measurement data.

[0059] The haze measurement data includes the haze value of the sample 4 under each driving voltage; the optimal haze voltage can be the driving voltage corresponding to the maximum haze value when the haze value of the sample 4 is stable.

[0060] The technical solution of this invention utilizes a main control circuit board to control a driver to apply different driving voltages to the sample under test and automatically acquires haze data measured by a haze measuring device. By analyzing the haze data, the optimal haze voltage for the sample under test is determined. This avoids the problem of low accuracy in relying solely on visual judgment by the measuring personnel to determine the stability of the sample under driving voltage. This invention achieves automatic acquisition and analysis of haze measuring device by automatically analyzing haze measurement data to determine the stability of the sample under test, thereby improving the accuracy of the optimal haze voltage and reducing labor costs.

[0061] Based on the above embodiments, Figure 3 This is a flowchart of a second method for determining fog voltage according to an embodiment of the present invention, as shown below. Figure 3 As shown, the determination method includes:

[0062] S11. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0063] S12. Obtain the haze measurement data of the sample under each driving voltage based on the haze measurement device.

[0064] S13. Obtain the time haze data set of the sample under each driving voltage. The time haze data set includes the haze value corresponding to each measurement time under the same driving voltage.

[0065] The time-based haze data set can be the haze values ​​of the sample under each driving voltage at different measurement times. The time-based haze data set can be a curve with time on the horizontal axis and haze value on the vertical axis, or it can be haze value data corresponding to different measurement times. This embodiment of the invention does not specifically limit the form of the time-based haze data set.

[0066] For example, Figure 4 This is a graph showing the relationship between measurement time and haze value under the same driving voltage, as provided in an embodiment of the present invention. Figure 4 As shown, the haze value was 83.6% at the 0-minute mark; 82% at the 2-minute mark; 81.8% at the 4-minute mark; 81.7% at the 6-minute mark; 81.6% at the 8-minute mark; 81.6% at the 10-minute mark; 81.5% at the 12-minute mark; 81.6% at the 14-minute mark; and 81.6% at the 16-minute mark.

[0067] S14. Determine the haze value of each driving voltage based on each set of time haze data.

[0068] You can continue to refer to this. Figure 4 As shown, from Figure 4 As can be seen from the curve of haze value changing with time under the same driving voltage, after the 10th minute, the downward trend of haze value becomes flat. At this time, it is considered that the haze value of the sample under test tends to be stable under this driving voltage. The stable haze value in each group of time haze data is taken as the haze value of each driving voltage.

[0069] S15. Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage.

[0070] For example, Figure 5 This is a graph showing the relationship between driving voltage and haze value at the same temperature, provided by an embodiment of the present invention. Figure 5 As shown, a curve of haze versus voltage can be plotted for each driving voltage and its haze value. The horizontal axis represents voltage and the vertical axis represents haze value. The maximum haze value of the sample under test is 83.5%, and the driving voltage corresponding to this haze value is 27V. At this time, 27V is taken as the optimal haze voltage.

[0071] The technical solution of this invention determines the haze value corresponding to each driving voltage by acquiring the time haze data set of the sample to be tested, and takes the driving voltage corresponding to the maximum haze value as the optimal haze voltage. This ensures that the haze value corresponding to each driving voltage obtained from the time haze data set is the haze value of the sample to be tested in a stable haze state, which makes the accuracy of the haze value higher and further improves the accuracy of obtaining the optimal haze voltage.

[0072] Based on the above embodiments, Figure 6 This is a flowchart of a third method for determining fog voltage according to an embodiment of the present invention, combined with... Figure 2 , Figure 4 and Figure 6 As shown, the determination method includes:

[0073] S21. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0074] S22. Obtain the haze measurement data of the sample under each driving voltage based on the haze measurement device.

[0075] S23. Obtain the time haze data set of the sample under each driving voltage. The time haze data set includes the haze value corresponding to each measurement time under the same driving voltage.

[0076] S24. Determine the stable haze range of the sample under each driving voltage based on each set of time haze data.

[0077] The stable haze range can be defined as the measurement period during which the haze region of the sample 4 remains stable under the same driving voltage. For example, refer to... Figure 4 As shown, under the same driving voltage, after about 10 minutes of applying the driving voltage, the trend of haze decrease becomes gradual and basically remains stable. Therefore, the period from the 10th minute to the 16th minute is determined as the stable haze range.

[0078] S25. Determine the haze value of each driving voltage based on each stable haze range.

[0079] Specifically, determining the haze value of each driving voltage based on each stable haze interval can be achieved by selecting any haze value within the stable haze interval, which is the haze value of the sample 4 under test when it is stable; alternatively, determining the haze value of each driving voltage based on each stable haze interval can be achieved by calculating the average of all haze values ​​within the stable haze interval, which is the average haze value of the sample 4 under test when it is stable.

