A detection method, device, medium and product

Abstract

The application discloses a kind of detection method, equipment, medium and product.It relates to mobile communication indoor distribution network operation and maintenance technical field, the method comprises: the radio frequency data of indoor device to be measured is collected by unmanned aerial vehicle;According to preset gain compensation value, the frequency spectrum information of forward signal, target distance, space propagation path loss amount and multipath interference compensation amount, the reflection power of the device to be measured is handled, and the processed reflection power of the device to be measured is obtained;According to the forward power of device to be measured, the processed reflection power of device to be measured, preset feeder loss value and preset joint loss value, the insertion loss of device to be measured is determined;According to the forward power of device to be measured and the processed reflection power, the return loss of device to be measured is determined;According to the return loss of device to be measured, the voltage standing wave ratio of device to be measured is determined;According to the insertion loss of device to be measured, the return loss of device to be measured and the voltage standing wave ratio of device to be measured, the detection result of device to be measured is determined.

Description

Technical Field

[0001] This invention relates to the field of mobile communication indoor distributed network operation and maintenance technology, and in particular to a detection method, device, medium and product. Background Technology

[0002] In-Building Distribution Systems (IBDS) are critical infrastructure for deep coverage in mobile communication networks, and their performance directly impacts user experience and network quality. Passive components, such as power dividers, couplers, combiners, and antennas, act as the "nerve endings" of the system, and their stable and accurate operation is crucial for ensuring uniform and efficient network signal distribution. However, current methods for testing and maintaining these passive components are lagging behind, failing to meet the high-density, high-reliability network operation and maintenance requirements of the 5G era.

[0003] Currently, mainstream testing methods heavily rely on manual operation, which presents numerous bottlenecks. Maintenance personnel must carry specialized equipment such as VSWR testers, network analyzers, and handheld frequency sweepers to conduct on-site near-end testing. This process typically involves working at heights, which is not only labor-intensive and inefficient but also poses significant personal safety risks. More importantly, to obtain accurate device specifications, technicians often need to disconnect the feeder connection and connect the instruments directly to the device port for offline testing. This "disassembly testing" mode inevitably causes service interruptions in localized areas, affecting user communication and potentially negatively impacting the operator's service level agreement. Furthermore, the results of manual testing are susceptible to environmental interference, instrument accuracy, and personnel skill levels, leading to low accuracy. Summary of the Invention

[0004] This invention provides a detection method, device, medium, and product that can improve detection accuracy and efficiency while ensuring network reliability.

[0005] According to one aspect of the present invention, a detection method is provided, comprising: Radio frequency (RF) data of the device under test (DUT) is collected indoors by a drone. The RF data includes forward power, reflected power, and spectral information of the forward signal. Based on the preset gain compensation value, the spectrum information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, the reflected power of the device under test is processed to obtain the processed reflected power of the device under test. The target distance is the distance between the acquisition position and the device under test, and the acquisition position is the position where the UAV acquires the radio frequency data of the device under test. The insertion loss of the device under test is determined based on the forward power of the device under test, the processed reflected power of the device under test, the preset feeder loss value, and the preset connector loss value. The return loss of the device under test is determined based on the forward power and the processed reflected power. Determine the voltage standing wave ratio (VSWR) of the device under test (DUT) based on its return loss. The test results of the device under test (DUT) are determined based on its insertion loss, return loss, and voltage standing wave ratio (VSWR).

[0006] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and a memory communicatively connected to said at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the detection method described in any embodiment of the present invention.

[0007] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the detection method described in any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer program product is provided, which, when executed by a processor, implements the detection method as described in any of the embodiments of the present invention.

[0009] This invention utilizes a drone to collect radio frequency data from an indoor device under test (DUT). Based on a preset gain compensation value, the spectral information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, the reflected power of the DUT is processed to obtain the processed reflected power. The insertion loss of the DUT is determined based on its forward power, the processed reflected power, a preset feeder loss value, and a preset connector loss value. The return loss of the DUT is determined based on its forward power and the processed reflected power. The voltage standing wave ratio (VSWR) of the DUT is determined based on its return loss. Finally, the detection result of the DUT is determined based on its insertion loss, return loss, and VSWR. This invention addresses the problems of high labor intensity, low efficiency, and significant personal safety risks associated with manual operation, improving detection accuracy and efficiency while ensuring network reliability.

[0010] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart of a detection method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0014] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0015] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0016] Example 1 Figure 1This is a flowchart of a detection method provided by an embodiment of the present invention. This embodiment is applicable to the detection of devices under test. The method can be executed by the detection device in this embodiment, which can be implemented in software and / or hardware, such as... Figure 1 As shown, the method specifically includes the following steps: The S110 uses a drone to collect radio frequency data from indoor devices under test.

[0017] The radio frequency data includes: forward power, reflected power, and spectral information of the forward signal.

[0018] In this embodiment, the method of collecting raw radio frequency data of devices under test (DUTs) within the entire area using a drone can be as follows: An indoor 3D digital twin model is constructed based on indoor architectural drawings, an indoor distribution system topology diagram, and a DUT inventory. The DUT inventory includes: DUT identifier, the type corresponding to the DUT identifier, installation location, height, and port orientation. Based on the indoor 3D digital twin model, sampling points corresponding to each DUT are determined. Path planning is performed based on the sampling points corresponding to each DUT to obtain a target flight path. The drone is then controlled to collect the radio frequency data of the indoor DUTs based on the target flight path.

