Multi-modal endoscope video transmission harness system and method based on high-speed serdes chip

Abstract

The application relates to the field of medical devices and discloses a multi-modal endoscope video transmission cable system based on a high-speed SerDes chip, which comprises an endoscope front-end module used for collecting video data and front-end control signals and comprising a first data collection unit used for collecting first physical data; a SerDes serializer module used for serializing the video data and the first physical data into high-speed SerDes signals; and a multi-modal transmission cable used for transmitting the high-speed SerDes signals, wherein the multi-modal transmission cable comprises a second data collection unit used for collecting second physical data. By adopting the high-speed SerDes chip, multi-channel video and sensor parallel data are serialized into a single pair or a small number of differential pairs for transmission, the internal structure of the cable is optimized, and the lightness and flexibility of the cable are greatly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of medical devices, in particular to a multi-modal endoscope video transmission cable system and method based on a high-speed SerDes chip. BACKGROUND

[0002] Currently, minimally invasive surgery has become an important direction of modern medical development, and endoscopic technology plays a core role in this process. Although endoscopic systems continue to improve in optical imaging, instrument operation, etc., the reliability problems of the data transmission cable supporting its key functions have become increasingly prominent, becoming a bottleneck restricting the overall performance and safety of the system.

[0003] Existing endoscopic transmission cables have significant limitations. They usually focus on single high-speed video signal transmission, which leads to insufficient adaptability to physical stress in complex operating environments. The cable frequently experiences bending, twisting and stretching during surgery, and these continuous mechanical stresses can easily cause fatigue damage to the internal conductor material. As the use time increases, the signal transmission quality inevitably decreases, showing video flickering, artifacts, or even signal interruption, which may cause serious consequences in medical operations that require real-time performance.

[0004] In addition, the existing technology lacks the ability to monitor the health status of the cable itself. For example, the cable may suffer from local excessive bending or transient stretching during operation, and this critical physical deformation information is often not real-time perceptible. This is like walking on the edge of device performance degradation without an effective warning mechanism. This information blind area makes it difficult for the operator to accurately judge the stress on the cable, unintentionally accelerating the aging of the cable material. Ultimately, the cable fails due to cumulative damage long before its expected lifespan, which undoubtedly increases the operating costs of medical institutions and reduces the efficiency of the device. SUMMARY

[0005] To overcome the shortcomings of the prior art, the present application provides a multi-modal endoscope video transmission cable system and method based on a high-speed SerDes chip, which solves the technical problem that the existing endoscopic transmission cable lacks real-time perception, intelligent evaluation and active warning capability of its own health status in complex operating environments, making it difficult to guarantee its reliability, service life and operating safety.

[0006] To achieve the above purpose, the present application realizes the following technical scheme: a multi-modal endoscope video transmission cable system based on a high-speed SerDes chip, comprising:

[0007] An endoscope front-end module for collecting video data and front-end control signals, and comprising a first data acquisition unit for collecting first physical data;

[0008] a SerDes serializer module for serializing video data and first physical data into a high-speed SerDes signal;

[0009] a multi-modal transmission harness for transmitting the high-speed SerDes signal, the multi-modal transmission harness comprising a second data acquisition unit for acquiring second physical data;

[0010] a SerDes deserializer module for deserializing the high-speed SerDes signal to recover the video data and generate quality data of the SerDes signal;

[0011] a host-side state monitoring module for acquiring connector state data;

[0012] a harness health assessment module for receiving the second physical data, the SerDes signal quality data, and the connector state data, and for performing health state assessment of the multi-modal transmission harness based on the second physical data, the SerDes signal quality data, and the connector state data;

[0013] an operational behavior analysis module for receiving the second physical data, and for generating a real-time alert signal based on a comparison result of the second physical data against a pre-set stress threshold;

[0014] a user interface module for receiving the health state assessment result and the real-time alert signal, and for displaying the health state assessment result and the real-time alert signal.

[0015] Preferably, the first data acquisition unit and the second data acquisition unit each comprises a physical sensor, and the physical sensor comprises a fiber Bragg grating sensor.

[0016] Preferably, the first physical data and the second physical data comprise instantaneous bending radius data and instantaneous tensile strain data.

[0017] Preferably, the SerDes deserializer module generates the SerDes signal quality data comprising bit error rate data, eye margin data, and jitter data.

[0018] Preferably, the host-side state monitoring module is configured to acquire the connector state data, and the connector state data comprises connector contact resistance data and connector plug-in times data.

[0019] Preferably, the harness health assessment module is configured to perform health state assessment of the multi-modal transmission harness, and the health state assessment comprises harness remaining service life prediction.

[0020] Preferably, the pre-set stress threshold in the operational behavior analysis module comprises a pre-set minimum safe bending radius threshold and a pre-set maximum safe tensile force threshold.

[0021] Preferably, the operation behavior analysis module is configured to generate the real-time reminding signal when the second physical data exceeds the preset stress threshold and lasts for a preset time length.

[0022] Preferably, the user interface module is configured to display the real-time reminding signal in a visual manner, including displaying a text prompt or color change at the edge of a video screen.

[0023] The multi-modal endoscope video transmission harness method based on a high-speed SerDes chip comprises the following steps:

[0024] S1: collecting video data, front-end control signals, and first physical data collected by a first data collection unit;

[0025] S2: serializing the video data and the first physical data into high-speed SerDes signals;

[0026] S3: transmitting the high-speed SerDes signals through a multi-modal transmission harness, and collecting second physical data by a second data collection unit in the multi-modal transmission harness;

[0027] S4: deserializing the high-speed SerDes signals to recover the video data, and generating quality data of the SerDes signals;

[0028] S5: collecting connector state data;

[0029] S6: performing health state evaluation on the multi-modal transmission harness based on the second physical data, the SerDes signal quality data, and the connector state data;

[0030] S7: generating a real-time reminding signal based on a comparison result of the second physical data and a preset stress threshold;

[0031] S8: displaying the health state evaluation result and the real-time reminding signal.

[0032] The present application provides a multi-modal endoscope video transmission harness system and method based on a high-speed SerDes chip.

[0033] 1. The present application serializes multiple video and sensor parallel data into a single pair or a small number of differential pairs for transmission by using a high-speed SerDes chip, optimizes the internal structure of the harness, and greatly improves the lightness and flexibility of the harness, thereby reducing the complexity of the harness, significantly reducing the wire diameter, and making it easier to operate flexibly in a narrow cavity.

