Tail fiber parameter testing method and system

Abstract

The invention discloses a tail fiber parameter testing method and system, and the method comprises the steps: placing a tail fiber in a transmission module, and enabling the tail fiber to be connected to a detection module through the transmission module; a detection unit is arranged in the detection module and comprises an imaging unit, a light source unit and an interferometer unit; when a tail fiber is connected to the detection module through the transmission module, the imaging unit, the light source unit and the interferometer unit perform data acquisition on the tail fiber at the same time. The collected data are uploaded to an analysis module, and the analysis module carries out comprehensive analysis on the tail fiber through the data; and uploading an analysis result to the terminal for storage. By introducing automatic detection, manpower and time cost are greatly saved, human errors are effectively reduced, key indexes such as a tail fiber end face image, insertion loss and return loss can be obtained at the same time by integrating the imaging unit, the light source unit and the interferometer unit through the detection module, comprehensive evaluation of the tail fiber performance is achieved, and the detection efficiency is improved. And the data accuracy and consistency are ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of pigtail detection, and in particular relates to a pigtail parameter testing method and system. Background Art

[0002] With the rapid advancement of fiber optic communication technology, the performance and quality of fiber pigtails (such as patch cords and pigtails) are crucial to link stability. To ensure fiber performance, traditional production requires multiple inspections before shipment, including insertion loss and return loss testing, end-face cleanliness, and geometry inspection. Traditional inspections often involve a series of instruments: end-face inspection using a microscope or 3D interferometer, insertion loss measurement using a light source and optical power meter, and return loss measurement using an interferometer. These testing steps are fragmented and complex, requiring high operator skills. Existing testing equipment with low levels of automation still requires manual insertion of each fiber core into a test head and post-test sorting of qualified / unqualified fibers, resulting in wasted labor and increased production costs. Furthermore, manual visual assessment of end-face quality is highly subjective and prone to misjudgment due to experience. This results in inefficient batch data collection and analysis, long overall inspection times, and a high misjudgment rate, making it difficult to meet the automated production requirements of modern factories. Summary of the Invention

[0003] In view of the above-mentioned defects in the prior art, an object of the present invention is to provide a method and system for testing pigtail parameters.

[0004] The technical solution of the present invention: A method for testing fiber pigtail parameters, comprising a transmission module, a detection module, an analysis module and a terminal, and the method steps include: S1: placing the fiber pigtail into the transmission module, and connecting the fiber pigtail to the detection module through the transmission module; S2: arranging a detection unit in the detection module, comprising an imaging unit, a light source unit and an interferometer unit; collecting the end face image of the fiber pigtail through the imaging unit; collecting the output and input power of the fiber pigtail through the light source unit; collecting the reflected signal intensity of the end face of the fiber pigtail through the interferometer unit; S3: when the fiber pigtail is connected to the detection module through the transmission module, the imaging unit, the light source unit and the interferometer unit all collect data on the fiber pigtail at the same time; S4: uploading the data collected in S3 to the analysis module, and the analysis module performs a comprehensive analysis on the fiber pigtail through the data; S5: uploading the results obtained by the analysis in S4 to the terminal for storage.

[0005] Furthermore, the imaging unit includes a high-definition camera; the high-definition camera captures the end face image of the pigtail and optimizes the clarity of the end face image; the pollution on the surface of the pigtail is identified in the optimized image; the pollution level is evaluated according to the type and distribution of the pollutants; a pollution threshold is set, and the final detection result and the end face image are output based on the comparison of the pollution level with the pollution threshold.

[0006] Furthermore, the light source unit includes a first light source and an optical power meter; one end of the fiber pigtail is connected to the first light source, and the other end is connected to the optical power meter; the first light source emits an optical signal, which reaches the optical power meter through the fiber pigtail; the output power of the first light source and the input power of the optical power meter are measured; the measured data are uploaded to the analysis module; and the insertion loss value of the fiber pigtail is calculated using the output power and the input power.

[0007] Furthermore, the interferometer unit includes an interferometer and a second light source; the second light source emits a light signal; the interferometer receives the light signal reflected from the end face of the pigtail; the output power of the second light source and the input power of the reflected light signal received by the interferometer are measured; and the return loss value of the pigtail is calculated using the output power and the input power.

[0008] Furthermore, the analysis module includes at least one AI server equipped with a pre-trained machine learning model for automatically analyzing and judging the images and parameter data collected by the detection unit.

