WiFi radio frequency automatic detection system

Abstract

The invention provides a WiFi radio frequency automatic detection system, and relates to the technical field of WiFi radio frequency detection. Through cooperation of the mechanical arm unit and the automatic control module, full-automatic execution of equipment grabbing, interface butt joint, parameter switching and data acquisition is achieved, and the detection efficiency is remarkably improved; an adjustable attenuator, an interference signal generator and a multi-parameter sensor are arranged in the radio frequency darkroom, a complex electromagnetic environment can be simulated, conditions such as temperature, humidity and air pressure can be monitored in real time, and the reliability of test data is ensured; a spectrum analyzer, a vector signal analyzer, a power meter and a radio frequency switch matrix are integrated, 12 core indexes such as transmitting power, ACLR and EVM are synchronously obtained, and comprehensive quantitative evaluation of radio frequency performance is achieved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of WiFi radio frequency detection, in particular to a WiFi radio frequency automatic detection system. BACKGROUND

[0002] With the rapid development of wireless network technology, WiFi devices have been widely applied to home, enterprise, industry and other scenes, and the radio frequency performance (such as signal strength, spectral purity, anti-interference ability and the like) directly affects the communication quality and user experience. At present, WiFi radio frequency detection mainly relies on manual operation of professional equipment such as spectrum analyzers and signal generators, and the following problems exist: manual configuration of test environment and data recording, single detection lasting for several hours, which is difficult to meet the large-scale production demand; the test methods and environmental parameter controls of different operators are different, resulting in large fluctuations in the detection results; the traditional method is mainly for a single channel or a fixed frequency band, and cannot simulate the radio frequency performance in a complex electromagnetic environment. Therefore, we improve it and propose a WiFi radio frequency automatic detection system. SUMMARY

[0003] The application provides a WiFi radio frequency automatic detection system, which comprises: A mechanical arm unit is configured to automatically grab a WiFi device to be detected and access a test interface, and the mechanical arm unit is provided with a multi-degree-of-freedom motion joint and an end effector. A radio frequency darkroom is configured to provide an electromagnetic shielding environment, and is internally provided with an adjustable attenuator, a multi-protocol interference signal generator and an environmental parameter sensor. A signal acquisition module comprises a spectrum analyzer, a vector signal analyzer, a power meter and a multi-port radio frequency switch matrix, and is configured to acquire the transmission power, frequency deviation, adjacent channel leakage ratio (ACLR), error vector magnitude (EVM) and receiving sensitivity of the device to be detected. An automatic control module is integrated with a PLC controller and an industrial computer, and is configured to communicate with the mechanical arm unit, the radio frequency darkroom and the signal acquisition module through a real-time Ethernet protocol, and execute a preset detection process. A data analysis module is configured to perform real-time analysis on the collected data based on a deep learning model, and output a radio frequency performance score, a fault diagnosis result and an optimization suggestion. A calibration unit is internally provided with a standard signal source and a power attenuator, and is configured to periodically calibrate the accuracy of the signal acquisition module.

[0004] As a preferred technical solution of the application, the end effector of the mechanical arm unit is a gripper, which is configured to grab the WiFi device to be detected.

[0005] As a preferred technical solution of the application, the inner wall of the radio frequency darkroom is covered with a foam wave absorber.

[0006] As a preferred technical solution of the present application, the minimum resolution bandwidth of the spectrum analyzer of the signal acquisition module is 1Hz, the frequency range is DC-50GHz, the sampling rate is ≥200MS / s, and the dynamic range is ≥90dB.

[0007] As a preferred technical solution of the present application, the automatic control module has an open programmable logic controller, supports IEC 61131-3 standard programming language, and connects MES and ERP systems through API interface to realize detection data and production process linkage.

[0008] As a preferred technical solution of the present application, the data analysis module comprises: A data preprocessing unit: filtering, denoising and time synchronization of original collected data, supporting multi-channel data fusion; A feature extraction unit: for extracting key parameters, including transmit power fluctuation, spectral template margin, phase noise, and receive sensitivity threshold; An anomaly detection unit: using an improved isolation forest algorithm, combined with a device model historical database, to identify power amplifier nonlinear distortion, crystal oscillator drift, and antenna standing wave ratio anomaly; A report generation unit: automatically generating a detection report conforming to the CTIA / 3GPP standard, supporting PDF / Excel format export and cloud storage.