[0019] Optionally, raw radio frequency data of the device under test can be collected across the entire area using a drone, including: Based on the indoor architectural drawings, indoor distribution system topology diagram, and the list of devices under test, a three-dimensional digital twin model of the indoor space is constructed.

[0020] The device under test (DUT) register includes: DUT identifier, type, installation location, height, and port orientation.

[0021] In this embodiment, a UAV radio frequency acquisition and detection system is pre-built, using a small indoor multi-rotor UAV as the carrier platform. It is equipped with a three-dimensional visual obstacle avoidance, inertial navigation, and indoor high-precision positioning unit to ensure that the UAV's hovering accuracy is better than ±0.1m in an indoor environment without satellite signals. The UAV payload platform is equipped with a lightweight, wide-band, low-power radio frequency acquisition module. The module weighs ≤350g, operates in a frequency band covering 800MHz-6GHz, has a receiving sensitivity ≤-100dBm, a noise figure NF ≤3.5dB, and a linear dynamic range ≥70dB. It can simultaneously complete the real-time acquisition of signal power, reflection components, phase information, and spectral characteristics, and has the characteristics of high sensitivity, low noise, and wide linear range. The RF acquisition module employs a directional dual-antenna orthogonal receiving architecture. The main lobe of the antenna receives the forward signal transmitted along the feed line, while the side lobes receive the reverse echo signal reflected by the device. Combining directional coupling and time-domain gated filtering algorithms, non-contact separation and measurement of the reflected components are achieved. Simultaneously, an orthogonal I / Q demodulation architecture is used to perform orthogonal down-conversion on the RF signal, acquiring the in-phase component I and the quadrature component Q, and calculating and acquiring phase information in real time. The module can simultaneously complete real-time acquisition of signal power, reflected components, phase information, and spectral characteristics, meeting the testing requirements of multi-system, multi-band passive devices in indoor distribution systems. A wireless data backhaul link is established between the UAV, the ground control terminal, and the backend server to achieve real-time transmission of acquired RF data, UAV position and attitude information, device operating status, acquisition timestamps, and other information. It also supports remote task scheduling, parameter configuration, and command issuance. The RF acquisition module undergoes power-on self-test, zero-point drift correction, and overall gain calibration: After power-on, the RF acquisition module outputs a zero-level reference signal through its internal reference source. It then performs DC bias acquisition and mean subtraction on the reflected echo signal received from the receiving channel to complete zero-point drift correction. By connecting an onboard standard calibration signal source, a standard reference signal with known power is input to the RF channel. A gain error correction table is established by comparing measured and theoretical values, enabling real-time calibration of the channel gain across the entire frequency band and power range. Simultaneously, key operating parameters such as sampling rate, number of sampling points, number of multiple averaging operations, operating frequency band, and reference power are configured to eliminate system errors introduced by the hardware itself, ensuring the accuracy and consistency of the acquired data.

[0022] In a specific example, a small multi-rotor UAV platform suitable for enclosed indoor environments is selected. This UAV adopts a hexacopter structure, with a maximum size of ≤350mm×350mm×120mm, a minimum passable gap width of ≥400mm, a maximum climb speed of 3m / s, a maximum descent speed of 2m / s, a maximum horizontal flight speed of 5m / s, and an unloaded endurance of ≥35min. It possesses the capabilities for low-altitude maneuvering, automatic obstacle avoidance, and long-term stable flight. The UAV is equipped with an inertial measurement unit (IMU), a visual obstacle avoidance module, and an indoor fusion positioning module. The indoor fusion positioning module adopts a tightly coupled fusion positioning scheme of visual SLAM + LiDAR + inertial navigation. It collects indoor environmental feature points through visual sensors, constructs a 3D point cloud map through LiDAR, and provides high-frequency attitude and position estimation through the inertial navigation unit. The three are tightly coupled and jointly solved, which can achieve continuous, stable and high-precision positioning in complex indoor scenarios such as ceilings, pipe corridors, weak current shafts and enclosed corridors without satellite signals. It ensures that the UAV can still achieve stable hovering and accurate positioning in the absence of satellite signals, with a hovering positioning error of no more than 0.1m. It has the ability to pass through low altitudes, avoid obstacles and fly stably for a long time.

[0023] In this embodiment, based on indoor building CAD drawings, indoor distribution system topology diagrams, and a list of devices under test (including a passive device installation list), an indoor three-dimensional digital twin model is constructed, which includes the distribution of walls, ceilings, floors, pipes, equipment, and obstacles. In the indoor three-dimensional digital twin model, various devices under test, such as power dividers, couplers, antennas, and combiners, are uniformly labeled, and the device number, type, installation location, height, and port orientation are clearly defined.

[0024] In a specific example, the ICP iterative nearest-point algorithm is used to accurately match the indoor 3D point cloud data collected by LiDAR with the outline of CAD drawings. Using building structure corners, ceiling access panels, and column centers as reference control points, coordinate unification and mapping are achieved among the world coordinate system, the UAV body coordinate system, and the CAD drawing coordinate system. A rigid transformation matrix is ​​used to achieve spatial registration of multi-source data, ultimately constructing an indoor 3D digital twin model that includes the distribution of walls, ceilings, floors, pipes, equipment, and obstacles. The minimum modeling accuracy is no less than 0.05m, achieving a precise correspondence between the physical scene and the virtual model.

[0025] It should be noted that all devices under test are uniformly identified and numbered in the indoor 3D digital twin model, including power dividers, couplers, combiners, indoor antennas, loads, etc. The device type, installation location, installation height, port orientation, coverage direction and design specifications are clearly marked to form a structured and searchable device information database.