[0009] A pigtail parameter testing system includes a transmission module, a detection module, an analysis module and a terminal. The pigtail parameter testing method steps described above are executed during the pigtail parameter testing. It is characterized in that the transmission module is used to transport the required pigtail; the detection module includes an imaging unit, a light source unit and an interferometer unit, which are used to collect the pigtail parameters; the analysis module is used to perform a comprehensive analysis of the pigtail based on the collected data parameters; and the terminal is used to record the results of the analysis obtained by the analysis module.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] 1) The present invention introduces automated detection. Existing end face detection often requires manual plugging and unplugging of each wire and visual judgment, which is inefficient and has a high error rate. This system realizes a fully automatic process from sample loading, plugging and unplugging testing to judgment, which greatly saves manpower and time costs and effectively reduces human errors.

[0012] 2) The present invention integrates an imaging unit, a light source unit, and an interferometer unit through a detection module, which can simultaneously obtain key indicators such as the pigtail end face image, insertion loss, and return loss, thereby achieving a comprehensive evaluation of the pigtail performance and ensuring data accuracy and consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of the steps of a method for testing pigtail parameters of the present invention;

[0014] Figure 2 This is a flow chart of the steps of end face detection of a pigtail parameter testing method of the present invention;

[0015] Figure 3 This is a flow chart of the steps of insertion loss testing of a pigtail parameter testing method of the present invention;

[0016] Figure 4 This is a flow chart of the steps of return loss testing of a pigtail parameter testing method of the present invention;

[0017] Figure 5 It is a structural diagram of a pigtail parameter testing system of the present invention;

[0018] 10-transmission module, 20-detection module, 30-analysis module, 40-terminal, 21-imaging unit, 22-light source unit, 23-interferometer unit, 211-HD camera, 221-first light source, 222-optical power meter, 231-second light source, 232-interferometer DETAILED DESCRIPTION

[0019] The embodiments of the present invention are described in detail below. The following embodiments are implemented based on the technical solutions of the present invention, and provide detailed implementation methods and specific operating procedures. However, the protection scope of the present invention is not limited to the following embodiments.

[0020] The present invention discloses a method and system for testing pigtail parameters. Figure 1 As shown, a flowchart of a method for testing pigtail parameters is shown, including a transmission module 10, a detection module 20, an analysis module 30 and a terminal 40. The method steps include:

[0021] S1: placing the pigtail into the conveying module 10, and connecting the pigtail to the detection module 20 through the conveying module 10. The conveying module 10 is a robotic arm, conveyor belt or fiber switch for automatically loading / unloading pigtail samples to achieve batch processing;

[0022] S2: A detection unit including an imaging unit 21, a light source unit 22 and an interferometer unit 23 is provided in the detection module 20; the end face image of the pigtail is collected by the imaging unit 21; the output and input power of the pigtail is collected by the light source unit 22; and the reflection signal intensity of the pigtail end face is collected by the interferometer unit 23;

[0023] S3: When the pigtail is connected to the detection module 20 through the transmission module 10, the imaging unit 21, the light source unit 22 and the interferometer unit 23 simultaneously collect data from the pigtail;

[0024] S4: Uploading the data collected in S3 to the analysis module 30, which performs a comprehensive analysis of the pigtail using the data. The analysis module 30 includes at least one AI server equipped with a pre-trained machine learning model for automatically analyzing and judging the images and parameter data collected by the detection unit. The AI ​​system uses an image classification model to identify the end face quality grade, uses a loss prediction model to evaluate the insertion loss performance, and determines whether there is an abnormality based on a preset threshold or model result.

[0025] S5: Upload the analysis result obtained in S4 to the terminal 40 for storage.

[0026] like Figure 2 As shown, a flowchart of the steps of end face detection of a pigtail parameter testing method is shown. The imaging unit 21 includes a high-definition camera 231, which is composed of a high-resolution microscope camera or a CCD / CMOS camera to capture the pigtail end face image in real time;

[0027] The high-definition camera 231 captures the end face image of the pigtail and performs clarity optimization processing on the end face image; the clarity optimization includes sharpening, denoising, exposure, and contrast adjustment, and applies image enhancement algorithms (such as high-frequency enhancement and Laplace sharpening) to improve the end face contour clarity; uses filters (such as median filtering and Gaussian filtering) to remove background noise and highlight features such as contamination and scratches; and dynamically adjusts exposure time and contrast to highlight end face defects.