[0034] 2、The application realizes real-time, comprehensive evaluation of the harness health state and accurate prediction of the remaining useful life by online integration of micro physical sensors (such as fiber Bragg grating sensors) inside the harness, monitoring of SerDes signal quality and connector status, and fusion analysis of multi-source data by algorithms, obtains the effects of harness failure warning, active maintenance and significant reduction of medical equipment unplanned downtime.

[0035] 3、The application realizes immediate correction of improper operation behavior by real-time monitoring of the instantaneous physical stress (such as bending radius, tensile strain) borne by the harness and comparing it with the preset safety threshold, and then generating a non-invasive real-time reminder feedback to the operator, obtains the effects of reducing harness human damage from the source, prolonging the service life of the harness, and assisting medical staff in standard operation.

[0036] 4、The application realizes low delay and high stability of endoscope high-definition video data transmission over long distances (such as 10 meters without relay) by the data transmission capability of high-speed SerDes chips, combining their advantages in signal integrity and anti-interference, and optimizing the harness structure design to take into account mechanical performance, breaks through the traditional transmission distance limit, guarantees the quality of real-time high-definition image transmission, and improves the efficiency of diagnosis and surgery. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 is a system architecture diagram of the application;

[0038] Figure 2 is a step schematic diagram of the application. DETAILED DESCRIPTION

[0039] The technical solutions of the application will be described clearly and completely below in combination with the drawings of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all embodiments. Based on the embodiments in the application, all other embodiments obtained by those of ordinary skill in the art without creative labor belong to the scope of protection of the application.

[0040] Embodiment one:

[0041] Please refer to the accompanying Figure 1 The embodiment of the application provides a multi-modal endoscope video transmission harness system based on a high-speed SerDes chip, which comprises:

[0042] An endoscope front-end module is used to collect video data and front-end control signals, and comprises a first data collection unit for collecting first physical data; the first physical data and the second physical data comprise instantaneous bending radius data and instantaneous tensile strain data.

[0043] Specifically, the endoscope front-end module is the starting link of the system, and its main function is to collect high-quality video data and necessary front-end control signals. In addition, the module also critically integrates the first data acquisition unit. The design of this unit is crucial for real-time monitoring of the physical stress of the endoscope tip during operation.

[0044] The core of the first data acquisition unit lies in the fiber Bragg grating (FBG) sensor array it employs. Specifically, multiple miniature FBG sensors will be strategically embedded along the outer wall or internal structure of the endoscope front-end's head and proximal end. These FBG sensors are distributed in an array, for example, at different orientations (such as up, down, left, and right) of the front-end and at multiple points along its length. When the endoscope front-end is bent, twisted, or stretched in the body, the optical fiber at the location of the FBG sensor will experience a slight strain. This strain will cause the periodic structure of the fiber Bragg grating to change, in turn causing the central wavelength of its reflected light to shift accordingly.

[0045] To accurately obtain these wavelength shifts, the first data acquisition unit will be equipped with a compact optical spectrum demodulator. This demodulator is usually based on a broadband light source (such as an LED or a superluminescent diode) and a high-resolution spectrometer, or uses a tunable laser to scan the reflection spectrum peak of the FBG. By monitoring and analyzing the spectral signals returned from the FBG sensors in real time, the demodulator can accurately capture the central wavelength shift of each FBG sensor. These raw wavelength shift data are then sent to a built-in microcontroller or dedicated signal processing unit. In this unit, a pre-established strain-wavelength calibration model and geometric solving algorithm will be run. This model, through experimental calibration, establishes a correspondence between a specific wavelength shift and the exact strain value that the optical fiber bears.

[0046] Based on the spatial distribution of multiple FBG sensors and their respective strain data, the geometric solving algorithm can calculate the instantaneous bending radius and instantaneous tensile strain of the endoscope front-end in real time. For example, by measuring the wavelength changes of at least three non-collinear FBG sensors in the bending plane, the bending radius of the section can be accurately calculated. FBG sensors distributed along the axial direction are used to detect tensile or compressive strain.

[0047] In addition, to cope with complex surgical environments, the first data acquisition unit can also integrate miniature temperature sensors, such as high-precision thermistors or thin-film thermocouples, inside the front-end module or in close proximity, as needed. These temperature sensors can monitor the working temperature of the endoscope front end in real time, providing environmental parameters for the system, helping to correct the temperature cross-sensitivity of the FBG sensor, ensuring the accuracy of physical data acquisition, and providing the basis for system overheating protection. All of these collected video data, front-end control signals, and processed first physical data (i.e., instantaneous bending radius data and instantaneous tensile strain data) will be transmitted through internal interfaces to the SerDes serializer module for high-speed serialization.

[0048] The SerDes serializer module is in communication connection with the endoscope front-end module, and is configured to serialize the video data and the first physical data into high-speed SerDes signals.

[0049] Specifically, the core component of the SerDes serializer module is a high-performance SerDes serializer chip. In actual applications, appropriate chip models can be selected according to the required video resolution, frame rate, and sensor data bandwidth. For example, industrial or medical SerDes chips such as TI's DS90UB9x series or Analog Devices' ADV76xx series can be selected. These chips usually have multiple parallel input interfaces and one or more high-speed serial output interfaces. Key parameters of the serializer chip include: supported transmission rate (e.g., capable of handling data streams up to 10 Gbps or higher to meet 4K or even 8K ultra-high-definition video transmission requirements), channel number (usually referring to the number of parallel input data bits, such as 10 bits, 12 bits, or 24 bits), and packaging form (compact packaging is required to fit the integration space of the endoscope wire bundle front end).

[0050] The working process of the serializer module is as follows:

[0051] First, it receives video data from the endoscope front-end module. These video data are usually transmitted in the form of parallel digital signals, such as RGB or YUV format pixel data. At the same time, it also receives first physical data, i.e., instantaneous bending radius data and instantaneous tensile strain data generated by the front-end first data acquisition unit. These physical data are usually digitized low-speed control or status information.