[0009] As a preferred technical solution of the present application, the multi-protocol interference signal generator is used to simulate multi-protocol interference sources, including WiFi, Bluetooth, ZigBee, and LTE.

[0010] As a preferred technical solution of the present application, the calibration unit realizes time synchronization with the signal acquisition module through IEEE 1588 PTP protocol, the calibration period is configured as 1-24 hours, and the calibration result is automatically uploaded to the block chain for storage.

[0011] As a preferred technical solution of the present application, the frequency of the environmental parameter sensor of the radio frequency darkroom is 1Hz.

[0012] As a preferred technical solution of the present application, the device to be detected enters the feeding station through the conveyor belt, the mechanical arm unit grasps the device through visual positioning and connects to the radio frequency test interface; the radio frequency darkroom closes the electromagnetic shielding door, the environmental parameter sensor starts monitoring, and the automatic control module calls the preset test scheme according to the device model; The signal acquisition module performs detection in the following order: a. Transmitter performance test: continuous wave power, frequency error, ACLR, EVM, and occupied bandwidth; b. Receiver performance test: sensitivity, maximum input level, adjacent channel selectivity, and blocking characteristics; c. Anti-interference test: repeat steps a-b under preset interference sources; The data analysis module receives the collected data in real time, generates a performance score after comparison with a standard threshold, and starts the abnormal detection unit to locate the fault module if the score is less than 90; The mechanical arm unit classifies the equipment into a qualified area, a rework area or a scrap area, and a detection report is synchronously uploaded to a cloud platform.

[0013] Compared with the prior art, the WiFi radio frequency automatic detection system has the following beneficial effects: In the scheme of the present application, The present application realizes full-automatic execution of equipment grabbing, interface docking, parameter switching and data collection through the cooperation of the mechanical arm unit and the automatic control module, significantly improving the detection efficiency; the adjustable attenuator, the interference signal generator and the multi-parameter sensor built-in the radio frequency darkroom can simulate complex electromagnetic environments and monitor conditions such as temperature, humidity and air pressure in real time, ensuring the reliability of test data; the spectrum analyzer, the vector signal analyzer, the power meter and the radio frequency switch matrix are integrated to synchronously obtain 12 core indicators such as transmit power, ACLR and EVM, realizing comprehensive quantitative evaluation of radio frequency performance. BRIEF DESCRIPTION OF DRAWINGS

[0014] Fig. 1 A schematic diagram of a WiFi radio frequency automatic detection system provided by the present application is shown in the figure; Fig. 2 A structural schematic diagram of a mechanical arm unit provided by the present application is shown in the figure; Fig. 3 A test flowchart of a WiFi radio frequency automatic detection system provided by the present application is shown in the figure.

[0015] Indicated in the figure: DETAILED DESCRIPTION In order to enable personnel in the art to better understand the present application scheme, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0016] It should be noted that the embodiments in the present application and the features and technical solutions in the embodiments can be combined with each other without conflict.

