Method, device, equipment and medium for predicting the health status of an optical module

Abstract

The present application relates to a method, device, equipment and medium for predicting the health status of an optical module, including: collecting historical operating data of the optical module; pre-processing the historical operating data to obtain target historical operating data; calculating the probability of occurrence of the optical module failure type corresponding to the indicator based on the historical data of each indicator in the target historical operating data; calculating the probability of optical module failure based on the probability of occurrence of the optical module failure type corresponding to each indicator in the multiple indicators; and predicting the health status of the optical module based on the probability of optical module failure. It can be seen that the technical solution of the present application calculates the probability of optical module failure based on multiple indicators of the optical module, and then predicts the health status of the optical module based on the probability of optical module failure. In this way, the health status of the optical module can be accurately predicted, so that the user can discover the problem of the optical module in time, effectively reduce the risk of network service interruption, and improve user experience.

Description

Technical Field

[0001] The present application relates to the field of optical modules, and in particular to a method, device, equipment, and medium for predicting the health status of an optical module. Background Art

[0002] With the development of the internet, optical fiber is becoming increasingly popular. Optical fiber boasts advantages such as high efficiency, high speed, and low loss in transmitting optical signals, making it commonly used for long-distance data transmission. Optical modules are the primary components for optical fiber data transmission. A failure in an optical module can disrupt downstream network services. Therefore, predicting the health of optical modules is particularly important.

[0003] Currently, existing technical solutions collect data on specific indicators of optical modules and analyze the data to predict the health status of the optical modules.

[0004] However, the above technical solution predicts the health status of the optical module based on the data of a single indicator of the optical module, which makes it impossible to accurately predict the health status of the optical module, making it impossible for users to discover problems with the optical module in advance, thereby causing network service interruption and affecting user experience. Summary of the Invention

[0005] The embodiments of the present application provide a method, apparatus, device, and medium for predicting the health status of an optical module, which aims to solve the problem that the health status of an optical module cannot be accurately predicted by predicting the health status of the optical module based on the data of a single indicator of the optical module.

[0006] In a first aspect, an embodiment of the present application provides a method for predicting the health status of an optical module, comprising:

[0007] Collecting historical operation data of the optical module, the historical operation data including historical data of multiple indicators of the optical module, each of the multiple indicators corresponding to a fault type of the optical module;

[0008] Preprocessing the historical operation data to obtain target historical operation data;

[0009] Calculating the probability of occurrence of the optical module fault type corresponding to the indicator according to the historical data of each indicator in the target historical operation data;

[0010] Calculating the probability of the optical module failure according to the probability of occurrence of the optical module failure type corresponding to each indicator in the multiple indicators;

[0011] The health status of the optical module is predicted according to the probability of failure of the optical module.

[0012] Optionally, calculating the probability of occurrence of an optical module failure type corresponding to each indicator in the target historical operation data according to the historical data of the indicator includes:

[0013] Obtaining the normal usage time of the optical module;

[0014] Obtaining the usage time of the optical module;

[0015] Counting the number of abnormal data in the historical data of each indicator in the target historical operation data;

[0016] The occurrence probability of the optical module fault type corresponding to the indicator is calculated according to the normal use time, the used time, the total number of historical data of each indicator in the target historical operation data, and the number of abnormal data.

[0017] Optionally, the multiple indicators include: optical power, temperature, bias current and bias voltage.

[0018] Optionally, the calculation formula for the probability of the optical module failing is:

[0019] λ OM =40%*λ OP +10%*λ T +40%*λ I +10%*λ V

[0020] Among them, λ OM is the probability of optical module failure, λ OP is the probability of occurrence of optical module failure type corresponding to optical power, λ T is the probability of occurrence of optical module failure type corresponding to temperature, λ I is the probability of occurrence of optical module failure type corresponding to bias current, λ V is the probability of occurrence of the optical module fault type corresponding to the bias voltage.

[0021] Optionally, after calculating the probability of failure of the optical module according to the probability of occurrence of the optical module failure type corresponding to each indicator in the multiple indicators, and before predicting the health status of the optical module according to the probability of failure of the optical module, the method further includes:

[0022] Calculating the remaining usage time of the optical module according to the probability of failure of the optical module, the normal usage time of the optical module, and the usage time of the optical module;

[0023] The predicting the health status of the optical module according to the probability of failure of the optical module includes:

[0024] The health status of the optical module is predicted according to the probability of failure of the optical module and the remaining usage time.

