CN114938242A

CN114938242A - Nonlinear BOB power calibration method and system based on table lookup method and slope prediction

Info

Publication number: CN114938242A
Application number: CN202210858320.5A
Authority: CN
Inventors: 宋祥林; 王喜祝; 彭旋; 陈政; 王周锋
Original assignee: Shenzhen Comnect Technology Co ltd
Current assignee: Shenzhen Yilian Unlimited Technology Co ltd
Priority date: 2022-07-21
Filing date: 2022-07-21
Publication date: 2022-08-23
Anticipated expiration: 2042-07-21
Also published as: CN114938242B

Abstract

The invention relates to a nonlinear BOB power calibration method and a system based on a table look-up method and slope prediction, wherein the method comprises the following steps: s1, importing the Bosa parameters into a database and realizing the binding with the product serial number; s2, loading the BOB nonlinear power DA value and the corresponding MPD current value into the system; s3, inquiring a database according to the product serial number to obtain Bosa parameters and reading the current MPD current value in the Bosa parameters; s4 fuzzy searching the closest nonlinear power DA value and DA index by using a binary search method; s5, setting DA, reading a new power value, and jumping to S7 if the power reaches the standard; s6 calculating slope and predicting next PW _ DA index, returning to S5; s7 saves the power DA register value, calibration is complete and exits. The invention can complete the power calibration of the product by the way of packaging the functions of the lookup table, applying a binary lookup method and fuzzy matching and calculating the approximate slope so as to calculate the index of the next nonlinear power DA value.

Description

Nonlinear BOB power calibration method and system based on table lookup method and slope prediction

Technical Field

The application relates to the field of PON product production calibration, in particular to a nonlinear BOB power calibration method based on a table look-up method and slope prediction.

Background

In the field of PON product production calibration, PON products designed based on a BOB all need to calibrate a series of parameters of the BOB to ensure the communication performance of the product. The BOB design is Bosa-On-Board, Bosa-On-Board design. And BOB power calibration is a very important part thereof. PW _ DA of most BOBs is linear, namely PW _ DA is that under a set function DA value (the function DA value corresponds to an analog value for controlling Bosa laser emission power in design, and actually controls a resistance value of Bosa laser emission tube current), the BOB emits corresponding laser power, and when the DA value is increased, the emission power is increased. When the DA value is reduced, the corresponding power is reduced, the PW _ DA is increased and decreased repeatedly through comparison of the target power and the actual power, and then the BOB power calibration can be achieved, so that the BOB laser emission power of the product is in a target range. For a nonlinear BOB power driving system, the DA value for controlling the BOB power is used for controlling a register similar to a group of resistors connected in parallel, so that the DA value changes in a jumping manner according to a required resistance value, and at this time, the PW _ DA cannot be increased or decreased in a linear calibration manner to achieve the purpose of increasing or decreasing the power, and finally the power is controlled in a target range. A new algorithm is needed to implement a method for properly adjusting PW _ DA so that the transmission power of the BOB reaches the target range.

Disclosure of Invention

The invention provides a nonlinear BOB power calibration method based on a table look-up method and slope prediction, which can solve the technical problems in the process.

The technical scheme for solving the technical problems is as follows:

in a first aspect, the present invention provides a method for calibrating a non-linear BOB power based on a table lookup method and slope prediction, comprising the following steps:

s1: importing Bosa parameters into a database and binding the Bosa parameters with a product serial number;

s2: generating a corresponding lookup table according to the BOB nonlinear power DA value and the corresponding MPD current value, and sorting according to the MPD current value from small to large;

s3: calling a Webservice interface of the MES system, inquiring a corresponding Bosa parameter according to the product serial number, and reading a current MPD current value in the Bosa parameter;

s4: according to the lookup table and the current MPD current value, a binary lookup method is adopted to perform fuzzy lookup on a nonlinear power DA value and a DA index corresponding to the current MPD current value;

s5: setting the current nonlinear power DA value as the nonlinear power DA value found in the step S4, reading the corresponding power value and judging whether the power value is in the target range, if so, jumping to the step S7;

s6: calculating the slopes of the power value and the DA index according to the difference between the current power value and the last read power value and the difference between the current DA index and the last DA index, predicting the next DA index according to the slopes, and returning to the step S5;

s7: and saving the current nonlinear power DA value, completing calibration and exiting.

