WO2018006539A1 - SoC健康监测的方法、装置及系统 - Google Patents

SoC健康监测的方法、装置及系统 Download PDF

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WO2018006539A1
WO2018006539A1 PCT/CN2016/107703 CN2016107703W WO2018006539A1 WO 2018006539 A1 WO2018006539 A1 WO 2018006539A1 CN 2016107703 W CN2016107703 W CN 2016107703W WO 2018006539 A1 WO2018006539 A1 WO 2018006539A1
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sensor data
soc
performance
degradation
data
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English (en)
French (fr)
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陈义强
雷登云
恩云飞
方文啸
侯波
刘远
黄云
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工业和信息化部电子第五研究所
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Priority to US15/554,581 priority Critical patent/US11231702B2/en
Publication of WO2018006539A1 publication Critical patent/WO2018006539A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0208—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
    • G05B23/0213—Modular or universal configuration of the monitoring system, e.g. monitoring system having modules that may be combined to build monitoring program; monitoring system that can be applied to legacy systems; adaptable monitoring system; using different communication protocols
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2855—Environmental, reliability or burn-in testing
    • G01R31/2856—Internal circuit aspects, e.g. built-in test features; Test chips; Measuring material aspects, e.g. electro migration [EM]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2855—Environmental, reliability or burn-in testing
    • G01R31/2872—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2894—Aspects of quality control [QC]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/24—Pc safety
    • G05B2219/24065—Real time diagnostics

