A method and device for detecting health status of an optical module

Abstract

According to an embodiment of the present invention, a method, a detection device and a computer storage medium for detecting the health status of an optical module are provided. The data of the operating temperature, bias current and output power of the optical module within a preset time period are obtained; the obtained data of the operating temperature, bias current and output power are substituted into a preset state detection algorithm to obtain a state calculation result; the state calculation result is compared with a preset judgment condition, and the health status of the optical module is determined according to the comparison result. In some implementation processes, the data of the operating temperature, bias current and output power of the optical module within a preset time period are obtained and substituted into a preset state detection algorithm, and the health status of the optical module within the preset time period can be determined by comparing the calculation result with the judgment condition, thereby predicting the health status of the optical module in advance.

Description

Technical Field

[0001] The embodiments of the present invention relate to, but are not limited to, the field of communication technology, and specifically, relate to, but are not limited to, a method and a device for detecting the health status of an optical module. Background Art

[0002] The optical module is one of the core components of today's core network, wireless network and other network products, and is mainly used for photoelectric conversion of communication services. Once the optical module fails, it will lead to the interruption of downstream network services. Therefore, in order to ensure the normal operation of the network, the built-in register of the optical module usually sets the alarm threshold of the bias current. When the optical module detects that the bias current exceeds the preset threshold, it triggers an alarm.

[0003] The performance of current optical module lasers decreases as the temperature increases. To ensure performance, the higher the temperature, the higher the bias current required. At the same time, in order to avoid the problem of frequent alarms caused by bias current due to temperature increase, manufacturers will set the threshold of bias current very high, resulting in the optical module being in a failed or about to fail state when the alarm is generated, resulting in poor warning effect. Summary of the invention

[0004] An optical module health status detection method and detection device provided by the embodiment of the present invention mainly solve the technical problem that the current optical module alarm method cannot give an alarm in a timely and effective manner, and provides a method for predicting the health status of an optical module in advance.

[0005] To solve the above technical problems, an embodiment of the present invention provides a method for detecting the health status of an optical module, comprising: obtaining data on the operating temperature, bias current and output power of the optical module within a preset time period; substituting the obtained data on the operating temperature, bias current and output power into a preset state detection algorithm to obtain a state calculation result; comparing the state calculation result with a preset judgment condition, and determining the health status of the optical module according to the comparison result.

[0006] An embodiment of the present invention also provides a device for detecting the health status of an optical module, comprising: a data acquisition unit, used to acquire data on the operating temperature, bias current, output power and bias current of the optical module; a calculation unit, used to calculate the data on the operating temperature, bias current and output power according to a preset state detection algorithm to obtain a state calculation result; and an early warning unit, used to compare the state calculation result with a preset judgment condition and determine the health status of the optical module according to the comparison result.

[0007] An embodiment of the present invention further provides a computer storage medium, wherein the computer-readable storage medium stores one or more computer programs, and the one or more computer programs can be executed by one or more processors to implement the steps of the above-mentioned method for detecting the health status of an optical module.

[0008] According to an embodiment of the present invention, a method, a detection device and a computer storage medium for detecting the health status of an optical module are provided. The data of the operating temperature, bias current and output power of the optical module within a preset time period are obtained; the obtained data of the operating temperature, bias current and output power are substituted into a preset state detection algorithm to obtain a state calculation result; the state calculation result is compared with a preset judgment condition, and the health status of the optical module is determined according to the comparison result. In some implementation processes, the data of the operating temperature, bias current and output power of the optical module within a preset time period are obtained and substituted into a preset state detection algorithm, and the health status of the optical module within the preset time period can be determined by comparing the calculation result with the judgment condition, thereby predicting the health status of the optical module in advance.

