Laser service life prediction method and device and electronic equipment

Abstract

The invention discloses a laser service life prediction method, a laser service life prediction device and electronic equipment. The life prediction method comprises the following steps: controlling a to-be-tested object to output laser under a test condition to obtain a test failure time length of the to-be-tested object, a life acceleration model with determined parameters and a corresponding first failure life length; controlling the to-be-tested object to output laser under a normal working condition to obtain a second failure life length of the to-be-tested object; and finally, according to the test failure time length, the first failure life time length and the second failure life time length, determining a predicted failure time length of the to-be-tested object. According to the method, the failure data is obtained by simulating the continuous light emitting working state of the to-be-tested object in the actual application, the aging behavior of the to-be-tested object in the actual application can be truly reflected, and the accuracy is high.

Description

Technical Field

[0001] This invention relates to the field of laser technology, and in particular to a laser lifetime prediction method, apparatus, and electronic device. Background Technology

[0002] A laser is a device that generates laser light through stimulated emission. It is widely used in industry, medicine, communications, and other fields. In its application, reliability and lifespan are key factors determining the performance, maintenance costs, and user satisfaction of related equipment. Therefore, accurately predicting the working lifespan of lasers is of paramount importance in the research, development, production, and application stages.

[0003] Current laser lifetime prediction technologies require operating the laser continuously under normal conditions until failure to obtain lifetime data. This process is time-consuming; for high-reliability lasers, the testing cycle can typically last for months or even years, resulting in extremely low efficiency. While some lifetime testing methods shorten testing time by increasing stress—for example, testing for 1000 hours at 85℃ / 85%RH is equivalent to several years of use—they fail to effectively integrate test data from different temperature points and establish an accurate lifetime model based on this data. This often necessitates repeated testing to compensate for errors (as inconsistencies in lifetimes obtained under multiple temperature conditions are inevitable), leading to overall low prediction efficiency. Furthermore, due to the inability to obtain accurate lifetime data, manufacturers often have to conservatively set a fixed warranty period, and this uncertainty severely hinders brand image enhancement.

[0004] Therefore, there is a need to design a method that can quickly and accurately predict the lifespan of laser products. Summary of the Invention

[0005] This invention provides a laser lifetime prediction method, apparatus, and electronic device to solve the problems of low efficiency and inaccuracy in current laser lifetime testing.

[0006] As one aspect of this application, a laser lifetime prediction method is also proposed, comprising:

[0007] The test object is controlled to output test output power at different first temperature points in the test conditions, and the test failure time length from the test output power to the failure power when the test object is working at each temperature point is determined.

[0008] Based on each of the first temperature points and the test failure time length corresponding to the first temperature point, the parameters of the life acceleration model are analyzed and determined.

[0009] Based on any of the first temperature points and the lifetime acceleration model with known parameters, determine the corresponding first failure lifetime length;

[0010] The test object is controlled to operate at a second temperature point under normal operating conditions, and the second failure lifetime length is determined based on the second temperature point and the lifetime acceleration model.

[0011] The predicted failure time of the test object is determined based on the test failure time length, the first failure lifetime time length, and the second failure lifetime time length.

[0012] As a preferred embodiment, determining the test failure time length from the test output power drop to the failure power when the test object operates at each of the first temperature points includes:

[0013] The following formula is used to fit the test output power, the failure power, and the corresponding time from the test output power to the failure power:

[0014]

[0015] Determine the test failure time length of the object under test under the test conditions; where P(t) is the test output power, P(0) is the failure power, and t is the time from the test output power to the failure power. f ′ represents the test failure time length, and β is an exponential parameter.

[0016] As a preferred embodiment, the parameters of the accelerated life model are analyzed and determined based on each of the first temperature points and the test failure time length corresponding to the first temperature point, including:

[0017] A linear regression analysis was performed on the reciprocal values ​​of each of the first temperature points and the logarithm of the test failure time length corresponding to the first temperature point, resulting in the following fitted linear equation:

[0018]

[0019] Where T is the first temperature point, L is the test failure time length of the laser at the current first temperature point, a is the slope of the fitted straight line equation, and b is the intercept of the fitted straight line equation.

