CN110334308B - Calculation method for optimizing bias condition in power supply scanning parameter test - Google Patents
Calculation method for optimizing bias condition in power supply scanning parameter test Download PDFInfo
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Abstract
The invention belongs to the field of automatic testing; the method comprises extracting the latest test data of several power supply scan parameters, and eliminating out-of-range data; dividing the maximum value and the minimum value in the data into a plurality of regions at equal intervals; finding out the packet with the maximum data volume, comparing the data coverage rate with the threshold value, if the data coverage rate is smaller than the threshold value, expanding the packet to the left or the right, and taking the expanded packet as the packet with the maximum data volume; calculating a temporary offset range according to grouping conditions, expanding the two sides of the temporary offset range according to a fixed expansion value, and taking the expanded offset range as a test offset condition of the next power supply scanning parameter test; the invention calculates new test bias conditions according to historical test result data on the premise of not changing the existing power supply product scanning parameter test hardware, can greatly improve the test efficiency, and is suitable for wide test product range.
Description
Technical Field
The invention belongs to the field of automatic testing; in particular to a calculation method for optimizing bias conditions in power supply scanning parameter tests.
Background
In power supply products such as DC/DC, a plurality of products need to test scanning parameters such as input under-voltage opening or closing voltage, input over-voltage opening or closing voltage, frequency synchronization range, output over-voltage protection point, output over-current protection point and the like. When testing these parameters, usually, the bias condition is set according to the product data manual or the detailed specifications, and if the input overvoltage protection voltage index of a certain product is 4.8V-5.2V, the bias condition is generally set to 4.78V-5.22V for testing. But the method is easy to generate the problems of low parameter testing efficiency, incapability of changing the testing bias condition once the testing program is released, self-adaption to the state change of the product and the like.
Disclosure of Invention
Based on the problems in the prior art, the invention considers the products in the same production batch or continuous production batches, and the test results have stronger consistency and are generally distributed in a certain smaller interval in a centralized way; therefore, the invention provides a calculation method for optimizing the bias condition in the power supply scanning parameter test, which can calculate the test bias condition in the next test in real time by analyzing and processing the scanning parameter test result of the tested product, thereby greatly reducing the test bias condition range and greatly improving the test efficiency.
A calculation method for optimizing bias conditions in power supply scanning parameter tests comprises the following steps:
step one, extracting the latest historical test data of a plurality of power supply scanning parameter tests, and carrying out effectiveness screening on the historical test data so as to eliminate out-of-range data;
grouping the screened validity data, and dividing the maximum value and the minimum value in the data into a plurality of regions at equal intervals;
step three, finding out the grouping with the maximum data quantity, comparing the data coverage rate with the data coverage rate threshold value, if the data coverage rate is smaller than the data coverage rate threshold value, performing the step four, otherwise, performing the step five;
step four, expanding the packets towards the left or the right, taking the expanded packets as the packets with the largest data volume, and returning to the step three;
step five, calculating a temporary offset range according to grouping conditions, expanding two sides of the temporary offset range according to a fixed expansion value, and taking the expanded offset range as a test offset condition of the next power supply scanning parameter test;
the power supply scanning parameters comprise input under-voltage starting or stopping voltage, input overvoltage starting or stopping voltage, a frequency synchronization range, output overvoltage protection points and output overcurrent protection points.
Further, the first step comprises connecting to a database for storing test results, scanning parameter names according to power supplies to be tested through query commands, extracting a plurality of latest tested results corresponding to parameters, and arranging the latest tested results in a descending order according to a test time sequence; and judging according to the given effective interval range, and if the read data value exceeds the given effective interval, rejecting the data.
Further, the second step includes determining the number of the packets M, and counting the maximum value and the minimum value of the data in the first step; dividing the range between the maximum value and the minimum value into M intervals with equal intervals, and calculating the boundary value of the test data in each interval; and comparing the acquired test data with the boundary values of each group one by one, thereby counting the number of data in each group.
Further, the formula for calculating the data coverage in step three is as follows:
data.count is the total number of the effective data extracted in the step one, group [ i ]. Cnt is the data number of the ith packet, K is the packet number of the maximum packet, L is the number of groups extending leftward from the K packet, and R is the number of groups extending rightward from the K packet.
