Test machine monitoring method and system, computer equipment and storage medium

Abstract

The invention discloses a test machine monitoring method and system, computer equipment and a storage medium, and the method comprises the steps: obtaining machine correction data sent by all test machines, the machine correction data comprising a machine ID, coefficient correction data and a chip type ID, the coefficient correction data is a comparison correction result of the test data of the corresponding test machine and the standard data; pairing the chip type ID with a preset type database to obtain a preset threshold range group of a corresponding type; whether the coefficient correction data is within a preset threshold range group is judged, if yes, a production test instruction is sent to a corresponding test machine according to the machine ID, so that the test machine performs production test work according to the coefficient correction data, and if not, the test machine is controlled to give an alarm. According to the invention, the machine checking and correcting work of all testing machines can be monitored, and the accuracy of the machine checking and correcting work is improved, so that the production quality and the production efficiency are improved, and the burden of manual monitoring is reduced.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a test machine monitoring method, system, computer equipment and storage medium. Background Art

[0002] LED chip testing and calibration is an important process involving precise measurement and data consistency. At present, when different types of LED bare chips are tested separately by multiple or a large number of test machines, the test machine, probe, and external environment may introduce errors. In this regard, standard samples of the corresponding type are generally made in advance, and the standard samples of the type are tested using a standard machine to determine the wavelengths of each band; before batch production testing of multiple test machines or regular machine calibration, engineering and technical personnel need to use the corresponding standard samples to calibrate each test machine, and compare the test data with the standard data, etc., and determine whether the comparison and calibration results are abnormal based on manual experience, so as to calibrate and adjust the test machine; however, manual machine calibration equipment is prone to errors due to human factors (such as negligence, fatigue or misjudgment factors), and the machine calibration cannot detect problems in time, which will lead to batch abnormalities of LED chips tested in production, reduce production quality and production efficiency, and due to the large number of testing institutions, increase the burden of manual monitoring and labor costs. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a test machine monitoring method, system, computer equipment and storage medium, which can monitor the inspection and calibration work of all test machines, improve the accuracy of the inspection and calibration work, thereby improving production quality and production efficiency, and reducing the burden of manual monitoring and reducing labor costs.

[0004] In order to solve the above technical problems, the present invention provides a test machine monitoring method, including: obtaining machine correction data sent by all test machines, wherein the machine correction data includes machine ID, coefficient correction data and chip type ID, and the coefficient correction data is the comparison and correction result of the test data of the corresponding test machine and the standard data; pairing the chip type ID with a preset type database to obtain a preset threshold range group of the corresponding type; judging whether the coefficient correction data is within the preset threshold range group, and if it is judged as yes, sending a production test instruction to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data, and if it is judged as no, sending an alarm instruction to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0005] As an improvement of the above solution, the coefficient correction data includes a voltage correction Offset value, a brightness correction Gain value and a wavelength correction Offset value;

[0006] The preset type database includes a preset threshold range group of all LED types, and the preset threshold range includes a preset voltage threshold range, a preset brightness ratio threshold range, and a preset wavelength threshold range.

[0007] As an improvement on the above scheme, it is determined whether the coefficient correction data is within the preset threshold range group. If it is determined to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is determined to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms. The steps include: determining whether the voltage correction Offset value is within the preset voltage threshold range, whether the brightness correction Gain value is within the preset brightness ratio threshold range, and whether the wavelength correction Offset value is within the preset wavelength threshold range. If it is determined to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is determined to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0008] As an improvement of the above scheme, the step of obtaining the machine correction data sent by all test machines also includes: generating a test type and coefficient report of the corresponding test machine based on the coefficient correction data and chip type ID according to the machine ID; and storing the test data and coefficient report of the test machine in the server.

[0009] As an improvement of the above scheme, the method of obtaining the machine calibration data sent by all test machines is: when the test machine is in production testing, switching gears or performing regular machine inspection, the test machine will upload the machine calibration data after the coefficient correction work and be in a standby waiting state.