[0009] Other features and corresponding beneficial effects of the present invention are described in the latter part of the specification, and it should be understood that at least part of the beneficial effects become obvious from the description in the specification of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 This is a flow chart of a method for detecting the health status of an optical module according to Embodiment 1 of the present invention;

[0011] Figure 2 A detailed flow chart of a method for detecting the health status of an optical module according to Embodiment 1 of the present invention;

[0012] Figure 3 A schematic diagram of four degradation stages of a method for detecting the health status of an optical module according to Embodiment 2 of the present invention;

[0013] Figure 4 This is a historical data curve diagram of the optical module H853CA56985 in the first degradation stage according to the third embodiment of the present invention;

[0014] Figure 5 This is a historical data curve chart of the optical module EB150500040100 in the second degradation stage according to the third embodiment of the present invention;

[0015] Figure 6 This is a historical data curve diagram of the optical module EB150400280832 in the third degradation stage according to the third embodiment of the present invention;

[0016] Figure 7This is a historical data curve diagram of the optical module H8541A63811 in the fourth degradation stage according to the third embodiment of the present invention;

[0017] Figure 8 A schematic diagram of a device for detecting the health status of an optical module according to a fourth embodiment of the present invention;

[0018] Fig. 9 This is a schematic diagram of the coordination of various units in a device for detecting the health status of an optical module according to a fourth embodiment of the present invention;. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the following is a further detailed description of the embodiments of the present invention through specific implementation methods combined with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0020] Embodiment 1:

[0021] In order to predict the health status of the optical module in advance, it is necessary to analyze the historical data of the optical module. By analyzing these historical data, the current health status of the optical module can be known, so as to predict when the optical module will fail. In order to accurately predict the health status of the optical module, this embodiment provides a method for detecting the health status of the optical module.

[0022] See also Figure 1 , Figure 1 A flowchart of a method for detecting the health status of an optical module provided in this embodiment, the process steps of the method for detecting the health status of an optical module include:

[0023] Step S101: Acquire data on the operating temperature, bias current and output power of the optical module within a preset time period.

[0024] In some embodiments, a time interval for instantly acquiring data on the operating temperature, bias current, and output power of the optical module is preset in a time period, and the time interval for acquiring the optical module data can be set according to actual conditions. For example, when the device is running in a well-ventilated place, the heat dissipation conditions are good, and the time interval between two data acquisitions can be appropriately extended; when the device is running in a closed place, the heat dissipation conditions are poor, and the time interval between two data acquisitions needs to be appropriately shortened.

[0025] Step S102: Substitute the acquired data of operating temperature, bias current and output power into a preset state detection algorithm to obtain a state calculation result.

[0026] In some embodiments, the health status of the optical module in the time period can be quickly and accurately determined by a preset state detection algorithm. The preset algorithm is one or more groups of calculation methods summarized based on historical data.

[0027] Step S103: Compare the state calculation result with a preset judgment condition, and determine the health state of the optical module according to the comparison result.

[0028] In some embodiments, the data of the operating temperature, bias current and output power of the optical module within the preset time period is obtained, including: respectively obtaining the data of the operating temperature, bias current and output power of N sampling points in the preset time period. During the operation of the optical module, the operating temperature, bias current and output power are usually complete curves. In the actual process of obtaining data, the preset time period can be divided into N sampling points, and the data of the operating temperature, bias current and output power are obtained once at each sampling point. The more data of the sampling points, the more accurate the calculated result.

[0029] In some embodiments, before obtaining the data of the operating temperature, bias current and output power of the optical module within the preset time period, the method further includes: obtaining the data of the maximum bias current operating threshold and the minimum output power operating threshold of the optical module. The data of the maximum bias current operating threshold and the minimum output power operating threshold of the optical module are usually the data marked by the optical module manufacturer at the time of leaving the factory. In some cases, the data of the maximum bias current operating threshold and the minimum output power operating threshold of the optical module can also be determined by analyzing historical data.

[0030] In some embodiments, the preset state detection algorithm includes: calculating the Pearson correlation coefficient of the collected data of operating temperature, bias current and output power to obtain two sets of calculation results of operating temperature-bias current and operating temperature-output power; if the positive correlation coefficient between the operating temperature-bias current and the operating temperature-output power is greater than a threshold, the state of the optical module is normal; if the positive correlation coefficient between the operating temperature-bias current and the operating temperature-output power is less than or equal to the threshold, the state of the optical module is abnormal. See Figure 2 Step S202 in .