[0025] Optionally, the calculation formula for the remaining usage time of the optical module is:

[0026] T re =(T1-T2)*(1-λ OM )

[0027] Among them, T re is the remaining usage time of the optical module, T1 is the normal usage time of the optical module, T2 is the usage time of the optical module, and λ OM is the probability of an optical module failure.

[0028] In a second aspect, an embodiment of the present application further provides an optical module health status prediction device, which includes a unit for executing the above method.

[0029] In a third aspect, an embodiment of the present application further provides a computer device, which includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above method when executing the computer program.

[0030] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program can implement the above method when executed by a processor.

[0031] The embodiment of the present application provides a method, device, equipment and medium for predicting the health status of an optical module. The method includes: collecting historical operating data of the optical module, the historical operating data includes historical data of multiple indicators in the optical module, each of the multiple indicators corresponds to a type of optical module fault; preprocessing the historical operating data to obtain target historical operating data; calculating the probability of occurrence of the optical module fault type corresponding to the indicator based on the historical data of each indicator in the multiple indicators in the target historical operating data; calculating the probability of failure of the optical module based on the probability of occurrence of the optical module fault type corresponding to each indicator in the multiple indicators; and predicting the health status of the optical module based on the probability of failure of the optical module. It can be seen that the technical solution of the present application calculates the probability of failure of the optical module based on multiple indicators of the optical module, and then predicts the health status of the optical module based on the probability of failure of the optical module. In this way, the health status of the optical module is accurately predicted, so that the user can discover the problem of the optical module in time, effectively reduce the risk of network service interruption, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings. These exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements. Unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0035] Figure 1 This is a flow chart of a method for predicting the health status of an optical module provided in an embodiment of the present application;

[0036] Figure 2 A second flow chart of a method for predicting the health status of an optical module provided in an embodiment of the present application;

[0037] Figure 3 The third flowchart of a method for predicting the health status of an optical module provided in an embodiment of the present application;

[0038] Figure 4 A schematic block diagram of an optical module health status prediction device provided in an embodiment of the present application;

[0039] Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0041] The disclosure below provides many different embodiments or examples for implementing different structures of the present application. In order to simplify the disclosure of the present application, the components and settings of specific examples are described below. Of course, these are merely examples and are not intended to limit the present application. In addition, the present application may repeat reference numbers and / or letters in different examples. Such repetition is for the purpose of simplicity and clarity and does not in itself indicate the relationship between the various embodiments and / or settings discussed.

[0042] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0043] It should also be understood that the terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0044] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0045] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0046] In order to solve the technical problem in the prior art that the health status of an optical module cannot be accurately predicted by predicting the health status of the optical module through the data of a single indicator of the optical module, the present application provides an optical module health status prediction device that can accurately predict the health status of the optical module.

[0047] See also Figure 1 , Figure 1 An embodiment of the present application provides a method for predicting the health status of an optical module. In one embodiment, the method includes:

[0048] S1. Collect historical operating data of the optical module.

[0049] The historical operation data includes historical data of multiple indicators in the optical module. The multiple indicators include: optical power, temperature, bias current and bias voltage. It should be noted that the optical power includes the transmitted optical power and the received optical power. The temperature is the operating temperature of the optical module. The collector periodically collects data corresponding to multiple indicators of the optical module to obtain the historical operation data of the optical module. It should be noted that different indicators can correspond to the same collection period or different collection periods. This application does not impose any restrictions on this.

[0050] Each of the multiple indicators corresponds to an optical module fault type. Table 1 shows the correspondence between optical module indicators and optical module fault types. For example, the optical module fault type corresponding to optical power is optical power abnormality.

[0051] Table 1

[0052]

[0053]

[0054] S2. Preprocess the historical operation data to obtain target historical operation data.

[0055] To eliminate the impact of noise in historical operating data, the collected historical operating data is cleaned, denoised, and normalized to obtain target historical operating data. This improves the quality of the target historical operating data and facilitates accurate prediction of the health status of optical modules. The target historical operating data includes historical data on multiple indicators of the optical module.

[0056] S3. Calculate, based on historical data of each indicator among the multiple indicators in the target historical operating data, the probability of occurrence of the optical module fault type corresponding to the indicator.

[0057] For example, the historical data corresponding to the optical power indicator in the target historical operating data is data set A, and the probability of the optical power abnormality of the optical module is calculated based on the data in data set A.