[0010] Correspondingly, the present invention also provides a test machine monitoring system, including: an acquisition module, used to acquire machine correction data sent by all test machines, wherein the machine correction data includes a machine ID, coefficient correction data and a chip type ID, and the coefficient correction data is a comparison and correction result of the test data of the corresponding test machine with the standard data; a type matching module, used to match the chip type ID with a preset type database to obtain a preset threshold range group of the corresponding type; a judgment processing module, used to judge whether the coefficient correction data is within the preset threshold range group, and if it is judged to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data, and if it is judged to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0011] As an improvement of the above scheme, the judgment processing module includes: a judgment processing unit, used to judge whether the voltage correction Offset value is within a preset voltage threshold range, whether the brightness correction Gain value is within a preset brightness ratio threshold range, and whether the wavelength correction Offset value is within a preset wavelength threshold range; if the judgment is yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data; if the judgment is no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0012] As an improvement of the above scheme, it also includes a report generation module and a storage module; a report processing module, used to generate or update the test type and coefficient report of the corresponding test machine according to the coefficient correction data and chip type ID according to the machine ID; a storage module, used to store the test data and coefficient report of the test machine in the server.

[0013] Correspondingly, the present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0014] Accordingly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0015] The implementation of the present invention has the following beneficial effects:

[0016] The present invention can monitor all test machines, and can automatically perform data judgment and processing on the machine calibration data of the test type performed by each test machine, so as to accurately determine the calibration status of the test machine and improve the accuracy of the machine inspection and calibration work; if an abnormal situation occurs, the test machine can be controlled in time to alarm, so as to promptly notify the technical personnel to perform manual machine inspection and calibration processing, effectively avoiding the batch production test of LED chips, thereby improving production quality and production efficiency, and reducing the burden of manual monitoring and labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of the test machine monitoring method of the present invention;

[0018] Figure 2 This is a flow chart after the step of obtaining the machine calibration data sent by all test machines of the present invention:

[0019] Figure 3 It is a structural schematic diagram of the test machine monitoring system of the present invention. DETAILED DESCRIPTION

[0020] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

[0021] like Figure 1 As shown, a specific embodiment of the present invention provides a test machine monitoring method, including:

[0022] S101, acquiring machine calibration data sent by all test machines, wherein the machine calibration data includes machine ID, coefficient calibration data and chip type ID, and the coefficient calibration data is a comparison and calibration result of the test data of the corresponding test machine and the standard data;

[0023] It should be noted that the acquisition of machine calibration data sent by all test machines is as follows: when the test machine is in production testing, switching gears or performing regular machine inspection, the test machine will determine its own working test type according to the assigned LED chip type and use the corresponding standard film for comparison and calibration processing. The test machine compares and calibrates the test data of the same LED chip with the standard data to obtain the machine calibration data. For example, the voltage difference, brightness ratio and wavelength difference between the test data and the standard data, i.e., the voltage correction Offset value, brightness correction Gain value and wavelength correction Offset value, are calculated based on the test data and the standard data, and the above coefficient correction data is stored; finally, the machine calibration data will be uploaded after the coefficient correction work, and it will be in a standby waiting state to wait for the returned information and perform corresponding processing.

[0024] Different types of LED chips have different chip type IDs. Due to the differences in performance between different LED chips, the test machine needs to perform calibration and adjustment of the corresponding test type for different types of LED chips to ensure the stability and accuracy of production testing.

[0025] S102, matching the chip type ID with a preset type database to obtain a preset threshold range group of a corresponding type;

[0026] It should be noted that the preset type database includes preset threshold range groups for all LED types to accommodate machine calibration work for different types of LED production tests. By matching the LED chip types required for production testing by the test machine with the preset type database, a preset threshold range group of the corresponding type can be obtained. Through this preset threshold range group, the test machine of the specified working test type can be calibrated and tested to ensure the stability and accuracy of the production test. Among them, the preset threshold range includes a preset voltage threshold range, a preset brightness ratio threshold range, and a preset wavelength threshold range.

[0027] S103, determine whether the coefficient correction data is within the preset threshold range group. If it is judged to be yes, send a production test instruction to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is judged to be no, send an alarm instruction to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0028] Preferably, the step of obtaining the machine correction data sent by all test machines also includes: generating a test type and coefficient report of the corresponding test machine according to the machine ID using the coefficient correction data and the chip type ID; and storing the test data and coefficient report of the test machine in the server.

[0029] It should be noted that the machine calibration data obtained generates or updates the test type and coefficient report of the corresponding machine and stores the test type and coefficient report in the server, which makes it convenient for staff to view the machine calibration status of all test machines at different times or time periods by accessing the server, so as to timely discover and troubleshoot potential safety hazards and risk points of the test machines, and ensure the stable operation of the test machines.

