A method for testing optoelectronic devices

Abstract

The present invention discloses a method for testing an optoelectronic device, which relates to the field of optoelectronics, and includes collecting historical test data, setting initial environmental parameters for the optoelectronic device to be tested, adjusting the initial environmental parameters according to an environmental parameter adjustment strategy, and recording specific values ​​of the adjusted environmental parameters in each stage, performing a preliminary analysis on performance indicators in each stage based on the recorded environmental parameters, obtaining a preliminary identification result of the optoelectronic device, establishing a fault identification model according to the historical test data and the preliminary identification result of the optoelectronic device, and obtaining a fault mode of the optoelectronic device; by combining the historical test data and the preliminary identification result to establish the fault identification model, accurate prediction of the fault mode of the optoelectronic device is achieved, and a clear direction is provided for subsequent specific part inspections.

Description

Technical Field

[0001] The invention relates to the field of optoelectronics, in particular to a method for testing an optoelectronic device. Background Art

[0002] As core components of modern communication and information processing systems, the performance and reliability of optoelectronic devices are directly related to the stability and efficiency of the entire system. However, the working environment of optoelectronic devices is complex and changeable, and factors such as temperature, humidity, and electromagnetic interference have a significant impact on their performance. Therefore, it is particularly important to develop a test method that can comprehensively evaluate the performance of optoelectronic devices and accurately identify failure modes.

[0003] Traditional optoelectronic device testing methods mainly rely on the measurement of key performance indicators under static test conditions. Although these methods can reflect the basic performance of the device to a certain extent, it is difficult to capture the true working state of the device and its potential failures under dynamic environmental changes. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides an optoelectronic device testing method to solve the problem that it is difficult to capture the actual working state of the device and its potential failures under dynamic environmental changes.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for testing an optoelectronic device, comprising:

[0008] Collect historical test data and set initial environmental parameters for the optoelectronic devices to be tested;

[0009] Adjust the initial environmental parameters according to the environmental parameter adjustment strategy, and record the specific values ​​of the adjusted environmental parameters at each stage;

[0010] Based on the recorded environmental parameters, the performance indicators of each stage are preliminarily analyzed to obtain preliminary identification results of optoelectronic devices;

[0011] Based on historical test data and preliminary identification results of optoelectronic devices, a fault identification model is established to obtain the failure mode of optoelectronic devices;

[0012] According to the failure mode of the optoelectronic device, the specific location of the optoelectronic device failure is further checked and recorded as a failure detection report.

[0013] As a preferred solution of the optoelectronic device testing method of the present invention, wherein: the historical test data includes environmental parameters, performance index values, failure modes and failure diagnosis results of the optoelectronic device;

[0014] The environmental parameters include temperature, humidity and electromagnetic interference;

[0015] The performance indicator values ​​include response frequency, output power and bit error rate.

[0016] As a preferred solution of the optoelectronic device testing method of the present invention, wherein: the initial environmental parameters for the optoelectronic device are set, specifically comprising the following steps:

[0017] Determine the application scenarios of optoelectronic devices;

[0018] Use an environmental control unit combined with a precision temperature and humidity sensor and an electromagnetic interference generator to set initial environmental parameters for optoelectronic devices according to the application scenario;

[0019] Mount the optoelectronic device to the test fixture and record the initial environmental parameters.

[0020] As a preferred solution of the optoelectronic device testing method of the present invention, the initial environmental parameters are adjusted according to the environmental parameter adjustment strategy, and the specific values ​​of the environmental parameters after adjustment in each stage are recorded, which specifically includes the following steps:

[0021] Setting environmental parameter adjustment strategies according to the application scenarios of optoelectronic devices;

[0022] The environmental parameter adjustment strategy includes the value of the environmental parameter adjusted each time and the target value of the environmental parameter;

[0023] Determine the preheating time of the optoelectronic device, and operate the optoelectronic device in the set initial environmental parameters according to the preheating time to complete the preheating of the optoelectronic device;

[0024] According to the environmental parameter adjustment strategy, the environmental parameters are adjusted using the environmental control unit and the electromagnetic interference generator;

[0025] After each adjustment, the current environmental parameters of the optoelectronic device and their corresponding timestamps are recorded, and the environmental parameters and their timestamps of each stage are saved in a log file.