[0052] The SerDes serializer chip integrates a data multiplexer and a high-speed encoder inside. The data multiplexer is responsible for time-multiplexing the parallel video data and the first physical data, integrating them onto a single parallel data bus. Subsequently, the high-speed encoder (e.g., using an 8b / 10b or 10b / 12b encoding scheme) encodes these multiplexed data to increase the signal's DC balance, reduce inter-symbol interference, and embed clock information. The encoded data is converted into differential signals and transmitted through the SerDes output interface. This serialization process effectively converts multiple independent parallel signals into a high-speed serial data stream on one or a small number of differential pairs, significantly reducing the number of physical wires required for the wiring harness.

[0053] In addition to the basic data serialization function, some advanced SerDes chips also have a preliminary signal integrity monitoring function. Although the main signal quality analysis is performed at the deserializer end, the serializer can perform pre-emphasis or de-emphasis processing before data transmission to compensate for high-frequency losses during cable transmission, which helps to improve the overall signal quality. In addition, some serializer chips may also provide a simple line loopback test function for preliminary verification of link connectivity.

[0054] Through the effective operation of the SerDes serializer module, synchronous, efficient, and high-bandwidth transmission of video data and physical sensor data is achieved, laying the foundation for subsequent long-distance, low-latency transmission.

[0055] The multi-modal transmission harness is in communication connection with the SerDes serializer module and is used for transmitting high-speed SerDes signals. The multi-modal transmission harness includes a second data acquisition unit for acquiring second physical data. The first data acquisition unit and the second data acquisition unit each include a physical sensor, and the physical sensor includes a fiber Bragg grating sensor.

[0056] Specifically, in constructing the endoscope system, the manufacturing and integration of the multi-modal transmission harness are core steps. In actual operation, this harness is connected with the SerDes serializer module in this way and high-speed SerDes signal transmission is achieved. At the same time, it contains an essential component, the second data acquisition unit. It is worth noting that whether it is the "first data acquisition unit" at the front end of the endoscope or the "second data acquisition unit" of this harness itself, the fiber Bragg grating (FBG) sensor is uniformly selected as the main physical sensing element.

[0057] In the implementation of this harness, the internal structure adopts a hybrid cable solution. First, high-speed differential copper cable pairs are deployed, using high-purity oxygen-free copper conductors. The specifications usually use AWG30 to AWG34 wire diameters, which are twisted together to minimize common-mode noise during transmission and ensure signal purity. The insulation material for each pair of differential lines is low-dielectric-constant material such as foamed FEP or Teflon, which reduces signal attenuation and crosstalk, allowing high-speed data to travel further and more stably.

[0058] Next, embedded optical fibers are integrated, which form the second data acquisition unit. In actual manufacturing of the harness, multiple thin optical fibers are pre-buried inside the harness along its longitudinal axis or in a spiral manner. These optical fibers are not ordinary optical fibers; they have been pre-written with multiple Fiber Bragg Grating (FBG) sensors before leaving the factory. The positions of these FBG sensors are carefully designed and evenly distributed along the length of the harness body, usually with one every 5 to 10 mm. The purpose of this is to form a continuous distributed sensor array. When the harness is bent or stretched in use, the optical fibers where the FBG sensors are located will deform, and their reflected light wavelengths will shift. These wavelength shifts are monitored in real time by a supporting demodulation device, and based on a pre-set calibration model, the instantaneous bending radius and instantaneous tensile strain of the harness at different positions are accurately calculated. This real-time and high-precision acquisition of the harness's own deformation data provides direct perception of the "health status" of the harness, which is not possible with traditional harnesses.

[0059] In addition to the above core parts, power lines and auxiliary data lines are integrated inside the harness. The specifications and materials of these cables are also optimized to ensure that they provide power and transmit low-speed control signals without affecting the flexibility and overall performance of the entire harness.

[0060] In terms of shielding design, a multi-layer shielding structure is used to achieve excellent EMI suppression capability. Specifically, each pair of high-speed differential copper cables has its own independent shielding layer, usually aluminum foil or copper braid shielding layer, which is designed to reduce crosstalk between them. Then, the outside of all internal cables and optical fibers is wrapped with a layer of high-density copper braid shielding layer, which is the first external protection. In the outermost layer, an additional layer of aluminum foil or special conductive polymer is added as the final electromagnetic barrier. All these shielding layers are effectively grounded through low-impedance paths, so that external electromagnetic interference signals can be effectively guided to the ground, significantly reducing their impact on SerDes signals and ensuring clear and stable transmission.

[0061] Finally, the outer sheath material of the wire harness is critical. It is a medical-grade polymer, such as medical-grade thermoplastic polyurethane (TPU) or polyether ether ketone (PEEK). These materials not only have excellent biocompatibility, but more importantly, they are resistant to wear and tear, chemical corrosion (can withstand repeated disinfection), and maintain high flexibility and resilience even after repeated bending. It is precisely because of these materials and precise internal structure that the diameter of the entire wire harness can be strictly controlled within 3 mm. Compared with traditional solutions, this greatly reduces the volume and weight of the wire harness, significantly improving the convenience and flexibility of the endoscope in narrow spaces.

[0062] The SerDes deserializer module is in communication connection with the multi-modal transmission wire harness, and is used for deserializing the high-speed SerDes signal to recover video data and generating SerDes signal quality data; the SerDes signal quality data generated by the SerDes deserializer module includes bit error rate data, eye diagram margin data and jitter data.

[0063] Specifically, in the construction of the endoscope system, the integration of the SerDes deserializer module is the core link of the receiving end. In actual operation, this module is in communication connection with the multi-modal transmission wire harness in the following way. Its main tasks are: first, to deserialize the received high-speed SerDes signal to recover the original video data; second, to generate key SerDes signal quality data at the same time. These data include bit error rate data, eye diagram margin data and jitter data, which are crucial for evaluating the performance of the transmission link.

[0064] When deploying the SerDes deserializer module, its core is a high-performance SerDes deserializer chip. In actual projects, a model that is compatible with the front-end SerDes serializer chip is usually selected, such as the DS90UB9x series of TI or the ADV76xx series of Analog Devices, to ensure the best compatibility and performance matching. This chip is designed to directly receive the differential high-speed SerDes signal from the multi-modal transmission wire harness.

[0065] The chip integrates multiple key functional units inside. First, the clock data recovery (CDR) circuit. Because there is no independent clock line during SerDes signal transmission. The task of the CDR circuit is to accurately extract the clock information from the received serial data stream. Then, it will use this recovered clock to synchronize the data stream, ensuring that each bit can be correctly sampled within the correct clock period.