[0030] like Figure 2 As shown, the present invention also provides a testing machine monitoring system, comprising:

[0031] An acquisition module, used to acquire machine calibration data sent by all test machines, wherein the machine calibration data includes a machine ID, coefficient calibration data and a chip type ID, and the coefficient calibration data is a comparison and calibration result of the test data of the corresponding test machine with the standard data;

[0032] It should be noted that the acquisition of machine calibration data sent by all test machines is as follows: when the test machine is in production testing, switching gears or performing regular machine inspection, the test machine will determine its own working test type according to the assigned LED chip type and use the corresponding standard film for comparison and calibration processing. The test machine compares and calibrates the test data of the same LED chip with the standard data to obtain the machine calibration data. For example, the voltage difference, brightness ratio and wavelength difference between the test data and the standard data, i.e., the voltage correction Offset value, brightness correction Gain value and wavelength correction Offset value, are calculated based on the test data and the standard data, and the above coefficient correction data is stored; finally, the machine calibration data will be uploaded after the coefficient correction work, and it will be in a standby waiting state to wait for the returned information and perform corresponding processing.

[0033] Different types of LED chips have different chip type IDs. Due to the differences in performance between different LED chips, the test machine needs to perform calibration and adjustment of the corresponding test type for different types of LED chips to ensure the stability and accuracy of production testing.

[0034] A type matching module, used for matching the chip type ID with a preset type database to obtain a preset threshold range group of a corresponding type;

[0035] It should be noted that the preset type database includes preset threshold range groups for all LED types to accommodate machine calibration work for different types of LED production tests. By matching the LED chip type ID required for production testing by the test machine with the preset type database, a preset threshold range group of the corresponding type can be obtained. Through this preset threshold range group, the test machine of the specified working test type can be calibrated and tested to ensure the stability and accuracy of the production test. Among them, the preset threshold range includes a preset voltage threshold range, a preset brightness ratio threshold range, and a preset wavelength threshold range.

[0036] The judgment processing module is used to judge whether the coefficient correction data is within a preset threshold range group. If it is judged to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is judged to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0037] Specifically, the judgment processing module includes: a judgment processing unit, used to judge whether the voltage correction Offset value is within a preset voltage threshold range, whether the brightness correction Gain value is within a preset brightness ratio threshold range, and whether the wavelength correction Offset value is within a preset wavelength threshold range; if it is judged to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data; if it is judged to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

[0038] It should be noted that when the voltage correction Offset value is within the preset voltage threshold range, the brightness correction Gain value is within the preset brightness ratio threshold range, and the wavelength correction Offset value is within the preset wavelength threshold range, it means that the correction of the test machine is within the normal range. At this time, a production test instruction can be sent to the corresponding test machine according to the machine ID, so that the test machine can perform the Gain and Offset coefficients of the test machine according to the coefficient correction data and perform production testing. If the voltage correction Offset value in the coefficient correction data is added to the original voltage Offset value on the test machine, the corrected voltage Offset value can be obtained. Correspondingly, the other Gain and Offset coefficients of the machine are also corrected, so that the test machine can use the corrected Gain and Offset coefficients to perform accurate production testing during mass production testing to ensure the stability and accuracy of production testing.

[0039] When any coefficient value is not within the corresponding preset threshold range, it means that the calibration of the test machine may be abnormal, and the coefficient difference is large, and the LED chip cannot be normally produced and tested. At this time, an alarm instruction can be sent to the corresponding test machine according to the machine ID to make the test machine alarm, so as to promptly notify the on-site technicians to perform manual machine inspection and calibration, such as determining whether the inspection is correct. If correct, production testing will be carried out. If incorrect, re-inspection will be carried out to ensure the working stability and accuracy of the test machine, effectively avoid the occurrence of LED chip batch production testing, thereby improving production quality and efficiency, and reducing the burden of manual monitoring and labor costs.

[0040] In this embodiment, the preset voltage threshold range is preferably ±0.03V, but is not limited thereto.

[0041] In this embodiment, the preset brightness ratio threshold range is ±5%, but not limited thereto.

[0042] In this embodiment, the preset wavelength threshold range is ±0.7 nm, but is not limited thereto.

[0043] like Figure 3 As shown, the test machine monitoring system also includes a report generation module and a storage module; a report processing module, used to generate or update the test type and coefficient report of the corresponding test machine according to the coefficient correction data and chip type ID of the machine ID; a storage module, used to store the test data and coefficient report of the test machine in the server.