[0020] Based on the fitted values ​​a and b, the activation energy E of the lifetime acceleration model is calculated using the following formula. a And pre-index factor A:

[0021] E a = -a×k, where k is the Boltzmann constant;

[0022] A = e b .

[0023] As a preferred embodiment, determining the corresponding first failure lifetime length based on the lifetime acceleration model with known parameters at any of the first temperature points includes:

[0024] The first failure lifetime length corresponding to the first temperature point is determined based on the following formula:

[0025]

[0026] Among them, L high T is the length of the first failure lifetime; high E is the first temperature point; a is the activation energy; A is the pre-exponential factor; and k is the Boltzmann constant.

[0027] As a preferred embodiment, determining the second failure lifetime length based on the second temperature point and the lifetime acceleration model includes:

[0028] The second failure lifetime length corresponding to the pre-second temperature point is determined based on the following formula:

[0029]

[0030] Among them, L use T is the second failure lifetime length; use This is the second temperature point.

[0031] As a preferred embodiment, determining the predicted failure time of the laser based on the test failure time length, the first failure lifetime time length, and the second failure lifetime time length includes:

[0032] The predicted failure time of the laser is determined based on the following formula:

[0033]

[0034] Among them, t f t is the predicted failure time length; f ′ represents the test failure time length; L high L represents the first failure lifetime length; use This refers to the second failure lifetime length.

[0035] As a preferred embodiment, the object to be tested includes at least a laser and the optoelectronic components within the laser.

[0036] As a preferred embodiment, when the object to be tested is an optoelectronic component in the laser, the laser lifetime prediction method further includes:

[0037] The parallel pump reliability of the parallel pump subsystem and the device reliability of the series devices in the laser are determined based on the predicted failure time length, and the overall reliability of the laser is determined based on the parallel pump reliability and the device reliability.

[0038] As another aspect of this application, a laser lifetime prediction device is also proposed, comprising a control module, a model parameter analysis module, a first failure lifetime determination module, a second failure lifetime determination module, and a normal failure lifetime determination module, wherein...

[0039] The control module is used to control the test object to output the test output power at different first temperature points in the test conditions, and to record the test failure time length from the test output power to the failure power when the test object works at each first temperature point.

[0040] The model parameter analysis module is used to analyze and determine the parameters of the life acceleration model based on each first temperature point and the test failure time length corresponding to the first temperature point.

[0041] The first failure lifetime determination module is used to determine the corresponding first failure lifetime length based on any first temperature point and the lifetime acceleration model with known parameters;

[0042] The control module is also configured to operate at a second temperature point under normal working conditions based on the test object, and the second failure lifetime determination module is configured to determine the second failure lifetime length based on the second temperature point and the lifetime acceleration model.

[0043] The normal failure life determination module is used to determine the predicted failure life of the object under test based on the test failure time length, the first failure life length, and the second failure life length.

[0044] As another aspect of this application, an electronic device is also provided, the electronic device comprising:

[0045] At least one processor; and,

[0046] A memory communicatively connected to the at least one processor; wherein,

[0047] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the laser lifetime prediction method described above.

[0048] The technical solution of this invention involves controlling the test object to output power at different first temperature points under test conditions, determining the test failure time length from the test output power to the failure power when the test object operates at each temperature point, and then analyzing and determining the parameters of the lifetime acceleration model based on the first temperature point and the corresponding test failure time length. Further, based on any first temperature point and the lifetime acceleration model with known parameters, the corresponding first failure lifetime length is determined. Next, the test object is controlled to operate at a second temperature point under normal operating conditions, and a second failure lifetime length is determined based on the second operating temperature point and the lifetime acceleration model. Finally, the predicted failure time length of the test object is determined based on the test failure time length, the first failure lifetime length, and the second failure lifetime length.