Definitions

  • the present invention relates to the field of system-on-a-chip technology, and more particularly to a method, apparatus and system for SoC health monitoring.
  • SoC system-on-chip
  • embodiments of the present invention provide a method, device, and system for SoC health monitoring, which can monitor the performance status of the SoC in real time and predict the performance degradation trend of the SoC in real time.
  • One aspect of the present invention provides a method for SoC health monitoring, including:
  • Sensor data monitoring SoC performance is acquired in real time, the sensor data including reliability degradation sensor data, temperature sensor data, noise sensor data, and current sensor data;
  • Another aspect of the present invention provides an apparatus for monitoring health of a SoC, comprising:
  • a data acquisition module configured to acquire sensor data for monitoring SoC performance in real time, the sensor data including reliability degradation sensor data, temperature sensor data, noise sensor data, and current sensor data;
  • An analysis and prediction module configured to extract feature data included in the sensor data representative of the SoC performance; and Performing real-time analysis and prediction on the feature data by using a prediction algorithm to obtain a performance state and a performance degradation trend of the SoC;
  • An information output module configured to output performance state information of the SoC and performance degradation trend information.
  • SoC system including: a system hardware layer, a system kernel layer, a system service layer, and an application layer;
  • the sensor of the hardware layer of the system monitors the SoC performance in real time
  • the operating system kernel of the system kernel layer acquires sensor data of the hardware layer of the system in real time, and transmits the sensor data to the system service layer;
  • the sensor data includes reliability degradation sensor data, temperature sensor data, and noise sensor. Data and current sensor data;
  • the prediction module of the system service layer extracts feature data that is included in the sensor data and represents the performance of the SoC; and performs real-time analysis and prediction on the feature data by using a prediction algorithm to obtain performance status and performance degradation of the SoC. trend;
  • the APP preset by the application layer outputs performance status information of the SoC system and the performance degradation trend information.
  • the above technical solution acquires sensor data for monitoring SoC performance in real time, the sensor data includes reliability degradation sensor data, temperature sensor data, noise sensor data, and current sensor data; and extracting performance of the SoC included in the sensor data Feature data; real-time analysis and prediction of the feature data by using a prediction algorithm to obtain a performance state and a performance degradation trend of the SoC, and output performance state information of the SoC system and the performance degradation trend information.
  • the solution of the foregoing embodiment of the present invention can provide real-time health monitoring and real-time prediction information of the SoC for the user.
  • FIG. 1 is a schematic flowchart of a method for monitoring health of a SoC according to an embodiment
  • FIG. 2 is a specific application scenario diagram of a method for monitoring health of a SoC
  • FIG. 3 is a schematic structural diagram of an apparatus for SoC health monitoring according to an embodiment.
  • FIG. 1 is a schematic flowchart of a method for monitoring health of a SoC according to an embodiment; as shown in FIG. 1, the method for monitoring health of a SoC in this embodiment includes the following steps:
  • S11 real-time acquiring sensor data for monitoring SoC performance, the sensor data including reliability degradation sensor data, temperature sensor data, noise sensor data, and current sensor data;
  • the reliability degradation sensor data includes TDDB (time dependent dielectric breakdown) degradation sensor data, HCI (hot carrier injection) degradation sensor data, BTI (bias temperature instability) Set temperature instability) Degraded sensor data.
  • TDDB time dependent dielectric breakdown
  • HCI hot carrier injection
  • BTI bias temperature instability
  • sensors for monitoring the performance of the SoC in the present invention may include many kinds, and only some of them are listed above, and any other sensor that can be implemented on the SoC chip belongs to the protection scope of the present invention.
  • the feature data representing the SoC performance included in the sensor data may be extracted by using a Gabor transform algorithm or a fast Fourier transform algorithm.
  • the Gabor transform belongs to the windowed Fourier transform, and the Gabor function can extract related features in different scales and directions in the frequency domain.
  • the Gabor function is similar to the biological function of the human eye, so it is often used as a texture recognition and has achieved good results.
  • FFT Fast Fourier transform
  • the FFT algorithm which is used to make the number of multiplications required for computer calculation of discrete Fourier transform greatly reduced, especially the number of sample points N that are transformed, the FFT algorithm The savings in calculations are more significant.
  • the method for extracting the feature data representing the SoC performance included in the sensor data is not limited to the specific two, and other methods for extracting the feature data are also applicable.
  • the algorithm for predicting the performance degradation trend in the embodiment of the present invention may include a plurality of prediction algorithms, which are not specifically limited in the present invention.