In some embodiments, the step S1 includes:

s11: importing parameters of Bosa into a database system before production of a product, wherein the imported parameters comprise Bosa serial numbers and MPD current values;

s12: and scanning the product serial number and the Bosa serial number in a production link, and binding the two serial numbers.

In some embodiments, the step S2 includes:

s21: loading the BOB nonlinear power DA value and the corresponding MPD current value into a system;

s22: and sorting the MPD current values from small to large, assigning a record ID to each group of nonlinear power DA values and the corresponding MPD current value, and generating a lookup table.

In some embodiments, the step S4 includes the steps of:

s41: taking the first record of the lookup table as a starting point and the last record as an end point, calculating an intermediate record ID of the starting point and the end point, and reading a corresponding intermediate MPD current value according to the intermediate record ID;

s42: comparing the current MPD current value with the intermediate MPD current value, and if the current MPD current value is larger than the intermediate MPD current value, setting the intermediate record ID as the starting point of the second query, wherein the end point is unchanged; otherwise, setting the intermediate record ID as the terminal point of the second query, and keeping the starting point unchanged; calculating the intermediate record ID of the starting point and the end point again until the starting point and the end point coincide;

s43: and reading the corresponding nonlinear power DA value and recording the corresponding DA index according to the coincidence point record ID.

In some embodiments, the step S5 includes:

s51: setting the nonlinear power DA value read in the step S43 to a power DA register, so that the BOB emits corresponding laser power and reads the current power value;

s52: comparing the read current power value with the target power value, and if the current power value does not fall into the range of the target power value, jumping to step S6; and if the current power value falls within the range of the target power value, jumping to step S7 to complete the calibration.

In some embodiments, the step S6 includes:

s61: calculating a power difference value between the current power value and the last read power value and an index difference value between the current DA index and the last DA index;

s62: calculating an approximate slope between the power value and the DA index according to the power difference value and the index difference value;

s63: and predicting the next DA index according to the approximate slope, and reading a corresponding non-linear power DA value according to the DA index.

In a second aspect, the present invention provides a non-linear BOB power calibration system based on a table lookup method and slope prediction, including:

the data import module is used for importing the Bosa parameters into the database and binding the Bosa parameters with the product serial number;

the lookup table generating module is used for generating a corresponding lookup table according to the BOB nonlinear power DA value and the corresponding MPD current value and sorting the lookup table from small to large according to the MPD current value;

the Bosa parameter reading module is used for calling a Webservice interface of the MES system, inquiring a corresponding Bosa parameter according to the product serial number, and reading the current MPD current value in the Bosa parameter;

the binary search module is used for fuzzily searching a nonlinear power DA value and a DA index corresponding to the current MPD current value by adopting a binary search method according to the search table and the current MPD current value;

a power judgment module, configured to set the current nonlinear power DA value as the nonlinear power DA value found in step S4, read a corresponding power value and judge whether the power value is within a target range, and if so, jump to step S7;

the slope prediction module is used for calculating the power value and the slope of the DA index according to the difference value between the current power value and the last read power value and the difference value between the current DA index and the last DA index, predicting the next DA index according to the slope, and returning to the step S5;

and the calibration completion module is used for storing the current nonlinear power DA value, completing calibration and exiting.

In some embodiments, the data import module comprises:

the parameter import submodule is used for importing parameters of the Bosa into the database system before production of the product, and the import parameters comprise a Bosa serial number and an MPD current value;

and the serial number binding submodule is used for binding the product serial number and the Bosa serial number by scanning in a production link.