[0049] The laser lifetime prediction method of this application rapidly acquires the failure time data of the test object at a specific power at multiple test temperature points. On the one hand, it can accurately calibrate the parameters of the lifetime acceleration model to ensure the accuracy of the prediction and provide a reliable basis for enterprises to determine a reasonable warranty period for lasers. On the other hand, it eliminates the need for lengthy full-cycle testing and repeated testing to compensate for errors, significantly shortening the prediction cycle and improving prediction efficiency.

[0050] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used 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 those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of a laser lifetime prediction method provided in an embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of a laser lifetime prediction device according to an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the structure of an electronic device that implements the laser lifetime prediction method provided in one embodiment of the present invention. Detailed Implementation

[0055] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0056] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0057] Figure 1 This is a flowchart of a laser lifetime prediction method provided by the present invention. This embodiment is applicable to situations where the normal lifetime of a laser is inferred using mathematical models and accelerated aging tests. The laser lifetime prediction method can be executed by a laser lifetime prediction device, which can be implemented in hardware and / or software. This laser lifetime prediction device can be configured in various electronic devices used for determining laser lifetime. For example... Figure 1 As shown, the laser lifetime prediction method includes:

[0058] S110. Control the test object to output at the test output power at different first temperature points in the test conditions, and determine the test failure time length from the test output power to the failure power when the laser is working at each temperature point.

[0059] The test conditions refer to the accelerated aging environment applied to the test object. This environment intensifies the aging process of the laser by increasing environmental stress, thereby facilitating the acquisition of failure evidence in a short time. The test output power is the rated power of the corresponding laser.

[0060] In some embodiments, the test conditions can be selected as high temperature or high stress, that is, the laser device aging is accelerated by increasing the temperature or current stress under the test conditions.

[0061] The prediction method of this application involves controlling the test object to operate under test conditions (i.e., an accelerated aging environment), which accelerates the aging of the test object by applying stress (high temperature) higher than normal operating conditions. The plurality of first temperature points are all set values ​​significantly higher than the actual operating temperature of the test object, thereby significantly shortening the failure time. The specific number of first temperature points can be flexibly set according to the model fitting requirements, and this embodiment does not impose any special limitations on this.

[0062] In the embodiments of this application, the object to be tested includes at least a laser and optoelectronic components within the laser. Optoelectronic devices in a laser typically include pump diodes, optical fibers, and beam combiners, and the reliability of these devices directly affects the overall performance of the laser.

[0063] When performing lifetime prediction on a test object, its failure criteria must be clearly defined. In this embodiment, when the output power P(0) of the test object decays to a certain preset proportion α of the initial test output power, it is considered to have reached a failure state (failure power P). fail =αP(0)) where the proportional threshold α can be flexibly set according to the reliability requirements of the actual application scenario (e.g., 1%-50%), and this embodiment does not impose any restrictions.

[0064] Furthermore, power normalization is performed based on the initial test output power at each first temperature point: the real-time output power P(t) is converted into normalized power by dividing P(0). This can eliminate the influence of initial power differences under different test conditions on attenuation analysis. Then, the normalized power... Curve fitting (e.g., exponential decay fitting) is performed on the time series data of the descent process to obtain the normalized power. The time required for the temperature to drop to the set threshold is the test failure time length at that temperature point.

[0065] In one embodiment, based on the above principles, the following formula can be used to obtain the fitting curve and calculate the test failure time of the object under test conditions, specifically:

[0066]

[0067] Where P(t) is the test output power; P(0) is the failure power; t is the time data from the test output power to the failure power; t f ′ represents the test failure time length; β is an exponential parameter that describes the test output power decay rate and curve shape.

[0068] S120. Based on each first temperature point and the test failure time length corresponding to the first temperature point, analyze and determine the parameters of the life acceleration model.