  • the obtained performance status information and the performance degradation trend information are sent to the application layer to output the performance status and the performance degradation trend through the corresponding APP of the application layer.
  • the health monitoring and early warning APP is preset, and the performance status and the performance degradation trend are output through the display interface of the APP, so that the user can view the SoC health status and the reliability degradation trend in real time.
  • the corresponding warning prompt may be output, for example, the preset warning prompt information is output through the health monitoring and early warning APP, so that the user is timely Overhaul to prevent more serious problems.
  • FIG. 2 is a specific application scenario diagram of a method for monitoring health of a SoC according to an embodiment of the present invention
  • the SoC100 system is composed of a system hardware layer 200, a system kernel layer 300, a system service layer 400, and an application layer 500.
  • the system hardware layer 200 includes a function circuit 210 and a sensor 220.
  • the sensor 220 mainly includes a reliability degradation sensor 227, a temperature sensor 226, a noise sensor 225, and a current sensor 224.
  • the reliability degradation sensor 227 mainly includes a TDDB degradation sensor 223.
  • the system kernel layer 300 includes an operating system kernel 310 and a sensor driver 320.
  • the system service layer 400 includes an application interface 410 and a prediction model 420.
  • the application layer 500 includes a plurality of APPs, such as APP1 510, APP2 520, and health monitoring and alerting APP 530.
  • the method for monitoring the SoC health needs to perform sensor hardware design, sensor driver design, predictive model construction, health monitoring and early warning APP design in advance.
  • the sensor hardware design mainly includes a reliability degradation sensor 227, a temperature sensor 226, a noise sensor 225, and a current sensor 224.
  • the reliability degradation sensor 227 mainly includes a TDDB degradation sensor 223, an HCI degradation sensor 222, and a BTI degradation sensor 221.
  • the sensor and function circuit 210 together form the system hardware layer 200 of the SoC;
  • the sensor driver design is mainly combined with the operating system kernel 310 to design a driver for the sensor.
  • the predictive model is constructed, and the sensor data is acquired according to the interface provided by the operating system kernel 310, and the feature data is extracted for the sensor data, and the algorithm is used to perform real-time analysis and prediction on the feature data.
  • the predictive model together with the application interface 410, constitutes the system service layer 400 of the SoC.
  • the health monitoring and early warning APP design is mainly based on the prediction model 420 and the application interface 410 provided by the system service layer 400, and provides the user with real-time health monitoring and real-time prediction information of the SoC.
  • the working principle is as follows: the sensor hardware designed in the system hardware layer 200 of the SoC 100 monitors the SoC performance in real time, and the sensor driver 320 of the system kernel layer 300 reads the system in real time.
  • the feature extraction is performed in the model 420, and the feature data is predicted in real time by using the prediction algorithm, and the obtained prediction result is displayed in the health monitoring and early warning APP 530 in the application layer 500 of the SoC 100, thereby providing the user with real-time health monitoring and real-time of the SoC. Forecast information.
  • the present invention also provides a system for SoC health monitoring, which can be used to perform the above method of SoC health monitoring.
  • a system for SoC health monitoring which can be used to perform the above method of SoC health monitoring.
  • the illustrated structure does not constitute a limitation on the system, and may include More or fewer components are illustrated, or some components are combined, or different component arrangements.
  • FIG. 3 is a schematic structural diagram of an apparatus for monitoring health of a SoC according to an embodiment of the present invention.
  • the apparatus for monitoring the SoC of the present embodiment includes: a data acquisition module 10, an analysis and prediction module 20, and an information output module 30. Description as follows:
  • the data acquisition module 10 is configured to acquire sensor data for monitoring SoC performance in real time, and the sensor data includes reliability degradation sensor data, temperature sensor data, noise sensor data, and current sensor data;
  • the reliability degradation sensor data includes TDDB degradation sensor data, HCI degradation sensor data, BTI degradation sensor data.
  • the analysis and prediction module 20 is configured to extract feature data representative of the SoC performance included in the sensor data, and perform real-time analysis and prediction on the feature data by using a prediction algorithm to obtain performance status of the SoC and Performance degradation trend;
  • the information output module 30 is configured to output performance state information and performance degradation trend information of the SoC.
  • each functional module is only an example, and the actual application may be according to requirements, for example, due to the configuration requirements of the corresponding hardware or the convenience of implementation of the software.
  • the above-mentioned function allocation is completed by different functional modules, that is, the internal structure of the device for monitoring the SoC health is divided into different functional modules to complete all or part of the functions described above.
  • Each function module can be implemented in the form of hardware or in the form of a software function module.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