[0066] Following the adaptive equalizer is the adaptive equalizer. This equalizer is dynamically working. The length of the transmission line bundle, material properties and connectors and other factors, all of which can cause high-speed signals to attenuate and intersymbol interference during transmission, and the signal waveform will become blurred. The adaptive equalizer can analyze the received signal in real time and dynamically adjust its equalization parameters to compensate for these transmission impairments. Even if the signal quality has declined after a long distance transmission, the equalizer can maximize the recovery of the original waveform of the signal, thereby ensuring that the high-definition video data can be accurately restored. This compensation mechanism is a key technology guarantee for long-distance, low-latency (for example, the end-to-end delay can be controlled within 50 milliseconds) high-definition video transmission.

[0067] In addition to the core deserializing and data recovery function, the SerDes deserializer module also has a powerful signal quality monitoring function. This is not a simple bypass detection, but a real-time internal chip:

[0068] The deserializer chip integrates a bit error rate tester. It continuously monitors the deserialized data stream, identifies the number of error bits through internal algorithms, and calculates the bit error rate in real time. This bit error rate value, usually expressed in the form of negative power of 10 (for example, the typical value is 10 -12 ), directly reflects the reliability and anti-interference ability of signal transmission.

[0069] The deserializer module can internally generate and analyze the "eye diagram" of the received signal. The eye diagram is a direct graphical representation of the quality of high-speed digital signals. The module analyzes multiple parameters of the eye diagram in real time and generates key data such as "eye height" (reflecting the noise margin of the signal) and "eye width" (reflecting the jitter margin of the signal). The larger the "opening" of the eye diagram, the better the signal quality and the higher the tolerance to noise and jitter. These data provide quantitative indicators of signal link margins.

[0070] Jitter is the uncertainty of high-speed digital signals on the time axis, and is an important factor affecting signal integrity. The deserializer module can analyze and quantify the jitter components of the received signal in real time, including identifying random jitter (RJ) and deterministic jitter (DJ). Excessive jitter will directly lead to an increase in the bit error rate. The jitter data generated by the module provides an important basis for evaluating and optimizing the stability and reliability of the transmission link.

[0071] These signal quality data generated by the SerDes deserializer module in real time will be transmitted to the subsequent cable health assessment module through the internal interface. They serve as important diagnostic information, allowing the system to continuously monitor the health of the transmission link and provide early warning of potential transmission performance issues, thereby ensuring the clarity of video images and the stability of the entire system.

[0072] Host-side state monitoring module, the host-side state monitoring module is used for collecting connector state data; the host-side state monitoring module is used for collecting connector state data, and the connector state data includes connector contact resistance data and connector plug-in times data.

[0073] Specifically, in the construction of the endoscope system, the deployment of the host-side state monitoring module is indispensable. In actual operation, this module focuses on collecting connector state data, and its core purpose is to assess the health status of the connection point of the multi-modal transmission wire harness and the host device. These key connector state data include connector contact resistance data and connector plug-in times data.

[0074] When implementing the host-side state monitoring module, its design is not simply a list of data, but focuses on high precision and real-time performance.

[0075] First, for the collection of connector contact resistance data, the industry-recognized four-wire Kelvin measurement method is used. This method can eliminate the influence of measurement lead resistance on the results, so as to obtain the true and small contact resistance value between the connector pins. In actual operation, the independent current loop (injecting accurate constant current) and voltage measurement loop (directly measuring voltage drop between the connector pins) are used to periodically or continuously measure the key pins in the connector insertion state. For example, the connector pins of high-speed SerDes signal paths, power supply paths and important control signal paths can be measured. By continuously monitoring the small changes in contact resistance, potential problems such as poor contact, oxidation, wear or fretting corrosion in the connector can be detected early. Abnormal increase in contact resistance is an important indication of connector performance degradation, which may eventually lead to signal interruption or performance degradation. This precise measurement method provides a quantitative basis for the stability of the electrical connection of the connector.

[0076] Secondly, for the collection of connector plug-in times data, a dedicated plug-in counting mechanism is integrated. There are many choices for the implementation method, and it can be optimized according to actual needs:

[0077] Mechanical trigger-based counting scheme: a common implementation is to trigger a counting signal through a microswitch or mechanical lever when the connector is plugged in. For example, a precise mechanical contact can be set on the connector housing or fixing mechanism, which is closed or opened when the wire harness connector is fully inserted into the host connector, thereby driving a digital counter.

[0078] Optical sensor-based counting: A more advanced solution is to use photoelectric or reflective sensors. Along the connector insertion path, a pair of infrared photoelectric sensors or a reflective sensor is installed. When the connector is inserted or removed, it will block or reflect the light beam, triggering the sensor signal, which is then accumulated by the counter. This non-contact counting method can reduce mechanical wear and tear, improve the life and reliability of the counter.

[0079] Counting based on electrical contact state changes: The insertion and removal events can also be detected by monitoring the on-off state or impedance changes of a specific pin inside the connector. For example, a low-speed detection pin can be set up, which establishes a stable connection with the ground or power supply when the connector is fully inserted, resulting in a clear level jump that triggers the count. When removed, the opposite level jump occurs.

[0080] Smart counting combined with identification chips: For more complex connectors, if they have integrated identification chips (such as EEPROM or microcontrollers), specific identification information can be read or written through bus communication every time the connector is inserted, and the insertion and removal events can be recorded on the host side. This method can provide more comprehensive connector information, even including connection time, etc.

[0081] Regardless of the counting method, the internal counter in the module accurately records the total number of times the connector is inserted from the harness end to the host end. The mechanical life of the connector is usually directly related to the number of insertions and removals, which is a common understanding in the industry. Through real-time monitoring of this data, the system can accurately determine whether the connector is approaching its designed life. Once the number of insertions and removals reaches the pre-set threshold, the system can issue an early warning, indicating potential failures due to connector wear, such as unstable signals, poor contact, or even complete failure.

[0082] The host-side state monitoring module transmits these real-time contact resistance data and insertion and removal count data to the harness health assessment module through an internal digital interface. These data provide important supplementary information for the predictive maintenance of the entire harness, combined with physical stress data from the harness itself and signal quality data provided by the SerDes deserializer module, to create a complete view of the endoscope harness's overall, multi-dimensional health assessment, significantly improving the system's reliability and safety.