[0026] As a preferred solution of the optoelectronic device testing method of the present invention, the performance indicators of each stage are preliminarily analyzed based on the recorded environmental parameters to obtain the preliminary identification results of the optoelectronic device, which specifically includes the following steps:

[0027] According to the recorded environmental parameters and timestamps, the performance index values ​​of the optoelectronic devices that change with the environmental parameters at each stage are collected;

[0028] Based on the performance index values ​​of optoelectronic devices, the moving average method is used to smooth the data curve and identify potential trends. The expression is:

[0029] ;

[0030] in, Indicates time point The moving average at is the time window size, An index variable representing the performance indicator value within the time window, Indicates time point The performance index value at

[0031] Based on the moving average, draw a time series graph to show the changing trend of performance indicator values ​​over time;

[0032] Use statistical analysis to calculate the mean and standard deviation of performance indicator values;

[0033] Based on the calculated average value and standard deviation, the abnormal points of the optoelectronic device are further confirmed;

[0034] The abnormal point of the optoelectronic device is the preliminary identification result.

[0035] As a preferred solution of the optoelectronic device testing method of the present invention, wherein: according to historical test data and the preliminary identification results of the optoelectronic device, a fault identification model is established to obtain the fault mode of the optoelectronic device, which specifically includes the following steps:

[0036] At the same time stamp, the temperature value, humidity value and electromagnetic interference intensity value of the environmental parameters of the optoelectronic device are extracted from the collected historical test data, and the response frequency, output power and bit error rate of the performance index value of the optoelectronic device in the historical test data are extracted;

[0037] The temperature value, humidity value, electromagnetic interference intensity value, response frequency, output power, and bit error rate extracted at each time point are arranged in order and directly concatenated into a device feature vector;

[0038] A Gaussian filter is introduced to process the device characteristic vector to obtain the device characteristic vector after Gaussian filtering;

[0039] The preliminary recognition results at each time point are concatenated into a preliminary recognition result vector;

[0040] According to the preliminary identification result vector of the optoelectronic device and the device feature vector after Gaussian filtering, an exponentially weighted moving average function is defined to obtain a comprehensive feature vector, which is expressed as:

[0041] ;

[0042] in, Indicates time point The comprehensive feature vector at represents the exponential weighting coefficient, Indicates time point The device feature vector after Gaussian filtering, Indicates time point The result vector of optoelectronic device identification at represents the weight of the initial identification result vector of optoelectronic devices, Indicates time point The comprehensive feature vector at ;

[0043] Based on the comprehensive feature vector, the LSTM network is used to calculate the occurrence probability of each potential failure mode, and the normalized exponential function is introduced to convert the occurrence probability of the potential failure mode into the probability distribution of the failure mode, which is expressed as follows:

[0044] ;

[0045] in, Indicates time point The probability distribution of failure modes at represents the normalized exponential function, represents the LSTM network, represents the weight matrix, represents element-wise multiplication, Represents the index of each time point in the time window, Indicates time point The comprehensive feature vector at Indicates time point The initial recognition result vector at ;

[0046] According to the obtained failure mode probability distribution, the failure mode with the highest failure probability is taken as the failure mode of the optoelectronic device.

[0047] As a preferred solution of the optoelectronic device testing method of the present invention, wherein: the introduction of a Gaussian filter to process the device feature vector to obtain the device feature vector after Gaussian filtering specifically includes the following steps:

[0048] Define the Gaussian kernel function and set the time range and integration range;

[0049] Iterate through each time point in the time range;

[0050] For a time point within the time range, the time difference between the time point and the time point within the time range is calculated, and the Gaussian kernel function is applied for calculation and accumulation to obtain the device feature vector after Gaussian filtering, which is expressed as:

[0051] ;

[0052] in, Indicates time point The device feature vector after Gaussian filtering, Indicates from the time point A time range that extends forward and backward, Indicates a point in time within a time range The device characteristic vector, represents the Gaussian kernel function, represents the differential variable.

[0053] As a preferred solution of the optoelectronic device testing method of the present invention, the specific location of the optoelectronic device failure is further checked according to the failure mode of the optoelectronic device and recorded as a failure detection report, which specifically includes the following steps:

[0054] Correlate the failure modes of optoelectronic devices with specific parts of the optoelectronic devices;

[0055] Locate specific parts according to the obtained failure mode of optoelectronic devices, perform physical inspection and functional testing, and obtain test results;

[0056] The test results and basic information of the optoelectronic device are recorded in the fault detection report.

[0057] In a second aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the optoelectronic device testing method as described in the first aspect of the present invention is implemented.

[0058] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the optoelectronic device testing method as described in the first aspect of the present invention is implemented.

[0059] The beneficial effects of the present invention are: setting and implementing a heating strategy for optoelectronic devices, realizing trend identification and abnormal point detection of the performance indicators of optoelectronic devices by preliminary analysis of the performance indicators at each stage, obtaining preliminary identification results of optoelectronic devices, and intuitively displaying the changing trends of performance indicators through visualization means; in addition, by combining historical test data and preliminary identification results to establish a fault identification model, accurate prediction of the failure mode of optoelectronic devices is achieved, providing a clear direction for subsequent specific part inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0061] Figure 1 This is a flow chart of the optoelectronic device testing method in Example 1.