[0069] It is understood that this accelerated lifespan model includes, but is not limited to, existing physical models describing the relationship between aging rate and temperature. In the embodiments of this application, the accelerated lifespan model preferably employs the Arrhenius model (whose core principle is based on the Arrhenius equation), a model commonly used to describe the effect of temperature on product lifespan. Its core formula is typically expressed as:

[0070]

[0071] Where L(T) represents the laser's lifetime (failure time) at temperature T; A is the pre-exponential factor, which is related to the laser's characteristics and is a constant; E α The activation energy is a key parameter for measuring the failure of a laser under temperature stress, representing the minimum energy threshold required for the laser to fail; k is the Boltzmann constant, and T is the absolute temperature.

[0072] In the embodiments of this application, the activation energy E in the model is obtained by data fitting through multiple first temperature points and their corresponding test failure times. α And a pre-index factor A, so as to extrapolate lifetime data under high temperature conditions to normal temperatures.

[0073] Specifically, the core formulas in the Arrhenius model are first logarithmically transformed, converting the nonlinear relationships into linear ones to simplify the parameter calculation process. The formulas... Taking the natural logarithm of both sides, we get:

[0074]

[0075] Among them, E a is the activation energy; A is the pre-exponential factor, which can be obtained by fitting experimental data; k is the Boltzmann constant.

[0076] Let y = ln(t′) f ), b = ln(A), The above formula is then transformed into a linear equation y = mx + b. At this point, each first temperature point and its corresponding test failure time can be converted into a set of data points (x...). i ,y i By performing a linear fit on multiple sets of data points using the least squares method, the slope *m* and intercept *b* in the linear equation can be solved. Based on the fitted *m* and *b*, the activation energy *E* in the Arrhenius model can be further deduced. a And the pre-index factor A, where the activation energy E a =mk, pre-exponential factor A=e bThis allows us to determine the parameters of the accelerated lifespan model.

[0077] S130. Based on any first temperature point and the lifetime acceleration model with known parameters, determine the corresponding first failure lifetime length.

[0078] In this embodiment, after the parameters of the accelerated life model are determined and verified, any first temperature point that has participated in parameter fitting is selected and substituted into the accelerated life model with known parameters.

[0079] Specifically, the length of the first failure lifetime corresponding to the first temperature point is determined based on the following formula:

[0080]

[0081] Among them, L high T represents the first failure lifespan. high Let A and E be the first temperature point chosen arbitrarily. a It has been determined through step S120 (A = e) b E a =mk); k is the Boltzmann constant. This first failure lifetime length is a theoretical value calculated based on the model, and corresponds to the test failure time length obtained through actual testing in step S110.

[0082] It is understandable that the normal operating temperature represents the expected actual operating temperature of the laser. This temperature is usually much lower than the test temperature, meaning that the first temperature point can be set much higher than the second temperature point.

[0083] S140. Control the test object to operate at the second temperature point under normal operating conditions, and determine the second failure lifetime length based on the second temperature point and the lifetime acceleration model.

[0084] Specifically, the second failure lifetime length corresponding to the second temperature point is determined based on the following formula:

[0085]

[0086] Among them, L use The second failure life duration; T use This is the second temperature point; A and E a It has been determined through step S120 (A = e) b E a =mk); k is the Boltzmann constant.

[0087] In this embodiment, by extrapolating the lifetime parameters obtained under test conditions to normal operating conditions using the Arrhenius model, the test failure time length determined under test conditions can be converted into the predicted failure time length under normal operating conditions. The simulated normal operating conditions represent the actual working scenario of the test object in a real-world application, and its output power during operation should be the rated output power of the corresponding laser or lower than the rated output power.

[0088] S150. Determine the predicted failure time of the test object based on the test failure time length, the first failure lifetime time length, and the second failure lifetime time length.

[0089] In this embodiment, due to the test failure time length t f If the lifetime corresponding to ′ has the same distribution characteristics as the failure lifetime L of the object under test, then:

[0090]

[0091] Furthermore, the predicted failure time of the object under test is determined based on the following formula:

[0092]

[0093] Among them, t f To predict the duration of failure; t′ f To test the failure time length; L high L represents the first failure lifespan. use This refers to the second failure lifespan.