[0080] S26. Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage.

[0081] The technical solution of this invention, by determining a stable haze range and determining the haze value of each driving voltage based on the stable haze range, avoids the problem of inaccurate determination of the optimal haze voltage when the haze state of the sample under test is unstable, and improves the accuracy of obtaining the optimal haze voltage.

[0082] Based on the above embodiments, Figure 7 This is a flowchart of a fourth method for determining fog voltage according to an embodiment of the present invention, combined with... Figure 4 and Figure 7 As shown, the determination method includes:

[0083] S31. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0084] S32. Obtain the haze measurement data of the sample under each driving voltage based on the haze measurement device.

[0085] S33. Obtain the time haze data set of the sample under each driving voltage. The time haze data set includes the haze value corresponding to each measurement time under the same driving voltage.

[0086] S34. Determine the actual fluctuation values ​​of multiple fog values ​​in each group of time fog data within a preset time period.

[0087] The preset time period can be obtained based on the measurement time, and the interval between two adjacent measurement times is the preset time period. Determining the actual fluctuation value of multiple haze values ​​in each set of time haze data within the preset time period can be achieved by obtaining the actual fluctuation value corresponding to each adjacent measurement time.

[0088] For example, continue to refer to Figure 4 As shown, the actual fluctuation value can be the haze value fluctuation range between 0 minutes and 2 minutes, between 2 minutes and 4 minutes, between 4 minutes and 6 minutes, between 6 minutes and 8 minutes, between 8 minutes and 10 minutes, between 10 minutes and 12 minutes, between 12 minutes and 14 minutes, and between 14 minutes and 16 minutes.

[0089] S35. When the actual fluctuation value of the i-th preset time period is within the standard fluctuation value range and the actual fluctuation value of the (i+1)-th preset time period is within the standard fluctuation value range, a stable haze interval is determined. The stable haze interval includes all haze values ​​corresponding to the time from the i-th preset time period to the time after the i-th preset time period; i is a positive integer.

[0090] The standard fluctuation range can be set according to the characteristics of the dimming glass. Each actual fluctuation value is compared with the standard fluctuation range. When two adjacent actual fluctuation values ​​are both within the standard fluctuation range, the haze of the sample is considered to have stabilized from the i-th preset time period. Therefore, all haze values ​​corresponding to the time from the i-th preset time period to after the i-th preset time period are taken as the stable haze value interval. Figure 4 The fog values ​​corresponding to the 10th to 16th minutes.

[0091] S36. Determine the haze value of each driving voltage based on each stable haze range.

[0092] S37. Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage.

[0093] The technical solution of this invention specifically defines the method for determining the stable haze range, ensuring the accuracy of obtaining the stable haze value range and improving the accuracy of determining the optimal haze voltage.

[0094] Based on the above embodiments, Figure 8 This is a flowchart of the fifth method for determining fog voltage according to an embodiment of the present invention, combined with... Figure 4 and Figure 8 As shown, the determination method includes:

[0095] S41. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0096] S42. Obtain the haze measurement data of the sample under each driving voltage based on the haze measurement device.

[0097] S43. Obtain the time haze data set of the sample under each driving voltage. The time haze data set includes the haze value corresponding to each measurement time under the same driving voltage.

[0098] S44. Determine the stable haze range of the sample under each driving voltage based on each set of time haze data.

[0099] S45. Determine the mean haze value of all haze values ​​in each stable haze interval.

[0100] S46. Determine the average haze value corresponding to different driving voltages as the haze value for different driving voltages.

[0101] Specifically, determining the mean haze value of all haze values ​​in each stable haze interval can be achieved by calculating the mean of all haze values ​​in each stable haze interval. Then, each driving voltage will have a corresponding mean haze value, and the mean haze value will be further determined as the haze value corresponding to the driving voltage.

[0102] For example, such as Figure 4 As shown, under a 32V driving voltage, the haze values ​​corresponding to the 10th to 16th minutes are the stable haze value range, and the average haze value of all haze values ​​in each stable haze range is 81.67%.

[0103] S47. Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage.

[0104] The technical solution of this invention determines the haze value of each driving voltage by calculating the average haze value, which ensures the stability of the haze value corresponding to the driving voltage and further improves the accuracy of subsequent determination of the optimal haze voltage.

[0105] Based on the above embodiments, Figure 9 This is a flowchart of the sixth method for determining fog voltage according to an embodiment of the present invention, combined with... Figure 4 and Figure 9 As shown, the determination method includes:

[0106] S51, Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0107] S52. Obtain the haze measurement data of the sample under test for each driving voltage based on the haze measurement device.