[0044] It should be noted that the machine calibration data obtained generates or updates the test type and coefficient report of the corresponding machine and stores the test type and coefficient report in the server, which makes it convenient for staff to view the machine calibration status of all test machines at different times or time periods by accessing the server, so as to timely discover and troubleshoot potential safety hazards and risk points of the test machines, and ensure the stable operation of the test machines.

[0045] Correspondingly, the present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0046] Accordingly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0047] In summary, the present invention can monitor all test machines, and can automatically perform data judgment and processing on the machine calibration data of each test type performed by the test machine, so as to accurately determine the calibration status of the test machine and improve the accuracy of the machine inspection and calibration work; if an abnormal situation occurs, the test machine can be controlled in time to alarm, so as to promptly notify the technicians to perform manual machine inspection and calibration processing, effectively avoiding the occurrence of batch production testing of LED chips, thereby improving production quality and production efficiency, and reducing the burden of manual monitoring and reducing labor costs.

[0048] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A test machine monitoring method, characterized in that: include: Acquire machine calibration data sent by all test machines, wherein the machine calibration data includes machine ID, coefficient calibration data and chip type ID, and the coefficient calibration data is the comparison and calibration result of the test data of the corresponding test machine with the standard data; Matching the chip type ID with a preset type database to obtain a preset threshold range group of a corresponding type; Determine whether the coefficient correction data is within a preset threshold range group. If it is, send a production test instruction to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is not, send an alarm instruction to the corresponding test machine according to the machine ID, so that the test machine alarms.

2. The test machine monitoring method according to claim 1, characterized in that: The coefficient correction data includes a voltage correction Offset value, a brightness correction Gain value and a wavelength correction Offset value; The preset type database includes a preset threshold range group of all LED types, and the preset threshold range includes a preset voltage threshold range, a preset brightness ratio threshold range, and a preset wavelength threshold range.

3. The test machine monitoring method according to claim 2, characterized in that: The steps of determining whether the coefficient correction data is within a preset threshold range group, and if so, sending a production test instruction to the corresponding test machine according to the machine ID so that the test machine performs a production test according to the coefficient correction data; and if not, sending an alarm instruction to the corresponding test machine according to the machine ID so that the test machine performs an alarm, include: Determine whether the voltage correction Offset value is within the preset voltage threshold range, whether the brightness correction Gain value is within the preset brightness ratio threshold range, and whether the wavelength correction Offset value is within the preset wavelength threshold range. If it is judged to be yes, send a production test instruction to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is judged to be no, send an alarm instruction to the corresponding test machine according to the machine ID, so that the test machine alarms.

4. The test machine monitoring method according to claim 1, characterized in that: After the step of obtaining the machine calibration data sent by all the test machines, the method further includes: Generate a test type and coefficient report of the corresponding test machine based on the coefficient correction data and chip type ID according to the machine ID; The test data and coefficient report of the test machine are stored in the server.

5. The test machine monitoring method according to claim 1, characterized in that: The method of obtaining the machine calibration data sent by all test machines is as follows: when the test machine is in production testing, switching gears or performing regular machine inspection, the test machine will upload the machine calibration data after coefficient calibration and be in a standby waiting state.

6. A testing machine monitoring system, characterized in that: include: An acquisition module, used to acquire machine calibration data sent by all test machines, wherein the machine calibration data includes a machine ID, coefficient calibration data and a chip type ID, and the coefficient calibration data is a comparison and calibration result of the test data of the corresponding test machine with the standard data; A type matching module, used for matching the chip type ID with a preset type database to obtain a preset threshold range group of a corresponding type; The judgment processing module is used to judge whether the coefficient correction data is within a preset threshold range group. If it is judged to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is judged to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

7. The testing machine monitoring system according to claim 6, characterized in that: The judgment processing module includes: A judgment processing unit is used to judge whether the voltage correction Offset value is within a preset voltage threshold range, whether the brightness correction Gain value is within a preset brightness ratio threshold range, and whether the wavelength correction Offset value is within a preset wavelength threshold range. If it is judged to be yes, a production test instruction is sent to the corresponding test machine according to the machine ID, so that the test machine performs production testing according to the coefficient correction data. If it is judged to be no, an alarm instruction is sent to the corresponding test machine according to the machine ID, so that the test machine alarms.

8. The test machine monitoring system according to claim 6, characterized in that: It also includes a report generation module and a storage module; A report processing module, used to generate or update a test type and coefficient report of a corresponding test machine based on the coefficient correction data and chip type ID according to the machine ID; The storage module is used to store the test data and coefficient report of the test machine in the server.

9. 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 computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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