[0028] Gaussian filter formula:

[0029]

[0030] Convolution processing to remove high-frequency noise

[0031] Identifying contamination on the surface of the pigtail using the optimized image; and assessing the contamination level based on the type and distribution of the contaminants.

[0032] The collected end-face images are subjected to feature extraction and classification using a deep convolutional neural network. The model can automatically identify defects such as scratches, cracks, pits, and contamination:

[0033]

[0034] Where I is the input image, K is the convolution kernel, and the end face features are extracted by stacking convolution layers and adding residual connections.

[0035] Set a contamination threshold, compare the contamination level with the contamination threshold, and classify the end face into different grades (such as A / B / C) according to the TIA standard or training data. Compared with manual visual inspection, AI classification is fast and highly consistent, which can avoid subjective misjudgment and output the final inspection results and end face images;

[0036] By introducing automated detection, the present invention realizes a fully automatic process from sample loading, plug-in and plug-out testing to judgment, which greatly saves manpower and time costs and effectively reduces human errors.

[0037] like Figure 3 As shown, a flowchart of the insertion loss test steps of a pigtail parameter test method is shown. The light source unit 22 includes a first light source 221 and an optical power meter 222. The light source can be a laser.

[0038] One end of the pigtail is connected to the first light source 221, and the other end is connected to the optical power meter 222;

[0039] The first light source 221 transmits an optical signal, which reaches the optical power meter 222 via the pigtail;

[0040] Measuring the output power of the first light source 221 and the input power of the optical power meter 222;

[0041] Uploading the measured data to the analysis module 30;

[0042] The insertion loss value of the pigtail is calculated by the output power and the input power. When calculating, the input power (P in ) and the output power to the pigtail (P out ):

[0043]

[0044] The insertion loss of the pigtail is calculated according to the formula. For example, if the input power is 0dBm (1mW) and the output power is -0.5dBm (about 0.89mW), then the IL is approximately equal to 0.5dB.

[0045] like Figure 4 As shown, a flow chart of the steps of a pigtail parameter test method return loss test is shown, including an interferometer 232 and a second light source 231. The interferometer 232 can use a white light interferometer or an optical profiler. A reference pigtail (with known return loss) is connected to the input end of the interferometer 232, and the reference echo signal strength is recorded to establish a benchmark.

[0046] Connect the fiber pigtail to be tested to the optical path of the interferometer, and the second light source 231 emits an optical signal, and the second light source 231 can be a laser;

[0047] The interferometer 232 receives the optical signal reflected from the end face of the pigtail, and part of the light is reflected back by the end face of the pigtail;

[0048] The interferometer measures the intensity of the reflected light by superimposing the interference signals, and measures the output power of the second light source 231 and the input power of the reflected light signal received by the interferometer 232. The system automatically reads the reflected light power (P r ) and the transmitted optical power (P i );

[0049] Calculate the return loss value of the pigtail using the output power and the input power

[0050]

[0051] The unit is dB. A larger value indicates smaller reflection and better quality. For example, if RL=55dB is measured, it indicates a high-quality end face. The system determines that the pigtail return loss value is qualified.

[0052] like Figure 5 As shown, a structural diagram of a fiber pigtail parameter testing system is shown, including a transmission module 10, a detection module 20, an analysis module 30 and a terminal 40. The fiber pigtail parameter testing method steps described above are executed during the fiber pigtail parameter testing, and is characterized in that the transmission module 10 is used to transport the required fiber pigtail; the detection module 20 includes an imaging unit 21, a light source unit 22 and an interferometer unit 23, which are used to collect the fiber pigtail parameters; the analysis module 30 is used to perform a comprehensive analysis of the fiber pigtail based on the collected data parameters; and the terminal 40 is used to record the results obtained by the analysis module 30.

[0053] The present invention integrates the imaging unit 21, the light source unit 22 and the interferometer unit 23 through the detection module 20, which can simultaneously obtain key indicators such as the pigtail end face image, insertion loss and return loss, so as to achieve a comprehensive evaluation of the pigtail performance and ensure data accuracy and consistency.

[0054] In summary, the principle of a pigtail parameter testing method and system is as follows:

[0055] The pigtail to be tested is placed in the transmission module 10 and sent to the detection module 20 through the transmission module 10. At this time, the detection unit in the detection module 20 simultaneously detects the pigtail to be tested, including the pigtail end face image detection by the imaging unit 21, the insertion loss detection by the light source unit 22, and the return loss detection by the interferometer unit 23. The data collected by the detection module 20 is uploaded to the analysis module 30, and the pigtail is comprehensively analyzed through calculation. Finally, the results are fed back to the terminal 40 to complete the test of the pigtail parameters.