[0026] Based on the indoor three-dimensional digital twin model, the sampling points corresponding to each device under test are determined.

[0027] In this embodiment, an optimal acquisition point is set for each device under test based on the indoor three-dimensional digital twin model, and the distance between the acquisition point and the radiation port surface of the device is controlled within the range of 0.5m–1.5m, and the angle between the incident angle and the device normal is not greater than 15°.

[0028] Path planning is performed based on the sampling points corresponding to each device under test to obtain the target route.

[0029] In this embodiment, a collision-free flight path is generated based on an improved path planning algorithm; collision detection and coverage verification are performed on the collision-free flight path, and after confirming that there are no errors, the collision-free flight path is used as the target flight path.

[0030] The drone is controlled to collect radio frequency data of the indoor device under test based on the target flight path.

[0031] In this embodiment, a patrol start command is issued via a ground control terminal. The UAV automatically takes off and cruises along the target route, arriving at each collection point sequentially before entering a stable hovering state. The UAV's onboard RF acquisition module is equipped with a directional receiving antenna array, a directional coupler module, and a dual-channel synchronous acquisition unit. It employs a non-contact near-field coupling detection method, using spatial beamforming to distinguish between the incident forward RF signal and the reflected echo signal. Combined with orthogonal demodulation and time-domain gated filtering algorithms, it achieves non-contact separation of forward power and reflected power. The RF acquisition module automatically starts working, employing a directional dual-antenna orthogonal receiving architecture. Through antenna pattern differences and dual-channel synchronous acquisition, it achieves non-contact separation measurement of forward power and reflected power. The forward signal is transmitted using a directional antenna with the main lobe pointing towards the device's transmission direction, and the reverse echo signal formed by the device's reflection is received using the side lobes / back lobes. Combined with time-domain gated filtering and orthogonal phase demodulation algorithms, the signal transmission direction is distinguished, and the forward power and reflected power are extracted. The system continuously collects N sets (N≥5) of raw RF data from the device under test (DUT). The collected data includes forward power, reflected power, spectrum information, and timestamps after separation and processing. Simultaneously, it records the UAV's three-dimensional coordinates, altitude, device ID, ambient temperature, and module operating status at the time of collection, forming a complete raw dataset with spatiotemporal correlation. The system performs arithmetic averaging on multiple sets of collected data from the same sampling point to output stable and reliable RF data. After completing the collection of RF data from all DUTs in the room, the UAV automatically returns to base and uploads the collected RF data from the DUTs in the room to the backend processing server.

[0032] In this embodiment, the reflected power collected multiple times from the same sampling point needs to be arithmetically averaged to eliminate the influence of instantaneous fluctuations and obtain a stable and reliable reflected power. The calculation method is as follows: ; in, For the number of data collections, ≥5, For the first The reflected power of the sampled sample.

[0033] S120: Based on the preset gain compensation value, the spectrum information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, the reflected power of the device under test is processed to obtain the processed reflected power of the device under test.

[0034] Wherein, the target distance is the distance between the acquisition location and the device under test, and the acquisition location is the position where the UAV acquires the radio frequency data of the device under test.

[0035] Optionally, the reflected power of the device under test is processed based on a preset gain compensation value, the spectral information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, to obtain the processed reflected power of the device under test, including: The sum of the preset gain compensation value and the reflected power of the device under test is taken as the first reflected power.

[0036] In this embodiment, the reflected power of the device under test is calibrated using hardware gain calibration to eliminate the systematic error caused by the gain deviation of the RF acquisition module itself, thus obtaining the calibrated reflected power, which is the first reflected power: in, This is the preset gain compensation value calibrated at the module's factory. The reflected power of the device under test is denoted as .

[0037] The carrier wavelength is determined based on the spectral information of the forward signal.

[0038] In this embodiment, the carrier wavelength can be determined based on the spectral information of the forward signal by performing spectral analysis on the forward signal, extracting the carrier center frequency, and determining the carrier wavelength based on the carrier center frequency.

[0039] The distance loss is determined based on the target distance and the carrier wavelength.

[0040] In this embodiment, the distance loss can be determined based on the target distance and the carrier wavelength by: determining the distance loss based on the target distance, the carrier wavelength, and a first formula, wherein the first formula is: ;in, For the target distance, For carrier wavelength, This represents the distance loss.

[0041] The sum of the distance loss and the first reflection power is taken as the second reflection power.

[0042] In this embodiment, the second reflection power is determined based on the following formula: .in, This is the second reflected power.

[0043] The sum of the second reflected power, the spatial propagation path loss, and the multipath interference compensation is taken as the processed reflected power of the device under test.

[0044] In this embodiment, the processed reflected power of the device under test is determined based on the following formula: in, For the second reflected power, This represents the spatial propagation path loss (calculated based on the indoor logarithmic distance loss model). The multipath interference compensation value is obtained by taking the statistical average of the power collected by the UAV at the same location in multiple attitudes (≥3 groups). This represents the processed reflected power of the device under test.

[0045] Optionally, determining the range loss based on the target distance and the carrier wavelength includes: The distance loss is determined based on the target distance, the carrier wavelength, and a first formula, wherein the first formula is: ; in, For the target distance, For carrier wavelength, This represents the distance loss.

