Abnormality determination method of optical modem, computer program product and optical modem detection system

Abstract

The invention provides an abnormity determination method of an optical modem, a computer program product and an optical modem detection system. The method comprises the following steps: acquiring related data of an optical modem; an intelligent analysis model is constructed, the intelligent analysis model is obtained through training of multiple sets of training data, each set of training data in the multiple sets of training data comprises historical related data obtained in a historical time period and historical analysis results corresponding to the historical related data, and the historical analysis results correspond to the historical related data; the historical analysis result is used for representing whether the optical modem is abnormal in a historical time period; inputting the related data into the intelligent analysis model to obtain an analysis result corresponding to the related data; and when the analysis result represents that the optical modem is abnormal, generating early warning information, and sending the early warning information to the target terminal. According to the scheme, the problem of high cost of a manual optical modem checking mode in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of fixed terminal detection technology, and in particular, to an optical modem abnormality determination method, device, computer program product and optical modem detection system. Background Art

[0002] Fixed-line terminals refer to devices connected to fixed networks, such as broadband Internet, telephone networks, etc., and are usually used in home or corporate environments. Fixed-line terminals, commonly known as optical modems, are the digital base of smart homes. Their importance is becoming increasingly prominent. However, for existing technologies, the annual terminal costs continue to rise. In the specific manual inspection and maintenance process, the conventional fixed-line terminal quality control inspection method is complicated and cumbersome, and basic testing requires an investment of testing costs that exceed estimates for a large number of fixed-line terminals. Summary of the invention

[0003] The main purpose of the present application is to provide a method, device, computer program product and optical modem detection system for determining an abnormality of an optical modem, so as to at least solve the problem of high cost of manual inspection of optical modems in the prior art.

[0004] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for determining an abnormality of an optical modem is provided, comprising: obtaining relevant data of the optical modem, wherein the relevant data include one or more of an activation state, an online state, a current light receiving value, a current light emitting value, a chip temperature, a chip current and a chip voltage; constructing an intelligent analysis model, wherein the intelligent analysis model is trained using multiple sets of training data, each set of the multiple sets of training data includes historical relevant data acquired within a historical time period, and historical analysis results corresponding to the historical relevant data, wherein the historical analysis results are used to characterize whether the optical modem is abnormal within the historical time period; inputting the relevant data into the intelligent analysis model to obtain an analysis result corresponding to the relevant data; when the analysis result characterizes that the optical modem is abnormal, generating early warning information, and sending the early warning information to a target terminal.

[0005] Optionally, before obtaining relevant data of the optical modem, the method further includes: upon receiving a detection request, obtaining a unique code of the optical modem, wherein the optical modem is electrically connected to an optical line terminal, the optical line terminal includes a plurality of service boards, the service boards include a plurality of PON interfaces, the optical modem and the unique code correspond one-to-one, and the unique code is used to locate the optical modem; upon obtaining the unique code, obtaining device information according to the unique code, wherein the device information is location information of the optical line terminal, location information of the service board and the PON interface used.

[0006] Optionally, obtaining the unique code of the optical modem includes: generating the unique code according to a first formula, wherein the first formula is: Code = (N OLT ×S max ×P max )+(S×P max )+P+ID ONU , Code represents the unique code, N OLT Indicates the code number of the optical modem in the optical line terminal, S max Indicates the maximum number of service boards, P max Indicates the maximum number of the PON interface, S indicates the position number of the service board used by the optical modem, P indicates the port number of the PON interface used by the optical modem, ID ONU The unique identifier of the optical modem.

[0007] Optionally, acquiring device information according to the unique code includes: calculating a code number of the optical modem in the optical line terminal according to a second formula, wherein the second formula is:

[0008]

[0009] N OLT represents the code number of the optical modem in the optical line terminal, Code represents the unique code of the optical modem, S max Indicates the maximum number of service boards, P max Indicates the maximum number of PON interfaces, ID ONU The unique identifier of the optical modem; according to the third formula, calculate the remaining code, wherein the remaining code is the partial code affected by the code number of the optical modem in the optical line terminal, and the third formula is:

[0010] R=Code-(N OLT ×S max ×P max ), R represents the remaining code; according to the fourth formula, the position number of the service board used by the optical modem is calculated, wherein the fourth formula is:

[0011]

[0012] S represents the position number of the service board used by the optical modem; according to the fifth formula, the port number of the PON interface used by the optical modem is calculated, wherein the fifth formula is: R ′ =R-(S×P max ), R ′ Represents the port number of the PON interface used by the optical modem.

[0013] Optionally, before obtaining the relevant data of the optical modem, the method further includes: obtaining initial relevant data of the optical modem;

[0014] According to the sixth formula, the characteristic value of the current optical modem is calculated, wherein the sixth formula is:

[0015]

[0016] Z represents the eigenvalue, p represents the position of the optical modem in the feature space, N k (p) represents the k nearest neighbor set of the optical modem, the k nearest neighbor set includes the initial related data of multiple optical modems, r represents the distance from o to p, t represents the average reachable distance of the k nearest neighbor set of o, |N k (p)| represents the set size of k nearest neighbors; the initial relevant data whose eigenvalues ​​are not within the normal eigenvalue range are deleted to obtain the relevant data.

[0017] Optionally, after obtaining relevant data of the optical modem, the method further includes: obtaining an impact voltage value, wherein the impact voltage value is a voltage value obtained by subjecting the optical modem to a current impact when the optical modem is in a standby state; obtaining a baking temperature value, wherein the baking temperature value is a temperature value obtained by baking the optical modem when the optical modem is in a standby state; determining the stability of the optical modem based on the impact voltage value and the baking temperature value, wherein the fluctuation of the impact voltage value is negatively correlated with the stability, and the baking temperature value is negatively correlated with the stability.

[0018] Optionally, obtaining relevant data of the optical modem includes: obtaining initial relevant data; preprocessing the initial relevant data to obtain the relevant data, wherein the preprocessing method includes one or more of filling missing values, denoising, normalization, and feature engineering.

[0019] According to another aspect of the present application, an abnormality determination device for an optical modem is provided, comprising: a first acquisition unit, used to acquire relevant data of the optical modem, wherein the relevant data include one or more of an activation state, an online state, a current light receiving value, a current light emitting value, a chip temperature, a chip current and a chip voltage; a construction unit, used to construct an intelligent analysis model, wherein the intelligent analysis model is trained using multiple sets of training data, each set of the multiple sets of training data includes historical relevant data acquired within a historical time period, and historical analysis results corresponding to the historical relevant data, wherein the historical analysis results are used to characterize whether the optical modem is abnormal within the historical time period; a first processing unit, used to input the relevant data into the intelligent analysis model to obtain an analysis result corresponding to the relevant data; a second processing unit, used to generate early warning information when the analysis result characterizes that the optical modem is abnormal, and send the early warning information to a target terminal.

[0020] According to another aspect of the present application, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps of the method for determining an abnormality of any optical modem.

[0021] According to another aspect of the present application, an optical modem detection system is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the optical modem abnormality determination methods.

[0022] By applying the technical solution of the present application, anomalies of the optical modem are detected in an automated manner, an analysis model is constructed, and the detection results of the optical modem are output through an intelligent analysis module, thereby reducing manual intervention and lowering the cost of manual inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0024] Figure 1 A hardware structure block diagram of a mobile terminal for executing an abnormality determination method of an optical modem provided in an embodiment of the present application is shown;

[0025] Figure 2 A schematic flow chart of a method for determining an abnormality of an optical modem provided according to an embodiment of the present application is shown;

[0026] Figure 3 The schematic diagram of the architecture of this solution is shown;

[0027] Figure 4 The schematic diagram of the structure of the physical stacking and encoding module of the present solution is shown;

[0028] Figure 5 It shows the schematic diagram of the platform digital transformation and application network topology;

[0029] Figure 6 A structural block diagram of an abnormality determination device for an optical modem provided according to an embodiment of the present application is shown.

