A panel temperature calibration method

Abstract

This patent discloses a panel temperature calibration method, which uses a temperature chamber to collect a mapping table of the sensor temperature and the actual ambient temperature of the HBS panel in a stable state. According to the mapping table, the deviation between a certain temperature value of the sensor and the actual ambient temperature value at the actual ambient temperature can be found for calibration. The calibrated result is accurate and low-cost.

Description

Technical Field

[0001] The invention relates to a temperature calibration method, in particular to a temperature calibration method for an HBS (Home Bus System) panel. Background Art

[0002] The accuracy of the temperature and humidity sensor on the HBS panel will be affected by the heating of the HBS panel when it is powered on and the heating of the screen when it is on. In order to accurately display the temperature sent back by the temperature sensor on the screen when the HBS panel is in a stable state, the temperature sensor temperature needs to be calibrated. Summary of the invention

[0003] When the HBS panel is powered on and in a stable state, some influencing factors such as heating and heat dissipation of the HBS panel and screen will also reach a stable state and have correlation. After the experiment, the mapping table of the sensor temperature and the real ambient temperature of the HBS panel in a stable state is collected through a temperature box. According to the mapping table, the deviation between a certain temperature value of the sensor and the real ambient temperature value under the real ambient temperature can be found for calibration. The calibration result is accurate and the cost is low.

[0004] This patent is a HBS panel temperature calibration method, including the following steps:

[0005] A. Collect data:

[0006] Set up a temperature box, place 3-10 HBS panels in the temperature box, use every 10 degrees as a segment, the step temperature of the collected temperature is not less than 0.1°, and collect for 20 hours in each segment;

[0007] B. Process the collected data and extract the mapping table:

[0008] B-1: Obtain the sensor temperature table sent back by each panel at each time point, with the fields of time, boxID and sensor temperature, and convert the sensor temperature table recorded by the hardware into a format that can be recognized by the software;

[0009] B-2: Obtain a temperature table that records the temperature of the temperature chamber at each time point, where the fields include time and the temperature of the temperature chamber corresponding to the time; and convert the temperature table of the temperature chamber recorded by the hardware into a format that can be recognized by the software;

[0010] B-3: Extract the data corresponding to each box ID in step B-1 into a separate file; B-4: Merge the data files in steps B-2 and B-1 according to the time parameter to obtain the sensor temperature sensors_temp and the temperature box environment temperature Env_temp data table at the same time;

[0011] B-5 Extract mapping table rules based on the data table in step B-4:

[0012] Rule 1: Get the largest monotonically increasing or decreasing data segment in the temperature sensor column sensors_temp of the file;

[0013] Rule 2: Eliminate duplicate data in the table;

[0014] Rule 3: Sort the temperature sensor column sensors_temp in ascending order in the table;

[0015] Rule 4: If multiple identical temperature sensors correspond to different incubator ambient temperatures, they are combined into one and the incubator ambient temperature is averaged.

[0016] Rule 5: Sort the sensor temperature column sensors_temp in reverse order and generate two columns of json mapping data in the format [env_temp, sensors_temp];

[0017] Rule 6: Select four temperature ranges: 0-10, 10-20, 20-30, 30-40, and merge the collected JSON data, and perform downsampling, that is, calculate the average value of each three adjacent data and merge them into one, and generate the final two-column format [env_temp, sensors_temp] format mapping list file; C. Real environment data collection

[0018] C-1: Get the sensor temperature table sent back by each panel at each time point, with the fields of time, boxID and sensor temperature, and convert the sensor temperature table recorded by the hardware into a format that can be recognized by the software;

[0019] C-2: Obtain a table of the actual ambient temperature at each time point, with fields including time and the ambient temperature of the incubator corresponding to the time; and convert the actual ambient temperature table recorded by the hardware into a format that can be recognized by the software;

[0020] C-3: Extract the data corresponding to each box ID in step C-1 into a separate file; C-4: Merge the data files in steps C-2 and C-1 according to the time parameter to obtain the sensor temperature sensors_temp and the temperature box environment temperature Env_temp data table at the same time;

[0021] C-5 Extract mapping table rules based on the data table in step C-4:

[0022] Rule 1: Get the largest monotonically increasing or decreasing data segment in the temperature sensor column sensors_temp of the file;

[0023] Rule 2: Eliminate duplicate data in the table;

[0024] Rule 3: Sort the temperature sensor column sensors_temp in ascending order in the table;

[0025] Rule 4: If multiple identical temperature sensors correspond to different real ambient temperatures, they are combined into one and the average ambient temperature is calculated;

[0026] Rule 5: Sort the sensor temperature column sensors_temp in reverse order and generate two columns of json mapping data in the format [env_temp, sensors_temp];

[0027] Rule 6: Select four temperature ranges: 0-10, 10-20, 20-30, 30-40, and merge the collected JSON data. Then downsample them. That is, calculate the average value of every three adjacent data and merge them into one. Then generate the final two-column [env_temp, sensors_temp] format mapping list file.