[0031] In some embodiments, the preset state detection algorithm further includes: when it is determined that the optical module is in an abnormal state, fitting the bias current sequence of the optical module with a linear function to obtain a slope calculation result; if the slope is greater than 0 and greater than or equal to a preset slope value, the optical module is in a sub-healthy state. Figure 2Step S203 in. In this step, if the slope is greater than 0 and greater than or equal to the preset slope value, the optical module is in a sub-healthy state. The preset slope value here is an empirical value, which is a value summarized in actual applications. For example, in the current common optical modules, when the bias current-time curve of the optical module increases by 6mA / day within a sampling interval of one week, that is, the slope is greater than or equal to 0.17, it can be determined that the optical module is in a sub-healthy state. It should be noted that the specific examples given here are only for the convenience of understanding the present invention and are not used to limit the present invention. The empirical values ​​will be adjusted in actual applications according to factors such as different models and different working environments.

[0032] In some embodiments, the preset state detection algorithm further includes: when the slope is less than or equal to 0, calculating the mean of the bias current sequence of the optical module; if the mean of the bias current sequence of the optical module is greater than the preset ratio of the maximum working threshold of the bias current of the optical module, and the working temperature-output power coefficient calculated by the Pearson correlation coefficient is less than the negative correlation coefficient threshold, then the optical module is in a risk warning state. See Figure 2 Step S204 in .

[0033] In some embodiments, the preset state detection algorithm further includes: when the optical module does not meet the risk warning state, fitting the output power sequence of the optical module with a linear function to obtain a slope calculation result; if the slope is less than 0 and less than or equal to a preset slope value, the optical module is in a high risk warning state. Figure 2 Step S205 in. In this step, if the slope is less than 0 and less than or equal to the preset slope value, the optical module is in a high-risk alarm state. The preset slope value here is an empirical value, which is a value summarized in actual applications. For example, in the current common optical modules, when the output power-time curve of the optical module decreases by 0.05dB / day within a sampling interval of one week, that is, the slope is less than or equal to -0.05, it can be determined that the optical module is in a high-risk alarm state. It should be noted that the specific examples given here are only for the convenience of understanding the present invention and are not used to limit the present invention. The empirical values ​​will be adjusted in actual applications according to factors such as different models and different working environments.

[0034] In some embodiments, the preset state detection algorithm further includes: when the optical module does not meet the high-risk alarm state, calculating the mean of the output power sequence of the optical module; if the mean of the output power sequence of the optical module is less than the minimum operating threshold value of the output power of the optical module, the optical module is in a fault state. Figure 2 Step S206 in .

[0035] The embodiment of the present invention provides a method for detecting the health status of an optical module, which obtains the data of the operating temperature, bias current and output power of the optical module within a preset time period; substitutes the obtained data of the operating temperature, bias current and output power into a preset state detection algorithm to obtain a state calculation result; compares the state calculation result with a preset judgment condition, and determines the health status of the optical module according to the comparison result. By obtaining the data of the operating temperature, bias current and output power of the optical module within a preset time period and substituting them into a preset state detection algorithm, the health status of the optical module within the preset time period can be determined by comparing the calculation result with the judgment condition, thereby predicting the health status of the optical module in advance.

[0036] Embodiment 2:

[0037] In the operation and maintenance scenarios of operator networks, there are many cases of local network service interruptions due to optical module failure. Generally speaking, when the internal bias current of an optical module remains unchanged, its output power and operating temperature are inversely proportional. In order to maintain stable optical power output, the optical power feedback control unit inside the optical module will control the module's output power at a stable level by adjusting the bias current; however, as the laser ages, the laser's quantum efficiency decreases, and the bias current required to maintain stable output optical power will become higher and higher.

[0038] Based on the above analysis, this embodiment proposes four stages in the degradation process of the optical module: degradation stage 1, the historical temperature data and the bias current are no longer highly positively correlated, and the bias current continues to increase; degradation stage 2, the bias current continues to remain near the maximum threshold, and the output power change is negatively correlated with the module temperature change; degradation stage 3, the output power begins to decrease continuously; degradation stage 4, the output power drops below the working threshold value, and the optical module has failed. The process steps for determining the health status of the optical module by degradation stage can be found in Figure 3 .

[0039] Embodiment three:

[0040] This embodiment uses degradation stages to explain and illustrate a method for detecting the health status of an optical module provided by an embodiment of the present invention. The steps of the process include:

[0041] Step S1, obtaining the historical data of the temperature, current and output power of the optical module. The historical data of the temperature, current and output power of the optical module includes the data within a period of time, as well as the data of the highest working threshold and the lowest working threshold of the output power marked on the optical module.