[0030] The above drawings include the following reference numerals:

[0031] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] As introduced in the background technology, the manual inspection of optical modems in the prior art is costly. To solve the above problem, the embodiments of the present application provide an optical modem abnormality determination method, device, computer program product and optical modem detection system.

[0036] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0037] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal of a method for determining abnormality of an optical modem according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0038] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the display method of device information in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0039] In this embodiment, a method for determining an abnormality of an optical modem running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0040] Figure 2 FIG. 1 is a flow chart of a method for determining an abnormality of an optical modem according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0041] Step S201, obtaining relevant data of the optical modem, wherein the relevant data includes one or more of activation state, online state, current light receiving value, current light emitting value, chip temperature, chip current and chip voltage;

[0042] Specifically, we first collect a series of operating status data from the optical modem, including but not limited to whether the optical modem is activated, whether it is online, the intensity of optical signal reception and transmission (received light value and emitted light value), the temperature of the chip, and the current and voltage of the chip. These data constitute the basic indicators of the health status of the optical modem and are the basis for subsequent abnormality detection and analysis.

[0043] Step S202, constructing an intelligent analysis model, wherein the intelligent analysis model is obtained by training using multiple sets of training data, each set of training data in the multiple sets of training data includes historical related data obtained in a historical time period and historical analysis results corresponding to the historical related data, wherein the historical analysis results are used to characterize whether the optical modem is abnormal in the historical time period;

[0044] Specifically, a smart analysis model is built using machine learning technology. The model is trained based on multiple sets of existing historical data, each of which contains the optical modem operation data collected during a certain period of time, as well as the manual or system analysis results of the optical modem status at that time (i.e., whether the optical modem is abnormal). Through training with a large amount of historical data, the model can learn the characteristics of the optical modem in normal and abnormal states, thereby making accurate anomaly predictions on unknown data.

[0045] Step S203, inputting the above-mentioned relevant data into the above-mentioned intelligent analysis model to obtain the analysis results corresponding to the above-mentioned relevant data;

[0046] Specifically, after the model is built, the real-time collected optical modem data will be used as input and sent to the intelligent analysis model for analysis. The model will process the real-time data according to the patterns and rules learned in the training phase, and finally output an analysis result, which can be a probability value for predicting whether the optical modem is abnormal, or a direct abnormal status label (such as "normal" or "abnormal").

[0047] Step S204: when the analysis result indicates that the optical modem is abnormal, generate warning information and send the warning information to the target terminal.

[0048] Specifically, if the output of the model indicates that the optical modem is abnormal, the system will automatically trigger the warning mechanism and generate warning information. This information usually contains the details of the optical modem abnormality and recommended treatment measures. The warning information will then be sent to the designated target terminal, such as the display screen of the monitoring center, the mobile device of the maintenance engineer, etc., so that relevant personnel can receive the alarm in time and take corresponding maintenance or investigation actions, thereby preventing potential network failures or service interruptions.

[0049] Through this embodiment, anomalies of the optical modem are detected in an automated manner, an analysis model is constructed, and the detection results of the optical modem are output through an intelligent analysis module, thereby reducing manual intervention and lowering the cost of manual inspection.

[0050] In addition, during the testing process, existing solutions will produce deviations in targeted issues due to excessive numbers, reducing the accuracy of detection, which will result in excessive investment and reduced overall efficiency.

[0051] During the specific implementation process, before obtaining the relevant data of the optical modem, the method also includes the following steps: when receiving a detection request, obtaining the unique code of the optical modem, wherein the optical modem is electrically connected to the optical line terminal, the optical line terminal includes multiple service boards, the service boards include multiple PON interfaces, the optical modem and the unique code correspond one to one, and the unique code is used to locate the optical modem; when the unique code is obtained, obtaining device information according to the unique code, wherein the device information is the location information of the optical line terminal, the location information of the service board and the PON interface used.

[0052] In this solution, each optical modem in the network can be accurately located by obtaining unique codes and related device information. Before performing anomaly detection, it is necessary to know "who" is the target of detection. The unique code ensures that the target optical modem can be accurately identified and located, preparing for the start of the automated detection process. In large fixed networks, the allocation of resources (such as network bandwidth, monitoring resources, and maintenance manpower) needs to be optimized. The unique code and device information positioning enable the system to focus resources on the optical modems that really need to be detected, avoiding indiscriminate data collection and analysis of all optical modems, thereby reducing the overall cost of detection and improving resource utilization efficiency.

[0053] Specifically, when the system receives a request for abnormal detection of an optical modem (which may be triggered by a network monitoring system, a user report, or a regular detection plan), the first task is to locate the specific optical modem that needs to be detected. Each optical modem is assigned a unique code, which is not only bound to the optical modem itself, but also corresponds to the OLT it is connected to, the specific service board on the OLT, and the PON interface on the service board. Therefore, through the unique code, the system can accurately identify and locate any optical modem in the network, which provides the necessary prerequisite for subsequent abnormal detection.

[0054] Once the system obtains the unique code of the optical modem, the next step is to obtain the detailed device information of the optical modem based on this code. This includes the physical location of the optical line terminal (OLT), the installation location of the service board on the OLT, and the PON interface number to which the optical modem is specifically connected. This information is crucial for understanding the network environment of the optical modem, performing remote configuration or troubleshooting.

[0055] Specifically, this solution can be applied to fixed-line terminal quality control detection systems (i.e., optical modem detection systems), such as Figure 3 As shown, the system mainly includes:

[0056] Physical stacking and coding module, which realizes the "one-to-one" arrangement of ONU physical objects (fixed network terminals, i.e. optical modems) and OLT management system codes (optical line terminals) by combining and coding the online data, and performs fine positioning of each PON port on a single service board of the OLT;

[0057] Data collection and storage module. The above data collection and storage module can be compatible with various types of ONU terminals of telecom operators according to business needs. The OLT management software has the ability of iterative development and upgrading. Through the intelligent collection system and physical stacking and encoding modules, it can realize real-time batch monitoring of ONU activation status, online status, current light receiving value, current light emitting value, and current temperature, current, voltage and other related data of the optical modem main chip, and store them in real time in the database;

[0058] Data analysis and processing module: The above-mentioned data analysis and processing module uses the simulation distribution mechanism to distribute simulated business data from the ITMS platform, realizes the full-process simulation registration of the optical modem, and can read the optical modem's device identification number, brand, model, and software and hardware versions and other related information, allowing the setting of "threshold audit points", implementing an online early warning system, discovering problematic optical modems at the first time, and re-inspecting the batch of optical modems, introducing a manual intervention mechanism;

[0059] Management cockpit module (i.e., digital large screen and display module). The above-mentioned management cockpit module integrates and displays OLT and ITMS platform monitoring information through a digital large screen, performs OLT data configuration and ITMS data monitoring in real time, and uses various common charts in the form of a cockpit to indicate the key parameters of fixed-line terminal operation, intuitively monitor the operation of fixed-line terminals, and can provide early warning and mining analysis of abnormal key indicators, set up decentralized management, assign important passwords and roles to specific people, and perform regular updates and maintenance.

[0060] Specifically, Figure 4 As shown, the above-mentioned physical stacking and encoding module is equipped with a corresponding management module, which is responsible for generating and managing the unique identification code of the ONU, and matching it with the PON port in the OLT management system to ensure that the physical position of each ONU is consistent with the logical position in the system. According to the standard configuration of the OLT, 4 service boards are configured, each service board is configured with 8 PON ports, and each PON port carries a maximum of 128 ONUs. In theory, a maximum of 4096 ONUs can be arranged in a "one-to-one" corresponding manner. Visual detection capability.