Further, the fourth step includes the following steps:
step 1) judging whether a vacant group exists on the left side of the maximum group K; if no spare packet exists, expanding the selected packet item to the right by one group, taking the expanded packet as the packet with the maximum data volume, and returning to the third step; otherwise, entering step 2);
step 2) judging whether the left side of the maximum grouping K has a vacant grouping; if no spare packet exists, expanding the selected packet item to the left by one group, taking the expanded packet as the packet with the maximum data volume, and returning to the third step; otherwise, entering step 3);
and 3) judging the group number of the left and right vacant groups, selecting the larger side of the vacant group to expand, if the vacant groups on the two sides are equal, expanding one group to the left, taking the expanded group as the group with the largest data size, and returning to the third step.
Further, the calculation formulas of the offset ranges after the expansion in the fourth step are respectively as follows:
Bias.LowVal＝Data.Min+GroupSpan*(K-L-1)-F
Bias.HighVal＝Data.Max+GroupSpan*(K+R)+F
wherein, bias.lowval represents the lower limit value of the final test bias condition range; bias.highval represents the upper limit of the final test bias condition range; min is the minimum value in the second step, max is the maximum value in the second step, group span is the distance of each group, K is the group number of the maximum group, L is the number of groups extending from the group K to the left, and F is a fixed extension value; r is the number of groups extending from the K groups to the left.
Optionally, based on the method provided by the present invention, the present invention further provides a computing system for optimizing the bias condition in the power scan parameter test, where the system includes an electrically connected database, a data extraction module, a data grouping statistics module, and a bias condition computing module;
the database is used for storing test results;
the data extraction module is used for screening and extracting the measurement results stored in the database and carrying out data validity screening;
the data grouping counting module is used for judging and grouping a plurality of pieces of data acquired by the data extracting module according to grouping conditions and counting the number of the data falling into each data grouping;
and the bias condition calculating module is used for searching and positioning the maximum data packet according to the packet information, calculating a new test bias value by expanding the adjacent packet of the maximum packet and using the new test bias value as the next test bias condition.
The invention has the technical effects that:
1. the invention can calculate the bias condition of the next test according to the historical test result data on the premise of not changing the scanning parameter test hardware of the existing power supply product, can greatly improve the test efficiency, is suitable for wide range of test products, and is particularly suitable for the field of automatic test.
2. The invention solves the problems that the parameter testing efficiency is low, the testing bias condition can not be changed and the product state change can not be adapted after the testing program is released by optimizing the testing bias condition on the premise of not changing the existing power supply product scanning parameter testing hardware, and has higher innovation and practical application significance.
3. The invention adopts a packet extension mode to carry out data statistics and data coverage rate calculation, can quickly determine the initial position and the packet extension direction of packet extension, and calculates a more reasonable bias condition range. Meanwhile, proper absolute value expansion is carried out on the calculated bias condition range, so that the problem that when the calculated bias condition range is extremely small, the maximum resolution or the effective range of the bias setting of a test instrument is possibly exceeded, and the test is invalid is solved, and the effectiveness of the final test of the bias condition is further improved.
Drawings
FIG. 1 is a flow chart of a method employed in the present invention;
FIG. 2 is a flow chart of the present invention for extracting historical test data;
FIG. 3 is a flow chart of historical data grouping statistics in the present invention;
FIG. 4 is a flow chart of the present invention for calculating new bias conditions;
FIG. 5 is a diagram illustrating the statistics (frequency) distribution of the test results according to the present invention;
FIG. 6 is a schematic diagram of a data packet according to the present invention;
fig. 7 is a schematic diagram of coverage calculation in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clearly and completely apparent, the technical solutions in the embodiments of the present invention are described below with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The invention is described in detail below with reference to the following figures and examples:
as shown in fig. 1, a method for calculating a bias condition in an optimized power scan parameter test in the present invention includes the following steps:
step one, extracting the latest historical test data of a plurality of power supply scanning parameter tests, and carrying out effectiveness screening on the historical test data so as to eliminate out-of-range data;
grouping the screened valid data, dividing the maximum value and the minimum value in the data into a plurality of regions at equal intervals, and searching out the group with the maximum data quantity;
step three, comparing the data coverage rate of the packet with the maximum data quantity with a data coverage rate threshold value thereof, if the data coverage rate is smaller than the data coverage rate threshold value, performing step four, otherwise, performing step five;
step four, expanding the packets towards the left or the right, taking the expanded packets as the packets with the maximum data volume, and returning to the step three;
step five, calculating a temporary offset range according to grouping conditions, expanding two sides of the temporary offset range according to a fixed expansion value, and taking the expanded offset range as a test offset condition of the next power supply scanning parameter test;
the power supply scanning parameters comprise input under-voltage starting or stopping voltage, input overvoltage starting or stopping voltage, a frequency synchronization range, output overvoltage protection points and output overcurrent protection points.