[0042] Step S2: Calculate the Pearson correlation coefficient of the temperature sequence and the bias current sequence. If the correlation coefficient is greater than 0.9, it means that the optical module has no potential fault.

[0043] Step S3: If step S2 is not satisfied, a linear polynomial is used to fit the bias current sequence of the optical module. If the linear term coefficient, that is, the slope, is significantly greater than 0, the optical module is in the first stage of degradation.

[0044] Taking the optical module H853CA56985 as an example, the module shows a trend of continuous current increase within the sampling interval, which is the characteristic of the first stage of degradation. The implementation steps of the algorithm are as follows:

[0045] Step 1: Calculate the Pearson correlation coefficient of the historical temperature and bias current series of this module to be 0.45, which is much smaller than the threshold value of 0.9. Preliminary judgment shows that this module has a potential fault.

[0046] Step 2: Fit the bias current sequence of this module with a linear function, and obtain a slope of 0.29, which is significantly greater than 0. The bias current of this optical module rises abnormally, and it belongs to the first stage of degradation. The algorithm terminates.

[0047] Attached Figure 4 The graphs of the operating temperature, bias current and output optical power of this optical module are shown. It can be clearly seen that the yellow curve in the middle figure indicates an abnormal increase in the bias current. The alarm unit can issue an alarm for the sub-health status of the optical module based on this result.

[0048] Step S4: If step S3 is not satisfied, the mean of the optical module bias current sequence and the Pearson correlation coefficient of the temperature sequence and the power sequence are calculated. If the former is above 80% of the maximum operating threshold of the optical module bias current and the latter is less than -0.9, the optical module is in the second stage of degradation.

[0049] Taking the optical module EB150500040100 as an example, the module shows a continuous high current and a negative correlation between temperature and power in the sampling interval, which is the characteristic of the second stage of degradation. The implementation steps of the algorithm are as follows:

[0050] Step 1: Calculate the Pearson correlation coefficient of the historical temperature and bias current series of this module to be 0.375, which is much smaller than the threshold value of 0.9. Preliminary judgment shows that this module has a potential fault.

[0051] Step 2: Fit the module bias current sequence with a linear function and obtain a slope of -0.006, which is not significantly greater than 0. This condition is not met, so go to the next step.

[0052] Step 3: The calculated bias current average value is 75.7mA, which is greater than 80% of the threshold 80mA provided by the manufacturer, that is, 64mA; at the same time, the Pearson correlation coefficient of the temperature-power sequence is -0.92, which is less than the threshold -0.9. Both conditions are met, which is consistent with the characteristics of the second stage of laser degradation, and the algorithm terminates.

[0053] Attached Figure 5 The graphs of the operating temperature, bias current and output optical power of the optical module are shown. The negative correlation between the current mean and temperature-power of the module can be observed. The alarm unit can issue an alarm of the risk status of the optical module based on this result.

[0054] Step S5: If step S4 is not satisfied, the output power sequence of the optical module is fitted with a first-order polynomial. If the coefficient of the first-order term, that is, the slope, is significantly less than 0, the optical module is in the third degradation stage.

[0055] Taking the optical module EB150400280832 as an example, the module shows a trend of continuous decrease in output power within the sampling interval, which is the characteristic of the third stage of degradation. The implementation steps of the algorithm are as follows:

[0056] Step 1: Calculate the Pearson correlation coefficient of the historical temperature and bias current series of this module to be 0.458, which is much smaller than the threshold value of 0.9. Preliminary judgment shows that this module has a potential fault.

[0057] Step 2: Fit the module bias current sequence with a linear function and obtain a slope of -0.0014, which is not significantly greater than 0. This condition is not met, so go to the next step.

[0058] Step 3: The Pearson correlation coefficient of the temperature-power series is calculated to be -0.101, which is greater than the threshold of -0.9. This condition is not met, so go to the next step.

[0059] Step 4: Fit the output power sequence of this module with a linear function, and obtain a slope of -0.067, which is significantly less than 0, consistent with the characteristics of the third stage of laser degradation, and the algorithm terminates. Figure 6 This is a curve chart of real historical data of the third stage of optical module degradation.