[0094] It is understood that when the object under test is a complete laser device, by testing the target laser at multiple accelerated temperature points, combining the lifetime acceleration model (Arrhenius model), and introducing test conditions, the lifetime of the laser under normal operating conditions can be predicted quickly and accurately. This invention solves the problem of not being able to accurately obtain the precise lifespan of lasers, thus hindering timely laser warranty coverage. It achieves accurate prediction of the laser's usage time under normal operating conditions, providing an accurate basis for enterprises to determine warranty periods.

[0095] In one embodiment, when the component under test is an optoelectronic component in the laser, the laser lifetime prediction method further includes determining the parallel pump reliability of the parallel pump subsystem and the device reliability of the series devices based on the predicted failure time length of each optoelectronic component, and determining the overall reliability of the laser based on the parallel pump reliability and device reliability.

[0096] It should be noted that reliability refers to the ability of each optoelectronic component or laser to perform its intended function under specified conditions and within a specified time. It can be derived through a reliability calculation model. For example, for a laser system containing multiple parallel pump modules and multiple series devices, the overall reliability calculation must consider the reliability of each component. For instance, the reliability of the parallel pump subsystem and the reliability of the series devices can be calculated separately, and then combined to obtain the overall system reliability.

[0097] In practical laser systems, a parallel pump subsystem refers to a system composed of multiple pump modules with identical or different structures and performance connected in parallel, used to provide energy to the laser's gain medium. When one or a few pump modules fail due to aging or other reasons, the remaining normally functioning modules must meet the system's basic pump energy requirements to ensure that the laser does not immediately stop working. Series components, on the other hand, refer to critical devices connected sequentially in the laser's optical or electrical path, such as gain media, optical lenses, and modulators. Failure or aging of any one of these series components can directly cause the entire laser system to fail. Therefore, the overall system reliability can be calculated by separately determining the reliability of the pump subsystem and the series components.

[0098] Specifically, regarding the reliability of parallel pump subsystems,

[0099] If n pump modules are connected in parallel, the reliability of a single pump module is:

[0100]

[0101] Where t is the observation time, L pump Let e ​​be the mean time between failures (MTBF) of a single pump, and e be a natural constant.

[0102] The reliability of at least K pump modules operating normally (i.e., the parallel pump reliability of the parallel pump subsystem) is:

[0103]

[0104] For the reliability of lasers connected in series with other devices:

[0105] Suppose there are m other laser devices connected in series, such as mode strippers, beam combiners, etc., and the reliability of each laser device is... (Or calculated based on the parameters extrapolated from the determined distribution and the Arrhenius model), then

[0106] Regarding the overall reliability of the laser:

[0107] The laser system is a parallel pump subsystem connected in series with other devices, therefore:

[0108] R system (t)=R pumpsys (t)+R other (t)

[0109] In this application, the previously obtained predicted failure time length t is substituted... f This can be verified at t=t f Whether the overall reliability of the laser meets the set failure criteria.

[0110] It is understandable that when the object under test is the entire machine, the predicted lifetime obtained by combining accelerated temperature point testing with the Arrhenius model can be mutually verified with the overall machine reliability calculated when the optoelectronic components are the object under test.

[0111] The technical solution of this application will be further described using the following specific embodiments as examples.

[0112] Components type quantity Work mode pump diode pump 2 Parallel connection (at least one is normal) optical fiber Main passage 1 Series Bundle Optical components 1 Series

[0113] Table 1: Target Laser Components and Operating Mode Parameters

[0114] Table 1 shows the components and operating mode parameters of the target laser. The target laser includes two pump diodes, an optical fiber, and a beam combiner. The two pump diodes are connected in parallel to form a parallel pump subsystem. This parallel pump subsystem, the optical fiber, and the beam combiner are connected in series to form the laser transmission optical path. At least one pump diode in this parallel pump subsystem must function properly to ensure that the output power of the pump light meets the excitation requirements of the gain medium within the optical fiber. If both pump diodes fail simultaneously, the pump energy will be interrupted, and the laser output will immediately cease. However, when one pump diode fails, the other normally functioning pump diode can continue to provide some pump energy, which may slightly reduce the laser output power, but can still maintain normal laser operation for a certain period of time.