[0083] The wire harness health assessment module is in communication connection with the second data acquisition unit, the SerDes deserializer module, and the host end state monitoring module, is used for receiving the second physical data, the SerDes signal quality data, and the connector state data, and is used for performing health state assessment on the multi-modal transmission wire harness based on the second physical data, the SerDes signal quality data, and the connector state data; the wire harness health assessment module is used for performing health state assessment on the multi-modal transmission wire harness, and the health state assessment includes wire harness residual service life prediction.

[0084] Specifically, the wire harness health assessment module is a core component for realizing predictive maintenance. It is in close communication connection with multiple key units, including the second data acquisition unit responsible for collecting wire harness deformation, the SerDes deserializer module providing link performance indicators, and the host end state monitoring module monitoring interface conditions. Its core function is to receive and integrate various data from these units, namely second physical data, SerDes signal quality data, and connector state data, and perform comprehensive health state assessment on the multi-modal transmission wire harness based on these data. This assessment process is particularly critical, as it includes prediction of the wire harness residual service life.

[0085] When deploying the wire harness health assessment module, its calculation and running logic is implemented as follows:

[0086] This module is usually composed of a high-performance microcontroller (MCU) or an embedded processor, such as an ARMCortex-M series MCU or a Cortex-A series processor. It needs to be equipped with sufficient memory (RAM and non-volatile storage such as NANDFlash or EEPROM) to store assessment models, historical data, and configuration parameters.

[0087] The module is connected to various data sources through dedicated communication interfaces (such as SPI, I 2 C, UART, or higher-speed Ethernet / PCIe, etc.).

[0088] Receive second physical data: receive real-time fiber Bragg grating (FBG) sensor data from the second data acquisition unit. These data have been demodulated and represent the instantaneous bending radius and instantaneous tensile strain of the wire harness at different positions. The module will preliminarily timestamp and format this data to ensure data consistency.

[0089] Receive SerDes signal quality data: receive periodic or event-triggered SerDes signal quality data from the SerDes deserializer module, which includes real-time bit error rate (BER) data, eye diagram margin data (such as eye height and eye width), and jitter data (such as random jitter RJ and deterministic jitter DJ). These data are digitized, and the module will perform verification and storage.

[0090] Receive connector status data: Receive connector contact resistance data and connector plug-in times data from the host-side status monitoring module. The contact resistance data is usually periodically sampled values, and the plug-in times is a cumulative value. The module will record these data and monitor their trends.

[0091] To train the model, first need to build a set of representative features that can reflect the health status degradation of the wiring harness. These features not only include instantaneous values, but also include historical cumulative quantities and trends.

[0092] Feature set :

[0093] : Instantaneous maximum strain ;

[0094] : Instantaneous minimum bend radius ;

[0095] : Instantaneous bit error rate ;

[0096] : Instantaneous eye height ;

[0097] : Instantaneous eye width ;

[0098] : Instantaneous connector contact resistance ;

[0099] : Cumulative plug-in times ;

[0100] : Recent (e.g. in the past 1 hour) exceeding the preset threshold (e.g. ) cumulative duration;

[0101] : Recent (e.g. in the past 24 hours) less than the preset threshold (e.g. ) cumulative duration;

[0102] : Recent (e.g. in the past 10 minutes) average growth rate;

[0103] : Recent (e.g. in the past 1 hour) average decline rate;

[0104] Recent events (e.g., the last 100 plug-ins / unplugs) The average growth rate.

[0105] The calculation of these features requires the module to maintain a historical data buffer. Support vector regression is used as the core health assessment algorithm.

[0106] Dataset: A large amount of aging test data of wire harnesses under different operating conditions (such as bending, tension, temperature cycling, insertion and removal, etc.) was collected. During the experiments, the above feature set was continuously recorded. The data is collected and the actual health status of the harness is recorded simultaneously (for example, by physical testing, signal integrity testing, etc., to determine the critical point at which the harness performance begins to deteriorate, and to define a health index).

[0107] Label Definition: The health status of the wiring harness is defined as the Health Index (HI), a continuous value between 0 and 100. HI=100 indicates a brand new state, and HI=0 indicates complete failure. This is determined through expert experience or by preset performance thresholds (e.g., ...). High standards UI, or contact resistance > To determine the failure point.

[0108] SVR model training: using the collected feature set Using HI as input and HI as output, the SVR model is trained. The goal of SVR is to find a function This makes the features... to function value The deviation does not exceed a preset threshold. (Error tolerance) while minimizing model complexity. Radial basis function (RBF) kernels are typically used because of their strong nonlinear mapping capabilities.

[0109] Kernel function: ;

[0110] SVR model: in, It is a Lagrange multiplier. It is a bias term. Model parameters (such as C-value, ...) Value and The value was optimized through cross-validation.

[0111] Model running phase (online):

[0112] Real-time feature computation: During module runtime, it calculates and updates the feature set in real time based on the currently received real-time sensor data and historical buffer data. all feature values in the current time interval.

[0113] Health Index Calculation: The current calculated feature vector is input into the pre-trained SVR model, and the current health index is output. This calculation is performed periodically, for example, every 1 second.

[0114] Based on the health index , a Gaussian Process Regression (GPR) model is used to predict the Remaining Useful Life (RUL) of the wire harness. GPR can provide the mean and confidence interval of the prediction, enhancing the reliability of the prediction.

[0115] RUL Prediction Model Training Phase (Offline):

[0116] Dataset: Collect health index decay trajectory data from multiple wire harnesses from new to failure.

[0117] GPR Model Training: Take time or cumulative operation number as input, and health index as output, to train the GPR model. GPR does not regress data points, but rather regresses the functional distribution of data points. It learns the trend and uncertainty of health index changes over time / operation number. The model estimates the mean function and covariance function (through kernel functions such as RBF kernel), which describe the evolution path of the health index.

[0118] RUL Prediction Running Phase (Online): Historical Trajectory Input: The module inputs the recent health index historical trajectory (e.g., the past 24 hours of value sequence) of the current wire harness into the pre-trained GPR model.

[0119] Predict Future Trend: The GPR model will predict the mean and variance of future values based on this historical trajectory and its learned health index decay pattern.