[0060] Step S6: If step S5 is not satisfied, the mean of the optical module output power sequence is calculated. If the mean is less than the minimum operating power provided by the optical module manufacturer, the optical module is in the fourth degradation stage.

[0061] Taking the optical module H8541A63811 as an example, the module shows that the output power is continuously lower than the minimum working threshold within the sampling interval, which is the characteristic of the fourth stage of degradation. The implementation steps of the algorithm are as follows:

[0062] Step 1: Calculate the Pearson correlation coefficient of the historical temperature and bias current series of this module to be -0.986, which is much smaller than the threshold value of 0.9. Preliminary judgment shows that this module has a potential fault.

[0063] Step 2: Fit the module bias current sequence with a linear function and obtain a slope of -0.073, which is not significantly greater than 0. This condition is not met, so go to the next step.

[0064] Step 3: Calculate the Pearson correlation coefficient of the temperature-power series. Since the power reading is continuously the lowest at this time, the effective correlation coefficient value cannot be calculated, so go to the next step.

[0065] Step 4: Fit the output power sequence of this module with a linear function, and obtain a slope of 0, which is not significantly less than 0, and then go to the next step.

[0066] Step 5: The calculated average output power is -40dBm, which is much smaller than the minimum power threshold of -16dBm provided by the manufacturer. This meets the characteristics of the fourth stage of laser degradation and the algorithm is terminated. Figure 7 This is a curve chart of real historical data of the fourth stage of optical module degradation.

[0067] Embodiment 4:

[0068] This embodiment also provides a device for detecting the health status of an optical module, see Figure 8 As shown, it includes:

[0069] The data acquisition unit 100 is used to acquire data of the operating temperature, bias current, output power and bias current of the optical module;

[0070] The calculation unit 200 is used to calculate the data of the operating temperature, the bias current and the output power according to a preset state detection algorithm to obtain a state calculation result;

[0071] The early warning unit 300 is used to compare the state calculation result with a preset judgment condition, and determine the health state of the optical module according to the comparison result.

[0072] In some embodiments, the computing unit 200 includes:

[0073] Correlation coefficient calculation unit: used to calculate the Pearson correlation coefficient of temperature-current and temperature-power;

[0074] Mean value calculation unit: used to calculate the mean value of historical bias current and output power;

[0075] Slope calculation unit: used to calculate the first-order coefficient of bias current and output power;

[0076] Logical judgment unit: used to judge the fault level of the optical module according to the calculation result of the calculation unit.

[0077] In some embodiments, the warning unit 300 includes a fault warning unit: configured to issue an alarm according to an output result of the logic judgment unit.

[0078] See also Fig. 9 , Fig. 9This is a schematic diagram of the coordination between the units in a device for detecting the health status of an optical module according to the above units. The device is composed of a data acquisition unit, a correlation coefficient calculation unit, a mean value calculation unit, a slope calculation unit, a logic judgment unit, and an alarm unit. The coordination follows the following steps:

[0079] Step 1: The data acquisition unit obtains historical temperature, bias current and output power data of the entire network or part of the optical modules from the predefined interface of the network management.

[0080] Step 2: The correlation coefficient calculation unit obtains the temperature, bias current and output power data from the data acquisition unit, and calculates the Pearson correlation coefficients of the temperature-current sequence and the temperature-power sequence respectively.

[0081] Step 3: The mean calculation unit obtains the current and output power sequence data from the data acquisition unit, and calculates the means of the two sequences respectively.

[0082] Step 4: The slope calculation unit obtains the bias current and output power sequence data from the data acquisition unit, fits the two sequences with a linear function, and calculates the slope values ​​of the current and power.

[0083] Step 5: The logic judgment unit calculates the fault alarm level of this module according to the calculation results of the correlation coefficient calculation unit, the mean calculation unit and the slope calculation unit.

[0084] Step 6: The alarm unit issues an alarm of a corresponding level according to the optical module fault alarm level given by the logic judgment unit.

[0085] The present embodiment also provides a computer-readable storage medium, which includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read only memory), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer.

[0086] The computer-readable storage medium in this embodiment can be used to store one or more computer programs, and the one or more computer programs stored therein can be executed by a processor to implement at least one step of the optical module health status detection method in the above-mentioned embodiment 1 and embodiment 4.