[0115] The laser system is now considered to have failed when its output power drops to 80% of its initial power P0 and its overall reliability is between 10% and 20%.

[0116] The technical solution of this application will now be explained using the lifetime prediction steps of a pump diode as an example.

[0117] S110. Control the pump diode to output at the test output power at different first temperature points in the test conditions, and determine the test failure time length from the test output power to the failure power when the laser is working at each temperature point, as shown in the table below:

[0118] Temperature (°C) Temperature (K) Lifespan L (hours) 70 343 1000 85 358 300

[0119] Table 2: Test Failure Time Data of Pump Diodes at Different First Temperature Points

[0120] S120. Based on each first temperature point and the corresponding test failure time length at each first temperature point, analyze and determine the parameters of the accelerated life model. Given:

[0121]

[0122]

[0123] k = 8.617 * 10 -5 eV / K

[0124] And E a =-a×k, A=e b Where k is the Boltzmann constant, the pre-exponential factor A can be obtained as A = 1.73 * 10^- ... 15 E a =0.843.

[0125] Therefore, the lifetime acceleration model is as follows:

[0126]

[0127] S130. Based on the lifetime acceleration model of any of the first temperature points and known parameters, determine the corresponding first failure lifetime length:

[0128]

[0129] S140. Control the pump diode to operate at the second temperature point under normal operating conditions, and determine the second failure lifetime length based on the second temperature point and the lifetime acceleration model:

[0130]

[0131] S150. Determine the predicted failure time of the pump diode based on the test failure time length, the first failure lifetime time length, and the second failure lifetime time length:

[0132]

[0133] Ultimately, the pump diode lifetime at 30℃ (303K) is approximately t. f = 40,000 hours. The above steps only yield the lifetime of a single pump diode. Similarly, the lifetime of another pump diode and other optoelectronic devices can be measured, which will not be elaborated here.

[0134] For example, if the lifetime of another pump diode is also measured to be 40,000 hours, the fiber lifetime is 60,000 hours, and the combiner lifetime is 50,000 hours, the reliability of a single pump diode (calculated according to an exponential distribution) is: If the pumping system consists of two pump diodes connected in parallel, then the reliability of the parallel system is: R pumppsys (t)=1-[1-R pump (t)] 2 =0.601; while the reliability of optical fiber: R fiber =0.5134, Reliability of the combiner: R combiner =0.4493, then the reliability of the two connected in series structure is: R others =R fiber *R combiner =0.2305, therefore the overall reliability of the laser can be obtained as: R system =R pumpsys *R others =0.1386. That is, at t=40000 hours, the overall reliability is 13.86%, which is close to the common failure rate of 10% to 20%, so the life prediction is reasonable.

[0135] The technical solution of this invention obtains the lifetime parameters (A, E) for each period from the Arrhenius model. a and the corresponding L use ), from the Power Law model, t is obtained f Based on the defined failure criterion (output power drops to αP(0)) and the overall reliability analysis of the laser, the laser failure time t under normal operating conditions is obtained. f Using mathematical models and accelerated aging tests to infer the normal lifespan of a laser as its expected lifespan is beneficial for accurately predicting the duration of laser use under normal operating conditions. Similarly, it helps companies maximize the warranty period for their lasers.

[0136] Figure 2 This is a schematic diagram of a laser lifetime prediction device 200 provided in an embodiment of the present invention. Figure 2 As shown, the laser lifetime prediction device includes a control module 210, a model parameter analysis module 220, a first failure lifetime determination module 230, a second failure lifetime determination module 240, and a normal failure lifetime determination module 250, wherein...