[0062] Figure 2 This is a schematic diagram of the fault identification model outputting the fault mode of the optoelectronic device in Example 1. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0065] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0066] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a method for testing an optoelectronic device, comprising the following steps:

[0067] S1. Collect historical test data and set initial environmental parameters for the optoelectronic device to be tested.

[0068] The specific steps include:

[0069] S1.1. Collect environmental parameters including temperature, humidity and electromagnetic interference, because these parameters are key factors affecting the working state of optoelectronic devices. These parameters can reflect the performance of devices under different environmental conditions and provide a reference for subsequent tests.

[0070] The performance indicators including response frequency, output power and bit error rate are collected, because these indicators are the core parameters for evaluating the performance of optoelectronic devices and are directly related to their communication quality and stability.

[0071] The collected failure modes and fault diagnosis results record various failure modes identified in previous tests and their corresponding diagnosis results. This information not only helps to understand the common failure types of optoelectronic devices, but also provides valuable experience for the identification of new failures.

[0072] It is further explained that by comprehensively collecting historical test data, a rich data foundation has been established, providing important background information and reference standards for subsequent tests. This not only improves the reliability of the test results, but also provides solid data support for fault mode identification, ensuring the scientificity and accuracy of the test method.

[0073] S1.2. First, it is necessary to determine the specific application scenarios of optoelectronic devices, such as high-speed communication networks and precision measuring instruments. Different application scenarios have different requirements for environmental parameters, so the corresponding initial environmental parameters (such as temperature -20°C, humidity 20%RH, electromagnetic interference intensity level E1) must be set according to actual application needs. By clarifying the application scenarios, it is ensured that the test environment can truly simulate the actual working conditions of optoelectronic devices, and the applicability and reliability of the test results are improved.

[0074] The environmental control unit is used to accurately adjust the environmental parameters of temperature, humidity and electromagnetic interference to meet the set initial values. Multiple temperature and humidity sensors are evenly distributed in the test environment to ensure full coverage of the entire space. Ensure that the sensors are away from heat sources (such as heaters, cooling equipment) and moisture sources (such as water vapor exhaust ports) to prevent local temperature or humidity fluctuations from affecting the measurement results. It is used to monitor changes in environmental parameters in real time to ensure that they are stable within the set range. Select a generator that can generate a wide-band (such as 10kHz to 1GHz) electromagnetic interference signal and install the electromagnetic interference generator in an independent isolation area to avoid unnecessary interference to other test equipment. It is used to simulate the electromagnetic interference that may exist in the actual environment to further improve the authenticity and comprehensiveness of the test.

[0075] Install the optoelectronic device to be tested into a dedicated test fixture to ensure that it is firmly fixed and the electrical connection is reliable. After installation, record the current environmental parameters (such as temperature, humidity, and electromagnetic interference intensity) as the initial environmental parameters.

[0076] Further explanation: By using a dedicated test fixture, it is ensured that the optoelectronic device will not be disturbed by the outside world during the test process, ensuring the accuracy of the test results. Recording the initial environmental parameters not only provides a benchmark for subsequent adjustments, but also provides a guarantee for the traceability of the entire test process. These detailed records help to verify the consistency of the test conditions during the later data analysis, thereby improving the credibility of fault diagnosis.

[0077] S2. Adjust the initial environmental parameters according to the environmental parameter adjustment strategy, and record the specific values ​​of the adjusted environmental parameters in each stage.

[0078] The specific steps include:

[0079] S2.1. Set environmental parameter adjustment strategies according to specific application scenarios of optoelectronic devices (such as high-speed communication networks and precision measuring instruments, etc.). Different application scenarios have different requirements for environmental parameters such as temperature, humidity and electromagnetic interference.

[0080] For example, to test an optical transceiver module for a high-speed communication network, which is mainly used for high-speed data transmission between data centers. The environmental parameter adjustment strategy is set according to the specific application scenario of the optical transceiver module, that is, the high-speed communication network. Different data centers may be located in different climatic conditions, so the influence of factors such as temperature, humidity and electromagnetic interference must be considered. By clarifying the application scenario and setting the corresponding adjustment strategy, it is ensured that the test process can simulate various working conditions of the device in actual use, and improve the representativeness and reliability of the test results.

[0081] The environmental parameter adjustment strategy specifically includes the specific values ​​of each environmental parameter adjustment (such as a temperature increase of 5°C, a humidity increase of 10%RH, and an electromagnetic interference enhancement of one level) and the final target value to be achieved (such as a temperature of 35°C, a humidity of 70%RH, and an electromagnetic interference of E3). These strategies not only specify the specific operations of each adjustment, but also clarify the final desired environmental conditions.