[0046] In this embodiment, the reflected power of the device under test is processed using hardware gain calibration to eliminate the amplitude and phase errors inherent in the RF acquisition module, thus obtaining the calibrated power. = + ,in, The preset gain compensation value is the one calibrated at the factory for the module; based on the acquisition distance. With carrier wavelength Calculate distance loss And complete distance compensation to obtain the second reflection power. = + Taking into account the actual environmental conditions of the acquisition area, such as walls, ceilings, and metal obstructions, an environmental compensation model based on spatial fading characteristics and multipath interference statistics is used to perform secondary correction on the measured power. The power fluctuations caused by constructive / destructive multipath interference are eliminated by using the average sampling method of multiple orientations (≥3 groups) at the same location. The environmental compensation amount is calculated using an indoor logarithmic distance path loss model to obtain the processed reflected power of the device under test. in, For the second reflected power, This represents the spatial propagation path loss (calculated based on the indoor logarithmic distance loss model). The multipath interference compensation amount is obtained by taking the statistical average of the power collected by UAVs in multiple attitudes (≥3 groups) at the same location.

[0047] S130, determine the insertion loss of the device under test based on the forward power of the device under test, the processed reflected power of the device under test, the preset feeder loss value, and the preset connector loss value.

[0048] In this embodiment, the insertion loss of the device under test is calculated based on the following formula. ,in, For the conducted power of the signal source, For receiving conducted power at the end, To preset feeder loss, Preset connector loss.

[0049] S140, determine the return loss of the device under test based on the forward power and the processed reflected power.

[0050] In this embodiment, the return loss of the device under test (DUT) is determined based on its forward power and processed reflected power by: determining a first ratio, where the first ratio is the ratio of the processed reflected power to the forward power of the DUT; and determining the return loss of the DUT based on the first ratio and a second formula, where the second formula is: ;in, The first ratio, The processed reflected power of the device under test. Forward power, The return loss is the signal loss of the device under test.

[0051] Optionally, the return loss of the device under test (DUT) is determined based on the forward power and the processed reflected power, including: Determine the first ratio.

[0052] The first ratio is the ratio of the processed reflected power to the forward power of the device under test.

[0053] The return loss of the device under test is determined based on the first ratio and the second formula.

[0054] The second formula is: ; in, The first ratio, The processed reflected power of the device under test. Forward power, The return loss is the signal loss of the device under test.

[0055] S150, determine the voltage standing wave ratio (VSWR) of the device under test (DUT) based on its return loss.

[0056] In this embodiment, the voltage standing wave ratio (VSWR) of the device under test (DUT) can be determined based on its return loss as follows: the VSWR is determined using the return loss of the DUT and a third formula, where the third formula is: ;in, The voltage standing wave ratio (VSWR) of the device under test. The return loss is the signal loss of the device under test.

[0057] Optionally, the voltage standing wave ratio (VSWR) of the device under test (DUT) can be determined based on its return loss, including: The voltage standing wave ratio (VSWR) of the device under test (DUT) is determined based on the return loss and the third formula, where the third formula is: ; in, The voltage standing wave ratio (VSWR) of the device under test. The return loss is the signal loss of the device under test.

[0058] S160. Based on the insertion loss, return loss, and voltage standing wave ratio of the device under test (DUT), determine the test result of the DUT.

[0059] In this embodiment, the detection result of the device under test (DUT) can be determined based on its insertion loss, return loss, and voltage standing wave ratio (VSWR). This can be achieved by determining a coupling correlation coefficient, where the coefficient characterizes the coupling relationship between the DUT, its return loss, and its VSWR. The detection result of the DUT is then determined based on this coupling correlation coefficient, the DUT's insertion loss, return loss, and VSWR. The detection result of the device under test (DUT) can also be determined based on its insertion loss, return loss, and voltage standing wave ratio (VSWR). If the VSWR is greater than the VSWR threshold, the insertion loss is less than the insertion loss threshold, and the return loss is less than the return loss threshold, then the detection result indicates a slight local port mismatch fault. If the VSWR is less than or equal to the VSWR threshold, the insertion loss is greater than or equal to the insertion loss threshold, and the return loss is less than the return loss threshold, then the detection result indicates a passive device dielectric or cavity uniform loss rise fault. If the VSWR is less than or equal to the VSWR threshold, the insertion loss is less than the insertion loss threshold, and the return loss is greater than or equal to the return loss threshold, then the detection result indicates a branch port local weak reflection fault. In a specific example, if any one of the insertion loss, return loss, and voltage standing wave ratio of the device under test exceeds a threshold, while the others meet the standard (do not exceed the threshold), three single-indicator fault scenarios are defined: 1) If only VSWR > VSWR threshold (e.g., VSWR threshold is 1.5), and both insertion loss IL and return loss RL meet the standard, it is judged as a mild port partial mismatch fault. Typical causes include slight poor contact of device port springs, slight deformation of indoor antenna housing, and slight loosening of connector fastening screws. There is no water ingress or aging of the device's dielectric. The fault level is a mild warning. Only the periodic retest cycle needs to be adjusted. No emergency on-site maintenance is required.