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Abstract

一种SoC健康监测的方法、装置及系统。该方法包括：实时获取监测SoC性能的传感器数据，该传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据（S11）；提取该传感器数据中包含的代表该SoC性能的特征数据；并利用预测算法对该特征数据进行实时分析和预测，得到该SoC的性能状态以及性能退化趋势（S12）；输出该SoC的性能状态信息以及性能退化趋势信息（S13）。该方法能够实时监测SoC的性能状态，以及实时预测SoC的性能退化趋势。

Description

SoC健康监测的方法、装置及系统 技术领域
本发明涉及片上系统技术领域，特别是涉及SoC健康监测的方法、装置及系统。
背景技术
片上系统(System on Chip，SoC)芯片设计要求已从单纯追求高性能、小面积转为对性能、面积、功耗及可靠性的综合要求。尤其SoC芯片在航空航天、轨道交通、核电等高可靠领域应用非常广泛，其可靠性至关重要，备受关注。传统的可靠性模拟、工艺在线检测、可靠性试验与失效分析等离线可靠性评价方法，无法实时对SoC寿命进行预测。这种情况下，若按照传统“定时维修”的维修方式或“事后维修”的方式，将造成人力、物力、财力的巨大损失。
发明内容
基于此，本发明实施例提供SoC健康监测的方法、装置及系统，能够实时监测SoC的性能状态，以及实时预测SoC的性能退化趋势。
本发明一方面提供SoC健康监测的方法，包括：
实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
提取所述传感器数据中包含的代表所述SoC性能的特征数据；并利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
输出所述SoC的性能状态信息以及性能退化趋势信息。
本发明另一方面提供了一种SoC健康监测的装置，包括：
数据获取模块，用于实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
分析及预测模块，用于提取所述传感器数据中包含的代表所述SoC性能的特征数据；并 利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
信息输出模块，用于输出所述SoC的性能状态信息以及性能退化趋势信息。
本发明另一方面提供了一种SoC系统，包括：包括系统硬件层、系统内核层、系统服务层以及应用层；
所述系统硬件层的传感器实时监测SoC性能；
所述系统内核层的操作系统内核实时获取所述系统硬件层的传感器数据，并传递所述传感器数据给所述系统服务层；所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
所述系统服务层的预测模块提取所述传感器数据中包含的代表所述SoC性能的特征数据；并利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
所述应用层预设的APP输出所述SoC系统的性能状态信息以及所述性能退化趋势信息。
上述技术方案，通过实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；提取所述传感器数据中包含的代表所述SoC性能的特征数据；利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势，并输出所述SoC系统的性能状态信息以及所述性能退化趋势信息。本发明上述实施例的方案，能够为用户提供SoC的实时健康监测及实时预测信息。
附图说明
图1为一实施例的SoC健康监测的方法的示意性流程图；
图2为一SoC健康监测的方法的具体应用场景图；
图3为一实施例的SoC健康监测的装置的示意性结构图。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
图1为一实施例的SoC健康监测的方法的示意性流程图；如图1所示，本实施例中的SoC健康监测的方法包括步骤：
S11，实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；，
优选的，所述可靠性退化传感器数据包括TDDB(time dependent dielectric breakdown，经时击穿)退化传感器数据、HCI(hot carrier injection，热载流子注入)退化传感器数据、BTI(bias temperature instability，偏置温度不稳定性)退化传感器数据。
需要说明的是，本发明中监测SoC性能的传感器可包括许多种，上述仅列出了其中的一部分，其他任何可在SoC片上实现的传感器均属于本发明的保护范围。
S12，提取所述传感器数据中包含的代表所述SoC性能的特征数据；利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
优选的，可利用Gabor变换算法或快速傅里叶变换算法，提取所述传感器数据中包含的代表所述SoC性能的特征数据。其中，Gabor变换属于加窗傅立叶变换，Gabor函数可以在频域不同尺度、不同方向上提取相关的特征。另外Gabor函数与人眼的生物作用相仿，所以经常用作纹理识别上，并取得了较好的效果。快速傅里叶变换算法(fast Fourier transform)，简称FFT，采用这种算法能使计算机计算离散傅里叶变换所需要的乘法次数大为减少，特别是被变换的抽样点数N越多，FFT算法计算量的节省就越显著。需要说明的是，提取所述传感器数据中包含的代表所述SoC性能的特征数据的方法不限于这里具体的两种，其他可提取特征数据的方法同样适用。
本发明实施例中预测性能退化趋势的算法可包括许多种预测算法，本发明对此不作特别限定。
S13，输出所述性能状态以及所述性能退化趋势。
将得到的性能状态信息以及性能退化趋势信息发送给应用层，以通过应用层的对应APP输出所述性能状态以及所述性能退化趋势。例如预先设置了健康监测及预警APP，通过该APP的显示界面输出所述性能状态以及所述性能退化趋势，便于用户实时查看SoC健康状况和可靠性退化趋势。
需要说明的是，当S12中得到的SoC的性能状态或者性能退化趋势超出各自对应的阈值，还可输出对应的预警提示，例如通过健康监测及预警APP输出预设的预警提示信息，便于用户及时进行检修，防止引发更严重的问题。