[0017] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0018] Embodiment, please refer to Figs. 1-3 A WiFi radio frequency automatic detection system comprises: A mechanical arm unit 1 is configured to automatically grab a WiFi device to be detected and access a test interface. The mechanical arm unit 1 is provided with a multi-degree-of-freedom motion joint and an end effector 101. Through the multi-degree-of-freedom motion joint and the end effector 101, the mechanical arm unit 1 can flexibly and accurately grab WiFi devices to be detected in different positions and postures and accurately access the test interface, thereby improving the automation degree of detection, reducing errors and time costs caused by manual operation, and improving the detection efficiency. A radio frequency anechoic chamber is configured to provide an electromagnetic shielding environment. The radio frequency anechoic chamber is internally provided with an adjustable attenuator, a multi-protocol interference signal generator, and an environmental parameter sensor (temperature, humidity, and air pressure). The electromagnetic shielding environment can effectively avoid the influence of external electromagnetic interference on the detection results, thereby ensuring the accuracy and reliability of the detection. The adjustable attenuator can flexibly adjust the signal strength, the multi-protocol interference signal generator can simulate various complex interference scenarios, and the environmental parameter sensor can monitor the environmental changes in real time, thereby providing good test conditions for comprehensively and accurately evaluating the radio frequency performance of the WiFi device. A signal acquisition module includes a spectrum analyzer, a vector signal analyzer, a power meter, and a multi-port radio frequency switch matrix. The signal acquisition module is configured to acquire the transmission power, frequency deviation, adjacent channel leakage ratio (ACLR), error vector magnitude (EVM), and receiving sensitivity of the device to be detected. The combination of various professional instruments can comprehensively and accurately acquire various key parameters of the radio frequency performance of the WiFi device, thereby providing rich and accurate data support for subsequent data analysis and performance evaluation, and helping to timely discover potential performance problems of the device. An automatic control module integrates a PLC controller and an industrial computer. The automatic control module communicates with the mechanical arm unit 1, the radio frequency anechoic chamber, and the signal acquisition module through a real-time Ethernet protocol and executes a preset detection process. The automatic control module integrates the PLC controller and the industrial computer and uses the real-time Ethernet protocol to achieve efficient and stable communication and collaborative work among the modules. The automatic control module can automatically execute the detection task according to the preset detection process, thereby improving the standardization and consistency of the detection and reducing the interference of human factors on the detection process. A data analysis module is configured to analyze the collected data in real time based on a deep learning model and output a radio frequency performance score, a fault diagnosis result, and an optimization suggestion. The deep learning model has strong data processing and analysis capabilities and can quickly and accurately analyze a large amount of complex data collected. The data analysis module can output the performance score, the fault diagnosis result, and the optimization suggestion in real time, thereby helping engineers to timely understand the performance status of the device, quickly locate the fault cause, provide a strong basis for optimization and improvement of the device, and shorten the product development and debugging cycle. The calibration unit is internally provided with a standard signal source and a power attenuator, and is used for periodically calibrating the precision of the signal acquisition module, so as to ensure the long-term detection stability; the standard signal source and the power attenuator are used for periodically calibrating the precision of the signal acquisition module, so that the measurement error caused by long-time use, environmental change and other factors of the instrument can be effectively eliminated, the measurement precision of the signal acquisition module can be ensured to be in a stable state, and thus the long-term stability and reliability of the entire detection system are improved; The human-computer interaction unit is further configured with a touch display screen and a physical emergency stop button; the deep learning model of the data analysis module adopts a lightweight convolutional neural network; the lightweight convolutional neural network is adopted as the deep learning model, so that the model calculation amount and resource occupation are reduced while the analysis precision is ensured, and the real-time performance and efficiency of data analysis are improved.

[0019] Further, the end effector 101 of the mechanical arm unit 1 is a gripper, which is used for grabbing the WiFi equipment to be detected; as the end effector, the gripper has simple structure and flexible operation, can adapt to the grabbing requirements of WiFi equipment with different shapes and sizes, ensures the stability and reliability of grabbing, and provides guarantee for subsequent accurate access to test interfaces.

[0020] Further, the inner wall of the radio frequency anechoic chamber is covered with a foam wave absorber; the foam wave absorber can effectively absorb electromagnetic waves in the radio frequency anechoic chamber, reduce the reflection and scattering of electromagnetic waves, further optimize the electromagnetic shielding environment, reduce the interference of reflected waves on detection signals, improve the signal-to-noise ratio of detection signals, and thus improve the accuracy of detection results.

[0021] Further, the minimum resolution bandwidth (RBW) of the spectrum analyzer of the signal acquisition module is 1 Hz, the frequency range is DC-50GHz, the sampling rate is greater than or equal to 200MS / s, and the dynamic range is greater than or equal to 90dB; so that the spectrum analyzer can accurately capture weak signal changes, the wide frequency range can meet the detection requirements of WiFi equipment of different frequency bands, the high sampling rate ensures the real-time performance and accuracy of signal acquisition, and the large dynamic range can adapt to the detection of signals with different intensities, so that the radio frequency signal characteristics of WiFi equipment are comprehensively and accurately obtained.

[0022] Further, the automatic control module has an open programmable logic controller, supports IEC 61131-3 standard programming language, and is connected to MES and ERP systems through an API interface to realize linkage between detection data and production processes; the open programmable logic controller and the support for standard programming language make the automatic control module have higher flexibility and scalability, so that programming and adjustment can be conveniently performed according to different detection requirements; the API interface is used to connect the MES and ERP systems, so that seamless connection and information sharing between detection data and production processes are realized, which is helpful for enterprises to realize intelligent management and decision-making of production processes and improve production efficiency and product quality.