In some embodiments, the look-up table generation module comprises:

the parameter loading submodule is used for loading the BOB nonlinear power DA value and the corresponding MPD current value into the system;

and the sorting submodule is used for sorting the MPD current values from small to large, endowing each group of nonlinear power DA values and the corresponding MPD current values with record IDs, and generating a lookup table.

In some embodiments, the binary search module comprises:

the binary computation submodule is used for taking the first record of the lookup table as a starting point and the last record as an end point, computing the middle record ID of the starting point and the end point, and reading the corresponding middle MPD current value according to the middle record ID;

the comparison and judgment submodule is used for comparing the current MPD current value with the middle MPD current value, if the current MPD current value is larger than the middle MPD current value, the middle record ID is set as the starting point of the second query, and the end point is unchanged; otherwise, setting the intermediate record ID as the end point of the second query, and keeping the starting point unchanged; calculating the intermediate record ID of the starting point and the end point again until the starting point and the end point coincide;

and the data reading submodule is used for reading the corresponding nonlinear power DA value and recording the corresponding DA index according to the coincident point record ID.

The beneficial effect of this application is:

the application provides a method and a system for calibrating the power of the non-linear BOB based on a table lookup method and slope prediction. By leading in parameters of Bosa in advance and finishing the binding of the product serial number and the Bosa serial number, conditions are created for BOB power calibration by obtaining MPD current value of Bosa; the MPD current value is inquired through the product serial number, and then the corresponding nonlinear power DA value is searched in the lookup table so as to improve the one-time hit rate of BOB calibration (namely, after the nonlinear power DA value is set for the first time, the BOB laser emission power falls in a target range and the like); the actual measurement shows that the one-time hit rate is more than 80%; by the functional packaging of the lookup table, and the application of a binary lookup method and fuzzy matching, the lookup efficiency is improved; compared with the traditional single-step approximation algorithm, the method has the advantages that the efficiency is greatly improved by calculating the approximate slope and further calculating the index of the next nonlinear power DA value; actual test statistical data show that the hit rate of 1 time is more than 80%, the hit rate of 2 time is 15%, the hit rate of 3 time is 5%, namely, 100% calibration is completed at most 3 times; the calibration time of the algorithm is 3 seconds on average under the condition of the same product, while the efficiency is obviously improved about 12 seconds in the traditional calibration algorithm.

Additional advantages, objects, and features of the application will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the application. The objectives and other advantages of the present application may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.

Drawings

FIG. 1 is a flow chart of a method for calibrating the power of a non-linear BOB based on a table lookup method and slope prediction according to the present application;

FIG. 2 is a sub-flowchart of step S1 of the present application;

FIG. 3 is a sub-flowchart of step S2 of the present application;

FIG. 4 is a sub-flowchart of step S4 of the present application;

FIG. 5 is a sub-flowchart of step S5 of the present application;

FIG. 6 is a sub-flowchart of step S6 of the present application;

FIG. 7 is a power calibration diagram according to the present application.

Detailed Description

The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.

In order that the above objects, features and advantages of the present application can be more clearly understood, the present disclosure will be further described in detail with reference to the accompanying drawings and examples. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. The specific embodiments described herein are merely illustrative of the disclosure and are not intended to limit the disclosure. All other embodiments that can be derived by one of ordinary skill in the art from the description of the embodiments are intended to be within the scope of the present disclosure.

It is noted that, in this document, relational terms such as "first" and "second," and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.

Fig. 1 is a flowchart of a non-linear BOB power calibration method based on a table lookup and slope prediction according to the present application.

The non-linear BOB power calibration method flow chart based on the table look-up method and the slope prediction, combined with the figure 1, comprises the following steps:

in some embodiments, in conjunction with fig. 2, which is a sub-flowchart of step S1 of the present application, the step S1 includes:

specifically, the MPD current value is one of parameters of Bosa, so that the Bosa parameter bound with the serial number can be found by querying the product serial number, the MPD current value in the Bosa parameter is read, and the current DA value is queried according to the relationship between the MPD current value and the nonlinear power DA value.