[0060] 2) Only the insertion loss IL exceeds the IL threshold, while VSWR and RL both meet the standard: This is determined to be a passive device dielectric or cavity uniform loss rise fault, with the port matching status intact. Typical causes include long-term thermal aging of the internal dielectric of the device, slight overall pressure deformation of the feeder, and accumulation of small losses at multiple connectors in the link. There are no port reflection defects. The fault level is moderate performance degradation. A routine maintenance work order is generated, and an on-site inspection of the feeder and device is arranged during the monthly window period. 3) Only the return loss RL is greater than the RL threshold, while VSWR and IL meet the standard: This scenario often occurs in weak reflections of a single branch of a multi-port coupled device. The VSWR of the main path does not exceed the limit, and it is judged as a local weak reflection fault at the branch port. Typical causes include load matching offset at the secondary port of the coupler and slight oxidation of the plating of the branch jumper connector. The fault level is a slight warning, and the performance curve is continuously tracked and inspected multiple times. It should be noted that port isolation can also be obtained. If only the port isolation is lower than the port isolation threshold, and VSWR, IL, and RL all meet the standards, it is judged as a deterioration fault of the internal isolation layer of the multi-port device. The main path transmission and port matching performance are not impaired. Typical causes include aging of the internal isolation resistor of the power divider / coupler and slight failure of the cavity shielding structure. The fault level is a moderate warning, and the uplink adjacent channel interference spectrum of the cell should be monitored.

[0061] In this embodiment, the method for determining the test result of the device under test (DUT) based on its insertion loss, return loss, and voltage standing wave ratio (VSWR) can also be as follows: Perform a dual-index coupled fault determination, distinguishing the root cause of the fault based on different index combinations. 1) VSWR > VSWR threshold, return loss RL > RL threshold, and insertion loss IL meets the standard: This is judged as severe port mismatch. There is no additional power loss between the device body and the transmission link. Typical causes include completely loose connectors, broken antenna elements, open or short circuits at the end of the feeder, and detachment of the device port sealing structure. The fault level is severe fault. An emergency repair work order will be automatically dispatched. It is recommended to power off and repair the faulty device during off-peak hours. 2) VSWR > VSWR threshold, insertion loss IL exceeds IL threshold, RL meets standard: This is judged as a composite fault caused by port mismatch leading to round-trip reflection and additional transmission loss. Typical causes include water ingress and oxidation of connectors, bending and damage of feeder lines, and moisture corrosion of device ports accompanied by poor contact. The fault level is severe. Prioritize checking for water seepage and cable damage, and replace corroded connectors at the same time. 3) Return loss RL is greater than the RL threshold, insertion loss IL exceeds the IL threshold, and VSWR is less than or equal to the VSWR threshold: This is judged as a multi-point slight reflection cumulative superposition of progressive aging of the medium fault. Typical causes include oxidation of multiple connectors in the entire link, long-term compression deformation of the feeder, and moisture in the internal medium of passive devices; the fault level is a medium fault, and the aging connectors and damaged feeders in the link should be replaced in batches. It should be noted that if the port isolation is also obtained, then if the insertion loss IL exceeds the IL threshold and the port isolation is lower than the standard threshold, it is judged as a failure of the overall internal structure of the multi-port device, with simultaneous isolation failure and transmission loss increase. Typical causes include water ingress into the power divider and coupler cavity, and large-area oxidation of the internal metal plating. The fault level is a severe fault, and the faulty passive device should be replaced directly.

[0062] In this embodiment, the method for determining the test result of the device under test (DUT) based on its insertion loss, return loss, and voltage standing wave ratio (VSWR) can also be as follows: Perform a simultaneous comprehensive fault determination based on three indicators. When VSWR > VSWR threshold, return loss RL > RL threshold, and insertion loss IL exceeds IL threshold, and all three core indicators exceed the standard, it is determined to be a severe, composite fault in the passive device or transmission link, simultaneously exhibiting severe port mismatch, high-intensity signal reflection, and additional power attenuation throughout the link. Typical causes include... Passive components are completely submerged in water and damp; feeder cables are torn and short-circuited; main connectors are severely corroded and broken; antenna internal elements are damaged and the cavity is leaking water. These types of faults are prone to generating high-intensity passive intermodulation products, increasing the uplink electromagnetic noise floor of the cell, causing user speed lag and communication dropouts. The fault level is classified as a top-level fault. It is recommended to temporarily reduce the service capacity of the faulty area and complete the component replacement and link rectification within 24 hours. If all three indicators exceed the standard simultaneously and the port isolation is simultaneously below the standard threshold, it is further determined that the internal structure of the multi-port device is completely damaged and has no repair value. The entire unit should be replaced directly.

[0063] Optionally, the test results of the device under test (DUT) are determined based on the insertion loss, return loss, and voltage standing wave ratio (VSWR) of the DUT, including: Determine the coupling correlation coefficient.

[0064] The coupling correlation coefficient is used to characterize the coupling correlation between the insertion loss, return loss and voltage standing wave ratio of the device under test (DUT).

[0065] In this embodiment, a three-dimensional fault feature library is constructed, and the insertion loss, return loss, and voltage standing wave ratio of the device under test (DUT) are normalized and mapped into three-dimensional feature vectors. A fault feature space is established, with dimensions including index normalization deviation, inter-index coupling correlation coefficient, and fault mode sample feature center points. Various underlying fault mechanisms from historically known samples, such as single local defects, multi-point progressive degradation of the link, connector moisture oxidation, feeder damage, open / short circuits, and device dielectric aging due to water ingress, are bound to corresponding three-dimensional feature vector sample sets, establishing standard feature center vectors for various fault modes. Through feature vector space distance calculation, similarity matching and root cause tracing of single faults and multi-factor coupled composite faults are achieved, distinguishing between local single-point defects in passive devices and synchronous progressive degradation faults of the entire transmission link. The deviation after VSWR normalization is based on the VSWR threshold, for example, a VSWR threshold of 1.5; The deviation of the insertion loss IL after normalization is represented by the insertion loss threshold, which characterizes the loss offset. The deviation of the return loss RL normalization is based on the standard return loss threshold.