[0082] S2.2. The warm-up time is determined to ensure that the optoelectronic device can fully operate in a stable initial environment before starting formal testing to avoid the influence of transient effects. The warm-up time is usually determined based on the manufacturer's technical documents.

[0083] According to the environmental parameter adjustment strategy, the environmental control unit and the electromagnetic interference generator are used to adjust the environmental parameters. For example, the initial conditions are: temperature -40°C, humidity 20%RH, and electromagnetic interference intensity E1. Preheating time: 30 minutes. After preheating, the environmental adjustment strategy is implemented, specifically, the temperature range: from -40°C to +85°C, each time an increase of 5°C; humidity range: from 20%RH to 95%RH, each time an increase of 5%RH; electromagnetic interference intensity level: from E1 to E3, one level increased every two hours. In operation, the temperature, humidity, and electromagnetic interference intensity are adjusted independently. After each parameter is adjusted, the next parameter is adjusted. All temperature adjustments are completed, then all humidity adjustments are completed, and finally the electromagnetic interference intensity adjustment is completed. Specifically, heating from -40°C to +85°C, increasing by 5°C each time, has a total of 26 stages; from 20%RH to 95%RH, increasing by 5%RH each time, has a total of 16 stages; from E1 to E3, the temperature is enhanced by one level every two hours, has a total of 3 stages, 26+16+3=45, so there are a total of 45 stages, and 45 stages means that the environmental parameters are adjusted 45 times in total.

[0084] After each stage of adjustment, the current environmental parameters (such as temperature, humidity, electromagnetic interference intensity) and their corresponding timestamps are recorded immediately. These data are saved in the log file to form a complete test record.

[0085] S3. Based on the recorded environmental parameters, a preliminary analysis of the performance indicators of each stage is performed to obtain preliminary identification results of the optoelectronic devices.

[0086] The specific steps include:

[0087] After each environmental parameter adjustment phase, high-precision measuring instruments (such as spectrum analyzers, power meters, bit error rate testers, etc.) are used to collect performance indicator values ​​in real time according to the recorded timestamps, and these data are saved in log files together with the corresponding timestamps. Performance indicator values ​​will change as environmental parameters change.

[0088] Based on the performance index values ​​of optoelectronic devices, the moving average method is used to smooth the data curve and identify potential trends. The moving average method reduces the impact of short-term fluctuations by averaging the data at multiple time points, making the data curve smoother and facilitating the identification of potential trends. Its expression is:

[0089] ;

[0090] in, Indicates time point The moving average of is the time window size, Indicates time point The performance index value when An index variable representing the performance indicator value within the time window, Indicates time point The performance index value at

[0091] Use chart tools (such as Matplotlib) to draw time series graphs to visualize the changing trend of performance indicator values ​​over time. Time series graphs not only intuitively reflect the changes in performance indicators, but also facilitate observation and analysis.

[0092] Statistical analysis is used to calculate the mean and standard deviation of performance index values, and the expression is:

[0093] ;

[0094] ;

[0095] in, represents the average value of the performance indicator, represents the standard deviation of the performance indicator value, Indicates the number of performance indicator values.

[0096] The outliers are further confirmed based on the calculated mean and standard deviation. For example, if the value of a data point exceeds the mean plus or minus two standard deviations, the point is considered an outlier.

[0097] It is further explained that through statistical analysis, abnormal points can be accurately located, providing a clear direction for further fault diagnosis. These abnormal points are the preliminary identification results, which provide important clues for subsequent fault mode identification and specific part inspection.

[0098] S4. Based on historical test data and preliminary identification results of optoelectronic devices, a fault identification model is established to obtain the failure mode of the optoelectronic devices.

[0099] The specific steps include:

[0100] The temperature, humidity and electromagnetic interference intensity characteristics of the optoelectronic device environmental parameters in the historical test data are extracted, and the response frequency, output power and bit error rate characteristics of the optoelectronic device in the historical test data are extracted. These characteristic values ​​can fully reflect the performance of the optoelectronic device under different conditions. The accuracy of fault mode recognition is improved.

[0101] The temperature value, humidity value, electromagnetic interference intensity value, response frequency, output power, and bit error rate features extracted at each time point are combined into a device feature vector. The scattered feature values ​​are integrated into a unified vector form, simplifying the data processing process.

[0102] Define the Gaussian kernel function to smooth the data, reduce the impact of noise, and set the time range and integration range;

[0103] Iterate through each time point in the time range ;

[0104] For a point in time within a time range , calculate the time point and time points within the time range Time difference , and apply the Gaussian kernel function for calculation and accumulation to obtain the device feature vector after Gaussian filtering, which is expressed as:

[0105] ;

[0106] in, Indicates time point The device feature vector after Gaussian filtering, Indicates from the time point A time range that extends forward and backward, Indicates a point in time within a time range The device characteristic vector, represents the Gaussian kernel function, represents the differential variable.