[0028] D. Verify data collected in real environment

[0029] Step 1: Read the mapping list file of rule 6 in step B-5 as a list temp_mapping, and generate a new compensation temperature list compensate_mapping. The generation rule is: for the Nth row, read the difference A between the sensor temperature sensors_temp in the Nth row of temp_mapping and the sensor temperature and the temperature box in the Nth row, and the difference B between the sensor temperature sensors_temp in the N+1th row of temp_mapping and the sensor temperature and the temperature box in the Nth row, and put (A+B) / 2 into the Nth row of the compensate_mapping list. For the last row of temp_mapping, directly put the obtained A into the last row of the compensate_mapping list;

[0030] Step 2: Get the data collected in the real environment according to step C, read the sensor column into a list sensors_test and traverse it, get the item sensors_item in the list, use sensors_item to find the row number in the temp_mapping list where sensors_item is greater than or equal to the smallest sensor temperature in the list, get the compensation value under the sensor temperature in the compensate_mapping compensation list through the row number, and calculate the calibrated value = sensor temperature - compensation value.

[0031] Step D also includes:

[0032] Step 3: Subtract the calibrated value from the actual ambient temperature value to obtain the error value and display it in the chart.

[0033] The format that can be recognized by the software in steps B-1, B-2, C-1, and C-2 is a CSV file or an EXCEL file.

[0034] The compensation value in step 2 of step D needs to be multiplied by (1-exp(-0.1*t)), where exp is a natural exponential function and t is time in minutes. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0036] Attached Figure 1 : Graph of sensor temperature, calibrated temperature, and true ambient temperature

[0037] Attached Figure 2 :Compensation value formula DETAILED DESCRIPTION

[0038] The present invention provides a HBS panel temperature calibration method, comprising the following steps:

[0039] A. Collect data (use 3-10 HBS panels, box IDs are: increasing from 1)

[0040] In order to reduce the error value, the temperature accuracy of the collection needs to be as small as possible. Ideally, each step temperature (0.1°) has a corresponding real ambient temperature, so segmented collection (0-10 degrees, 10-20 degrees, 20-30 degrees, 30-40 degrees) is adopted, and each segment is collected for 20 hours.

[0041] B. Process the data collected by the temperature chamber and extract the mapping table

[0042] (1) The content of the collected record_1.txt file is the sensor temperature transmitted by each panel at each time point. The fields are time, boxID, and sensor temperature.

[0043] (2) The collected [record_2.CSV] file is the temperature of the incubator at each time point. The fields include time and the temperature of the incubator corresponding to the time.

[0044] (3) Process the record_1.txt file to generate a readable output_record_1.xlsx file in the following format:

[0045] Time (current time) boxID sensors_temp (sensor temperature)

[0046] (4) The file [output_record_1.xlsx] contains all the data collected by the HBS panel, which are extracted into separate files [output_record_1_boxID.xlsx] according to the panel BoxID. The boxID depends on the HBS panel settings. The format is

[0047] Time (current time) sensors_temp (temperature collected by device sensors)

[0048] (5) Process the record_2.CSV file to generate a readable output_record_2.xlsx file in the format

[0049] Time Env_temp (the actual ambient temperature of the collected incubator)

[0050] (6) According to the time parameter, merge [output_record_2.xlsx] and [output_record_1_boxID.xlsx] to generate output_record_2_[boxID].xlsx. At this time, the output_record_2_[boxID].xlsx file is the temperature sensor temperature and the temperature box environment temperature corresponding to each time point of a certain panel. The format is:

[0051]

[0052] (7) Extract mapping table rules based on output_record_2_[boxID].xlsx

[0053] Rule 1: Get the largest monotonically increasing or decreasing data segment in the temperature sensor column sensors_temp of the file;

[0054] Rule 2: Eliminate duplicate data in the table

[0055] Rule 3: Sort the temperature sensor column sensors_temp in ascending order in the table

[0056] Rule 4: If multiple identical temperature sensors correspond to different real ambient temperatures, they are merged into one and the temperature box temperature is averaged. Rule 5: Arrange the sensor temperature column sensors_temp in reverse order to generate json mapping data in the format of [env_temp, sensors_temp]. Rule 6: Merge the json data collected in four segments (0-10, 10-20, 20-30, 30-40) and perform downsampling. According to the average value of each adjacent three, merge them into one to generate the final mapping list file output_ascending_json_sample.txt. The numerical sample in the file is as follows:

[0057] [env_temp,sensors_temp]

[0058] [212,290],

[0059] [206,268],

[0060] [198,260],

[0061] [193,255],

[0062] [190,252],

[0063] [186,248]

[0064] The values ​​here are actual values ​​* 10 for ease of operation.