[0023] Further, the data analysis module comprises: The data preprocessing unit filters, denoises and time synchronizes the original collected data, and supports multi-channel data fusion. The data preprocessing unit can effectively remove noise and interference in the original collected data, improve data quality, and the time synchronization and multi-channel data fusion function ensures the consistency and integrity of data from different sources, providing a reliable data basis for subsequent accurate data analysis. The feature extraction unit is used to extract key parameters, including transmit power fluctuation, spectral template margin, phase noise, and receive sensitivity threshold. The feature extraction unit can accurately extract key parameters reflecting the radio frequency performance of WiFi devices from a large amount of data. These parameters can intuitively reflect the performance status of the device, providing an important basis for subsequent performance evaluation and fault diagnosis, and helping to quickly and accurately find potential problems in the device. The anomaly detection unit uses an improved isolation forest algorithm combined with a device model historical database to identify fault modes such as power amplifier nonlinear distortion, crystal oscillator drift, and antenna standing wave ratio anomaly. The improved isolation forest algorithm combined with the device model historical database can more effectively identify various complex fault modes, improving the accuracy and reliability of fault detection. Timely discovery of these fault modes helps engineers take targeted measures to repair and optimize, improving the stability and performance of the device. The report generation unit automatically generates detection reports that meet the CTIA / 3GPP standards, supports PDF / Excel format export and cloud storage, and automatically generates detection reports that meet industry standards, facilitating communication and communication between enterprises and customers, while also meeting industry standard requirements. Support for multiple formats for export and cloud storage makes it easy to view, share and store reports for a long time, improving work efficiency and data management convenience.

[0024] Further, the multi-protocol interference signal generator is used to simulate multi-protocol interference sources, including WiFi, Bluetooth, ZigBee, and LTE. It can simulate interference sources of multiple common protocols, more comprehensively simulate complex interference scenarios that WiFi devices may encounter in actual use environments, and more accurately evaluate the anti-interference performance of the device in complex electromagnetic environments, providing strong support for improving the actual application reliability of the device.

[0025] Further, the calibration unit realizes time synchronization with the signal collection module through the IEEE 1588 PTP protocol, the calibration period is configured to be 1-24 hours, and the calibration result is automatically uploaded to the block chain storage to ensure that the data cannot be tampered with; the IEEE 1588 PTP protocol can realize high-precision time synchronization, ensure the consistency of the calibration unit and the signal collection module in time, and improve the accuracy of calibration; the calibration result is automatically uploaded to the block chain storage, ensuring the authenticity and non-tamperability of the data, and providing a reliable basis for the quality traceability and responsibility identification of the detection system.

[0026] Further, the environmental parameter sensor of the radio frequency darkroom has a collection frequency of 1Hz; the collection frequency of 1Hz can monitor the change of the environmental parameters in the radio frequency darkroom in real time and accurately, timely find the influence of environmental factors on the detection result, and take corresponding measures for adjustment, so that the detection environment is always in a stable state, thereby improving the reliability and consistency of the detection result.

[0027] Further, the equipment to be detected enters the feeding station through the conveying belt, the mechanical arm unit 1 grasps the equipment through visual positioning and is connected to the radio frequency test interface; the radio frequency darkroom closes the electromagnetic shielding door, the environmental parameter sensor starts monitoring, and the automatic control module calls the preset test scheme according to the equipment model; The signal collection module performs detection in the following order: a. transmitter performance test: continuous wave power, frequency error, ACLR, EVM, occupied bandwidth; b. receiver performance test: sensitivity, maximum input level, adjacent channel selectivity, blocking characteristic; c. anti-interference test: repeat steps a-b under a preset interference source (such as-80dBm WiFi same-frequency interference); The data analysis module receives the collected data in real time, generates a performance score (0-100 points) after comparison with the standard threshold, and starts the abnormal detection unit to locate the fault module (such as "PA3 power amplifier output power deficiency") if the score is less than 90; The mechanical arm unit 1 classifies the equipment into the qualified area / rework area / scrap area, and the detection report is synchronously uploaded to the cloud platform.