[0058] S4. Calculate the probability of an optical module failure according to the probability of occurrence of an optical module failure type corresponding to each indicator in the multiple indicators.

[0059] In one embodiment, the probability of an optical module failure is calculated based on the probability of an optical power abnormality, the probability of an optical module temperature abnormality, the probability of an optical module bias current abnormality, and the probability of an optical module bias voltage abnormality.

[0060] S5. Predict the health status of the optical module based on the probability of the optical module failing.

[0061] The greater the probability of an optical module failure, the worse the health status of the optical module, and vice versa.

[0062] Specifically, the correspondence between the probability of failure of the optical module and the health status of the optical module is set according to the empirical value. For example, when the probability of failure of the optical module does not exceed 10%, the health status of the optical module is characterized as excellent. When the probability of failure of the optical module is between 10% and 30%, excluding 30%, the health status of the optical module is characterized as good. When the probability of failure of the optical module exceeds 30%, the health status of the optical module is characterized as poor. Of course, for optical modules from different manufacturers, the correspondence between the probability of failure of the optical module and the health status of the optical module may be different. For example, when the probability of failure of the optical module does not exceed 5%, the health status of the optical module is characterized as excellent. This application does not impose any restrictions on this.

[0063] The embodiment of the present application provides a method for predicting the health status of an optical module, comprising: collecting historical operating data of the optical module, the historical operating data including historical data of multiple indicators in the optical module, each of the multiple indicators corresponding to an optical module fault type; pre-processing the historical operating data to obtain target historical operating data; calculating the probability of occurrence of the optical module fault type corresponding to the indicator based on the historical data of each indicator in the multiple indicators in the target historical operating data; calculating the probability of failure of the optical module based on the probability of occurrence of the optical module fault type corresponding to each indicator in the multiple indicators; and predicting the health status of the optical module based on the probability of failure of the optical module. It can be seen that the technical solution of the present application calculates the probability of failure of the optical module based on multiple indicators of the optical module, and then predicts the health status of the optical module based on the probability of failure of the optical module. In this way, the health status of the optical module can be accurately predicted, so that the user can discover problems with the optical module in a timely manner, effectively reduce the risk of network service interruption, and improve user experience.

[0064] See also Figure 2 , Figure 2 This is a flow chart of a method for predicting the health status of an optical module provided in an embodiment of the present application. In one embodiment, the calculation of the probability of occurrence of the optical module fault type corresponding to each indicator in the target historical operating data includes:

[0065] S30: Obtain the normal usage time of the optical module.

[0066] The normal operating life of an optical module is the normal service life of the optical module. This service life is measured in years and is determined when the optical module leaves the factory.

[0067] S31. Obtain the usage time of the optical module.

[0068] The usage time of an optical module refers to the actual usage time of the optical module after it leaves the factory, expressed in years.

[0069] S32. Count the number of abnormal data in the historical data of each indicator in the target historical operation data.

[0070] Abnormal data in the historical data of each indicator indicates that the value of the abnormal data is not within the normal range of the indicator. The normal range of each indicator of the optical module is determined at the factory.

[0071] For example, the optical power of an optical module during normal operation is [-7, +2] dBm. The historical data corresponding to the optical power indicator in the target historical operating data is dataset A {-2, -3, -4, -8, 1, 1, 2}. The number of abnormal data in dataset A is 1, that is, the abnormal data is "-8."

[0072] S33. Calculate the probability of occurrence of the optical module fault type corresponding to the indicator based on the normal use time, the used time, the total number of historical data of each indicator in the target historical operation data, and the number of abnormal data.

[0073] In one embodiment, the probability of an optical module failure is calculated as follows:

[0074] λ OM =40%*λ OP +10%*λ T +40%*λ I +10%*λ V

[0075] Among them, λ OM is the probability of optical module failure, λ OP is the probability of occurrence of optical module failure type corresponding to optical power, λ T is the probability of occurrence of optical module failure type corresponding to temperature, λ I is the probability of occurrence of optical module failure type corresponding to bias current, λ V is the probability of occurrence of the optical module fault type corresponding to the bias voltage.

[0076] See also Figure 3 , Figure 3 This is a flowchart of a method for predicting the health status of an optical module provided in an embodiment of the present application. In one embodiment, after calculating the probability of the optical module failure based on the probability of occurrence of the optical module failure type corresponding to each indicator in the multiple indicators, the method further includes:

[0077] S6. Calculate the remaining usage time of the optical module according to the probability of failure of the optical module, the normal usage time of the optical module, and the usage time of the optical module.