[0108] S53. Obtain the time haze data set of the sample under each driving voltage. The time haze data set includes the haze value corresponding to each measurement time under the same driving voltage.

[0109] S54. Determine the amount of haze value change in each preset time period based on the haze value in each preset time period. The amount of haze value change is the difference between the maximum haze value and the minimum haze value in the preset time period.

[0110] S55. Determine the amount of haze value change for each preset time period as the actual fluctuation value for each preset time period.

[0111] The change in haze value is the difference between the maximum and minimum haze values ​​within a preset time period. The difference between the maximum and minimum haze values ​​is used to characterize the actual fluctuation value of each preset time period, which facilitates the determination of a stable haze range based on the actual fluctuation value.

[0112] It is understood that when the measurement time is the 0th minute, the 2nd minute...the 16th minute, the preset time period can be 2 minutes or other times. This embodiment of the invention does not limit this, as long as the accuracy of the stable haze range is guaranteed.

[0113] S56. When the actual fluctuation value of the i-th preset time period is within the standard fluctuation value range and the actual fluctuation value of the (i+1)-th preset time period is within the standard fluctuation value range, a stable haze interval is determined. The stable haze interval includes all haze values ​​corresponding to the time from the i-th preset time period to the time after the i-th preset time period; i is a positive integer.

[0114] S57. Determine the haze value of each driving voltage based on each stable haze range.

[0115] S58. Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage.

[0116] Based on the above embodiments, Figure 10 This is a flowchart of the seventh method for determining fog voltage according to an embodiment of the present invention, combined with... Figure 4 and Figure 10 As shown, the determination method includes:

[0117] S61. Output the first temperature control signal to adjust the ambient temperature of the sample to be tested to the first temperature.

[0118] Specifically, by inputting a first temperature control signal into the temperature chamber, the ambient temperature of the sample to be tested can be controlled by the temperature chamber, and the optimal fog voltage is the optimal fog voltage of the sample to be tested at the first temperature.

[0119] For example, continue to refer to Figure 4 As shown, Figure 4 The figure shows the relationship between measurement time and haze value at 30℃ and 32V driving voltage. It can be understood that the haze value of the sample under test is different at different temperatures and for the same measurement time. Therefore, the first temperature control signal is output to control the ambient temperature of the sample under test to the first temperature, and then the optimal haze voltage at the first temperature is determined.

[0120] S62, Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0121] S63. Obtain the haze measurement data of the sample under each driving voltage based on the haze measurement device.

[0122] S64. Determine the optimal fog voltage for the sample to be tested based on the fog measurement data.

[0123] S65. Output a second temperature control signal to adjust the ambient temperature of the sample to be tested to the second temperature, and the first temperature is not equal to the second temperature.

[0124] After the optimal fog voltage at the first temperature is determined, the temperature control signal is adjusted to become the second temperature control signal, thereby obtaining the optimal fog voltage at the second temperature.

[0125] S66. Output the first control signal to control the driver to apply multiple different driving voltages to the sample under test.

[0126] S67. Obtain haze measurement data for the sample under test at each driving voltage based on the haze measurement device.

[0127] S68. Determine the optimal fog voltage for the sample to be tested based on the fog measurement data.

[0128] It is understood that the embodiments of the present invention only show the optimal fog voltage at two different temperatures. Multiple different temperature control signals with different ambient temperatures can be controlled to be output according to the application range of the sample to be tested, so as to obtain the optimal fog voltage at multiple ambient temperatures.

[0129] The technical solution of this invention utilizes a main control circuit board to control a driver to apply different driving voltages to the sample under test and automatically acquires haze data measured by a haze measuring device. By analyzing the haze data, the optimal haze voltage of the sample under test at different temperatures is determined. This avoids the problem of low accuracy in relying solely on visual judgment by the measuring personnel to determine the stability of the sample under driving voltage. This invention achieves automatic acquisition and analysis of haze measuring device by automatically analyzing haze measurement data to determine the stability of the sample under test, thereby improving the accuracy of the optimal haze voltage and reducing labor costs.

[0130] Based on the same inventive concept, embodiments of the present invention also provide a computer device. Figure 11 This is a schematic diagram of the structure of an electronic device applied to a method for determining fog voltage according to an embodiment of the present invention, as shown below. Figure 11As shown, electronic devices are intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0131] like Figure 11 As shown, the electronic device 50 includes at least one processor 51 and a memory, such as a read-only memory (ROM) 52 and a random access memory (RAM) 53, communicatively connected to the at least one processor 51. The memory stores computer programs executable by the at least one processor. The processor 51 can perform various appropriate actions and processes based on the computer program stored in the ROM 52 or loaded into the RAM 53 from storage unit 58. The RAM 53 can also store various programs and data required for the operation of the electronic device 50. The processor 51, ROM 52, and RAM 53 are interconnected via a bus 54. An input / output (I / O) interface 55 is also connected to the bus 54.