[0065] C. Processing real ambient temperature data collection

[0066] The real ambient temperature in this patent has a specific meaning, which refers to the temperature measured by a professional thermometer with almost no error from the ambient temperature.

[0067] (1) The collected [test_record_1.txt] file contains the sensor temperature sent back by each panel at each time point. The fields are time, boxID, and sensor temperature. (2) The collected [test_record_2.CSV] file contains the actual ambient temperature and panel surface temperature at each time point. The fields include time and the actual ambient temperature corresponding to the time.

[0068] (3) Process the [test_record_1.txt] file to generate a readable [test_output_record_1.xlsx] file in the following format:

[0069] Time (current time) boxID sensors_temp (sensor temperature)

[0070] (4) The file [test_output_record_1.xlsx] contains all the data collected by the HBS panel, which are extracted into separate files [test_output_record_1_boxID.xlsx] according to the panel BoxID. The boxID depends on the HBS panel settings. Format

[0071] Time (current time) sensors_temp (temperature collected by device sensors)

[0072] (5) Process the [test_record_2_test.CSV] file to generate a readable [test_output_record_2.xlsx] file in the format

[0073] Time Env_temp (real ambient temperature collected)

[0074] (6) According to the time parameter, merge [test_output_record_2.xlsx] and [test_output_record_1_boxID.xlsx] to generate test_output_record_2_[boxID].xlsx. At this time, the test_output_record_2_[boxID].xlsx file is the temperature sensor temperature and the actual ambient temperature corresponding to each time point of a certain panel. The format is:

[0075]

[0076] D. Verify the data collected in the real environment. Step 1: Read the mapping list file of rule 6 in step B-5 as a list temp_mapping, and generate a new compensation temperature list compensate_mapping. The generation rule is: for the Nth row, read the difference A between the sensor temperature sensors_temp in the Nth row of temp_mapping and the sensor temperature and the temperature of the temperature box in the Nth row, and the difference B between the sensor temperature sensors_temp in the N+1th row of temp_mapping and the sensor temperature and the temperature of the temperature box in the Nth row, and put (A+B) / 2 into the Nth row of the compensate_mapping list. For the last row of temp_mapping, directly put the obtained A into the last row of the compensate_mapping list.

[0077] For example, for the following table,

[0078] [env_temp,sensors_temp]

[0079] [212,290],

[0080] [206,268],

[0081] [198,260],

[0082] [193,255],

[0083] [190,252],

[0084] [186,248]

[0085] The differences between the first and second rows are 78 and 62 respectively, so the result of (78+62) / 2, 70, is added to the third column of the first row, and so on, to obtain a list including the compensation values:

[0086] [env_temp, sensors_temp, compensation value]

[0087] [212,290],

[70]

[0088] [206,268],

[62]

[0089] [198,260],

[62]

[0090] [193,255],

[62]

[0091] [190,252],

[62]

[0092] [186,248],

[62]

[0093] Step 2: Get the data collected in the real environment according to step C, read the sensor column into a list sensors_test and traverse it, get the item sensors_item in the list, use sensors_item to find the row number in the temp_mapping list where sensors_item is greater than or equal to the smallest sensor temperature in the list, get the compensation value under the sensor temperature in the compensate_mapping compensation list through the row number, and calculate the calibrated value = sensor temperature - compensation value.

[0094] Step 3: Subtract the calibrated value from the actual ambient temperature value to obtain the error value, and display it in the chart, such as Figure 1 .

[0095] Red: Actual ambient temperature

[0096] Blue: Calibrated temperature

[0097] Green: Temperature collected by the sensor

[0098] E: Project Integration

[0099] In the project, the HBS panel will heat up and dissipate heat slowly and tend to a stable state after being powered on, so it can be simulated according to the time curve. The compensation value A obtained when the power is just turned on needs *(1-exp(-0.1*t))t as the time, in minutes. According to the curve, the panel tends to a stable state 30 minutes after powering on. Figure 2 .

[0100] Depend on Figure 1 It can be seen that by using the method of this patent, after the compensation value is calculated, the calculated result is basically consistent with the temperature measured with high precision using a thermometer, achieving the technical effect of accurate results and low cost.