[0056] The following describes the detection process with reference to an embodiment. In this embodiment, a single-mode pigtail sample is sequentially inserted into the detection system. After the imaging unit 21 captures the end-face image, the model analysis determines that the end-face has no obvious scratches or contamination, and the end-face is rated as "excellent." The optical power meter 222 measures the sample's insertion loss as 0.18dB and return loss as -58dB (meeting telecommunications-grade standards). The analysis module 30 determines that the loss is normal based on the model and threshold. The overall results show that the sample is fully qualified.

[0057] Another embodiment is a batch detection scenario: suppose the system continuously detects ten pigtails, and the detection data of the fifth sample is an insertion loss of 0.35dB and a return loss of -40dB, and the end face image shows that the vertex offset exceeds the standard. The analysis module 30 immediately identifies it as "unqualified". The measured data is transmitted to the terminal 40 to alarm and the sample is automatically sent to the unqualified product collection area, and the operator is prompted to re-inspect or discard the pigtail. Other qualified samples are automatically classified into qualified channels. During the entire process, no manual judgment is required, and the time to complete the entire process is significantly shortened.

[0058] The above describes in detail the preferred embodiments of the present invention. It should be understood that numerous modifications and variations based on the concepts of the present invention are possible by those skilled in the art without inventive effort. Therefore, any technical solution that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A method for testing pigtail parameters, comprising a transmission module, a detection module, an analysis module and a terminal, characterized in that: The method steps include: S1: placing the pigtail into the transmission module, and connecting the pigtail to the detection module through the transmission module; S2: A detection unit including an imaging unit, a light source unit, and an interferometer unit is provided in the detection module; the end face image of the pigtail is collected by the imaging unit; the output and input power of the pigtail is collected by the light source unit; and the reflection signal intensity of the end face of the pigtail is collected by the interferometer unit; S3: When the pigtail is connected to the detection module through the transmission module, the imaging unit, the light source unit and the interferometer unit all simultaneously collect data from the pigtail; S4: uploading the data collected in S3 to the analysis module, and the analysis module performs a comprehensive analysis on the pigtail based on the data; S5: Upload the analysis result obtained in S4 to the terminal for storage.

2. The method for testing pigtail parameters according to claim 1, wherein: The imaging unit includes a high-definition camera; the high-definition camera collects the end face image of the pigtail and performs definition optimization processing on the end face image; Identifying contamination on the surface of the pigtail using the optimized image; and assessing the contamination level based on the type and distribution of the contaminants. A pollution threshold is set, and the pollution level is compared with the pollution threshold; and a final detection result and an end face image are output.

3. The method for testing pigtail parameters according to claim 1, wherein: The light source unit includes a first light source and an optical power meter; one end of the fiber pigtail is connected to the light source, and the other end is connected to the optical power meter; the first light source transmits an optical signal, which reaches the optical power meter through the fiber pigtail; and the output power of the first light source and the input power of the optical power meter are measured; The measured data is uploaded to the analysis module; and the insertion loss value of the pigtail is calculated according to the output power and the input power.

4. The method for testing pigtail parameters according to claim 1, wherein: The interferometer unit includes an interferometer and a second light source; the second light source emits a light signal; the interferometer receives the light signal reflected from the end face of the pigtail; the output power of the second light source and the input power of the reflected light signal received by the interferometer are measured; and the return loss value of the pigtail is calculated based on the output power and the input power.

5. The method for testing pigtail parameters according to claim 1, wherein: The analysis module includes at least one AI server equipped with a pre-trained machine learning model for automatically analyzing and judging the images and parameter data collected by the detection unit.

6. A pigtail parameter testing system, comprising a transmission module, a detection module, an analysis module and a terminal, wherein the pigtail parameter testing method according to any one of claims 1 to 5 is performed during the pigtail parameter testing, characterized in that: The transport module is used to transport the pigtail; The detection module includes an imaging unit, a light source unit and an interferometer unit, which are used to collect the pigtail parameters; The analysis module is used to perform a comprehensive analysis on the pigtail according to the collected data parameters; The terminal is used to record the analysis results obtained by the analysis module.

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