[0066] The comprehensive fault cracking index is determined based on the insertion loss, return loss, voltage standing wave ratio (VSWR), coupling correlation coefficient, coupling penalty factor, weight of insertion loss, weight of return loss, and weight of VSWR of the device under test.

[0067] In this embodiment, the Fault Comprehensive Degradation Index (FDI) is calculated using the normalized three-dimensional feature vector. FDI characterizes the overall severity of device and link degradation and is determined based on the following formula: ; in, , , The weight coefficients for VSWR, IL, and RL are respectively, and can be obtained through training; The coupling correlation coefficient among the three indicators is used to characterize the synergistic effect of the synchronous shift of multiple indicators. To couple the penalty factor, a penalty amplification is introduced when multiple indicators deteriorate synchronously in the same direction, so as to avoid misjudging serious faults due to a small drift of a single indicator, and also to avoid missing compound faults due to the superposition of small deviations of multiple indicators.

[0068] In this embodiment, the fault risk levels can be divided according to the FDI value range: minor warning, moderate performance degradation, severe fault, and extreme composite fault; at the same time, the Euclidean space similarity between the measured feature vector and the standard center vector of each fault mode is calculated, and the TopN matching candidate fault types are output.

[0069] If the fault comprehensive cracking index is in the first range, the difference between the insertion loss of the device under test and the insertion loss threshold is greater than the first difference threshold, the difference between the return loss of the device under test and the return loss threshold is less than or equal to the second difference threshold, and the difference between the voltage standing wave ratio of the device under test and the voltage standing wave ratio threshold is less than or equal to the third difference threshold, then it is determined that the device under test has a passive device dielectric or cavity uniform loss rise fault. If the fault comprehensive cracking index is in the first range, the difference between the voltage standing wave ratio (VSWR) of the device under test and the VSWR threshold is greater than the third difference threshold, the difference between the insertion loss of the device under test and the insertion loss threshold is less than or equal to the first difference threshold, and the difference between the return loss of the device under test and the return loss threshold is less than or equal to the second difference threshold, then it is determined that the device under test has a mild port local mismatch fault. If the fault comprehensive cracking index is within the first range, the difference between the return loss of the device under test and the return loss threshold is greater than the second difference threshold, the difference between the insertion loss of the device under test and the insertion loss threshold is less than or equal to the first difference threshold, and the difference between the return loss of the device under test and the return loss threshold is less than or equal to the second difference threshold, then it is determined that the device under test has a local weak reflection fault at the branch port.

[0070] In this embodiment, the first range interval can be the lower range.

[0071] In a specific example, when the Fault Deterioration Index (FDI) is in the low range, and only one dimension of the three-dimensional feature vector significantly deviates from the standard center vector, while the other two dimensions deviate from the standard sample by less than a set threshold, it is judged as a single-dimensional dominant fault, which is further subdivided into three scenarios: (1) VSWR deviates significantly, while IL and RL deviate very little: only Significant offset, insertion loss and return loss are close to normal; feature similarity matches the sample cluster with local port mismatch.

[0072] Judgment: Mild port partial mismatch fault; Typical causes: slight poor contact of device port spring, slight deformation of indoor antenna cover, slight loosening of connector fastening screws, no water ingress into the device, and aging of the device's dielectric; Fault level: Minor warning; Handling: Only adjust the periodic retest cycle, no emergency on-site maintenance required.

[0073] (2) IL deviates significantly, while VSWR and RL deviate very little: only Significant offset, voltage standing wave ratio and return loss are close to normal; eigenvector matching dielectric uniform loss improves sample cluster.

[0074] Judgment: Passive device dielectric / cavity uniform loss rise fault; port reflection matching status is good; typical cause: long-term thermal aging of the internal dielectric of the device, slight pressure deformation of the feeder as a whole, accumulation of small losses at multiple joints of the link, and no port reflection defects; fault level: moderate performance degradation; generate a routine maintenance work order and arrange on-site inspection of the feeder and device during the monthly window period.

[0075] (3) The RL dimension deviates significantly, while the VSWR and IL dimensions deviate very little: only Significant offset, voltage standing wave ratio and insertion loss are close to normal; eigenvector matching branch weak reflection sample cluster.

[0076] Judgment: Local weak reflection fault at branch port; Typical causes: load mismatch at coupled ports, slight oxidation of plating on branch jumper connectors; Fault level: minor warning; Continuous tracking of performance curves during multiple rounds of inspections.

[0077] It should be noted that when two dimensions of the three-dimensional feature vector simultaneously and significantly deviate from the normal sample center, and the coupling correlation coefficient... When the coupling threshold is exceeded, the FDI rises to the middle range; by combining the similarity between the feature vector and the sample centers of various coupling faults, the root causes of different coupling faults are distinguished: (1) VSWR and RL are synchronously offset by a large amount, while IL is offset by a very small amount: Feature vector matching samples of loose connectors and broken antenna elements; determine severe port mismatch fault; no additional power loss between the device body and the transmission link; typical causes: completely loose connectors, broken antenna elements, open or short circuit at the end of the feeder, or detachment of the device port sealing structure; fault level: severe fault, automatically dispatch an emergency repair work order, and recommend power off during off-peak hours for inspection and replacement of faulty devices.

[0078] (2) VSWR and IL are significantly offset synchronously, while RL is very small; Feature vector matching is used to identify sample clusters of connectors with water ingress and oxidation, and feeder cable bending and damage; port mismatch is used to determine a composite fault caused by round-trip reflection and additional transmission loss; typical causes: connector oxidation due to water ingress, feeder cable bending and damage, and device port corrosion due to moisture accompanied by poor contact; fault level: severe fault; priority should be given to checking for water seepage and cable damage points, and corroded connectors should be replaced simultaneously.