[0078] In one embodiment, the calculation formula for the remaining usage time of the optical module is:

[0079] T re =(T1-T2)*(1-λ OM )

[0080] Among them, T re is the remaining usage time of the optical module, T1 is the normal usage time of the optical module, T2 is the usage time of the optical module, and λ OM is the probability of an optical module failure.

[0081] The predicting the health status of the optical module according to the probability of failure of the optical module includes:

[0082] S50: Predicting the health status of the optical module according to the probability of failure of the optical module and the remaining service life.

[0083] The longer the remaining service life of an optical module, the healthier the optical module is, and vice versa.

[0084] The health status of optical modules is predicted based on the probability of failure and remaining service life of the optical modules, enabling more accurate prediction of the health status of optical modules.

[0085] In one embodiment, the historical operation data of the optical module, the probability of occurrence of the optical module failure type corresponding to each indicator of the optical module, the probability of failure of the optical module and the health status assessment result of the optical module are displayed through a visual interface to facilitate engineers to view and manage the optical module.

[0086] See also Figure 4 , Figure 4 This is a schematic block diagram of an optical module health status prediction device provided in an embodiment of the present application. Corresponding to the above optical module health status prediction method, the present application also provides an optical module health status prediction device. The optical module health status prediction device includes a unit for executing the above optical module health status prediction method. The optical module health status prediction device can be configured in a terminal such as a desktop computer, tablet computer, or laptop computer. Specifically, the optical module health status prediction device includes:

[0087] A collection module 401 is configured to collect historical operating data of the optical module, wherein the historical operating data includes historical data of multiple indicators of the optical module, each of the multiple indicators corresponding to a fault type of the optical module;

[0088] A preprocessing module 402 is used to preprocess the historical operation data to obtain target historical operation data;

[0089] A first calculation unit 403 is configured to calculate, based on historical data of each indicator among a plurality of indicators in the target historical operation data, a probability of occurrence of an optical module fault type corresponding to the indicator;

[0090] A second calculation unit 404 is configured to calculate a probability of failure of the optical module according to a probability of occurrence of an optical module failure type corresponding to each indicator in the multiple indicators;

[0091] The prediction unit 405 is configured to predict the health status of the optical module according to the probability of failure of the optical module.

[0092] In one embodiment, the first calculation unit 403 is specifically configured to obtain a normal usage time of the optical module;

[0093] Obtaining the usage time of the optical module;

[0094] Counting the number of abnormal data in the historical data of each indicator in the target historical operation data;

[0095] The occurrence probability of the optical module fault type corresponding to the indicator is calculated according to the normal use time, the used time, the total number of historical data of each indicator in the target historical operation data, and the number of abnormal data.

[0096] In one embodiment, the multiple indicators include: optical power, temperature, bias current and bias voltage.

[0097] In one embodiment, the calculation formula for the probability of failure of the optical module is:

[0098] λ OM =40%*λ OP +10%*λ T +40%*λ I +10%*λ V

[0099] Among them, λ OM is the probability of optical module failure, λ OP is the probability of occurrence of optical module failure type corresponding to optical power, λ T is the probability of occurrence of optical module failure type corresponding to temperature, λ I is the probability of occurrence of optical module failure type corresponding to bias current, λ V is the probability of occurrence of the optical module fault type corresponding to the bias voltage.

[0100] In one embodiment, the apparatus further comprises:

[0101] The third calculation unit 406 is configured to calculate the remaining usage time of the optical module according to the probability of failure of the optical module, the normal usage time of the optical module, and the usage time of the optical module.

[0102] In one embodiment, the calculation formula for the remaining usage time of the optical module is:

[0103] T re =(T1-T2)*(1-λ OM )

[0104] Among them, T re is the remaining usage time of the optical module, T1 is the normal usage time of the optical module, T2 is the usage time of the optical module, and λ OM is the probability of an optical module failure.

[0105] In one embodiment, the prediction unit 405 is further configured to predict the health status of the optical module according to the probability of failure of the optical module and the remaining usage time.

[0106] like Figure 5 As shown, the embodiment of the present application provides a computer device, including a processor 51, a communication interface 52, a memory 53 and a communication bus 54, wherein the processor 51, the communication interface 52, and the memory 53 communicate with each other through the communication bus 54.

[0107] Memory 53, for storing computer programs;

[0108] In one embodiment of the present application, the processor 51 is configured to implement a control method for predicting the health status of an optical module provided by any one of the aforementioned method embodiments when executing a program stored in the memory 53 .