[0132] Multiple components in electronic device 50 are connected to I / O interface 55, including: input unit 56, such as keyboard, mouse, etc.; output unit 57, such as various types of monitors, speakers, etc.; storage unit 58, such as disk, optical disk, etc.; and communication unit 59, such as network card, modem, wireless transceiver, etc. Communication unit 59 allows electronic device 50 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0133] Processor 51 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 51 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 51 performs the various methods and processes described above, such as the method applied to the determination of fog voltage.

[0134] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a method for determining fog voltage.

[0135] Of course, the computer-readable storage medium provided in the embodiments of the present invention has computer-executable instructions that are not limited to the method operations described above, but can also execute related operations in the fog voltage determination method provided in any embodiment of the present invention. (Continue to refer to...) Figure 11 As shown, it is tangibly contained in a computer-readable storage medium, such as storage unit 58. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 50 via ROM 52 and / or communication unit 59. When the computer program is loaded into RAM 53 and executed by processor 51, one or more steps of the method for determining fog voltage described above may be performed. Alternatively, in other embodiments, processor 51 may be configured by any other suitable means (e.g., by means of firmware) to perform the method for determining fog voltage.

[0136] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0137] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0138] In the context of embodiments of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0139] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0140] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0141] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0142] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, combinations, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for determining fog voltage, characterized in that, The determination method is applied to a fog voltage measuring device, which includes a main control circuit board, a fog measurement device, and a driver; the main control circuit board is communicatively connected to the fog measurement device and the driver respectively. The determination method includes: S1. Output a first control signal to control the driver to apply multiple different driving voltages to the sample under test; S2. Obtain haze measurement data corresponding to the sample under each driving voltage based on the haze measurement device; S3. Determine the optimal fog voltage of the sample to be tested based on the fog measurement data; Determining the optimal haze voltage of the sample to be tested based on the haze measurement data includes: Acquire a time haze data set of the sample under each driving voltage, wherein the time haze data set includes the haze value corresponding to each measurement time under the same driving voltage; The haze value of each driving voltage is determined based on each set of time haze data. Based on each driving voltage and its haze value, determine the driving voltage corresponding to the maximum haze value, and take the driving voltage corresponding to the maximum haze value as the optimal haze voltage; Determining the haze value of each driving voltage based on each group of time-based haze data includes: The stable haze range of the sample under each driving voltage is determined based on each set of time haze data. The haze value of each driving voltage is determined according to each of the stable haze intervals; Based on each set of time-based haze data, the stable haze range of the sample under test at each driving voltage is determined, including: Determine the actual fluctuation values ​​of multiple haze values ​​in each group of time haze data within a preset time period; When the actual fluctuation value of the i-th preset time period is within the standard fluctuation value range and the actual fluctuation value of the (i+1)-th preset time period is within the standard fluctuation value range, a stable haze interval is determined. The stable haze interval includes all haze values ​​corresponding to the time from the i-th preset time period to the time after the i-th preset time period; i is a positive integer.

2. The determination method according to claim 1, characterized in that, Determining the haze value of each driving voltage based on each of the stable haze intervals includes: Determine the mean haze value of all haze values ​​in each of the said stable haze intervals; The average haze value corresponding to different driving voltages is determined as the haze value for different driving voltages.

3. The determination method according to claim 1, characterized in that, Determine the actual fluctuation values ​​of multiple haze values ​​in each group of time-based haze data within a preset time period, including: The amount of haze value change in each preset time period is determined based on the haze value in each preset time period, wherein the amount of haze value change is the difference between the maximum haze value and the minimum haze value in the preset time period; The amount of change in haze value for each preset time period is determined as the actual fluctuation value for each preset time period.

4. The determination method according to claim 1, characterized in that, Output a first control signal to control the driver to apply multiple different drive voltages to the sample under test, including the following: Output the first temperature control signal to adjust the ambient temperature of the sample to the first temperature. After determining the optimal fog voltage of the sample to be tested based on each of the fog measurement data, the method further includes: outputting a second temperature control signal to adjust the ambient temperature of the sample to the second temperature, wherein the first temperature is not equal to the second temperature; Repeat steps S1-S3 to determine the optimal fog voltage corresponding to the second temperature.

5. The determination method according to claim 1, characterized in that, Before acquiring the haze measurement data corresponding to the sample under each driving voltage based on the haze measurement device, the process includes: Output a haze measurement signal to control the haze measurement device to measure the haze of the sample to be tested.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the determination method as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the determination method as described in any one of claims 1-5.

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