[0107] It is further shown that the Gaussian filter effectively removes high-frequency noise in the data, improves the quality of the device feature vector, and the smoothed device feature vector is more stable, reducing the impact of short-term fluctuations and improving the reliability of the fault identification model.

[0108] The preliminary recognition results at each time point are converted into binary codes, and each preliminary recognition result is directly concatenated into a time series matrix in sequence, which is the preliminary recognition result vector.

[0109] According to the preliminary identification result vector of the optoelectronic device and the device feature vector after Gaussian filtering, the exponentially weighted moving average function is defined. The exponentially weighted moving average function takes into account the timing characteristics of the time series data, enhances the dynamic adaptability of the fault identification model, and obtains a comprehensive feature vector, which is expressed as follows:

[0110] ;

[0111] in, Indicates time point The comprehensive feature vector at represents the exponential weighting coefficient, Indicates time point The device feature vector after Gaussian filtering, Indicates time point The result vector of optoelectronic device identification at represents the weight of the initial identification result vector of optoelectronic devices, Indicates time point The comprehensive feature vector at ;

[0112] It is further explained that by introducing the preliminary recognition result vector and combining the information detected at an early stage, the accuracy of fault recognition is further improved.

[0113] Based on the comprehensive feature vector, the LSTM network is used to calculate the probability of occurrence of each potential fault mode. The LSTM network can capture long-term and short-term dependencies and improve the fault identification model's ability to identify complex fault modes. A normalized exponential function is introduced to convert the probability of occurrence of a potential fault mode into a probability distribution of the fault mode. By using the normalized exponential function, the probability of occurrence of a potential fault mode is converted into a probability distribution, which facilitates comparison and selection of the most likely fault mode. The expression is:

[0114] ;

[0115] in, Indicates time point The probability distribution of failure modes at represents the normalized exponential function, represents the LSTM network, represents the weight matrix, represents element-wise multiplication, Represents the index of each time point in the time window, Indicates time point The comprehensive feature vector at Indicates time point The initial recognition result vector at ;

[0116] Calculated failure mode probability distribution , represents the probability of each potential failure mode. Each element corresponds to a specific failure mode, its value range is [0,1], and the sum of all probability values ​​is 1.

[0117] The most likely failure mode is selected from multiple potential failure modes as the final failure mode, providing a clear direction for subsequent inspection of specific parts.

[0118] For example, at time point The probability distribution calculated at is: =[0.05,0.10,0.60,0.15,0.05,0.05].

[0119] This means that there is a 5% chance of an overheating failure; a 10% chance of a humidity-related failure; a 60% chance of an electromagnetic interference failure; a 15% chance of an abnormal response frequency; a 5% chance of insufficient output power; and a 5% chance of an excessively high bit error rate.

[0120] The results show that the probability of electromagnetic interference failure is the highest (60%), which indicates that the most likely failure is caused by electromagnetic interference. Based on this information, technicians can further check the electromagnetic environment and take measures to reduce interference.

[0121] It is further explained that by selecting the fault mode with the highest probability, the accuracy of fault location is ensured, the possibility of misjudgment is reduced, and clear fault diagnosis results are provided to technicians, which facilitates rapid repair measures and improves work efficiency.

[0122] S5. According to the failure mode of the optoelectronic device, further check the specific location of the failure of the optoelectronic device and record it as a failure detection report.

[0123] The specific steps include:

[0124] The identified fault modes are associated with specific parts of the optoelectronic device. For example, temperature-sensitive faults correspond to the laser and heat dissipation module; abnormal output power corresponds to the laser and optical coupling part; decreased response frequency corresponds to the detector and drive circuit; increased bit error rate corresponds to the transmission line and receiving module.

[0125] It is further explained that by associating the failure mode with the specific part, the potential location of the failure can be determined more accurately, reducing the time and cost of blind detection. It enables technicians to conduct more targeted inspections and improves detection efficiency.

[0126] The specific parts are located according to the obtained failure modes of the optoelectronic devices, and physical inspection and functional testing are carried out.

[0127] Physical inspection includes appearance inspection, internal structure inspection and connection inspection.

[0128] Appearance inspection is to check whether the appearance of the device has obvious damage or abnormalities, such as burn marks, deformation, cracks, etc.

[0129] Internal structure detection uses tools such as microscopes and X-ray imaging to check whether the internal structure of the device is intact and whether there are problems such as looseness or breakage.

[0130] The connection test is to check whether the electrical connection is firm and whether there are any cold solder joints or falling off at the welding points.