[0109] Those skilled in the art will appreciate that all or part of the steps in the method of the above-described embodiment can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the steps in the method of the above-described embodiment.

[0110] Therefore, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the optical module health status prediction method provided in any of the aforementioned method embodiments are implemented.

[0111] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a magnetic disk, or an optical disk, etc. Any physical storage medium capable of storing program code can be non-volatile or volatile.

[0112] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and other division methods may be used in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not implemented.

[0114] The steps in the method of the embodiment of the present application can be adjusted in order, combined, and deleted according to actual needs. The units in the device of the embodiment of the present application can be combined, divided, and deleted according to actual needs. In addition, the functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into a single unit.

[0115] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0116] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0117] Obviously, those skilled in the art may make various modifications and variations to this application without departing from the spirit and scope of this application. Thus, as long as these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

[0118] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for predicting the health status of an optical module, characterized in that: The method comprises: Collecting historical operation data of the optical module, the historical operation data including historical data of multiple indicators of the optical module, each of the multiple indicators corresponding to a fault type of the optical module; Preprocessing the historical operation data to obtain target historical operation data; Obtaining a normal service life of the optical module, where the normal service life is a nominal service life value provided by the manufacturer of the optical module; Obtaining the usage time of the optical module, where the usage time is the cumulative time of the optical module since the first operation to the present; Counting the number of abnormal data in the historical data of each indicator in the target historical operation data; Calculate the probability of occurrence of the optical module fault type corresponding to the indicator according to the normal use time, the used time, the total number of historical data of each indicator in the target historical operation data, and the number of abnormal data; Calculating the probability of the optical module failure according to the probability of occurrence of the optical module failure type corresponding to each indicator in the multiple indicators; Calculating the remaining usage time of the optical module according to the probability of failure of the optical module, the normal usage time of the optical module, and the usage time of the optical module; Predicting a health status of the optical module based on a probability of failure of the optical module and the remaining usage time; The calculation formula for the remaining usage time of the optical module is: T re =(T1-T2)*(1-λ OM ) Among them, T re is the remaining usage time of the optical module, T1 is the normal usage time of the optical module, T2 is the usage time of the optical module, and λ OM is the probability of an optical module failure.

2. The method according to claim 1, characterized in that The multiple indicators include: optical power, temperature, bias current and bias voltage.

3. The method according to claim 2, characterized in that The calculation formula for the probability of the optical module failing is: l OM =40%*l OP +10%*min T +40%*min I +10%*min V Among them, λ OM is the probability of optical module failure, λ OP is the probability of occurrence of optical module failure type corresponding to optical power, λ T is the probability of occurrence of optical module failure type corresponding to temperature, λ I is the probability of occurrence of optical module failure type corresponding to bias current, λ V is the probability of occurrence of the optical module fault type corresponding to the bias voltage.

4. An optical module health status prediction device, characterized in that: The device comprises: A collection module, configured to collect historical operation data of the optical module, wherein the historical operation data includes historical data of multiple indicators of the optical module, each of the multiple indicators corresponding to a fault type of the optical module; A preprocessing module, configured to preprocess the historical operation data to obtain target historical operation data; A first calculation unit is configured to obtain a normal usage time of the optical module, where the normal usage time is the nominal life value provided by the manufacturer of the optical module; obtain an already used time of the optical module, where the already used time is the cumulative time of the optical module from the first operation to the present; count the number of abnormal data in the historical data of each indicator in the target historical operation data; and calculate an occurrence probability of the optical module failure type corresponding to the indicator based on the normal usage time, the already used time, the total number of historical data of each indicator in the target historical operation data, and the number of abnormal data; a second calculating unit, configured to calculate a probability of failure of the optical module according to a probability of occurrence of an optical module failure type corresponding to each indicator in the plurality of indicators; a third calculating unit, configured to calculate a remaining usage time of the optical module according to a probability of failure of the optical module, a normal usage time of the optical module, and a usage time of the optical module; A prediction unit is configured to predict a health state of the optical module based on a probability of failure of the optical module and the remaining service life; the remaining service life of the optical module is calculated as follows: T re =(T1-T2)*(1-λ OM ) Among them, T re is the remaining usage time of the optical module, T1 is the normal usage time of the optical module, T2 is the usage time of the optical module, and λ OM is the probability of an optical module failure.

5. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 3 when executing the computer program.

6. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 3 can be implemented.

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