[0137] The control module 210 is used to control the test object to output the test output power at different first temperature points in the test conditions, and to record the test failure time length from the test output power to the failure power when the test object works at each first temperature point.

[0138] The model parameter analysis module 220 is used to analyze and determine the parameters of the life acceleration model based on each first temperature point and the test failure time length corresponding to the first temperature point.

[0139] The first lifetime determination module 230 is used to determine the corresponding first failure lifetime length based on any first temperature point and a lifetime acceleration model with known parameters.

[0140] The control module 210 is also used to determine the second failure lifetime length based on the second temperature point of the test object under normal operating conditions, and the second failure lifetime determination module is used to determine the second failure lifetime length based on the second temperature point and the lifetime acceleration model.

[0141] The normal failure life determination module 250 is used to determine the predicted failure life of the object under test based on the test failure time length, the first failure life length, and the second failure life length.

[0142] Optionally, the laser lifetime prediction device 200 also includes:

[0143] The overall reliability determination module (not shown in the figure) is used to determine the parallel pump reliability of the parallel pump subsystem and the device reliability of the series devices based on the predicted failure time length, and to determine the overall reliability of the laser based on the parallel pump reliability and device reliability.

[0144] It should be emphasized that the above division of the various modules in the laser lifetime prediction device 200 is only a logical breakdown based on the functional level, and does not refer to physically independent hardware structures.

[0145] For example, although the first failure lifetime determination module 230 and the second failure lifetime determination module 240 correspond to the operation of determining the failure lifetime length based on the first temperature point and the second temperature point, respectively, this does not mean that they must be implemented by two different physical components. In fact, the core calculations of both revolve around the lifetime acceleration model, and the only difference lies in the input parameters (the first temperature point or the second temperature point). Therefore, they can be integrated into the same module. By calling the same algorithm and receiving different input parameters, the determination of the first and second failure lifetime lengths can be completed respectively. Similarly, the control module 210, the model parameter analysis module 220, the normal failure lifetime determination module 250, and the overall system reliability determination module may also be merged at the physical level according to the actual hardware design requirements. The functions corresponding to each module can be implemented through the same processor or integrated circuit chip, and can be called by dividing different functional modules through software programs.

[0146] It is understood that each module in the laser lifetime prediction device of this invention corresponds one-to-one with each step in the laser lifetime prediction method. They belong to the same inventive concept, can achieve the same technical objective, solve the same technical problem, and achieve the same technical effect. They complement each other in their technical solutions, forming a unified inventive concept. This laser lifetime prediction device can execute the laser lifetime prediction method provided in any embodiment of this invention, and possesses the corresponding functional modules and beneficial effects for executing the laser lifetime prediction method.

[0147] Please refer to again Figure 3 , Figure 3 A schematic diagram of an electronic device 410 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0148] like Figure 3 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM 412) or a random access memory (RAM 413), communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 can also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An I / O (input / output) interface 415 is also connected to the bus 414.

[0149] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0150] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as laser lifetime prediction methods.

[0151] In some embodiments, the laser lifetime prediction method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the laser lifetime prediction method described above may be performed. Alternatively, in other embodiments, processor 411 may be configured to perform the laser lifetime prediction method by any other suitable means (e.g., by means of firmware).

[0152] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0154] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0155] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0156] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0157] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0158] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0159] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for predicting laser lifetime, characterized in that, include: The test object is controlled to output test output power at different first temperature points in the test conditions, and the test failure time length from the test output power to the failure power when the test object is working at each temperature point is determined. Based on each of the first temperature points and the test failure time length corresponding to the first temperature point, the parameters of the life acceleration model are analyzed and determined. Based on any of the first temperature points and the lifetime acceleration model with known parameters, determine the corresponding first failure lifetime length; The test object is controlled to operate at a second temperature point under normal operating conditions, and the second failure lifetime length is determined based on the second temperature point and the lifetime acceleration model. The predicted failure time of the test object is determined based on the test failure time length, the first failure lifetime time length, and the second failure lifetime time length.