[0131] Functional testing includes performance parameter testing, environmental adaptability testing and specific function testing.

[0132] It is further explained that through physical inspection and functional testing, the existence and nature of the fault are fully verified, the accuracy of the test results is ensured, and the risk of misjudgment that may be caused by a single detection method is reduced.

[0133] All test results and basic information of optoelectronic components (such as model, batch, date of manufacture, etc.) shall be recorded in detail in the fault detection report to form a complete document record.

[0134] The records include basic information of optoelectronic devices, failure modes, test results and repair suggestions.

[0135] Further explanation: detailed records ensure the transparency of the testing process, which is convenient for later review and audit. And complete documentation provides important reference materials for subsequent fault analysis and improvement.

[0136] This embodiment also provides a computer device, which is suitable for the optoelectronic device testing method, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the optoelectronic device testing method proposed in the above embodiment.

[0137] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0138] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the optoelectronic device testing method proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0139] In summary, the present invention achieves trend identification and abnormal point detection of optoelectronic device performance indicators by setting and implementing a heating strategy for optoelectronic devices, and obtains preliminary identification results of optoelectronic devices through preliminary analysis of performance indicators at each stage, and intuitively displays the changing trends of performance indicators through visualization. In addition, a fault identification model is established by combining historical test data and preliminary identification results, thereby achieving accurate prediction of optoelectronic device failure modes and providing a clear direction for subsequent specific part inspections.

[0140] Example 2, referring to Table 1, is the second example of the present invention. To further verify the technical solution of the present invention, experimental simulation data of the optoelectronic device testing method are provided.

[0141] In order to verify the effectiveness and innovation of the optoelectronic device testing method proposed in this invention, an optical transceiver module used in high-speed communication networks was selected as the test object. This module is mainly used for high-speed data transmission between data centers, and the working environment is complex and changeable, so its performance and reliability requirements are extremely high.

[0142] Test preparation:

[0143] Collect historical test data: Collect test data of this model of optical transceiver module under different temperature, humidity and electromagnetic interference conditions in the past three years. These data include performance indicators such as response frequency, output power and bit error rate, as well as failure modes and fault diagnosis results.

[0144] Historical test data provides an important reference for subsequent fault identification models, ensuring the scientificity and accuracy of the test methods.

[0145] Setting initial environmental parameters: Based on the specific application scenario of the optical transceiver module, i.e., high-speed communication network, the initial environmental parameter setting strategy was determined. Considering that data centers may be located all over the world, from cold regions to tropical regions, the temperature range is set to 20°C to 40°C; the humidity range is set to 30%RH to 70%RH; and the electromagnetic interference intensity is set to 0dBm to 30dBm.

[0146] The initial environmental parameters for the optical transceiver module were set using an environmental control unit combined with a precision temperature and humidity sensor and an electromagnetic interference generator. The module was installed in a dedicated test fixture and the initial environmental parameters were recorded, such as temperature 25°C, humidity 40%RH, and no electromagnetic interference.

[0147] Preheating and adjusting environmental parameters: The preheating time of the optical transceiver module is determined to be 30 minutes. During this period, the module operates stably under the initial environmental parameters to ensure that all components reach a thermal equilibrium state.

[0148] Then, according to the set environmental parameter adjustment strategy, the temperature, humidity and electromagnetic interference intensity are gradually adjusted. After each adjustment, the current environmental parameters and their corresponding timestamps are immediately recorded and saved in the log file. For example, the temperature increases or decreases irregularly, the humidity increases or decreases irregularly, and the electromagnetic interference increases irregularly.

[0149] Preliminary analysis and confirmation of abnormal points: Based on the recorded environmental parameter settings and timestamps, the performance index values ​​of the optical transceiver module (such as response frequency, output power, bit error rate) are collected in real time. The moving average method is used to smooth the data curve, identify potential trends, and draw a time series graph to show the trend of performance indicators over time.

[0150] Statistical analysis is used to calculate the average and standard deviation of the performance index values ​​to further confirm the abnormal points of the optical transceiver module. By comparing the performance index values ​​at each time point with the average and standard deviation, the abnormal points that significantly deviate from the normal range are identified as the preliminary identification results.

[0151] Establish a fault identification model: extract environmental parameter characteristics (temperature, humidity, electromagnetic interference intensity) and performance indicator characteristics (response frequency, output power, bit error rate) from historical test data, and combine them into a device feature vector.

[0152] A Gaussian filter is introduced to process the feature vector to obtain the device feature vector after Gaussian filtering. An exponentially weighted moving average function is defined and combined with the preliminary identification result vector to obtain a comprehensive feature vector.