S12: in the production link, the product serial number and the Bosa serial number are scanned and bound;

specifically, in the production link of the product, before calibrating the BOB of the product, the product test software scans the product serial number and the Bosa serial number and submits the product serial number and the Bosa serial number to the MES database, so that the binding of the two serial numbers is realized, and conditions are created for inquiring the corresponding parameters of the Bosa through the product serial number in the process of calibrating the product BOB.

in some embodiments, in conjunction with fig. 3, which is a sub-flowchart of step S2 of the present application, the step S2 includes:

s22: sorting the MPD current values from small to large, giving a record ID to each group of nonlinear power DA values and the corresponding MPD current values, and generating a lookup table;

specifically, the MPD current value and the nonlinear power DA value in the Bosa parameter have a corresponding relationship, the loaded BOB nonlinear DA value and the corresponding MPD value are sorted from small to large based on the MPD value, the sorting work is realized in the process of generating imported data, the re-sorting during each loading is avoided, the MPD value corresponding to each record ID from small to large is also from small to large, and each record corresponds to one corresponding nonlinear power DA value. Therefore, a lookup table based on MPD current value sorting is generated, and the lookup table realizes the approximate linear relation between the record ID and the corresponding nonlinear power DA value and the actual power; after the offset record ID is obtained and the corresponding DA value is set to the product, the actual power transmitted by the BOB of the product is correspondingly increased or decreased, so that the feasibility of power calibration becomes practical.

S3: and calling a Webservice interface of the MES system, inquiring a corresponding Bosa parameter according to the product serial number, and reading the current MPD current value in the Bosa parameter.

Specifically, a Webservice interface provided by the MES system is called, and since the binding between the product serial number and the Bosa serial number is completed in step S1, the Bosa parameter can be queried through the product serial number, so as to read the current MPD current value in the Bosa parameter.

S4: and according to the lookup table and the current MPD current value, a binary lookup method is adopted to perform fuzzy lookup on the nonlinear power DA value and the DA index corresponding to the current MPD current value.

In some embodiments, in conjunction with fig. 4, which is a sub-flowchart of step S4 of the present application, the step S4 includes the following steps:

s42: comparing the current MPD current value with the intermediate MPD current value, and if the current MPD current value is larger than the intermediate MPD current value, setting the intermediate record ID as the starting point of the second query, wherein the end point is unchanged; otherwise, setting the intermediate record ID as the end point of the second query, and keeping the starting point unchanged; calculating the intermediate record ID of the starting point and the end point again until the starting point and the end point coincide;

s43: and reading the corresponding non-linear power DA value and recording the corresponding DA index according to the coincident point record ID.

Specifically, according to an input parameter, namely an actual MPD current value of the product corresponding to Bosa, a binary search method is adopted to search in a search table; the specific implementation mode is as follows:

taking the first record of the whole lookup table as a starting point and the last record as an end point, calculating a middle value, and indexing a corresponding MPD current value, namely, the first halving;

comparing the current value of MPD to be currently input with the current value of MPD recorded in the middle;

when the input MPD current value is larger than the current MPD current value of the middle record, setting the starting point as the current record ID, and keeping the end point unchanged; otherwise, setting the end point as the current record ID and keeping the starting point unchanged; the intermediate values of the starting point and the end point are timely performed again, and the corresponding records are indexed; namely, carrying out next bisection; circulating until the starting point and the end point are overlapped; then the corresponding MPD current value recorded by the look-up table at the overlapping point is the one closest to the input MPD current value, so as to implement the best fuzzy matching.

S5: and setting the current nonlinear power DA value as the nonlinear power DA value found in the step S4, reading the corresponding power value and judging whether the power value is in the target range, and if so, jumping to the step S7.

In some embodiments, in conjunction with fig. 5, which is a sub-flowchart of step S5 of the present application, the step S5 includes the following steps:

S6: calculating the slope of the power value and the DA index according to the difference between the current power value and the last read power value and the difference between the current DA index and the last DA index, predicting the next DA index according to the slope, and returning to step S5.