2. The laser lifetime prediction method according to claim 1, characterized in that, Determining the test failure time length from the test output power drop to the failure power when the test object operates at each of the first temperature points includes: The following formula is used to fit the test output power, the failure power, and the corresponding time from the test output power to the failure power: Determine the test failure time length of the object under test under the test conditions; where P(t) is the test output power, P(0) is the failure power, and t is the time from the test output power to the failure power. f ′ β represents the test failure time length, and β is an exponential parameter.

3. The laser lifetime prediction method according to claim 1, characterized in that, Based on each of the first temperature points and the test failure time length corresponding to the first temperature point, the parameters of the accelerated life model are analyzed and determined, including: A linear regression analysis was performed on the reciprocal values ​​of each of the first temperature points and the logarithm of the test failure time length corresponding to the first temperature point, resulting in the following fitted linear equation: Where T is the first temperature point, L is the test failure time length of the laser at the current first temperature point, a is the slope of the fitted straight line equation, and b is the intercept of the fitted straight line equation. Based on the fitted values ​​a and b, the activation energy E of the lifetime acceleration model is calculated using the following formula. a And pre-index factor A: E a = -a×k, where k is the Boltzmann constant; A=e b 。 4. The laser lifetime prediction method according to claim 1, characterized in that, Determining the corresponding first failure lifetime length based on the lifetime acceleration model using any of the first temperature points and known parameters includes: The first failure lifetime length corresponding to the first temperature point is determined based on the following formula: Among them, L high T is the length of the first failure lifetime; high E is the first temperature point; a is the activation energy; A is the pre-exponential factor, and k is the Boltzmann constant.

5. The laser lifetime prediction method according to claim 1, characterized in that, The second failure lifetime length is determined based on the second temperature point and the lifetime acceleration model, including: The second failure lifetime length corresponding to the pre-second temperature point is determined based on the following formula: Among them, L use T is the second failure lifetime length; use This is the second temperature point.

6. The laser lifetime prediction method according to claim 1, characterized in that, Determining the predicted failure time of the laser based on the test failure time length, the first failure lifetime time length, and the second failure lifetime time length includes: The predicted failure time of the laser is determined based on the following formula: Among them, t f t is the predicted failure time length; f ′ L is the test failure time length; high L represents the first failure lifetime length; use This refers to the second failure lifetime length.

7. The lifetime prediction method according to claim 1, characterized in that, The object to be tested includes at least a laser and the optoelectronic components within the laser.

8. The laser lifetime prediction method according to claim 7, characterized in that, When the object to be tested is an optoelectronic component in the laser, the laser lifetime prediction method further includes: The parallel pump reliability of the parallel pump subsystem and the device reliability of the series devices in the laser are determined based on the predicted failure time length, and the overall reliability of the laser is determined based on the parallel pump reliability and the device reliability.

9. A laser lifetime prediction device, characterized in that, It includes a control module, a model parameter analysis module, a first failure lifetime determination module, a second failure lifetime determination module, and a normal failure lifetime determination module, among which, The control module is used to control the test object to output the test output power at different first temperature points in the test conditions, and to record the test failure time length from the test output power to the failure power when the test object works at each first temperature point. The model parameter analysis module is used to analyze and determine the parameters of the life acceleration model based on each first temperature point and the test failure time length corresponding to the first temperature point. The first failure lifetime determination module is used to determine the corresponding first failure lifetime length based on any first temperature point and the lifetime acceleration model with known parameters; The control module is also configured to operate at a second temperature point under normal working conditions based on the test object, and the second failure lifetime determination module is configured to determine the second failure lifetime length based on the second temperature point and the lifetime acceleration model. The normal failure life determination module is used to determine the predicted failure life of the object under test based on the test failure time length, the first failure life length, and the second failure life length.

10. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the laser lifetime prediction method according to any one of claims 1-8.

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