[0153] The LSTM network is used to calculate the probability of occurrence of each potential failure mode, and a normalized exponential function is introduced to convert the probability into the probability distribution of the failure mode. Finally, the failure mode with the highest failure probability is selected as the failure mode of the optical transceiver module.

[0154] Specific part inspection and fault detection report: Associate the identified fault mode with the specific part of the optical transceiver module to locate the specific fault location. Perform physical inspection and functional testing to confirm the existence and nature of the fault.

[0155] Record the test results and basic information of the optical transceiver module (such as model, batch, production date, etc.) in detail in the fault detection report to form a complete document record.

[0156] The details are shown in Table 1 below:

[0157] Table 1 Optoelectronic device test table

[0158] Test subject name Temperature (°C) Humidity (%RH) Electromagnetic interference intensity (dBm) Response frequency(GHz) Output power(dBm) Bit Error Rate (BER) Initial state 25 40 0 28.5 15.2 1.2e-9 Adjustment Phase 1 28 47 7 28.3 15 1.5e-9 Adjustment Phase 2 32 58 15 28 14.8 1.7e-9 Adjustment Phase 3 37 65 23 27.7 14.5 2.1e-9 Adjustment Phase 4 39 68 27 27.5 14.3 2.3e-9

[0159] From the above table, it can be clearly seen that the optoelectronic device testing method proposed in the present invention has significant advantages and innovations in many aspects:

[0160] Accurate environment simulation:

[0161] In general technology, only the performance index measurement under static or quasi-static conditions is usually considered, ignoring the impact of dynamic changes in environmental parameters on device performance. The present invention ensures that the test process can simulate the actual use environment by setting different environmental parameters and adjusting them in real time, thereby improving the reliability and applicability of the test results.

[0162] For example, it can be seen from the table that as the temperature, humidity and electromagnetic interference intensity gradually increase, the response frequency, output power and bit error rate of the optical transceiver module also change accordingly, which shows that the test method can accurately reflect the actual performance of the device under different environmental conditions.

[0163] Detailed data records:

[0164] Conventional technologies have deficiencies in data recording, usually only recording the final performance index value, ignoring the intermediate state and timestamp information during the environmental parameter change process. The present invention not only records the environmental parameters adjusted at each stage and their corresponding timestamps in detail, but also identifies potential trends and anomalies through preliminary analysis of these data, providing a solid foundation for subsequent fault mode identification.

[0165] For example, by smoothing the data curve using the moving average method, we can more clearly see the trend of key performance indicators evolving over time, which helps to capture early signs of abnormalities and take timely measures to avoid larger failures.

[0166] Efficient Fault Mode Identification:

[0167] Conventional techniques tend to focus on static data analysis in fault diagnosis, and fail to make full use of the changing information of dynamic environmental parameters, thus limiting the comprehensiveness and accuracy of fault diagnosis. The present invention introduces Gaussian filter and smoothing technology, combined with exponentially weighted moving average function and LSTM network, to achieve more accurate fault pattern recognition.

[0168] For example, by extracting multiple eigenvalues ​​from historical test data, combining them into a comprehensive feature vector, and using an LSTM network to calculate the probability of occurrence of each potential failure mode, the failure mode with the highest probability is finally selected, which significantly improves the accuracy and efficiency of fault diagnosis.

[0169] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for testing an optoelectronic device, characterized in that: include, Collect historical test data and set initial environmental parameters for optoelectronic devices; Adjust the initial environmental parameters according to the environmental parameter adjustment strategy, and record the specific values ​​of the adjusted environmental parameters at each stage; Based on the recorded environmental parameters, the performance indicators of each stage are preliminarily analyzed to obtain preliminary identification results of optoelectronic devices; Based on historical test data and preliminary identification results of optoelectronic devices, a fault identification model is established to obtain the failure mode of optoelectronic devices; According to the failure mode of the optoelectronic device, further check the specific location of the optoelectronic device failure and record it as a failure detection report; According to the historical test data and the preliminary identification results of optoelectronic devices, a fault identification model is established to obtain the failure mode of optoelectronic devices, which specifically includes the following steps: At the same time stamp, the temperature value, humidity value and electromagnetic interference intensity value of the environmental parameters of the optoelectronic device are extracted from the collected historical test data, and the response frequency, output power and bit error rate of the performance index value of the optoelectronic device in the historical test data are extracted; The temperature value, humidity value, electromagnetic interference intensity value, response frequency, output power, and bit error rate extracted at each time point are arranged in order and directly concatenated into a device feature vector; A Gaussian filter is introduced to process the device characteristic vector to obtain the device characteristic vector after Gaussian filtering; The preliminary recognition results at each time point are concatenated into a preliminary recognition result vector; According to the preliminary identification result vector of the optoelectronic device and the device feature vector after Gaussian filtering, an exponentially weighted moving average function is defined to obtain a comprehensive feature vector, which is expressed as: ； in, Indicates time point The comprehensive feature vector at represents the exponential weighting coefficient, Indicates time point The device feature vector after Gaussian filtering, Indicates time point The result vector of optoelectronic device identification at represents the weight of the initial identification result vector of optoelectronic devices, Indicates time point The comprehensive feature vector at ; Based on the comprehensive feature vector, the LSTM network is used to calculate the occurrence probability of each potential failure mode, and the normalized exponential function is introduced to convert the occurrence probability of the potential failure mode into the probability distribution of the failure mode, which is expressed as follows: ； in, Indicates time point The probability distribution of failure modes at represents the normalized exponential function, represents the LSTM network, represents the weight matrix, represents element-wise multiplication, Represents the index of each time point in the time window, Indicates time point The comprehensive feature vector at Indicates time point The initial recognition result vector at ; According to the obtained failure mode probability distribution, the failure mode with the highest failure probability is taken as the failure mode of the optoelectronic device.