[0079] (3) RL and IL shifted significantly in sync, while VSWR deviated very little and did not experience significant jumps: Feature vector matching of multi-point cumulative degradation sample clusters in the link; determination of multi-point slight reflection cumulative superposition of progressive aging of medium faults in the link; typical causes: oxidation of multiple joints in the entire link, long-term compression deformation of feeders, and moisture in the internal medium of passive devices; fault level: moderate fault; batch replacement of aging joints and damaged feeders in the link.

[0080] In this embodiment, when VSWR, IL, and RL are synchronously offset significantly, the coupling correlation coefficient... The strong coupling threshold has been reached, and the Fault Degradation Index (FDI) has fallen into the high range. The measured feature vector shows the highest similarity to the sample cluster of devices damaged by water ingress. The system is identified as a severe composite fault in passive devices or transmission links, characterized by severe port mismatch, high-intensity signal reflection, and additional power attenuation across the entire link. Typical causes include: complete water ingress and moisture damage to passive devices, torn and short-circuited feeder lines, severe corrosion and breakage of main connectors, and damage to the antenna's internal vibrator and water seepage into the cavity. This type of fault is highly prone to generating high-intensity passive intermodulation products, increasing the uplink electromagnetic noise floor of the cell, causing user speed lag and communication drops. The fault level is classified as severe. It is recommended to temporarily reduce the service capacity in the faulty area and complete device replacement and link rectification within 24 hours.

[0081] In this embodiment, by combining high-precision 3D positioning information collected by UAV with the unique ID of the device, the faulty devices of different levels are accurately labeled in the indoor 3D digital twin model, distinguishing between single-dimensional dominant slight attenuation points, two-dimensional coupled moderate degradation points, and three-dimensional all-dimensional extreme comprehensive fault points; the device number, installation coordinates, 3D radio frequency feature vector, FDI degradation index, feature similarity matching results, and fault severity level are displayed simultaneously; a layered visualized fault point heat map is generated, and preliminary operation and maintenance troubleshooting suggestions are output.

[0082] In this embodiment, based on the fault 3D feature vector matching results, FDI fault comprehensive degradation index, and fault severity level, it can automatically output graded executable operation and maintenance suggestions: minor early warning faults only require updating the digital twin device file and shortening the retest cycle, without on-site inspection; moderate degradation faults generate regular operation and maintenance work orders and arrange on-site inspections during off-peak hours; severe and critical faults generate emergency repair work orders, with accompanying temporary business control prompts, fault root cause analysis, and spare parts replacement lists, to achieve closed-loop tracking management of fault work orders.

[0083] In this embodiment, a standardized test report can be automatically generated based on the test results. This report includes the test area, component list, indicator details, status determination, fault list, anomaly analysis, and maintenance and rectification suggestions. The raw data, calibration data, indicator curves, fault information, and location results of this test are simultaneously written into the indoor distributed antenna system (DAS) digital twin database, establishing a full lifecycle test archive for passive components and supporting historical data query, comparison, and traceability. Based on multiple rounds of historical test data, time series analysis is used to predict the performance degradation trend of components, enabling early warning of potential faults and providing a basis for preventative maintenance. Periodic retest plans are automatically generated based on component status, supporting the integration of test results with the maintenance work order system to achieve automatic dispatch, processing, feedback, and closed-loop management of fault work orders. The inspection route, data acquisition parameters, compensation model, and judgment thresholds are continuously optimized based on historical test data to continuously improve test accuracy, coverage, and automation level, forming a standardized and replicable intelligent maintenance system for indoor distributed antenna systems (DAS) passive components.

[0084] The technical solution of this embodiment uses a drone to collect radio frequency data of the device under test (DUT) indoors; based on a preset gain compensation value, the spectrum information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, the reflected power of the DUT is processed to obtain the processed reflected power of the DUT; based on the forward power of the DUT, the processed reflected power of the DUT, the preset feeder loss value, and the preset connector loss value, the insertion loss of the DUT is determined; based on the forward power and the processed reflected power of the DUT, the return loss of the DUT is determined; based on the return loss of the DUT, the voltage standing wave ratio (VSWR) of the DUT is determined; based on the insertion loss, return loss, and VSWR of the DUT, the detection result of the DUT is determined. This solution solves the problems of high labor intensity, low efficiency, and significant personal safety risks associated with manual operation, and improves detection accuracy and efficiency while ensuring network reliability.

[0085] Example 2 Figure 2 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0086] like Figure 2 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory 12 or a random access memory 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the read-only memory 12 or loaded from storage unit 18 into the random access memory 13. The random access memory 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, read-only memory 12, and random access memory 13 are interconnected via a bus 14. An input / output interface 15 is also connected to the bus 14.

[0087] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0088] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing units, graphics processing units, various special-purpose artificial intelligence computing chips, various processors running machine learning model algorithms, digital signal processors, and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as detection methods.

[0089] In some embodiments, the detection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via read-only memory 12 and / or communication unit 19. When the computer program is loaded into random access memory 13 and executed by processor 11, one or more steps of the detection method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the detection method by any other suitable means (e.g., by means of firmware).