As an alternative, in the step one, the flow of the step of extracting the test history data is shown in fig. 2, and includes the following steps:
s101, extracting test history data and starting processing;
s102, connecting a test history database;
s103, extracting the stored latest N pieces of test data corresponding to the scanning parameters to be tested;
s104, performing data validity detection to remove invalid data in the extracted data;
and S105, returning the extracted data.
Specifically, the test device is first connected to a database storing test results and opens a test history database, and then extracts the latest N tested results (N values may be fixed values or may be set according to different test parameters) corresponding to parameters according to the name of the parameter to be tested by using a Structured Query Language (SQL) command, and arranges the results in a descending order according to the test time sequence. And judging the acquired data according to a given effective interval range, and rejecting the data if the read data value exceeds the given range. Until all data processing is completed.
Alternatively, in step two, the flow of the historical data packet statistics step is shown in fig. 3,
s201, starting grouping processing;
s202, fixing the number M of the groups;
s203, counting the maximum value and the minimum value in the extracted effective data;
s204, calculating boundary conditions of each grouping condition;
s205, counting the number (frequency) of data in each packet, as shown in fig. 5;
and S206, returning a grouping result.
Specifically, first, the number of packets M is determined. Then, the first step in the statistics process returns the maximum and minimum values in the data. Thirdly, M intervals with equal intervals are divided between the maximum value range and the minimum value range (the M value can be a fixed value and can also be set according to different test parameters), and the boundary value of each interval is calculated. Finally, the obtained data are compared with each group one by one, and the number of data in each group is counted, wherein the counting result is shown in fig. 6.
As an alternative, the invention regards steps three to five as a new bias calculation process, the flow of steps of calculating new bias conditions is shown in fig. 4,
s501, starting a new bias calculation process;
s502, searching a maximum grouping position K;
s503, fixing the minimum data coverage rate X (the X value can be a fixed value and can also be set according to different test parameters, and is usually set between 0.85 and 1 according to the product yield and the retest allowable frequency requirement);
s504, grouping and expanding;
s505, calculating an offset range according to the expanded groups;
s506, expanding the bias range by an absolute value F;
and S507, returning the bias range as the optimized bias range and as the parameter of the next measurement.
Wherein the packet extension process comprises:
s5041, whether the data coverage Y of the selected packet is less than its threshold X;
the calculation diagram is shown in FIG. 7:
data.count is the total number of the effective data extracted in the step one, group [ i ]. Cnt is the data number of the ith packet, K is the packet number of the maximum packet, L is the number of groups extending leftward from the K packet, and R is the number of groups extending rightward from the K packet.
S5042, if the maximum packet K is smaller than the threshold value, judging whether the left extension group of the maximum packet K has a spare packet;
s5043, if there are no empty packets in step S5042, selecting a packet to expand to the right by one group, where R = R +1;
s5404, if the spare packet exists in the step S5402, judging whether the right extended packet of the maximum packet K has the spare packet;
s5045, if there is no spare packet in the right extension group in step S5404, selecting a right extension group, where L = L + i;
s5046, if the left and right sides have spare groups, judging whether the left spare group is larger than the right spare group;
s5047, if the right vacant group is larger than the left vacant group, expanding one group rightwards, wherein R = R + i;
s5048, if the right free packet is not greater than the left free packet, then expand one group to the left, L = L +1.
Obviously, when there are no empty packets on both left and right sides, the data coverage is 100%.
According to the calculated grouping condition, firstly analyzing the grouping number with the maximum data amount in the grouping, then according to the set minimum data coverage rate, expanding a group of grouping to the left end and the right end of the maximum grouping each time and recalculating the coverage rate until the coverage rate meets the requirement, and stopping expansion. And finally, calculating an offset range according to the expanded group condition, and expanding absolute values of two sides of the calculated offset range to be used as the next test offset condition.
When the packet is expanded to the left and the right, if the packet on one side reaches the boundary, the packet is expanded to the other side; if both sides have spare packets (not reaching the packet boundary), then the side containing more data in the extended packet or any side is extended when the packet contains the same number of data is selected through judgment.
And finally, taking the expanded bias range as the optimized bias range for the next test. The calculation formula is as follows.