2. The optoelectronic device testing method according to claim 1, wherein: The historical test data includes environmental parameters, performance index values, failure modes and failure diagnosis results of optoelectronic devices; The environmental parameters include temperature, humidity and electromagnetic interference; The performance indicator values ​​include response frequency, output power and bit error rate.

3. The optoelectronic device testing method according to claim 2, wherein: The step of setting the initial environmental parameters for the optoelectronic device specifically includes the following steps: Determine the application scenarios of optoelectronic devices; According to the application scenario, the environmental control unit is used in combination with the temperature and humidity sensor and the electromagnetic interference generator to set the initial environmental parameters for the optoelectronic device; Mount the optoelectronic device to the test fixture and record the initial environmental parameters.

4. The optoelectronic device testing method according to claim 3, wherein: Adjust the initial environmental parameters according to the environmental parameter adjustment strategy, and record the specific values ​​of the environmental parameters after adjustment in each stage. The specific steps include: Setting environmental parameter adjustment strategies according to the application scenarios of optoelectronic devices; The environmental parameter adjustment strategy includes the value of the environmental parameter adjusted each time and the target value of the environmental parameter; Determine the preheating time of the optoelectronic device, and operate the optoelectronic device in the set initial environmental parameters according to the preheating time to complete the preheating of the optoelectronic device; According to the environmental parameter adjustment strategy, the environmental parameters are adjusted using the environmental control unit and the electromagnetic interference generator; After each adjustment, the current environmental parameters of the optoelectronic device and their corresponding timestamps are recorded, and the environmental parameters and their timestamps of each stage are saved in a log file.

5. The optoelectronic device testing method according to claim 4, characterized in that: Based on the recorded environmental parameters, the performance indicators of each stage are preliminarily analyzed to obtain the preliminary identification results of the optoelectronic devices, which specifically includes the following steps: According to the recorded environmental parameters and timestamps, the performance index values ​​of the optoelectronic devices that change with the environmental parameters at each stage are collected; Based on the performance index values ​​of optoelectronic devices, the moving average method is used to smooth the data curve, and its expression is: ； in, Indicates time point The moving average at is the time window size, An index variable representing the performance indicator value within the time window, Indicates time point The performance index value at Based on the moving average, draw a time series graph to show the changing trend of performance indicator values ​​over time; Use statistical analysis to calculate the mean and standard deviation of performance indicator values; According to the calculated average value and standard deviation of the performance index value, the abnormal point of the optoelectronic device is further confirmed; The abnormal point of the optoelectronic device is the preliminary identification result.

6. The optoelectronic device testing method according to claim 5, characterized in that: The step of introducing a Gaussian filter to process the device characteristic vector to obtain the device characteristic vector after Gaussian filtering specifically includes the following steps: Define the Gaussian kernel function and set the time range and integration range; Iterate through each time point in the time range; For a time point within the time range, the time difference between the time point and the time point within the time range is calculated, and the Gaussian kernel function is applied for calculation and accumulation to obtain the device feature vector after Gaussian filtering, which is expressed as: ； in, Indicates time point The device feature vector after Gaussian filtering, Indicates from the time point A time range that extends forward and backward, Indicates a point in time within a time range The device characteristic vector, represents the Gaussian kernel function, represents the differential variable.

7. The optoelectronic device testing method according to claim 6, characterized in that: According to the failure mode of the optoelectronic device, further check the specific location of the optoelectronic device failure and record it as a fault detection report, which specifically includes the following steps: Correlate the failure modes of optoelectronic devices with specific parts of the optoelectronic devices; Locate specific parts according to the obtained failure mode of optoelectronic devices, perform physical inspection and functional testing, and obtain test results; The test results and basic information of the optoelectronic device are recorded in the fault detection report.

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