[0120] RUL Calculation: Set a failure threshold (e.g., ). The module calculates when the predicted mean first reaches or falls below , and the difference between this time point and the current time is the remaining useful life (RUL). At the same time, GPR can give the prediction confidence interval, for example, "RUL is 100 hours ~ 20 hours", which provides more comprehensive information for user decision-making. The prediction frequency is usually every 5 minutes.

[0121] When the calculated health index is lower than a pre-set "warning threshold" (for example), the module will generate a level-1 warning signal.

[0122] When the predicted RUL is lower than a pre-set threshold, or the wire bundle health index reaches the warning line, the module will immediately issue a warning signal. These warnings can be output in various forms, such as sending to the upper computer through the network interface for human-computer interaction display, or triggering the indicator light, buzzer, etc. This allows the operator or maintenance personnel to take preventive measures in advance, such as arranging to replace the wire bundle, to avoid unexpected interruptions in critical medical operations, thereby significantly improving the reliability, safety and maintainability of equipment operation, and optimizing spare parts management.

[0123] When the predicted RUL is lower than a pre-set threshold, or the wire bundle health index reaches the warning line, the module will immediately issue a warning signal. These warnings can be output in various forms, such as sending to the upper computer through the network interface for human-computer interaction display, or triggering the indicator light, buzzer, etc. This allows the operator or maintenance personnel to take preventive measures in advance, such as arranging to replace the wire bundle, to avoid unexpected interruptions in critical medical operations, thereby significantly improving the reliability, safety and maintainability of equipment operation, and optimizing spare parts management.

[0124] When the predicted RUL is lower than a pre-set threshold, or the wire bundle health index reaches the warning line, the module will immediately issue a warning signal. These warnings can be output in various forms, such as sending to the upper computer through the network interface for human-computer interaction display, or triggering the indicator light, buzzer, etc. This allows the operator or maintenance personnel to take preventive measures in advance, such as arranging to replace the wire bundle, to avoid unexpected interruptions in critical medical operations, thereby significantly improving the reliability, safety and maintainability of equipment operation, and optimizing spare parts management.

[0125] The operation behavior analysis module is in communication connection with the wire bundle health evaluation module, is used for receiving the second physical data, and is used for generating a real-time reminding signal according to a comparison result of the second physical data and a preset stress threshold; the preset stress threshold in the operation behavior analysis module includes a preset minimum safe bending radius threshold and a preset maximum safe tensile force threshold. The operation behavior analysis module is used for generating the real-time reminding signal when the second physical data exceeds the preset stress threshold and lasts for a preset time length.

[0126] Specifically, it is usually implemented by a separate microcontroller (MCU) or as a dedicated processing thread or submodule within the wire bundle health evaluation module. It needs to have sufficient processing speed to process input data in real time and be able to quickly respond to generate a reminding signal.

[0127] The operation behavior analysis module receives the second physical data from the wire bundle health evaluation module through a communication interface (such as SPI or I 2 C) continuously. These data are updated in real time, representing the instantaneous bending radius and instantaneous tensile strain of the wire bundle at various points. The module will perform preliminary low-pass filtering or moving average processing on this data to eliminate transient noise or measurement fluctuations, ensuring the stability of subsequent judgments.

[0128] A series of preset stress thresholds are pre-stored in the module. These thresholds are determined comprehensively according to the design specifications of the wire bundle, material characteristics, fatigue life test results, and clinical operation experience, and are usually written into non-volatile memory when the system is shipped, but can also be calibrated or updated by the upper computer when needed.

[0129] Pre-set minimum safe bend radius threshold: This is a critical parameter. For example, if the minimum bend radius allowed by the design of the harness is R_min, the threshold set might be R_min or slightly larger than R_min. When the local bend radius of the harness is smaller than this threshold, it means that the harness is experiencing bending stress beyond the design range, and long-term exposure to this will cause fatigue damage and even internal breakage.

[0130] Pre-set maximum safe tensile force threshold: This is another important parameter. It corresponds to the maximum tensile strain or equivalent tensile force that the harness can withstand. Once the tensile strain experienced by the harness exceeds this threshold, it indicates that there might be excessive pulling or jamming, which will accelerate the stress fatigue of the internal conductors of the harness and even cause fiber or copper wire breakage.

[0131] The module will compare each received bend radius data with the pre-set minimum safe bend radius threshold in real time, and each tensile strain data with the pre-set maximum safe tensile force threshold.

[0132] More importantly, to avoid false positives, the module introduces a "pre-set duration" judgment mechanism. This means that even if the data at a certain moment exceeds the threshold, the module will not immediately alarm. Only when a certain stress data (whether the bend radius is too small or the tensile strain is too large) continuously exceeds its corresponding pre-set threshold, and this duration reaches a pre-set specific duration (for example, it can be set to 50 milliseconds, 100 milliseconds or longer), the module will generate and send a real-time reminder signal. This "pre-set duration" is a configurable parameter, and its purpose is to filter out transient, short-lived stress peaks and only respond to persistent, potentially dangerous abnormal operating behavior.

[0133] Once the judgment condition is met (i.e. the stress data exceeds the threshold and lasts for a pre-set duration), the operating behavior analysis module will immediately generate a real-time reminder signal. This signal can be output in several ways:

[0134] Visual cues: send signals to the host computer to drive warning icons, pop-up windows or change the color of the user interface on the display.

[0135] Auditory cues: drive the buzzer, speaker to emit alarm sounds or voice prompts.

[0136] Tactile cues: if the system supports, it can even drive the handle to vibrate feedback. These reminder signals will immediately feedback to the operating doctor, guiding him to adjust the operation method, such as prompting "Please do not over-bend the harness" or "Pay attention to whether the harness is jammed".

[0137] Through this real-time and intelligent stress monitoring and early warning mechanism, the operation behavior analysis module realizes instant feedback on the operation behavior of the doctor, effectively avoiding the instantaneous or cumulative damage to the wire harness caused by improper operation (such as sharp bending and excessive stretching), thereby significantly prolonging the actual service life of the multi-modal transmission wire harness, reducing the equipment maintenance cost, and further improving the safety of medical operation and the reliability of the equipment.

[0138] A user interface module, which is in communication connection with the wire harness health assessment module and the operation behavior analysis module, is used to receive the health state assessment result and the real-time reminding signal, and is used to display the health state assessment result and the real-time reminding signal. The user interface module is used to display the real-time reminding signal in a visual manner, and the visual manner includes displaying a text prompt or color change at the edge of a video screen.