[0101] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0102] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A panel temperature calibration method, comprising the following steps: A. Collect data: Set up a temperature box, place 3-10 HBS panels in the temperature box, use every 10 degrees as a segment, the step temperature of the collected temperature is not less than 0.1°, and collect for 20 hours in each segment; B. Process the collected data and extract the mapping table: B-1: Obtain the sensor temperature table sent back by each panel at each time point, with the fields of time, boxID and sensor temperature, and convert the sensor temperature table recorded by the hardware into a format that can be recognized by the software; B-2: Obtain a temperature table that records the temperature of the temperature chamber at each time point, where the fields include time and the temperature of the temperature chamber corresponding to the time; and convert the temperature table of the temperature chamber recorded by the hardware into a format that can be recognized by the software; B-3: Extract the data corresponding to each boxID in step B-1 into a separate file; B-4: Merge the data files in steps B-2 and B-1 according to the time parameter to obtain the sensor temperature sensors_temp and the temperature box environment temperature Env_temp data table at the same time; B-5 Extract mapping table rules based on the data table in step B-4: Rule 1: Get the largest monotonically increasing or decreasing data segment in the temperature sensor column sensors_temp of the file; Rule 2: Eliminate duplicate data in the table; Rule 3: Sort the temperature sensor column sensors_temp in ascending order in the table; Rule 4: If multiple identical temperature sensors correspond to different incubator ambient temperatures, they are combined into one and the incubator ambient temperature is averaged. Rule 5: Sort the sensor temperature column sensors_temp in reverse order and generate two columns of json mapping data in the format [env_temp, sensors_temp]; Rule 6: Select four temperature ranges: 0-10, 10-20, 20-30, 30-40, and merge the collected JSON data. Then downsample them. That is, calculate the average value of every three adjacent data and merge them into one. Finally, generate a two-column mapping list file in [env_temp, sensors_temp] format. C. Real environment data collection C-1: Get the sensor temperature table sent back by each panel at each time point, with the fields of time, boxID and sensor temperature, and convert the sensor temperature table recorded by the hardware into a format that can be recognized by the software; C-2: Obtain a table of the actual ambient temperature at each time point, with fields including time and the ambient temperature of the incubator corresponding to the time; and convert the actual ambient temperature table recorded by the hardware into a format that can be recognized by the software; C-3: Extract the data corresponding to each boxID in step C-1 into a separate file; C-4: Merge the data files in steps C-2 and C-1 according to the time parameter to obtain the sensor temperature sensors_temp and the temperature box environment temperature Env_temp data table at the same time; C-5 Extract mapping table rules based on the data table in step C-4: Rule 1: Get the largest monotonically increasing or decreasing data segment in the temperature sensor column sensors_temp of the file; Rule 2: Eliminate duplicate data in the table; Rule 3: Sort the temperature sensor column sensors_temp in ascending order in the table; Rule 4: If multiple identical temperature sensors correspond to different real ambient temperatures, they are combined into one and the average ambient temperature is calculated; Rule 5: Sort the sensor temperature column sensors_temp in reverse order and generate two columns of json mapping data in the format [env_temp, sensors_temp]; Rule 6: Select four temperature ranges: 0-10, 10-20, 20-30, 30-40, and merge the collected JSON data, and perform downsampling, that is, calculate the average value of each three adjacent data and merge them into one, and generate the final two-column format [env_temp, sensors_temp] format mapping list file; D. Verify the data collected in the real environment Step 1: Read the mapping list file of rule 6 in step B-5 as a list temp_mapping, and generate a new compensation temperature list compensate_mapping. The generation rule is: for the Nth row, read the difference A between the sensor temperature sensors_temp in the Nth row of temp_mapping and the sensor temperature and the temperature box in the Nth row, and the difference B between the sensor temperature sensors_temp in the N+1th row of temp_mapping and the sensor temperature and the temperature box in the Nth row, and put (A+B) / 2 into the Nth row of the compensate_mapping list. For the last row of temp_mapping, directly put the obtained A into the last row of the compensate_mapping list; Step 2: Get the data collected in the real environment according to step C, read the sensor column into a list sensors_test and traverse it, get the item sensors_item in the list, use sensors_item to find the row number in the temp_mapping list where sensors_item is greater than or equal to the smallest sensor temperature in the list, get the compensation value under the sensor temperature in the compensate_mapping compensation list through the row number, and calculate the calibrated value = sensor temperature - compensation value.

2. A panel temperature calibration method as claimed in claim 1, characterized in that: Step D also includes: Step 3: Subtract the calibrated value from the actual ambient temperature value to obtain the error value and display it in the chart.

3. A panel temperature calibration method as claimed in claim 1 or 2, characterized in that: The format that can be recognized by the software in steps B-1, B-2, C-1, and C-2 is a CSV file or an EXCEL file.

4. A panel temperature calibration method as claimed in claim 1, characterized in that: The compensation value in step 2 of step D needs to be multiplied by (1-exp(-0.1*t)), where exp is a natural exponential function and t is time in minutes.

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