[0090] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays, application-specific integrated circuits (ASICs), application-specific standard products (ASICs), systems-on-a-chip (SoCs), payload programmable logic devices, computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0091] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0092] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, optical fibers, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0093] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a cathode ray tube or liquid crystal display) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0094] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0095] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to address the shortcomings of traditional physical hosts and virtual private servers, such as high management difficulty and weak business scalability.

[0096] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0097] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the detection method according to any embodiment of the invention.

[0098] In the implementation of a computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0099] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A detection method, characterized in that, include: Radio frequency (RF) data of the device under test (DUT) is collected indoors by a drone. The RF data includes forward power, reflected power, and spectral information of the forward signal. Based on the preset gain compensation value, the spectrum information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, the reflected power of the device under test is processed to obtain the processed reflected power of the device under test. The target distance is the distance between the acquisition position and the device under test, and the acquisition position is the position where the UAV acquires the radio frequency data of the device under test. The insertion loss of the device under test is determined based on the forward power of the device under test, the processed reflected power of the device under test, the preset feeder loss value, and the preset connector loss value. The return loss of the device under test is determined based on the forward power and the processed reflected power. Determine the voltage standing wave ratio (VSWR) of the device under test (DUT) based on its return loss. The test results of the device under test (DUT) are determined based on its insertion loss, return loss, and voltage standing wave ratio (VSWR).

2. The method according to claim 1, characterized in that, Raw radio frequency data of the device under test (DUT) is collected across the entire area using drones, including: Based on the indoor architectural drawings, indoor distribution system topology diagram, and device under test (DUT) register, an indoor three-dimensional digital twin model is constructed. The DUT register includes: DUT identifier, the type corresponding to the DUT identifier, installation location, height, and port orientation. Based on the indoor three-dimensional digital twin model, the sampling points corresponding to each device under test are determined; Path planning is performed based on the sampling points corresponding to each device under test to obtain the target flight path; The drone is controlled to collect radio frequency data of the indoor device under test based on the target flight path.

3. The method according to claim 1, characterized in that, Based on a preset gain compensation value, the spectral information of the forward signal, the target distance, the spatial propagation path loss, and the multipath interference compensation, the reflected power of the device under test is processed to obtain the processed reflected power of the device under test, including: The sum of the preset gain compensation value and the reflected power of the device under test is taken as the first reflected power; The carrier wavelength is determined based on the spectral information of the forward signal; The distance loss is determined based on the target distance and the carrier wavelength; The sum of the distance loss and the first reflection power is taken as the second reflection power; The sum of the second reflected power, the spatial propagation path loss, and the multipath interference compensation is taken as the processed reflected power of the device under test.

4. The method according to claim 3, characterized in that, Determining the range loss based on the target distance and the carrier wavelength includes: The distance loss is determined based on the target distance, the carrier wavelength, and a first formula, wherein the first formula is: ； in, For the target distance, For carrier wavelength, This represents the distance loss.

5. The method according to claim 1, characterized in that, The return loss of the device under test (DUT) is determined based on its forward power and the processed reflected power, including: Determine a first ratio, wherein the first ratio is the ratio of the processed reflected power to the forward power of the device under test; The return loss of the device under test is determined based on the first ratio and the second formula, wherein the second formula is: ； in, The first ratio, The processed reflected power of the device under test. Forward power, This represents the return loss of the device under test.

6. The method according to claim 1, characterized in that, Based on the return loss of the device under test (DUT), determine the voltage standing wave ratio (VSWR) of the DUT, including: The voltage standing wave ratio (VSWR) of the device under test (DUT) is determined based on the return loss and the third formula, where the third formula is: ； in, The voltage standing wave ratio (VSWR) of the device under test. This represents the return loss of the device under test.

7. The method according to claim 1, characterized in that, Based on the insertion loss, return loss, and voltage standing wave ratio (VSWR) of the device under test (DUT), the test results of the DUT are determined, including: Determine the coupling correlation coefficient, wherein the coupling correlation coefficient is used to characterize the coupling correlation between the insertion loss of the device under test, the return loss of the device under test, and the voltage standing wave ratio of the device under test; The comprehensive fault cracking index is determined based on the insertion loss, return loss, voltage standing wave ratio, coupling correlation coefficient, coupling penalty factor, weight of insertion loss, weight of return loss, and weight of voltage standing wave ratio of the device under test. If the fault comprehensive cracking index is in the first range, the difference between the insertion loss of the device under test and the insertion loss threshold is greater than the first difference threshold, the difference between the return loss of the device under test and the return loss threshold is less than or equal to the second difference threshold, and the difference between the voltage standing wave ratio of the device under test and the voltage standing wave ratio threshold is less than or equal to the third difference threshold, then it is determined that the device under test has a passive device dielectric or cavity uniform loss rise fault. If the fault comprehensive cracking index is in the first range, the difference between the voltage standing wave ratio (VSWR) of the device under test and the VSWR threshold is greater than the third difference threshold, the difference between the insertion loss of the device under test and the insertion loss threshold is less than or equal to the first difference threshold, and the difference between the return loss of the device under test and the return loss threshold is less than or equal to the second difference threshold, then it is determined that the device under test has a mild port local mismatch fault. If the fault comprehensive cracking index is within the first range, the difference between the return loss of the device under test and the return loss threshold is greater than the second difference threshold, the difference between the insertion loss of the device under test and the insertion loss threshold is less than or equal to the first difference threshold, and the difference between the return loss of the device under test and the return loss threshold is less than or equal to the second difference threshold, then it is determined that the device under test has a local weak reflection fault at the branch port.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the detection method according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the detection method according to any one of claims 1-7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the detection method according to any one of claims 1-7.

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