[0028] In the present application, unless otherwise specified and limited, the terms "mounting", "connection", "connection", "fixing" and the like should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected or in communication with each other; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication or interaction relationship between two elements, unless otherwise specified. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0029] Obviously, the above-described embodiments are only some embodiments but not all the embodiments of the present application, the preferred embodiments of the present application are shown in the drawings, but do not limit the patent scope of the present application. The present application can be implemented in many different forms, and conversely, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing specific embodiments, or make equivalent replacements to some technical features therein. Any equivalent structure made by using the content of the present application specification and drawings, directly or indirectly applied to other related technical fields, is also within the patent protection scope of the present application.

Claims

1. A WiFi radio frequency automatic detection system, characterized in that: include: A robotic arm unit (1) is used to automatically grab a WiFi device to be tested and connect it to a test interface, wherein the robotic arm unit (1) is configured with a multi-degree-of-freedom motion joint and an end effector (101); RF darkroom, used to provide an electromagnetic shielding environment, with built-in adjustable attenuator, multi-protocol interference signal generator and environmental parameter sensor; The signal acquisition module includes a spectrum analyzer, vector signal analyzer, power meter, and multi-port RF switch matrix, which is used to collect the transmit power, frequency deviation, adjacent channel leakage ratio (ACLR), error vector magnitude (EVM), and receiving sensitivity of the device under test; An automation control module, integrating a PLC controller and an industrial computer, communicates with the robotic arm unit (1), the radio frequency darkroom, and the signal acquisition module via a real-time Ethernet protocol to execute a preset detection process; The data analysis module analyzes collected data in real time based on a deep learning model, outputting RF performance scores, fault diagnosis results, and optimization suggestions; The calibration unit has a built-in standard signal source and power attenuator to regularly calibrate the accuracy of the signal acquisition module.

2. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The end effector (101) of the mechanical arm unit (1) is a gripper, and the gripper is used to grasp the WiFi device to be detected.

3. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The inner wall of the radio frequency darkroom is covered with a foam absorber.

4. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The spectrum analyzer of the signal acquisition module has a minimum resolution bandwidth of 1 Hz, a frequency range of DC-50 GHz, a sampling rate of ≥200 MS / s, and a dynamic range of ≥90 dB.

5. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The automation control module has an open programmable logic controller, supports the IEC 61131-3 standard programming language, and connects to the MES and ERP systems through the API interface to realize the linkage between detection data and production processes.

6. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The data analysis module includes: Data preprocessing unit: Filters, removes noise and synchronizes time for the original collected data, and supports multi-channel data fusion; Feature extraction unit: used to extract key parameters, including transmit power fluctuation, spectrum mask margin, phase noise, and receive sensitivity threshold; Anomaly detection unit: uses an improved isolation forest algorithm, combined with a historical database of equipment models, to identify power amplifier nonlinear distortion, crystal oscillator drift, and antenna standing wave ratio anomalies; Report generation unit: Automatically generates test reports that comply with CTIA / 3GPP standards, supports PDF / Excel format export and cloud storage.

7. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The multi-protocol interference signal generator is used to simulate a multi-protocol interference source, which includes WiFi, Bluetooth, ZigBee, and LTE.

8. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The calibration unit achieves time synchronization with the signal acquisition module through the IEEE 1588 PTP protocol. The calibration period is configured to be 1-24 hours, and the calibration results are automatically uploaded to the blockchain for evidence storage.

9. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The environmental parameter sensor acquisition frequency of the radio frequency darkroom is 1 Hz.

10. The WiFi radio frequency automatic detection system according to claim 1, characterized in that: The device to be tested enters the loading station via a conveyor belt, and the robotic arm unit (1) grasps the device through visual positioning and connects it to the radio frequency test interface; the electromagnetic shielding door of the radio frequency darkroom is closed, the environmental parameter sensor starts monitoring, and the automatic control module calls the preset test plan according to the device model; The signal acquisition module performs tests in the following order: a. Transmitter performance test: continuous wave power, frequency error, ACLR, EVM, occupied bandwidth; b. Receiver performance test: sensitivity, maximum input level, adjacent channel selectivity, and blocking characteristics; c. Anti-interference test: Repeat steps a and b under the preset interference source; The data analysis module receives the collected data in real time, compares it with the standard threshold, and generates a performance score. If the score is less than 90 points, the anomaly detection unit is activated to locate the fault module. The robotic arm unit (1) classifies the equipment into qualified area / rework area / scrap area, and the inspection report is uploaded to the cloud platform simultaneously.

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