[0087] It can be seen that those skilled in the art should understand that all or some of the steps, systems, and functional modules / units in the above disclosed methods can be implemented as software (which can be implemented with computer program code executable by a computing device), firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component can have multiple functions, or a function or step can be performed by several physical components in cooperation. Some or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit.

[0088] In addition, it is well known to those skilled in the art that communication media generally contain computer readable instructions, data structures, computer program modules or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery media. Therefore, the present invention is not limited to any specific hardware and software combination.

[0089] The above contents are further detailed descriptions of the embodiments of the present invention in combination with specific implementation methods, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for detecting the health status of an optical module, characterized in that: include: Obtain data on the operating temperature, bias current and output power of the optical module within a preset time period; Substituting the acquired operating temperature, bias current and output power data into a preset state detection algorithm to determine the health state of the optical module; wherein the preset state detection algorithm includes: The collected data of operating temperature, bias current and output power are used to calculate the Pearson correlation coefficient to obtain two sets of calculation results: operating temperature-bias current and operating temperature-output power. If the positive correlation coefficient between the operating temperature-bias current and the operating temperature-output power is greater than a threshold, the optical module is in a normal state; If the positive correlation coefficient between the operating temperature-bias current and the operating temperature-output power is less than or equal to a threshold, the optical module is in an abnormal state.

2. The optical module health status detection method according to claim 1, characterized in that: The step of obtaining data on the operating temperature, bias current and output power of the optical module within a preset time period includes: The data of the operating temperature, bias current and output power of N sampling points are respectively obtained from the preset time period.

3. The optical module health status detection method according to claim 2, characterized in that: Before obtaining the data of the operating temperature, bias current and output power of the optical module within the preset time period, the method further includes: The data of the maximum operating threshold of the bias current and the minimum operating threshold of the output power of the optical module are obtained.

4. The optical module health status detection method according to claim 3, characterized in that: The preset state detection algorithm also includes: When it is determined that the optical module is in an abnormal state, a linear function is used to fit the bias current sequence of the optical module to obtain a slope calculation result; If the slope is greater than 0 and greater than or equal to a preset slope value, the optical module is in a sub-healthy state.

5. The optical module health status detection method according to claim 4, characterized in that: The preset state detection algorithm also includes: When the slope is less than or equal to 0, calculating the mean value of the bias current sequence of the optical module; If the mean of the bias current sequence of the optical module is greater than the preset ratio of the maximum operating threshold of the bias current of the optical module, and the operating temperature-output power coefficient calculated by the Pearson correlation coefficient is less than the negative correlation coefficient threshold, the optical module is in a risk warning state.

6. The optical module health status detection method according to claim 5, characterized in that: The preset state detection algorithm also includes: When the optical module does not meet the risk warning state, fitting the output power sequence of the optical module with a linear function to obtain a slope calculation result; If the slope is less than 0 and less than or equal to a preset slope value, the optical module is in a high-risk alarm state.

7. The optical module health status detection method according to claim 6, characterized in that: The preset state detection algorithm also includes: When the optical module does not meet the high-risk alarm state, calculating the mean of the output power sequence of the optical module; If the mean value of the output power sequence of the optical module is less than the minimum operating threshold value of the output power of the optical module, the optical module is in a fault state.

8. A device for detecting the health status of an optical module, characterized in that: include: A data acquisition unit, used to acquire data of the operating temperature, bias current, output power and bias current of the optical module; A calculation unit, used to calculate data of operating temperature, bias current and output power according to a preset state detection algorithm to determine the health state of the optical module; wherein the preset state detection algorithm includes: The collected data of operating temperature, bias current and output power are used to calculate the Pearson correlation coefficient to obtain two sets of calculation results: operating temperature-bias current and operating temperature-output power. If the positive correlation coefficient between the operating temperature-bias current and the operating temperature-output power is greater than a threshold, the optical module is in a normal state; If the positive correlation coefficient between the operating temperature-bias current and the operating temperature-output power is less than or equal to a threshold, the optical module is in an abnormal state.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more computer programs, and the one or more computer programs can be executed by one or more processors to implement the steps of the optical module health status detection method according to any one of claims 1 to 7.

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