Bias.LowVal＝Data.Min+GroupSpan*(K-L-1)-F，
Bias.HighVal＝Data.Max+GroupSpan*(K+R)+F，
Wherein, bias.lowval represents the lower limit value of the final test bias condition range; highval represents the upper limit of the final test bias condition range; min is the minimum value in the second step, max is the maximum value in the second step, groupSpan is the distance between each group, K is the group number of the maximum group, L is the number of groups extending from the group K to the left, and F is a fixed extension value; r is the number of groups extending from the K groups to the left.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by hardware related to instructions of a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: ROM, RAM, magnetic or optical disks, and the like.
The above-mentioned embodiments, which further illustrate the objects, technical solutions and advantages of the present invention, should be understood that the above-mentioned embodiments are only preferred embodiments of the present invention, and should not be construed as limiting the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A calculation method for optimizing bias conditions in power supply scanning parameter tests is characterized by comprising the following steps:
step one, extracting the latest historical test data of a plurality of power supply scanning parameter tests, and carrying out effectiveness screening on the historical test data so as to eliminate out-of-range data;
grouping the screened validity data, dividing the maximum value and the minimum value in the data into a plurality of regions at equal intervals, and finding out the group with the maximum data quantity;
step three, comparing the data coverage rate of the packet with the maximum data quantity with a data coverage rate threshold value thereof, if the data coverage rate is smaller than the data coverage rate threshold value, performing step four, otherwise, performing step five;
step four, expanding the packets towards the left or the right, taking the expanded packets as the packets with the maximum data volume, and returning to the step three;
step five, calculating a temporary offset range according to grouping conditions, expanding two sides of the temporary offset range according to a fixed expansion value, and taking the expanded offset range as a test offset condition of the next power supply scanning parameter test;
the power supply scanning parameters comprise input under-voltage starting or stopping voltage, input overvoltage starting or stopping voltage, a frequency synchronization range, output overvoltage protection points and output overcurrent protection points.
2. The method for calculating the bias condition in the optimized power supply scanning parameter test as claimed in claim 1, wherein the first step includes connecting to a database storing test results, extracting the latest tested results of the corresponding parameters according to the name of the power supply scanning parameter to be tested by the query command, and arranging the latest tested results in descending order according to the test time sequence; and judging according to the given effective interval range, and if the read data value exceeds the given effective interval, rejecting the data.
3. The method for calculating the bias condition in the optimized power supply scanning parameter test according to claim 1, wherein the second step comprises determining the number of groups M, and counting the maximum value and the minimum value of the data in the first step; dividing the range between the maximum value and the minimum value into M intervals with equal intervals, and calculating the boundary value of the test data in each interval; and comparing the acquired test data with the boundary values of each group one by one, thereby counting the number of data in each group.
4. The method of claim 1, wherein the data coverage in step three is calculated as:
wherein, data.count is the total number of the effective data extracted in the step one, group [ i ] Cnt is the data number of the ith packet, K is the packet number of the maximum packet, L is the number of groups extending from the K packet to the left, and R is the number of groups extending from the K packet to the right.
5. The method of claim 1, wherein the step four comprises the steps of:
step 1) judging whether a vacant group exists on the left side of the maximum group K; if no spare packet exists, expanding the selected packet item to the right by one group, taking the expanded packet as the packet with the maximum data volume, and returning to the third step; otherwise, entering step 2);
step 2) judging whether the left side of the maximum grouping K has a vacant grouping; if no spare packet exists, expanding the selected packet item to the left by one group, taking the expanded packet as the packet with the maximum data volume, and returning to the third step; otherwise, entering step 3);
and 3) judging the group number of the left and right vacant groups, selecting the larger side of the vacant group to expand, if the vacant groups on the two sides are equal, expanding one group to the left, taking the expanded group as the group with the largest data volume, and returning to the third step.
6. The method according to claim 1, wherein the extended bias range in step four is calculated by the following formulas:
Bias.LowVal＝Data.Min+GroupSpan*(K-L-1)-F
Bias.HighVal＝Data.Max+GroupSpan*(K+R)+F
wherein, bias.lowval represents the lower limit value of the final test bias condition range; highval represents the upper limit of the final test bias condition range; min is the minimum value in the second step, max is the maximum value in the second step, group span is the distance of each group, K is the group number of the maximum group, L is the number of groups extending from the group K to the left, and F is a fixed extension value; r is the number of groups extending from the K groups to the left.
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