[0139] Embodiment two:

[0140] Please refer to the accompanying Figure 2 The multi-modal endoscope video transmission wire harness method based on a high-speed SerDes chip includes the following steps:

[0141] S1: Collecting video data, front-end control signals, and first physical data collected by a first data collection unit;

[0142] S2: Serializing the video data and the first physical data into high-speed SerDes signals;

[0143] S3: Transmitting the high-speed SerDes signals through a multi-modal transmission wire harness, and collecting second physical data by a second data collection unit in the multi-modal transmission wire harness;

[0144] S4: Deserializing the high-speed SerDes signals to recover the video data, and generating quality data of the SerDes signals;

[0145] S5: Collecting connector state data;

[0146] S6: Assessing the health state of the multi-modal transmission wire harness based on the second physical data, the SerDes signal quality data, and the connector state data;

[0147] S7: Generating a real-time reminding signal based on the comparison result of the second physical data and a preset stress threshold;

[0148] S8: Displaying the health state assessment result and the real-time reminding signal.

[0149] In the construction of a high-performance, high-reliability endoscope system, a multi-modal video transmission harness method based on high-speed SerDes chips is proposed. The core of this scheme is not only to stably transmit high-definition video, but more importantly, it can "perceive" the health status of the harness in real time and comprehensively, and give early warning to potential risks, thereby greatly improving the safety of medical operations and the durability of equipment.

[0150] Here, the first data acquisition unit is deployed, and the high-definition video signal is captured here. High-resolution CMOS image sensors such as Sony IMX258 (13MP) or Ansonic AR0821 (8MP) are usually selected. They directly collect images of the lesion area, and then process them into 4K UHD (3840x2160) @60fps digital video streams through front-end image processors (such as Ansonic AP1302). At the same time, some necessary front-end control signals, such as PWM instructions for LED lighting, I 2 C or SPI control signals, and GPIO control signals for biopsy forceps, are also generated and aggregated by the front-end STM32F4 series microcontroller. More ingeniously, this unit also embeds a micro FBG sensor array. Usually, one is implanted every 5mm on the bendable part of the endoscope tip, and there are a total of 5 to 10. They can sense the instantaneous bending angle and local deformation strain of the endoscope tip at a frequency of 200Hz. These data are obtained through a customized micro fiber demodulation module.

[0151] Then, inside the endoscope front-end module, next to the data acquisition unit, a SerDes serializer module is integrated. It acts as an efficient "data packer" that integrates all the information collected by the front end. Here, 4K video data (code stream up to 12Gbps when uncompressed), front-end control signals (about 10Mbps), and first physical data (about 1Mbps) are first subjected to time division multiplexing and formatting processing. Then, high-performance SerDes serializer chips such as Texas Instruments' DS90UB949 or Analog Devices' ADV7480 are selected. They can efficiently serialize these parallel data streams (through MIPICSI-2 or LVDS interface) into single or dual high-speed differential SerDes signals. Usually, FPD-Link III protocol is used, with a single-link transmission rate set at 8Gbps to 12.5Gbps, and through two differential pairs of transmission, this bandwidth is sufficient to stably carry 4K@60fps video and all auxiliary data. The transmission protocol itself contains embedded clock, so no additional clock line is needed.

[0152] These high-speed SerDes signals, as well as the sensing data of the cable itself, are transmitted through a specially designed multi-modal cable. This cable is the physical lifeline of the entire system, and it contains 2 or 4 pairs of AWG30 to AWG34 high-purity oxygen-free copper differential pairs inside, each pair has an independent aluminum foil or copper braid shield layer, which is specifically designed to carry these high-speed SerDes signals, ensuring signal integrity even when the cable length reaches 5 to 15 meters. Its "multi-modal" feature is that it embeds 2 to 4 thin optical fibers inside the same cable. Each internal has 200 to 500 Fiber Bragg Grating (FBG) sensors pre-written, which are evenly distributed every 10 mm along the length of the cable. These FBG sensors can monitor the instantaneous bending radius (range 2mm to infinity) and instantaneous tensile strain (range -1000 micro-strain to +5000 micro-strain) of the entire cable in real time at a frequency of 100Hz. When the cable is bent or stretched, the center wavelength of the FBG sensor will drift, and these wavelength data are transmitted to the host's fiber demodulator (such as Luna Innovations ODiSI6000) to convert into specific deformation data, which is the second physical data. To ensure the reliability of the cable in a complex electromagnetic environment, a multi-layer shielding structure is also used: each pair of differential lines is independently shielded, plus a high-coverage (more than 95%) overall copper braid shielding layer, and the outermost layer is covered with a layer of conductive polymer shielding. The outer sheath of the cable is made of medical-grade TPU material, with a diameter strictly controlled within 2.8mm. This material can ensure that the cable has a bending life of more than 200,000 times and a tensile strength of more than 50N, fully meeting the stringent requirements of medical devices.

[0153] When the signal reaches the host, the SerDes deserializer module begins to work. Usually choose a deserializer chip matched with the front-end serializer, such as Texas Instruments DS90UB940 or Analog Devices ADV7680. It directly receives high-speed SerDes signals from the cable, extracts the clock through the internal clock data recovery (CDR) circuit, and then compensates for signal attenuation and distortion produced during cable transmission through a powerful adaptive equalizer, with a compensation gain of more than 30dB, ensuring that the recovered parallel video data stream (such as MIPICSI-2 or HDMI format) is clear. More importantly, the deserializer chip also has a signal quality monitoring function, which outputs SerDes signal quality data in real time, including bit error rate (BER), which is required to be less than 10 -12 Once elevated to 10 -9Considered abnormal; also eye diagram margin data, such as eye height should be greater than 70% UI, eye width greater than 60% UI; and jitter data, total jitter (TJ) should be less than 0.3 UI. These data are transmitted to the subsequent module at a frequency of 10 Hz through the I 2 C or SPI interface.

[0154] At the same time, on the host side, a host-side state monitoring module is also deployed at the interface connected to the multi-modal transmission harness. This module is specifically responsible for collecting connector state data. Using the four-wire Kelvin measurement method, a 10 mA current is periodically injected into the key pins at an interval of 500 ms, and the contact resistance is measured, which should be less than 20 mΩ normally, and more than 50 mΩ continuously is considered abnormal. This can accurately determine whether the connector is in poor contact or oxidation. At the same time, a micro switch or optical sensor is integrated on the connector's insertion mechanism, and a counting signal is triggered every time the harness is inserted or pulled out. The non-volatile counter inside the module will accumulate the number of insertions and extractions, for example, record once every 5000 times, and the maximum can reach 100,000 times. Because the design life of the connector is usually 5000 to 10000 insertions and extractions, this data can directly reflect the wear and tear of the connector.

[0155] Next, all these data will converge to the harness health assessment module. It is usually composed of a high-performance microcontroller or embedded processor. This module will receive the second physical data from the second data acquisition unit (100 Hz), the signal quality data from the SerDes deserializer module (10 Hz), and the connector state data from the host-side state monitoring module (2 Hz). It first synchronizes and normalizes these multi-source heterogeneous data, and then performs fine feature extraction, such as calculating the cumulative duration of the bending radius less than 5 mm, the peak and duration of the tensile strain exceeding 2000 micro-strain, the growth rate of BER within 1 minute, the decline percentage of eye diagram margin within 1 hour, and the average growth rate of contact resistance within 100 insertion and extraction cycles. These features are then input into a pre-trained machine learning model, which calculates a harness health index (0-100) in real time by analyzing historical failure patterns, for example, a health index below 30 is considered sub-healthy. Further, the module also uses Gaussian process regression or similarity prediction algorithms to predict the remaining useful life (RUL) of the harness based on the decline trend of the health index, for example, "remaining 200 hours" or "remaining 50 complete endoscopic surgeries". When the RUL is below the preset threshold, the module will immediately issue a warning.

[0156] Finally, there is a critical operational behavior analysis module. It receives the second physical data (instantaneous bending radius and instantaneous tensile strain) continuously at a frequency of 100 Hz, either independently or as a sub-function of the health assessment module. This module has preset stress thresholds stored internally: the minimum safe bending radius threshold is 3.0 mm, and the maximum safe tensile force threshold is 40 Newtons (or equivalent 3000 micro-strain). Its core logic is as follows: if the wire harness local bending radius is less than 3.0 mm, or the tensile strain is greater than 3000 micro-strain, and this abnormal state lasts more than 100 milliseconds, the module will immediately generate a real-time reminder signal. This "duration" judgment mechanism avoids transient false positives.

[0157] All these health status assessment results and real-time reminder signals will eventually be visually presented on the host's display interface. For example, there will be a special "wire harness health" dashboard to display the current health index in percentage (such as health 85%) or grade (excellent / good / warning / danger), and give a prediction of the remaining life (such as "remaining 200 hours"). At the same time, when the operational behavior analysis module triggers a real-time reminder, a red warning box (such as "wire harness over-bending!") will pop up on the display, accompanied by a flashing icon and a clear alarm sound (440 Hz intermittent beep), and even in extreme cases, the system can temporarily limit some operation functions until the wire harness posture is restored to safety.

[0158] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, replacements and variations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A multi-modal endoscope video transmission harness system based on high-speed SerDes chips, characterized in that, The application relates to a multi-modal transmission line bundle health monitoring system, comprising: an endoscope front-end module for collecting video data and front-end control signals, and comprising a first data collection unit for collecting first physical data; a SerDes serializer module for serializing the video data and the first physical data into high-speed SerDes signals; a multi-modal transmission line bundle for transmitting the high-speed SerDes signals, the multi-modal transmission line bundle comprising a second data collection unit for collecting second physical data; a SerDes deserializer module for deserializing the high-speed SerDes signals to recover the video data and generate quality data of the SerDes signals; a host-end state monitoring module for collecting connector state data; a line bundle health assessment module for receiving the second physical data, the SerDes signal quality data and the connector state data, and for performing health state assessment of the multi-modal transmission line bundle based on the second physical data, the SerDes signal quality data and the connector state data; an operating behavior analysis module for receiving the second physical data, and generating a real-time reminder signal according to a comparison result of the second physical data and a preset stress threshold; a user interface module for receiving the health state assessment result and the real-time reminder signal, and for displaying the health state assessment result and the real-time reminder signal; the first physical data and the second physical data comprise instantaneous bending radius data and instantaneous tensile strain data.

2. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the first data collection unit and the second data collection unit each comprise a physical sensor, and the physical sensor comprises a fiber Bragg grating sensor.

3. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the SerDes signal quality data generated by the SerDes deserializer module comprises bit error rate data, eye diagram margin data and jitter data.

4. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the host-end state monitoring module is used for collecting the connector state data, and the connector state data comprises connector contact resistance data and connector plugging frequency data.

5. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the line bundle health assessment module is used for performing health state assessment of the multi-modal transmission line bundle, and the health state assessment comprises line bundle residual service life prediction.

6. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the preset stress threshold in the operating behavior analysis module comprises a preset minimum safe bending radius threshold and a preset maximum safe tensile force threshold.

7. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the operating behavior analysis module is used for generating the real-time reminder signal when the second physical data exceeds the preset stress threshold and lasts for a preset time length.

8. The high-speed SerDes chip-based multi-modal endoscope video transmission harness system of claim 1, wherein: the user interface module is used for displaying the real-time reminder signal in a visual manner, and the visual manner comprises displaying a text prompt or color change at an edge of a video picture.

9. The multi-modal endoscope video transmission cable method based on high-speed SerDes chip according to any one of claims 1-8, characterized in that, The application relates to a multi-modal transmission line bundle health monitoring system, comprising the following steps: S1: collecting video data, front-end control signals and first physical data collected by a first data collection unit; the first physical data is instantaneous bending radius data; S2: serializing the video data and the first physical data into high-speed SerDes signals; S3: transmitting the high-speed SerDes signals through a multi-modal transmission line bundle, and collecting second physical data by a second data collection unit in the multi-modal transmission line bundle; the second physical data is instantaneous tensile strain data; S4: de-serializing the high-speed SerDes signal to recover the video data and generating quality data of the SerDes signal; S5: collecting connector status data; S6: performing health status evaluation on the multi-modal transmission wire harness based on the second physical data, the SerDes signal quality data and the connector status data; S7: generating a real-time reminder signal based on a comparison result of the second physical data and a preset stress threshold; S8: displaying the health status evaluation result and the real-time reminder signal.

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