[0061] Specifically, the above-mentioned physical stacking and encoding module is equipped with 4 standard inspection frames for quality control inspection, which can be expanded at any time according to actual needs. Each standard inspection frame can realize 512 ONU capacity inspections, and 4 standard inspection frames can realize a maximum of 2048 ONU capacity inspections at the same time. The optical fiber and power supply have been prefabricated in the standard inspection frame, and remote control is carried out through the intelligent control device to realize remote opening and closing of the standard inspection frame operation.

[0062] Specifically, the data collection and storage module is compatible with OLT devices of models MA5680T and MA5800, and is also compatible with ONU terminals of various telecom operators such as EPON, GPON, 10GEPON and XGPON.

[0063] Specifically, important data in the above-mentioned management cockpit module supports local export and can be remotely copied through VPN. Remote support personnel can obtain monitoring data through remote access at any time.

[0064] Specifically, when the system is running, it simulates the entire process of optical modem registration, and conducts real-time data collection and analysis on multiple key links such as OLT registration, obtaining management address, ITMS registration and data delivery. The system automatically analyzes and detects the data, marks the abnormal data found, and gives reminders on the application display page. The abnormal data situation is also reflected in the data report. Through data analysis, abnormal terminal situations are discovered in time, and abnormal terminals are processed and reminded. For data that exceeds the set rated threshold, it is sent to the corresponding personnel according to the set early warning contact method, and manual intervention is performed on this batch of equipment according to the emergency handling mechanism to prevent batch problems.

[0065] Specifically, in fixed-line communication systems, ONU (Optical Network Unit) and OLT (Optical Line Terminal) are two key components in the fiber-to-the-home (FTTH) network. ONU is usually located at the user end, such as a home or enterprise, and is responsible for converting the user's data into optical signals and transmitting them to OLT through the optical fiber network. OLT is located in the core network area of ​​the telecom operator, and is used to receive optical signals from multiple ONUs and convert them into electrical signals, which are then processed and forwarded to the Internet or telephone network, etc.

[0066] The physical ONU refers to the actual optical network unit device, which usually has one or more network interfaces for connecting to the user's computer, phone or other network devices. There are various hardware components inside the ONU, such as optical transceivers, main control chips, power modules, etc., as well as firmware or operating systems running on the hardware. Each ONU has a unique serial number or other identifier to physically distinguish different devices.

[0067] The OLT management system code refers to the logical code or address assigned to each ONU in the OLT management system in order to manage and locate the ONU devices connected to it. This code is usually associated with the physical location of the ONU (such as the service board and its PON port in the OLT) and the serial number of the ONU, so that the OLT can know the specific location and status of each ONU, so as to carry out effective management and control. For example, when an ONU registers with the OLT, the OLT will assign a specific code based on the registration request sent by the ONU to identify and track the ONU in the OLT management software.

[0068] The "one-to-one" arrangement means that each actual ONU device (ONU physical object) will correspond to a unique code in the OLT management system. This correspondence allows the system to accurately locate, monitor and manage the status and performance of each ONU. By establishing this coding system, batch management and automated testing of ONUs can be achieved, while ensuring that the test results and status of each device can be accurately tracked, improving the efficiency and accuracy of quality control testing.

[0069] ITMS (Integrated Terminal Management System) is a remote terminal management platform used by telecom operators, mainly used to manage and monitor various broadband terminal devices in telecom networks, such as ONU (Optical Network Unit), routers, modems, etc. The ITMS platform provides a centralized way for operators to remotely configure, monitor, diagnose and repair these terminal devices to ensure the continuity and high quality of network services.

[0070] In the fiber access network (especially FTTH, fiber to the home), ONU (Optical Network Unit), OLT (Optical Line Terminal), service board, PON (Passive Optical Network) technology and ITMS (Integrated Terminal Management System) are closely connected key components and management platforms, and they play different roles in building and maintaining the fiber network. The following explains the relationship between them in detail:

[0071] ONU (Optical Network Unit): ONU is located at the user end and is the access point for network services. It is responsible for converting the electrical signals on the user side into optical signals, transmitting them to the OLT through the optical fiber network, and then converting the optical signals from the OLT into electrical signals for use by user devices.

[0072] OLT (Optical Line Terminal): OLT is located on the core network side of the operator, responsible for managing and controlling the PON network, receiving optical signals from multiple ONUs, converting these signals into electrical signals, and forwarding them to the Internet or other services through traditional networks. OLT is also responsible for allocating network resources, controlling data flow in the PON network, and communicating with the ONU through the PON port on the service board.

[0073] Service board: The service board is a key component in the OLT. It contains multiple PON ports, each of which can be connected to multiple ONUs. The service board processes the data received from the PON port, controls the upstream and downstream data transmission, and is the bridge for data exchange between the OLT and the ONU.

[0074] PON (Passive Optical Network) Technology: PON technology is a network architecture for fiber access, which uses passive optical splitters (usually fiber distribution networks, ODN) to distribute and concentrate optical signals, reducing the number of active devices in the network, reducing costs and maintenance complexity. Through PON technology, a single OLT can serve hundreds or thousands of ONUs at the same time, improving network efficiency and resource utilization.

[0075] ITMS (Integrated Terminal Management System): ITMS is a platform for remote monitoring and management of terminal devices (such as ONU, routers, etc.) in broadband access networks. It can perform operations such as device configuration, fault diagnosis, performance monitoring, and firmware upgrades to ensure stable network operation and service quality. ITMS works with OLT. Through the OLT management software, it can remotely access the ONU, obtain its status information, and perform fault detection and performance optimization.

[0076] In general, ONU is connected to the service board of OLT through PON technology. OLT is the core device of the network, responsible for data aggregation and distribution, as well as communication control with ONU. ITMS is an upper-layer management system used to remotely manage and monitor the operation status of ONU and the entire network. It is an important tool for operators to manage the network and ensure customer service. These components and platforms together build an efficient, reliable and remotely monitorable fiber access network, in which each part plays a key role in the overall performance of the network and user experience.

[0077] In some embodiments, obtaining the unique code of the optical modem can be achieved by the following steps: generating the unique code according to a first formula, wherein the first formula is:

[0078] Code=(N OLT ×S max ×P max )+(S×P max )+P+ID ONU , Code represents the unique code above, N OLT Indicates the code number of the above optical modem in the above optical line terminal, S max Indicates the maximum number of the above service boards, P max Indicates the maximum number of the above PON interfaces, S indicates the position number of the above service board used by the above optical modem, P indicates the port number of the above PON interface used by the above optical modem, IDONU The unique identifier of the above optical modem.

[0079] In this solution, the code generated by the above formula ensures the uniqueness of each optical modem in the entire system. Even if there are a large number of optical modems of the same model in the network, accurate device identification and positioning can be achieved through the OLT, service board and PON port to which it is connected, as well as its own identifier.

[0080] Specifically, Figure 5 As shown, the physical stacking and encoding module includes multiple optical line terminals (i.e., power intelligent devices). The aging rack is a rack for placing optical line terminals, the data acquisition and storage module is used to collect and store data, the data analysis and processing module is used to analyze relevant data, and the digital large screen and display module is used to display data. Given a specific ONU connected to an OLT, its service board, and a specific PON port, the first formula can be used to generate a unique code.

[0081] N OLT is the OLT number in the entire system, S is the service board position number actually used, starting from 0, and P is the PON port number actually used, also starting from 0. ONU It is the unique identifier of the ONU device, which is a continuously increasing integer sequence.