In some embodiments, with reference to fig. 6, which is a sub-flowchart of step S6 of the present application, step S3 specifically includes the following steps:

Specifically, it should be noted that, after the nonlinear power DA value is set for the first time, when the actual power is read for the first time, since there is no comparable previous actual power, the index of the next nonlinear power DA value is calculated by using the slope of the empirical value. Except for setting the non-linear power DA value for the first time, reading the current actual power after setting the non-linear power DA value each time; subtracting the actual power of this time from the actual power of the last time, and calculating an approximate slope by using the difference value between the indexes of the nonlinear power DA (the approximate slope is not accurate, because the DA value and the power are in a logarithmic relation and are not in a linear relation, but the time is gradually reduced each time the DA value and the power are approximated, and the DA value and the power are approximate to a linear relation); and then calculating the next nonlinear power DA index according to the difference value between the target power and the current power and the slope, reading the corresponding nonlinear power DA value and returning to the step S5.

Fig. 7 is a schematic diagram of power calibration according to the present application, where a product to be tested is connected to a production test system BOB calibration software through a network cable or a serial port, and is connected to a BOB calibrator through an optical fiber, so that the product to be tested can be written with a non-linear power DA value by using the production test system BOB calibration software, and the corresponding power is read by using the BOB calibrator, thereby realizing power calibration of the product to be tested.

The second aspect of the present application further provides a non-linear BOB power calibration system based on a table lookup method and slope prediction, including:

the lookup table generation module is used for generating a corresponding lookup table according to the BOB nonlinear power DA value and the corresponding MPD current value and sorting the lookup table from small to large according to the MPD current value;

In some embodiments, the data import module comprises:

In some embodiments, the look-up table generation module comprises:

and the sorting submodule is used for sorting from small to large based on the MPD current value, assigning a record ID to each group of nonlinear power DA values and the corresponding MPD current value, and generating a lookup table.

In some embodiments, the binary search module comprises:

the comparison and judgment submodule is used for comparing the current MPD current value with the middle MPD current value, if the current MPD current value is larger than the middle MPD current value, the middle record ID is set as the starting point of the second query, and the end point is unchanged; otherwise, setting the intermediate record ID as the terminal point of the second query, and keeping the starting point unchanged; calculating the intermediate record ID of the starting point and the end point again until the starting point and the end point coincide;

It will be understood by those skilled in the art that although some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the application and form different embodiments.

Those skilled in the art will appreciate that the description of each embodiment has a respective emphasis, and reference may be made to the related description of other embodiments for those parts of an embodiment that are not described in detail.

Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art will be able to make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are included in the scope of the appended claims, which are intended to be only specific embodiments of the present invention, and the scope of the present invention is not limited thereto, and any equivalent modifications or substitutions may be easily made by those skilled in the art within the technical scope of the present disclosure, and these modifications or substitutions should be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A non-linear BOB power calibration method based on a table look-up method and slope prediction is characterized by comprising the following steps:

s6: calculating the slope of the power value and the DA index according to the difference between the current power value and the last read power value and the difference between the current DA index and the last DA index, predicting the next DA index according to the slope, and returning to the step S5;

2. The method for calibrating power of a non-linear BOB based on table lookup and slope prediction as claimed in claim 1, wherein the step S1 comprises:

3. The method of claim 1, wherein the step S2 comprises:

4. The method of claim 1, wherein the step S4 comprises the following steps:

5. The method of claim 1, wherein the step S5 comprises:

6. The method for calibrating power of a non-linear BOB based on table lookup and slope prediction as claimed in claim 5, wherein the step S6 comprises:

s63: and predicting the next DA index according to the approximate slope, and reading a corresponding nonlinear power DA value according to the DA index.

7. A non-linear BOB power calibration system based on table lookup and slope prediction, comprising:

8. The system of claim 7, wherein the data import module comprises:

9. The system of claim 7, wherein the lookup table generation module comprises:

10. The system of claim 7, wherein the binary search module comprises: