Circuit fault real-time diagnosis and dynamic management method of high-integration SiP frequency synthesizer

Abstract

The invention provides a circuit fault real-time diagnosis and dynamic management method for a high-integration SiP frequency synthesizer, and relates to the technical field of frequency synthesizers. Sensing data of all sensors in the SiP frequency synthesizer are collected, and all the sensors are sensors which are arranged in the SiP frequency synthesizer based on the structure, the signal transmission path and the heat conduction characteristic of the SiP frequency synthesizer in the design stage of the SiP frequency synthesizer; checking whether the SiP frequency synthesizer has a fault or not based on the sensing data and a fault diagnosis model; and when a fault is detected, tasks in the main function module are migrated to the standby function module by utilizing reconfigurable wiring resources in the SiP frequency synthesizer, and working parameters of the frequency synthesizer are adjusted through an intelligent algorithm by virtue of system-level cooperative control capability. According to the invention, by using the structure and performance advantages of SiP, real-time monitoring and rapid and accurate diagnosis of circuit faults are achieved, and dynamic and adaptive intelligent management is implemented according to different fault types.

Description

Technical Field

[0001] The present invention relates to the technical field of frequency synthesizers, and in particular to a method for real-time diagnosis and dynamic management of circuit faults of a highly integrated SiP frequency synthesizer. Background Art

[0002] Frequency synthesizers are core components in modern communications, radar, electronic measurement, and other fields, and their performance significantly impacts overall system performance. Highly integrated SiP (System in a Package) frequency synthesizers are widely used in a variety of high-end electronic devices due to their compact size, high integration density, and low signal transmission loss. However, their highly dense internal structure, complex inter-chip interconnections, and increasingly harsh operating environments increase the probability of circuit failures, making troubleshooting and repair more difficult.

[0003] Existing fault diagnosis methods rely primarily on external test equipment and manual judgment, often performed after the fact. This makes it difficult to effectively identify and address faults immediately after they occur. This not only leads to extended system downtime and increased maintenance costs, but can also seriously impact the stability and reliability of the entire electronic system. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In response to the deficiencies of the prior art, the present invention provides a method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer, which solves the technical problem that existing fault diagnosis methods are difficult to effectively identify and process faults at the moment they occur.

[0006] (2) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] In a first aspect, the present invention provides a method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer, comprising:

[0009] Collect sensor data from various sensors in the SiP frequency synthesizer, where the various sensors refer to sensors installed in key nodes of chip interconnection between the SiP frequency synthesizer, weak points of the power distribution network, signal transmission lines susceptible to interference, and heat-sensitive areas;

[0010] Checks whether the SiP frequency synthesizer has a fault based on sensor data and a pre-trained fault diagnosis model that incorporates SiP thermal characteristics. If a fault is detected, executes the next step.

[0011] The reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks in the main functional module to the backup functional module, and with the help of system-level collaborative control capabilities, the operating parameters of the SiP frequency synthesizer are adjusted through intelligent algorithms.

[0012] Preferably, the sensors include a voltage sensor, a current sensor, a temperature sensor and a stress sensor.

[0013] Preferably, the training process of the pre-trained fault diagnosis model integrating SiP thermal characteristics includes:

[0014] Electrical temperature data under different working conditions and fault modes are collected. After data cleaning and feature extraction, the data are divided into training set, validation set and test set. An intelligent algorithm is used to train the improved deep neural network architecture, so that the improved deep neural network architecture has the best diagnostic accuracy on the validation set. Training is stopped when the evaluation accuracy of the test set reaches more than 98%, and a fault diagnosis model integrating SiP thermal characteristics is obtained.

[0015] Preferably, the operating parameters include power distribution strategy and signal transmission path and timing.

[0016] In a second aspect, the present invention provides a highly integrated SiP frequency synthesizer, including several sensors, a main function module, reconfigurable wiring resources, a backup function module, a data acquisition module, and a data processing module;

[0017] Among them, several sensors are used to detect the sensing data of key nodes of chip interconnection between SiP frequency synthesizers, weak points of power distribution networks, signal transmission lines susceptible to interference, and heat-sensitive areas in highly integrated SiP frequency synthesizers;

[0018] The data acquisition module is used to collect sensor data from each sensor;

[0019] The data processing module is used to check whether the SiP frequency synthesizer has a fault based on sensor data and a fault diagnosis model that integrates the SiP thermal characteristics. When a fault is detected, the reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks in the main functional module to the backup functional module, and with the help of system-level collaborative control capabilities, the operating parameters of the frequency synthesizer are adjusted through intelligent algorithms.

[0020] Preferably, the sensors include a voltage sensor, a current sensor, a temperature sensor and a stress sensor.

[0021] Preferably, the data acquisition module includes a high-speed analog-to-digital converter with a sampling rate of GHz level.

[0022] Preferably, the data acquisition module and the data processing module perform signal transmission through a high-speed through silicon via interconnection structure of a SiP frequency synthesizer.

[0023] Preferably, the reconfigurable wiring resources adopt a flexible wiring structure based on programmable logic devices.

[0024] Preferably, the highly integrated SiP frequency synthesizer also includes a fault information recording and analysis module for recording the occurrence time, fault type, processing process and processing result information of each fault in real time, and optimizing the fault diagnosis model and intelligent algorithm by analyzing historical fault data.

[0025] (3) Beneficial effects

[0026] The present invention provides a method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer. Compared with the prior art, it has the following advantages:

[0027] The present invention collects sensor data from various sensors in a SiP frequency synthesizer, wherein the various sensors refer to sensors arranged inside the SiP frequency synthesizer during the design phase of the SiP frequency synthesizer based on the structure, signal transmission path, and thermal conductivity characteristics of the SiP frequency synthesizer; checks whether the SiP frequency synthesizer has a fault based on the sensor data and a pre-trained fault diagnosis model that integrates the SiP thermal characteristics; when a fault is detected, the reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks in the main function module to the backup function module, and with the help of system-level collaborative control capabilities, the operating parameters of the frequency synthesizer are adjusted through an intelligent algorithm. The present invention utilizes the structural and performance advantages of the SiP to achieve real-time monitoring of circuit faults, rapid and accurate diagnosis, and dynamic, adaptive intelligent management based on different fault types, thereby effectively improving the reliability and stability of the frequency synthesizer, significantly shortening system downtime caused by faults, and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 A block diagram of a method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer;

[0030] Figure 2 A specific flow chart of the method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer;

[0031] Figure 3Schematic diagram of the internal structure of a highly integrated SiP frequency synthesizer;

[0032] Figure 4 This is the architecture diagram of the data acquisition and transmission system. DETAILED DESCRIPTION

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0034] The embodiments of the present application provide a method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer, thereby solving the technical problem that existing fault diagnosis methods are difficult to effectively identify and process faults at the moment they occur. This enables real-time monitoring of circuit faults, rapid and accurate diagnosis, and dynamic, adaptive intelligent management based on different fault types.

[0035] The technical solution in the embodiments of the present application is to solve the above technical problems, and the overall idea is as follows:

[0036] Existing fault diagnosis methods primarily rely on external test equipment and manual judgment, often performed after the fact, making it difficult to effectively identify and address faults immediately. This not only increases system downtime and maintenance costs, but can also severely impact the stability and reliability of the entire electronic system. Furthermore, existing fault management strategies are often static and simplistic, making it difficult to dynamically adjust to varying fault types and severity. This inadequately addresses the complex and ever-changing application requirements of highly integrated SiP frequency synthesizers.

[0037] More importantly, the unique structure and working characteristics of SiP, such as chip stacking, through-silicon via (TSV) interconnection, and system-level thermal management, have not been fully considered and utilized in existing fault diagnosis and management methods. Therefore, there is an urgent need for an innovative method specifically for highly integrated SiP frequency synthesizers to achieve real-time, accurate diagnosis and efficient, intelligent dynamic management of circuit faults. In order to meet the above needs, the embodiment of the present invention proposes a method for real-time diagnosis and dynamic management of circuit faults of highly integrated SiP frequency synthesizers. The method fully utilizes the structural and performance advantages of SiP to achieve real-time monitoring of circuit faults, rapid and accurate diagnosis, and dynamic, adaptive intelligent management based on different fault types, thereby effectively improving the reliability and stability of the frequency synthesizer, significantly shortening the system downtime caused by faults, and reducing maintenance costs.

[0038] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0039] The embodiment of the present invention provides a method for real-time diagnosis and dynamic management of circuit faults of a highly integrated SiP frequency synthesizer, such as Figure 1 As shown, the method includes:

[0040] S1. Collect sensor data from each sensor in the SiP frequency synthesizer, where each sensor refers to sensors located at key nodes of chip interconnection, weak points of the power distribution network, signal transmission lines susceptible to interference, and heat-sensitive areas in the SiP frequency synthesizer;

[0041] S2. Check whether the SiP frequency synthesizer has a fault based on the sensor data and a pre-trained fault diagnosis model that integrates the SiP thermal characteristics; if a fault is detected, execute the next step;

[0042] S3. Utilize the reconfigurable wiring resources within the SiP frequency synthesizer to migrate tasks in the main functional module to the backup functional module, and with the help of system-level collaborative control capabilities, adjust the operating parameters of the frequency synthesizer through intelligent algorithms.

[0043] The embodiments of the present invention utilize the structural and performance advantages of SiP to achieve real-time monitoring of circuit faults, rapid and accurate diagnosis, and dynamic, adaptive intelligent management based on different fault types, thereby effectively improving the reliability and stability of the frequency synthesizer, significantly shortening system downtime caused by faults, and reducing maintenance costs.

[0044] The following is combined with Figure 2 The specific flow chart shown describes each step in detail:

[0045] In step S1, the sensor data of each sensor in the SiP frequency synthesizer is collected. The specific implementation process is as follows:

[0046] like Figure 2As shown, during the design phase of the SiP frequency synthesizer, advanced 3D electromagnetic simulation (such as ANSYS HFSS) and thermal analysis software (such as ANSYS Icepak) were used to deeply analyze the internal chip stacking structure, electromagnetic field distribution, signal transmission paths, and thermal conductivity characteristics. Based on these analysis results, ultra-miniature, highly sensitive sensors were precisely placed at key interconnect nodes between chips, vulnerable points in the SiP package's power distribution network (PDN), signal transmission lines susceptible to electromagnetic interference, and thermally sensitive areas. These sensors include voltage, current, temperature, and strain sensors, such as those based on MEMS technology, as well as high-precision thin-film temperature and strain sensors. Advanced flip-chip or wafer-level packaging technologies were used to establish reliable electrical connections between the sensors and key nodes within the SiP frequency synthesizer. These sensors can sense subtle changes in electrical parameters and physical quantities in real time. For example, by monitoring the subtle resistance changes of specific metal interconnects within the SiP frequency synthesizer, potential circuit failure risks can be preemptively identified. Leveraging the SiP's compact structure, this allows for more comprehensive and detailed monitoring of critical areas.

[0047] The sensor data from each sensor is collected through a high-speed ADC with a sampling rate of GHz level, and these sensor data are converted from analog signals into digital signals, and the data signals are transmitted to the data processing chip through TSV transmission.

[0048] In the embodiment of the present invention, the internal structure diagram of the highly integrated SiP frequency synthesizer is as follows: Figure 3 As shown, Figure 3 This diagram shows the chip stacking within the SiP frequency synthesizer, the locations of key functional modules, the nodes between various sensors, and the specific layout of the PDN. Figures 1 and 2 show the seam-welded package, 2 are embedded coupling lines, 3 are active RF components, 4 are embedded sensors, 5 are digital control components, 6 are passive RF components, 7 are pop-up balls, 8 are BGA solder balls, 9 are PDN components, and 10 are substrates.

[0049] Figure 4 This is a diagram of the data acquisition and transmission system architecture. It shows the complete path from sensor data acquisition, conversion by the high-speed, low-power data acquisition circuit, and transmission to the data processing unit via the high-speed through-silicon via (TSV) interconnect structure within the SiP frequency synthesizer. It should be noted that the number of monitoring points is set according to needs, and can monitor voltage, current, temperature stress, etc. Modules 1, 2, and 3 refer to the various functional modules in the highly integrated SiP frequency synthesizer, and paths 1-3 refer to the various backup functional modules in the highly integrated SiP frequency synthesizer.

[0050] In step S2, the SiP frequency synthesizer is checked for faults based on the sensor data and a pre-trained fault diagnosis model that integrates the SiP thermal characteristics. If a fault is detected, the next step is executed. The specific implementation process is as follows:

[0051] In an embodiment of the present invention, a fault diagnosis program integrating SiP thermal characteristics is written into the data processing chip, which is used to determine whether the SiP frequency synthesizer has a fault based on various sensor data (sensor data after conversion into digital signals). When a fault is detected, the next step S3 is executed. When no fault is detected, real-time monitoring is continued. In an embodiment of the present invention, the fault diagnosis program is a fault diagnosis model integrating SiP thermal characteristics using an improved deep neural network architecture. A special layer capable of processing thermal-electric multi-physical field coupling data is specially added. It is trained through a large amount of sample data under different working conditions and different fault modes, so that it can accurately identify various complex faults such as component performance degradation caused by overheating, solder joint failure, and chip interconnection failure. The fault diagnosis model integrating SiP thermal characteristics is pre-trained, and its training process is as follows:

[0052] A large amount of electrical parameter and temperature data was collected from highly integrated SiP frequency synthesizers under various operating conditions (e.g., varying operating frequencies, temperature ranges, and input signal strengths) and failure modes (including component short circuits, open circuits, performance degradation, and thermal failure). Data cleaning algorithms were used to preprocess the raw data, including denoising and filtering, to remove abnormal data and noise interference, thereby improving data quality. Next, feature extraction algorithms were used to extract key information from the preprocessed data that reflects fault characteristics, such as the signal's time and frequency domain characteristics and temperature gradient changes.

[0053] The processed data was divided into training, validation, and test sets, with the training set accounting for 70%, the validation set 15%, and the test set 15%. The training set was used to train a fault diagnosis model that incorporates SiP thermal characteristics. Intelligent algorithms such as stochastic gradient descent were employed during the training process to continuously adjust model parameters, such as the weight distribution of the thermal-electric coupling layer, the number of neurons in each neural network layer, and the connection weights. This optimized the diagnostic accuracy of the fault diagnosis model on the validation set. After multiple rounds of training and optimization, the trained fault diagnosis model that incorporates SiP thermal characteristics was evaluated using the test set to ensure a diagnostic accuracy exceeding 98%.

[0054] During real-time detection, the real-time sensor data is processed through a trained fault diagnosis model that integrates the thermal characteristics of the SiP. This model can accurately identify various complex faults such as component performance degradation caused by overheating, solder joint failure, and inter-chip interconnection failure.

[0055] In step S3, the reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks from the main functional module to the backup functional module. With the help of system-level collaborative control capabilities, the operating parameters of the frequency synthesizer are adjusted through intelligent algorithms. The operating parameters include power distribution strategy, signal transmission path and timing. The specific implementation process is as follows:

[0056] When the fault diagnosis model detects a fault, a dynamic management strategy is rapidly implemented based on the resource sharing and flexible configuration characteristics of the SiP frequency synthesizer. If a frequency synthesis functional module on a chip fails, the pre-designed reconfigurable routing resources within the SiP frequency synthesizer are used to quickly and dynamically migrate the task to other backup functional modules with similar functions within the same SiP frequency synthesizer. At the same time, leveraging the SiP's system-level collaborative control capabilities, intelligent algorithms are used to adjust the operating parameters of the entire frequency synthesizer in real time. For example, power distribution strategies are optimized to prioritize the stable power supply of key functional modules, and signal transmission paths and timing are adjusted to ensure that the system can maintain stable operation of basic functions even in the event of a fault.

[0057] It should be noted that, in its implementation, the algorithm's intelligent algorithm includes a weight analysis function that intelligently adjusts the weights of each heating unit. By eliminating external interference and accumulating historical data for comparison, the loop's delay, filter shape, and superposition phase shift are adjusted accordingly based on the characteristics revealed by the weight analysis.

[0058] Through TSV transmission, the operating parameters are transmitted to the internal circuit of the highly integrated SiP frequency synthesizer. At the same time, fault alarms and operating parameters can be transmitted to the PCB or other external devices through data line transmission.

[0059] An embodiment of the present invention further provides a highly integrated SiP frequency synthesizer, which includes several sensors, a main function module, a reconfigurable wiring resource, a backup function module, a data acquisition module, and a data processing module;

[0060] Among them, several sensors are used to detect the sensing data of key nodes of chip interconnection between SiP frequency synthesizers, weak points of power distribution networks, signal transmission lines susceptible to interference, and heat-sensitive areas in highly integrated SiP frequency synthesizers;

[0061] The data acquisition module is used to collect sensor data from each sensor;

[0062] The data processing module is used to check whether the SiP frequency synthesizer has a fault based on sensor data and a fault diagnosis model that integrates the SiP thermal characteristics. When a fault is detected, the reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks in the main functional module to the backup functional module, and with the help of system-level collaborative control capabilities, the operating parameters of the frequency synthesizer are adjusted through intelligent algorithms.

[0063] The data acquisition module uses a high-speed ADC with sampling rates up to GHz, enabling rapid and accurate conversion of the sensor's analog output signals with picosecond-level timing accuracy. The converted digital signals are transmitted with extremely low transmission loss via the high-speed through-silicon via (TSV) interconnect structure within the SiP to a data processing module (such as an FPGA (field programmable gate array) or a dedicated data processing chip) for preliminary processing and caching.

[0064] During the hardware design phase of a highly integrated SiP frequency synthesizer, reconfigurable routing resources and backup functional modules are pre-planned and designed. Reconfigurable routing resources utilize a flexible routing structure based on programmable logic devices (such as FPGAs), enabling rapid switching of signal transmission paths based on fault diagnosis results. The backup functional module has similar functionality and performance to the primary functional module, but normally operates in a standby state. In the event of a primary functional module failure, it can quickly start up and take over.

[0065] At the software level, a complete dynamic management strategy execution program was developed. Based on the output of the fault diagnosis model, this program uses an intelligent decision-making algorithm to determine the fault type and severity, and then automatically triggers the corresponding dynamic management strategy. For example, when a fault is detected in a frequency synthesis module on a specific chip, the program first controls the reconfigurable routing resources to switch the input signal to the input port of a backup module and adjusts the relevant timing and control signals to ensure the normal operation of the backup module. Simultaneously, based on the system's current operating status and fault conditions, an intelligent algorithm is used to adjust the operating parameters of the entire frequency synthesizer in real time. For example, power is reallocated to prioritize stable power supply to critical functional modules, and parameters such as signal transmission amplitude, phase, and frequency are adjusted to compensate for performance losses caused by the fault. Furthermore, a fault information recording and analysis module is established to record in real time the time, type, handling process, and results of each fault. By analyzing historical fault data, the fault diagnosis model and intelligent algorithm (i.e., the intelligent algorithm that adjusts the operating parameters of the entire frequency synthesizer in real time) are continuously optimized to improve system reliability and stability.

[0066] In summary, compared with the existing technology, the present invention has the following beneficial effects:

[0067] 1. The embodiments of the present invention utilize the structural and performance advantages of SiP to achieve real-time monitoring of circuit faults, rapid and accurate diagnosis, and dynamic, adaptive intelligent management based on different fault types, thereby effectively improving the reliability and stability of the frequency synthesizer, significantly shortening system downtime caused by faults, and reducing maintenance costs.

[0068] 2. This embodiment of the present invention leverages three-dimensional electromagnetic simulation and thermal analysis to precisely deploy ultra-micro, highly sensitive sensors at key locations within the SiP frequency synthesizer, enabling precise monitoring of electrical parameters and physical quantities. By building a deep learning fault diagnosis model that integrates the SiP's thermal characteristics and utilizing a thermal-electric multi-physics field coupled data processing layer, it accurately identifies a wide range of complex faults. When a fault occurs, reconfigurable wiring resources within the SiP are leveraged to transfer tasks, and system-level collaborative control adjusts operating parameters to ensure stable system operation.

[0069] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0070] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for real-time diagnosis and dynamic management of circuit faults in a highly integrated SiP frequency synthesizer, characterized in that: include: Collect sensor data from various sensors in the SiP frequency synthesizer, where the various sensors refer to sensors installed in key nodes of chip interconnection between the SiP frequency synthesizer, weak points of the power distribution network, signal transmission lines susceptible to interference, and heat-sensitive areas; Checks whether the SiP frequency synthesizer has a fault based on sensor data and a pre-trained fault diagnosis model that incorporates SiP thermal characteristics. If a fault is detected, executes the next step. The reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks in the main functional module to the backup functional module, and with the help of system-level collaborative control capabilities, the operating parameters of the SiP frequency synthesizer are adjusted through intelligent algorithms.

2. The method for real-time diagnosis and dynamic management of circuit faults of a highly integrated SiP frequency synthesizer according to claim 1, wherein: The sensors include a voltage sensor, a current sensor, a temperature sensor and a stress sensor.

3. The method for real-time diagnosis and dynamic management of circuit faults of a highly integrated SiP frequency synthesizer according to claim 1, wherein: The training process of the pre-trained fault diagnosis model integrating SiP thermal characteristics includes: Electrical temperature data under different working conditions and fault modes are collected. After data cleaning and feature extraction, the data are divided into training set, validation set and test set. An intelligent algorithm is used to train the improved deep neural network architecture, so that the improved deep neural network architecture has the best diagnostic accuracy on the validation set. Training is stopped when the evaluation accuracy of the test set reaches more than 98%, and a fault diagnosis model integrating SiP thermal characteristics is obtained.

4. The method for real-time diagnosis and dynamic management of circuit faults of a highly integrated SiP frequency synthesizer according to claim 1, wherein: The operating parameters include power distribution strategy and signal transmission path and timing.

5. A highly integrated SiP frequency synthesizer, characterized in that: It includes several sensors, main function modules, reconfigurable wiring resources, backup function modules, data acquisition modules, and data processing modules; Among them, several sensors are used to detect the sensing data of key nodes of chip interconnection between SiP frequency synthesizers, weak points of power distribution networks, signal transmission lines susceptible to interference, and heat-sensitive areas in highly integrated SiP frequency synthesizers; The data acquisition module is used to collect sensor data from each sensor; The data processing module is used to check whether the SiP frequency synthesizer has a fault based on sensor data and a fault diagnosis model that integrates the SiP thermal characteristics. When a fault is detected, the reconfigurable wiring resources within the SiP frequency synthesizer are used to migrate tasks in the main functional module to the backup functional module, and with the help of system-level collaborative control capabilities, the operating parameters of the frequency synthesizer are adjusted through intelligent algorithms.

6. The highly integrated SiP frequency synthesizer according to claim 5, wherein: The sensors include a voltage sensor, a current sensor, a temperature sensor and a stress sensor.

7. The highly integrated SiP frequency synthesizer according to claim 5, wherein: The data acquisition module includes a high-speed analog-to-digital converter with a sampling rate of GHz level.

8. The highly integrated SiP frequency synthesizer according to claim 5, wherein: The data acquisition module and the data processing module perform signal transmission via a high-speed silicon through-hole interconnection structure of the SiP frequency synthesizer.

9. The highly integrated SiP frequency synthesizer according to claim 5, wherein: The reconfigurable wiring resource adopts a flexible wiring structure based on programmable logic devices.

10. The highly integrated SiP frequency synthesizer according to any one of claims 5 to 9, characterized in that: The highly integrated SiP frequency synthesizer also includes a fault information recording and analysis module for recording the occurrence time, fault type, processing process and processing result information of each fault in real time, and optimizing the fault diagnosis model and intelligent algorithm by analyzing historical fault data.

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