[0082] Specifically, the generated unique code is used to represent the complete location information and unique identification of the ONU in the network system.

[0083] N OLT :The number of OLT in the entire system, used to identify different OLT devices. Each OLT will have its own specific number to distinguish different OLTs in the network.

[0084] S max : The maximum number of service boards, which refers to the maximum number of service boards that the OLT can support. In this example, it is assumed that each OLT is equipped with 4 service boards.

[0085] P max : The maximum number of PON ports, which refers to the maximum number of PON ports that each service board can support. Assume that each service board is configured with 8 PON ports.

[0086] S: The service board position number actually used, used to identify the specific service board in the OLT. The numbering starts from 0, so the service boards 0, 1, 2, and 3 are numbered 0, 1, 2, and 3.

[0087] P: PON port number actually used, used to identify the specific PON port on the service board. The numbering also starts from 0, so the PON ports 0, 1, 2, 3, ...nn are numbered 0, 1, 2, 3, ...n.

[0088] ID ONU : Unique identifier of the ONU device, which is a continuously increasing integer sequence used to uniquely identify each ONU in the OLT system. Even if the OLT and service board are the same, different ONUs will have different IDs.

[0089] In the specific implementation process, the device information is obtained according to the unique code, which can be achieved by the following steps: according to the second formula, the code number of the optical modem in the optical line terminal is calculated, wherein the second formula is:

[0090]

[0091] N OLT represents the above code number of the above optical modem in the above optical line terminal, Code represents the above unique code of the above optical modem, S max Indicates the maximum number of the above service boards, P max Indicates the maximum number of the above PON interfaces, ID ONU The unique identifier of the optical modem; according to the third formula, calculate the remaining code, wherein the remaining code is the partial code after removing the influence of the code number of the optical modem in the optical line terminal, and the third formula is:

[0092] R=Code-(N OLT ×S max ×P max ), R represents the remaining code; according to the fourth formula, the position number of the service board used by the optical modem is calculated, wherein the fourth formula is:

[0093]

[0094] S represents the position number of the service board used by the optical modem; according to the fifth formula, the port number of the PON interface used by the optical modem is calculated, wherein the fifth formula is: R ′ =R-(S×P max ), R ′ Represents the port number of the PON interface used by the optical modem.

[0095] In this solution, through the above reverse analysis steps, the specific connection position of each optical modem in a large-scale network can be quickly and accurately located, including the OLT device, service board location and PON interface to which it is connected. This is crucial for troubleshooting, equipment management, and network optimization, and can significantly improve processing efficiency and reduce maintenance time.

[0096] Specifically, when a code is received, we need to reversely parse it to determine the corresponding OLT, service board, PON port and ONU equipment information. First, calculate the OLT number, relying on the second formula for calculation. Then, rely on the third formula to remove the influence of the OLT part and continue to parse. Then rely on the fourth formula to calculate the service board position. Rely on the fifth formula to remove the influence of the service board part and continue to parse, and finally get the ID code of the current ONU to complete one-to-one precise positioning.

[0097] Specifically, R: residual code, that is, the remaining part after removing the influence of the OLT number from the original code, which is used for subsequent calculation of the position of the service board and the PON port.

[0098] By dividing by P max , the position number of the service board can be calculated because the total contribution of the PON ports on each service board is expressed as a multiple in R.

[0099] R ′ : The updated remaining code, which is the remaining part after removing the influence of the service board position, is used to calculate the PON port number.

[0100] Finally, the ID code of the current ONU is obtained.

[0101] The last step is to directly obtain the ONU ID from the updated remaining code, because at this time the remaining code only contains the ONU ID information.

[0102] The above coding mechanism ensures that in a large-scale detection and management environment, each ONU has a unique code containing its complete physical location information. This is conducive to large-scale automated detection, because once a problem is detected in an ONU, its code can be used to quickly locate the specific OLT, service board, PON port and ONU device without manual search one by one. At the same time, this mechanism also makes remote management and diagnosis possible, because the code contains all the necessary information, and data analysis and fault location can be performed remotely.

[0103] In some embodiments, before obtaining the relevant data of the optical modem, the method further includes the following steps: obtaining the initial relevant data of the optical modem; and calculating the current characteristic value of the optical modem according to the sixth formula, wherein the sixth formula is:

[0104]

[0105] Z represents the above eigenvalue, p represents the position of the above optical modem in the feature space, N k (p) represents the k nearest neighbor set of the above optical modem, the k nearest neighbor set includes the above initial related data of multiple optical modems, r represents the distance from o to p, t represents the average reachable distance of the k nearest neighbor set of o, |N k (p)| represents the set size of k nearest neighbors; the above initial related data whose eigenvalues ​​are not within the normal eigenvalue range are deleted to obtain the above related data.

[0106] In this solution, by calculating the abnormal analysis value Z, it is possible to determine whether the optical modem has deviated from the normal operating range based on its relative position in its feature space, which provides an important basis for abnormal identification in the training of the intelligent model and enhances the accuracy of abnormal detection. The calculation of the Z value is actually a feature engineering transformation, which converts the original optical modem operating parameters into an indicator that describes the degree of abnormality. This transformation helps the model better understand the abnormal pattern of the optical modem status, thereby improving the training effect and prediction performance of the model.

[0107] The sixth formula mentioned above is the anomaly detection formula, which is used for preliminary screening and feature quantification. It directly quantifies the relationship between data points and neighborhoods (such as distance, density, etc.) through mathematical rules, and quickly identifies abnormal points that are obviously deviated from the normal range (such as sudden changes in the light value of the optical modem, temperature anomalies, etc.). The machine learning model is used for complex pattern recognition and probability prediction, and mines nonlinear relationships and hidden patterns in the data. For example, by training the model with historical data, it can predict the probability of optical modem registration failure, hardware stability and other complex problems. It can integrate multi-dimensional features (such as version number, voltage fluctuation, ambient temperature, etc.). The model can optimize performance by continuously learning new data and adapt to equipment upgrades or changes in the network environment. When used in conjunction, the formula can quickly filter out obvious anomalies and reduce the computational load of subsequent models. For example, if the Z value exceeds the preset threshold, it is directly marked as an anomaly and triggers an early warning without entering the model analysis. The model serves to conduct in-depth analysis of devices that have not triggered the formula alarm and identify potential risks (such as hidden faults, performance degradation trends). The Z value calculated by the formula and the value after the version number conversion can be used as one of the input features of the model to enhance the model's sensitivity to abnormal signals.

[0108] If only formulas are used, rules are set based on manual experience, which makes it difficult to cover all types of anomalies (such as new failure modes) and it is impossible to quantify risk probabilities (such as "60% probability of system crash"). However, if only models are used, model training requires a large amount of labeled data, and there may be cold start problems in the early stages. Scenarios with high real-time requirements (such as millisecond-level warnings) may fail due to model reasoning delays. Therefore, when the two are used together, the formula can quickly screen and reduce the amount of model calculations, and the model can deeply analyze to improve overall accuracy, enhance robustness, reduce the risk of missed detection and false detection, and meet the needs of different scenarios.

[0109] Specifically, the relevant data of the optical modem and the calculated abnormal analysis value are used as part of the training data to generate a training data set, which is used to train the intelligent analysis model so that the model can learn the characteristic patterns of the optical modem in normal and abnormal states. When the calculated abnormal analysis value Z is greater than or equal to the preset analysis threshold, it is preliminarily judged that the optical modem is in an abnormal state. Conversely, if the Z value is less than the preset analysis threshold, it is preliminarily judged that the optical modem is in normal state. The preset analysis threshold can be set according to actual conditions.

[0110] Specifically, the above data analysis and processing module uses the following formula to implement feature engineering conversion and convert the version number into digital form. The conversion formula of the version is:

[0111]

[0112] Among them, d i :Each digit in the version number is numbered 0, 1, 2, ..., n starting from the leftmost (highest digit). n: The number of digits after the decimal point in the version number. If the version number is in the form of XYZ, then n is the number of digits in Z. i: The number of digits in the current number, starting from 0, where 0 represents the highest digit, and increasing to the right in sequence.

[0113] This formula converts each digit in the version number into a decimal form according to its place value, and then adds them up to get an overall numerical representation. For example, if the version number is 2.3.4 (assuming that the number of digits after the decimal point n = 1, in fact all digits should be considered), then the converted number is 2×13×0.1+4×0.01=2+0.3+0.04=2.34.

[0114] This conversion method helps convert version numbers, which are string data that cannot be directly used for mathematical operations, into numerical data that can be calculated and compared, facilitating subsequent data analysis and machine learning applications.

[0115] After the conversion is completed, the registration status is verified and the device type is classified, followed by intelligent anomaly detection. The anomaly detection formula is the sixth formula.

[0116] p: target point, which refers to the optical modem or ONU being detected.

[0117] N k (p): The k nearest neighbor set of point p, which refers to the k points (ONU or optical modem) closest to p in the feature space. k is a preset constant.

[0118] r: The reachable distance from point O to point p, which represents the distance between two devices in the feature space. It can be Euclidean distance, Hamming distance, etc.

[0119] t: The average reachable distance of the k nearest neighbors of point O, which means the average distance from point O to its k nearest neighbors.

[0120] |N k (p)|: The set size of k nearest neighbors, that is, the number of devices in N_k(p).

[0121] The Z value in the formula can be regarded as the degree of abnormality between the target point p and its k nearest neighbors in the feature space. If the Z value is much greater than 1, it means that the distance between the target point p and its neighbors in the feature space is much larger than the average distance, which may indicate that p is abnormal. On the contrary, if the Z value is close to 1, it means that the distance between p and its neighbors is close and the performance is normal.

[0122] After the anomaly detection is completed, the trained machine training model is used to predict indicators and calculate the probability of successful registration or failure. The above machine training model uses the logistic regression model algorithm to perform corresponding calculations and processing according to the following formula to solve the probability problem of binary classification and obtain the probability answer. The formula is as follows:

[0123]

[0124] P(y=1|x): The probability of event y=1 (e.g., device registration succeeds or a failure occurs) given feature x.

[0125] x: feature vector, containing multiple features, such as device type, version number, test results, etc.

[0126] a0,,a1,...,a n : Parameters of the logistic regression model, obtained through training, used to adjust the impact of features on the results.

[0127] y: the label of the classification result, y=1 indicates that the event occurs (such as successful registration or failure), and y=0 indicates that the event does not occur.

[0128] First, use sufficient historical data, which should include information such as user behavior characteristics, system status, and labels of successful registration / failure. Perform routine cleaning and feature selection on the acquired data, and then segment the data into training sets and test sets. The segmentation ratio must be maintained at at least 8:2. Then use the selected formula algorithm to train the collection, select appropriate model parameters through cross-validation, obtain the best model training performance, and then evaluate the model prediction performance. Finally, deploy the trained model to complete the application reception and prediction of actual data.

[0129] During the specific implementation process, after obtaining the relevant data of the optical modem, the above method also includes the following steps: obtaining an impact voltage value, wherein the above impact voltage value is a voltage value obtained by subjecting the above optical modem to a current impact when the above optical modem is in a standby state; obtaining a baking temperature value, wherein the above baking temperature value is a temperature value obtained by baking the above optical modem when the above optical modem is in a standby state; determining the stability of the above optical modem based on the above impact voltage value and the above baking temperature value, wherein the fluctuation of the above impact voltage value is negatively correlated with the above stability, and the above baking temperature value is negatively correlated with the above stability.

[0130] In this solution, the hardware quality and stability of the optical modem can be quantitatively evaluated through impulse voltage and baking tests, which helps to establish more stringent and scientific quality control standards to ensure that the optical modems put on the market or network have high stability and durability. Before the optical modem is put into actual use, these tests can detect potential hardware problems early, such as insufficient power management and heat dissipation design defects, to prevent problematic optical modems from adversely affecting network stability and user experience.

[0131] Specifically, when the optical modem is in standby mode, a series of current impact tests are performed on it, and the resulting voltage fluctuations can be measured. These impact voltage values ​​reflect the response of the optical modem when it is subjected to unexpected current impacts (such as lightning strikes or power grid fluctuations). If the circuit design and power management capabilities of the optical modem are weak, the fluctuation range of the impact voltage value will be large, otherwise it will be small.

[0132] Similarly, when the optical modem is in standby mode, a continuous high-temperature baking test is performed on it to monitor the temperature rise inside the optical modem. The baking temperature value indicates the thermal stability and heat dissipation performance of the optical modem when it is working continuously for a long time or in a high-temperature environment. If the heat dissipation design or performance of the optical modem is poor, the baking temperature value will increase significantly.

[0133] The stability of the optical modem can be comprehensively judged based on the fluctuation of the impulse voltage value and the baking temperature value. For the impulse voltage value, the smaller the fluctuation amplitude, the stronger the optical modem's resistance to current impulse and the better the stability. For the baking temperature value, the slower the temperature rise or the lower the temperature reached, the better the thermal stability of the optical modem and the stronger the stability.

[0134] Specifically, the data acquisition and storage module adopts a forced surge impulse voltage test, which tests the stability of the optical modem by applying forced current shocks to the optical modem for five consecutive times with an interval of five minutes each time in standby mode and performing an online baking test for four hours. The test also verifies the stability of the optical modem after real-time observation of the OLT management software monitoring data.

[0135] Specifically, in this scenario, the test module will apply a series of high-voltage or high-current shocks when the optical modem is in standby mode to simulate unstable conditions in the power system, such as lightning shocks or transients in the power network. Shock tests usually include multiple consecutive shocks with a certain interval between each shock to evaluate the device's response and recovery capabilities after experiencing continuous emergencies. The specific operation of the test is: 5 consecutive forced current shocks are applied to the optical modem in standby mode, with a 5-minute interval after each shock. The purpose is to simulate the performance of the device in an unstable power supply environment and check whether the optical modem can withstand such extreme conditions without damage or malfunction.

[0136] Baking is a type of equipment durability test, which usually involves applying a temperature higher than the normal operating range for a long time while the equipment is running, in order to test the stability and life of the equipment under high temperatures. "Online baking" here means that the optical modem is connected to the network and runs continuously for 4 hours, during which the device will experience normal network load and data transmission. At the same time, the system will monitor the performance of the device under high temperature conditions, such as processor temperature, network latency, packet loss rate, etc., to evaluate its stability in the actual use environment.

[0137] OLT (Optical Line Terminal) is the core device of the optical fiber network, responsible for processing and managing the signals received from multiple ONUs (Optical Network Units). The OLT management software can monitor the status of all ONUs connected to the OLT in real time, including but not limited to the online status, signal quality, device temperature, etc. of the ONU. When performing the above stability test, the data acquisition and storage module will read the monitoring data of the OLT management software in real time to obtain the real-time performance of the optical modem during the test. These data are helpful for analyzing the stability and durability of the optical modem.

[0138] Through the above forced surge impact and online baking test, combined with the real-time monitoring data of the OLT management software, the stability and reliability of the optical modem under power fluctuations and high temperature conditions can be fully evaluated. If the optical modem does not experience performance degradation, abnormal restart or signal loss during the test, it can be considered that it has good stability under these extreme conditions.

[0139] In some embodiments, obtaining relevant data of the optical modem can be specifically achieved through the following steps: obtaining initial relevant data; preprocessing the above-mentioned initial relevant data to obtain the above-mentioned relevant data, wherein the preprocessing method includes one or more of filling missing values, denoising, normalization, and feature engineering.

[0140] In this solution, preprocessing can reduce problems such as missing data, noise, and inconsistent dimensions, significantly improve the overall quality of data, and provide a more reliable basis for subsequent analysis and decision-making. Data preprocessing eliminates unnecessary interference, allowing the model to more accurately identify abnormal conditions of optical modems or predict their performance. Normalization and feature engineering can also help the model better understand the internal structure of the data and improve the analysis effect.

[0141] Specifically, the preprocessing methods may include the following:

[0142] Handling missing values: Handle missing values ​​in data by deleting records with missing values, filling missing values ​​(such as filling with mean, median, mode, or using a predictive model), etc.

[0143] Noise Removal: Identify and correct or remove outliers, erroneous data, duplicate data, or irrelevant data.

[0144] Consistency check: Ensure the consistency of data in terms of format, unit, range, etc., such as unified date format and consistent numerical units.

[0145] Standardization and normalization: Converting data to the same scale, such as scaling all numerical features to between 0 and 1 or to a distribution with a mean of 0 and a standard deviation of 1, can help improve model performance and computational efficiency.

[0146] Data encoding: Convert categorical data into numerical form, such as One-Hot Encoding, Label Encoding, etc.

[0147] Feature Engineering: Create new features based on business understanding, and combine or transform existing features to extract more meaningful information.

[0148] Specifically, the scheme of the present application is designed with low overall cost, strong practicality, fast delivery speed, maintainability, upgradeability and expandability through the comprehensive use of physical stacking and encoding modules, data collection and storage modules, data analysis and processing modules, and management cockpit modules. In the specific use process, it can simulate the entire process of optical modem registration to carry out process-based early warning, synchronously detect large quantities of optical modems in real time, and conduct intelligent analysis through real-time monitoring of operating data. After the processing is completed, it relies on digital large-screen display to observe the online status of optical modems in real time to achieve precise management. For abnormal problems in the entire process of optical modem registration, a "threshold audit point" can be set, and an online early warning system can be implemented to discover problematic optical modems at the first time, and re-inspect the batch of optical modems, introduce a manual intervention mechanism, effectively prevent batch problems from occurring, and effectively improve the first-line installation and maintenance usage perception. By batch reading the device identification code of the optical modem, the optical modem with inconsistent internal and external serial codes can be identified, avoiding the situation where the terminal cannot be shipped normally due to inconsistent internal and external serial codes when used on the front line, greatly improving the detection efficiency.

[0149] Specifically, in order to overcome the cumbersome and complicated quality control detection methods of conventional fixed-line terminals, it is necessary to invest in a large number of fixed-line terminals in basic testing, which exceeds the estimated testing cost. In addition, during the testing process, the deviation of targeted problems will occur due to the excessive number, which will reduce the accuracy of the detection. This will lead to the disadvantage of reducing the overall efficiency while investing too much. By combining and encoding the data of the physical stacking and encoding module, data acquisition and storage module, data analysis and processing module and management cockpit module, the "one-to-one" arrangement of the ONU physical object and the OLT management system encoding is achieved, and the PON ports on the single service board of the OLT are finely positioned. The overall cost is low, the practicality is strong, the delivery speed is fast, and it has the ability to be maintained, upgraded and expanded. In the specific use process, it can simulate the registration process of the optical modem to carry out process-based early warning, synchronously detect a large number of optical modems in real time, and conduct intelligent analysis through real-time monitoring of operation data. After the processing is completed, it relies on the digital large screen display to observe the online status of the optical modem in real time to achieve precise management.

[0150] In summary, the solution of the present application has low overall cost, strong practicality, fast delivery speed, and the ability to be maintainable, upgradeable and expandable. During specific use, it can perform process-based early warning by simulating the entire registration process of the optical modem, conduct synchronous real-time detection of large batches of optical modems, generate corresponding codes to achieve one-to-one precise positioning, and conduct intelligent analysis through real-time monitoring of operating data, calculate the probability of failure using models, and rely on digital large-screen display after processing to observe the online status of the optical modem in real time to achieve precise management.

[0151] This solution can set "threshold audit points" for abnormal problems in the entire process of optical modem registration, implement an online early warning system, discover problematic optical modems as soon as possible, and re-inspect the quality of the batch of optical modems, introduce a manual intervention mechanism, effectively prevent the occurrence of batch problems, and effectively improve the usage perception of front-line installation and maintenance.

[0152] This solution can identify optical modems with inconsistent internal and external serial codes by batch reading the device identification codes of optical modems, avoiding the situation where the terminal cannot be shipped out normally due to inconsistent internal and external serial codes when used on the front line, greatly improving detection efficiency.

[0153] This solution supports remote control and adopts intermittent normalized impact testing to test the stable state of the optical modem, realizes remote opening and closing of the standard detection frame operation, and improves the convenience of test operations.

[0154] This solution uses a cockpit to visually display the key parameters of fixed-line terminal operation through various common charts and graphs, intuitively monitor the operation of fixed-line terminals, and can provide early warning and mining analysis of abnormal key indicators, set up decentralized management, assign important passwords and roles to specific people, and perform regular updates and maintenance.

[0155] During the use of the scheme of the present application, by simulating the entire registration process of the optical modem, various forms of optical modems such as 10GPON and 1GPON are monitored simultaneously. The maximum monitoring capacity of the same batch can reach 4096 refurbished optical modems, which can detect various problems such as unsuccessful registration, disconnection, crash, inconsistent serial code, etc. For abnormal problems in the entire registration process of the optical modem, a "threshold audit point" can be set, and an online early warning system can be implemented to discover problematic optical modems as soon as possible, and re-inspect the quality of the batch of optical modems, introduce a manual intervention mechanism, effectively prevent the occurrence of batch problems, and effectively improve the first-line installation and maintenance perception. At the same time, through real-time monitoring of operating data, various intelligent analysis methods are provided for discovering problematic optical modems to check whether the optical modem can be activated. If the optical modem only receives light but does not emit light or only emits light but does not receive light, it cannot be activated, and the terminal with hardware problems can be distinguished; check whether the optical modem is online. After the optical modem is activated, if the optical modem is powered off and restarted multiple times and displays offline, it proves that the optical modem hardware is unstable, and power-off data loss or non-startup may occur in the user's home; check whether the optical modem's received and emitted light values ​​are within a reasonable range. If they are too large, it proves that the optical modem's light-emitting module is abnormal and needs maintenance; through The optical modem is powered off and restarted for 5 times in a row, with an interval of 5 minutes each time, and the online status of the optical modem is checked simultaneously. If it is displayed as offline, it proves that the optical modem has stability problems. By batch reading the device identification codes of the optical modems, the optical modems with inconsistent internal and external serial codes can be identified, avoiding the situation where the terminal cannot be normally shipped out of the warehouse due to inconsistent internal and external serial codes when used on the front line. Finally, the online status of the optical modem can be observed in real time on the digital large screen display. Parameters such as chip temperature, transmit and receive optical power, current, CPU utilization, etc. are intuitively presented, and reports can be exported. The ONU code corresponds to the physical code one by one. When an abnormal parameter is found, the optical modem with the corresponding code can be discovered and dialed out in time without repeatedly searching and checking the serial code. The smart socket can be remotely controlled through the Xiaoyi Guanjia APP to accurately control the power on / off status and number of each aging rack and the duration of the online baking machine, giving full play to the effectiveness of the forced surge impulse voltage test, so that the optical modems that are prone to disconnection and crashes are "exposed". Remote support personnel can remotely access the system at any time, and observe the optical modem detection data in time on the premise of ensuring network security, avoiding the time burden of support personnel having to be present, and effectively improving work efficiency.

[0156] The embodiment of the present application also provides an abnormality determination device for an optical modem. It should be noted that the abnormality determination device for the optical modem in the embodiment of the present application can be used to execute the abnormality determination method for the optical modem provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0157] The following is an introduction to the abnormality determination device of the optical modem provided in the embodiment of the present application.

[0158] Figure 6 1 is a structural block diagram of an abnormality determination device of an optical modem according to an embodiment of the present application. Figure 6 As shown, the device comprises:

[0159] A first acquisition unit 10 is used to acquire relevant data of the optical modem, wherein the relevant data includes one or more of activation state, online state, current light receiving value, current light emitting value, chip temperature, chip current and chip voltage;

[0160] A construction unit 20 is used to construct an intelligent analysis model, wherein the intelligent analysis model is obtained by training using multiple sets of training data, each set of training data in the multiple sets of training data includes historical related data obtained in a historical time period and historical analysis results corresponding to the historical related data, wherein the historical analysis results are used to characterize whether the optical modem is abnormal in the historical time period;

[0161] The first processing unit 30 is used to input the above-mentioned relevant data into the above-mentioned intelligent analysis model to obtain the analysis results corresponding to the above-mentioned relevant data;

[0162] The second processing unit 40 is used to generate warning information when the above analysis result indicates that the above optical modem is abnormal, and send the above warning information to the target terminal.

[0163] Through this embodiment, anomalies of the optical modem are detected in an automated manner, an analysis model is constructed, and the detection results of the optical modem are output through an intelligent analysis module, thereby reducing manual intervention and lowering the cost of manual inspection.

[0164] During the specific implementation process, the above-mentioned device also includes a second acquisition unit and a third acquisition unit. The second acquisition unit is used to obtain the unique code of the above-mentioned optical modem before obtaining the relevant data of the optical modem, when a detection request is received, wherein the above-mentioned optical modem is electrically connected to the optical line terminal, the above-mentioned optical line terminal includes multiple service boards, the above-mentioned service boards include multiple PON interfaces, the above-mentioned optical modem and the above-mentioned unique code correspond one-to-one, and the above-mentioned unique code is used to locate the above-mentioned optical modem; the third acquisition unit is used to obtain device information according to the above-mentioned unique code when the above-mentioned unique code is obtained, wherein the above-mentioned device information is the location information of the above-mentioned optical line terminal, the location information of the above-mentioned service board and the above-mentioned PON interface used.

[0165] In this solution, each optical modem in the network can be accurately located by obtaining unique codes and related device information. Before performing anomaly detection, it is necessary to know "who" is the target of detection. The unique code ensures that the target optical modem can be accurately identified and located, preparing for the start of the automated detection process. In large fixed networks, the allocation of resources (such as network bandwidth, monitoring resources, and maintenance manpower) needs to be optimized. The unique code and device information positioning enable the system to focus resources on the optical modems that really need to be detected, avoiding indiscriminate data collection and analysis of all optical modems, thereby reducing the overall cost of detection and improving resource utilization efficiency.

[0166] In some embodiments, the second acquisition unit includes a generation module, which is used to generate the unique code according to a first formula, wherein the first formula is:

[0167] Code=(N OLT ×S max ×P max )+(S×P max )+P+ID ONU , Code represents the unique code above, N OLT Indicates the code number of the above optical modem in the above optical line terminal, S max Indicates the maximum number of the above service boards, P max Indicates the maximum number of the above PON interfaces, S indicates the position number of the above service board used by the above optical modem, P indicates the port number of the above PON interface used by the above optical modem, ID ONU The unique identifier of the above optical modem.

[0168] In this solution, the code generated by the above formula ensures the uniqueness of each optical modem in the entire system. Even if there are a large number of optical modems of the same model in the network, accurate device identification and positioning can be achieved through the OLT, service board and PON port to which it is connected, as well as its own identifier.

[0169] In the specific implementation process, the third acquisition unit includes a first calculation module, a second calculation module, a third calculation module and a fourth calculation module, and the first calculation module is used to calculate the coding number of the optical modem in the optical line terminal according to the second formula, wherein the second formula is:

[0170]

[0171] N OLT represents the above code number of the above optical modem in the above optical line terminal, Code represents the above unique code of the above optical modem, S max Indicates the maximum number of the above service boards, P max Indicates the maximum number of the above PON interfaces, IDONU The unique identifier of the optical modem; the second calculation module is used to calculate the remaining code according to the third formula, wherein the remaining code is the partial code affected by the code number of the optical modem in the optical line terminal, and the third formula is:

[0172] R=Code-(N OLT ×S max ×P max ), R represents the remaining code; the third calculation module is used to calculate the position number of the service board used by the optical modem according to the fourth formula, wherein the fourth formula is:

[0173]

[0174] S represents the position number of the service board used by the optical modem; the fourth calculation module is used to calculate the port number of the PON interface used by the optical modem according to the fifth formula, wherein the fifth formula is: R ′ =R-(S×P max ), R ′ Represents the port number of the PON interface used by the optical modem.

[0175] In this solution, through the above reverse analysis steps, the specific connection position of each optical modem in a large-scale network can be quickly and accurately located, including the OLT device, service board location and PON interface to which it is connected. This is crucial for troubleshooting, equipment management, and network optimization, and can significantly improve processing efficiency and reduce maintenance time.

[0176] In some embodiments, the device further includes a fourth acquisition unit, a calculation unit and a deletion unit, wherein the fourth acquisition unit is used to obtain the initial relevant data of the optical modem before obtaining the relevant data of the optical modem; the calculation unit is used to calculate the characteristic value of the current optical modem according to the sixth formula, wherein the sixth formula is:

[0177]

[0178] Z represents the above eigenvalue, p represents the position of the above optical modem in the feature space, N k (p) represents the k nearest neighbor set of the above optical modem, the k nearest neighbor set includes the above initial related data of multiple optical modems, r represents the distance from o to p, t represents the average reachable distance of the k nearest neighbor set of o, |N k (p)| represents the set size of k nearest neighbors; the deleting unit is used to delete the above-mentioned initial related data whose characteristic values ​​are not within the normal characteristic range to obtain the above-mentioned related data.

[0179] In this scheme, by calculating the abnormal analysis value Z, it is possible to judge whether the optical modem has deviated from the normal operating range based on its relative position in its feature space. This provides an important basis for abnormal identification in the training of the intelligent model and enhances the accuracy of abnormal detection. The calculation of the Z value is actually a feature engineering transformation, which converts the original optical modem operating parameters into an indicator that describes the degree of abnormality. This conversion helps the model better understand the abnormal pattern of the optical modem status, thereby improving the training effect and prediction performance of the model. Adding abnormal analysis values ​​to the training data set can help the model learn the characteristic performance of different optical modems when they are abnormal. Even if anomalies occur in certain operating parameters, the model can judge the abnormal state of the optical modem based on the statistical information of the Z value, which enhances the robustness of the model in the face of complex network environments.

[0180] During the specific implementation process, the above-mentioned device also includes a fifth acquisition unit, a sixth acquisition unit and a determination unit. The fifth acquisition unit is used to obtain an impact voltage value after obtaining relevant data of the optical modem, wherein the impact voltage value is a voltage value obtained by subjecting the optical modem to a current impact when the optical modem is in a standby state; the sixth acquisition unit is used to obtain a baking temperature value, wherein the baking temperature value is a temperature value obtained by baking the optical modem when the optical modem is in a standby state; the determination unit is used to determine the stability of the optical modem based on the impact voltage value and the baking temperature value, wherein the fluctuation of the impact voltage value is negatively correlated with the stability, and the baking temperature value is negatively correlated with the stability.

[0181] In this solution, the hardware quality and stability of the optical modem can be quantitatively evaluated through impulse voltage and baking tests, which helps to establish more stringent and scientific quality control standards to ensure that the optical modems put on the market or network have high stability and durability. Before the optical modem is put into actual use, these tests can detect potential hardware problems early, such as insufficient power management and heat dissipation design defects, to prevent problematic optical modems from adversely affecting network stability and user experience.

[0182] In some embodiments, the first acquisition unit includes an acquisition module and a preprocessing module, the acquisition module is used to acquire initial relevant data; the preprocessing module is used to preprocess the above-mentioned initial relevant data to obtain the above-mentioned relevant data, wherein the preprocessing method includes one or more of filling missing values, denoising, normalization, and feature engineering.

[0183] In this solution, preprocessing can reduce problems such as missing data, noise, and inconsistent dimensions, significantly improve the overall quality of data, and provide a more reliable basis for subsequent analysis and decision-making. Data preprocessing eliminates unnecessary interference, allowing the model to more accurately identify abnormal conditions of optical modems or predict their performance. Normalization and feature engineering can also help the model better understand the internal structure of the data and improve the analysis effect.

[0184] The abnormality determination device of the optical modem includes a processor and a memory. The first acquisition unit, the construction unit, the first processing unit, and the second processing unit are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0185] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of high cost of manually checking the optical modem in the prior art can be solved by adjusting the kernel parameters.

[0186] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0187] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned optical modem abnormality determination method.

[0188] An embodiment of the present invention provides a processor, which is used to run a program, wherein the above-mentioned optical modem abnormality determination method is executed when the above-mentioned program is running.

[0189] An embodiment of the present invention provides a device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, at least the steps of the optical modem abnormality determination method are implemented. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0190] A computer program product includes a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the optical modem abnormality determination method in each embodiment of the present application are implemented.

[0191] The present application also provides an optical modem detection system, comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the above-mentioned optical modem abnormality determination methods.

[0192] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0193] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0194] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0195] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0196] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0197] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0198] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0199] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0200] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0201] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining abnormality of an optical modem, characterized in that: include: Obtain relevant data of the optical modem, wherein the relevant data includes one or more of activation state, online state, current light receiving value, current light emitting value, chip temperature, chip current and chip voltage; Constructing an intelligent analysis model, wherein the intelligent analysis model is trained using multiple sets of training data, each set of training data in the multiple sets of training data includes historical related data acquired within a historical time period and historical analysis results corresponding to the historical related data, wherein the historical analysis results are used to characterize whether the optical modem is abnormal within the historical time period; Inputting the relevant data into the intelligent analysis model to obtain analysis results corresponding to the relevant data; When the analysis result indicates that the optical modem is abnormal, a warning message is generated and sent to the target terminal.

2. The method according to claim 1, characterized in that Before obtaining the relevant data of the optical modem, the method further includes: In the case of receiving a detection demand, obtaining a unique code of the optical modem, wherein the optical modem is electrically connected to an optical line terminal, the optical line terminal includes a plurality of service boards, the service board includes a plurality of PON interfaces, the optical modem and the unique code correspond one to one, and the unique code is used to locate the optical modem; When the unique code is obtained, device information is obtained according to the unique code, wherein the device information is location information of the optical line terminal, location information of the service board and the used PON interface.

3. The method according to claim 2, characterized in that Obtain the unique code of the optical modem, including: The unique code is generated according to a first formula, wherein the first formula is: Code=(N OLT ×S max ×P max )+(S×P max )+P+ID ONU , Code represents the unique code, N OLT Indicates the code number of the optical modem in the optical line terminal, S max Indicates the maximum number of service boards, P max Indicates the maximum number of the PON interface, S indicates the position number of the service board used by the optical modem, P indicates the port number of the PON interface used by the optical modem, ID ONU The unique identifier of the optical modem.

4. The method according to claim 2, characterized in that: Obtaining device information according to the unique code includes: According to the second formula, the coding number of the optical modem in the optical line terminal is calculated, wherein the second formula is: N OLT represents the code number of the optical modem in the optical line terminal, Code represents the unique code of the optical modem, S max Indicates the maximum number of service boards, P max Indicates the maximum number of PON interfaces, ID ONU A unique identifier of the optical modem; According to the third formula, the remaining code is calculated, wherein the remaining code is the partial code after removing the influence of the code number of the optical modem in the optical line terminal, and the third formula is: R=Code-(N OLT ×S max ×P max ), R represents the remaining code; According to the fourth formula, the position number of the service board used by the optical modem is calculated, wherein the fourth formula is: S represents the position number of the service board used by the optical modem; According to the fifth formula, the port number of the PON interface used by the optical modem is calculated, wherein the fifth formula is: R ′ =R-(S×P max ), R ′ Represents the port number of the PON interface used by the optical modem.

5. The method according to claim 1, characterized in that Before obtaining the relevant data of the optical modem, the method further includes: Obtaining initial relevant data of the optical modem; According to the sixth formula, the characteristic value of the current optical modem is calculated, wherein the sixth formula is: Z represents the eigenvalue, p represents the position of the optical modem in the feature space, N k (p) represents the k nearest neighbor set of the optical modem, the k nearest neighbor set includes the initial related data of multiple optical modems, r represents the distance from o to p, t represents the average reachable distance of the k nearest neighbor set of o, |N k (p)| represents the set size of k nearest neighbors; The initial relevant data whose characteristic values ​​are not within the normal characteristic range are deleted to obtain the relevant data.

6. The method according to claim 1, characterized in that After obtaining the relevant data of the optical modem, the method further includes: Obtaining an impulse voltage value, wherein the impulse voltage value is a voltage value obtained by performing a current impulse on the optical modem when the optical modem is in a standby state; Obtain a baking machine temperature value, wherein the baking machine temperature value is a temperature value obtained by baking the optical modem when the optical modem is in a standby state; The stability of the optical modem is determined according to the impulse voltage value and the baking temperature value, wherein the fluctuation of the impulse voltage value is negatively correlated with the stability, and the baking temperature value is negatively correlated with the stability.

7. The method according to any one of claims 1 to 6, characterized in that: Get the relevant data of the optical modem, including: Obtaining initial relevant data; The initial relevant data is preprocessed to obtain the relevant data, wherein the preprocessing method includes one or more of filling missing values, denoising, normalization, and feature engineering.

8. An abnormality determination device for an optical modem, characterized in that: include: A first acquisition unit is used to acquire relevant data of the optical modem, wherein the relevant data includes one or more of an activation state, an online state, a current light receiving value, a current light emitting value, a chip temperature, a chip current and a chip voltage; A construction unit, used to construct an intelligent analysis model, wherein the intelligent analysis model is obtained by training using multiple sets of training data, each set of training data in the multiple sets of training data includes historical relevant data obtained in a historical time period and historical analysis results corresponding to the historical relevant data, wherein the historical analysis results are used to characterize whether the optical modem is abnormal in the historical time period; A first processing unit, used for inputting the relevant data into the intelligent analysis model to obtain analysis results corresponding to the relevant data; The second processing unit is used to generate warning information when the analysis result indicates that the optical modem is abnormal, and send the warning information to the target terminal.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for determining an abnormality of an optical modem according to any one of claims 1 to 7 are implemented.

10. An optical modem detection system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing the abnormality determination method of the optical modem described in any one of claims 1 to 7.

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