图2为本发明一实施例的SoC健康监测的方法的具体应用场景图；如图2所示，该SoC100系统由系统硬件层200、系统内核层300、系统服务层400、应用层500构成。所述系统硬件层200包括功能电路210、传感器220，其中传感器220主要包括可靠性退化传感器227、温度传感器226、噪声传感器225、电流传感器224，其中可靠性退化传感器227主要包括TDDB退化传感器223、HCI退化传感器222、BTI退化传感器221。所述系统内核层300包括操作系统内核310、传感器驱动程序320。所述系统服务层400包括应用接口410、预测模型420。所述应用层500包括若干APP，例如APP1 510、APP2 520、健康监测及预警APP 530。
所述SoC健康监测的方法，需预先进行传感器硬件设计、传感器驱动程序设计、预测模型构建、健康监测及预警APP设计等。
其中，所述传感器硬件设计，主要包括可靠性退化传感器227、温度传感器226、噪声传感器225、电流传感器224。其中可靠性退化传感器227主要包括TDDB退化传感器223、HCI退化传感器222、BTI退化传感器221。传感器与功能电路210一起构成SoC的系统硬件层200；
所述传感器驱动程序设计，主要结合操作系统内核310，针对传感器进行驱动程序设计。
所述预测模型构建，主要根据操作系统内核310提供的接口获取传感器数据，针对传感器数据进行特征提取，据此运用算法对特征数据进行实时分析与预测。所述预测模型与应用接口410一起构成SoC的系统服务层400。
所述健康监测及预警APP设计，主要基于系统服务层400所提供的预测模型420、应用接口410设计，为用户提供SoC的实时健康监测及实时预测信息。
如图2所述的应用场景，其工作原理为：在SoC 100的系统硬件层200中所设计的传感器硬件实时监测SoC性能，所述系统内核层300的传感器驱动程序320实时读取所述系统硬件层200的传感器数据；所述操作系统内核310通过对应的接口实时获取所述传感器驱动程序320读取到的传感器数据，并传递给所述系统服务层400的预测模块420；在所述预测模型420中进行特征提取，并利用预测算法对特征数据进行实时预测，在SoC 100的应用层500中的健康监测及预警APP 530中显示所获得预测结果，为用户提供SoC的实时健康监测及实时预测信息。
需要说明的是，对于前述的各方法实施例，为了简便描述，将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为依据本发明，某些步骤可以采用其它顺序或者同时进行。
基于与上述实施例中的SoC健康监测的方法相同的思想，本发明还提供SoC健康监测的系统，该系统可用于执行上述SoC健康监测的方法。为了便于说明，SoC健康监测的系统实施例的结构示意图中，仅仅示出了与本发明实施例相关的部分，本领域技术人员可以理解，图示结构并不构成对系统的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
图3为本发明一实施例的SoC健康监测的装置的示意性结构图，本实施例的SoC健康监测的装置包括：数据获取模块10、分析及预测模块20以及信息输出模块30，各模块详述 如下：
所述数据获取模块10，用于实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
优选的，所述可靠性退化传感器数据包括TDDB退化传感器数据、HCI退化传感器数据、BTI退化传感器数据。
所述分析及预测模块20，用于提取所述传感器数据中包含的代表所述SoC性能的特征数据；并利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
所述信息输出模块30，用于输出所述SoC的性能状态信息以及性能退化趋势信息。
需要说明的是，上述示例的SoC健康监测的装置的实施方式中，各模块/单元之间的信息交互、执行过程等内容，由于与本发明前述方法实施例基于同一构思，其带来的技术效果与本发明前述方法实施例相同，具体内容可参见本发明方法实施例中的叙述，此处不再赘述。
此外，上述示例的SoC健康监测的装置的实施方式中，各功能模块的逻辑划分仅是举例说明，实际应用中可以根据需要，例如出于相应硬件的配置要求或者软件的实现的便利考虑，将上述功能分配由不同的功能模块完成，即将所述SoC健康监测的装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。其中各功能模既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。
本领域普通技术人员可以理解，实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的程序可存储于一计算机可读取存储介质中，作为独立的产品销售或使用。所述程序在执行时，可执行如上述各方法的实施例的全部或部分步骤。其中，所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)或随机存储记忆体(Random Access Memory，RAM)等。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可 以参见其它实施例的相关描述。可以理解，其中所使用的术语“第一”、“第二”等在本文中用于区分对象，但这些对象不受这些术语限制。
以上所述实施例仅表达了本发明的几种实施方式，不能理解为对本发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。

Claims (10)

  1. 一种SoC健康监测的方法，其特征在于，包括：
    实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
    提取所述传感器数据中包含的代表所述SoC性能的特征数据；并利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
    输出所述SoC的性能状态信息以及性能退化趋势信息。
  2. 根据权利要求1所述的SoC健康监测的方法，其特征在于，所述输出SoC的性能状态信息以及性能退化趋势信息的步骤包括：
    将得到的性能状态信息以及性能退化趋势信息发送给应用层，以通过应用层的对应APP输出所述性能状态以及所述性能退化趋势。
  3. 根据权利要求1所述的SoC健康监测的方法，其特征在于，
    所述可靠性退化传感器数据包括TDDB退化传感器数据、HCI退化传感器数据、BTI退化传感器数据。
  4. 根据权利要求1所述的SoC健康监测的方法，其特征在于，提取所述传感器数据中包含的代表所述SoC性能的特征数据的步骤包括：
    利用Gabor变换算法或快速傅里叶变换算法，提取所述传感器数据中包含的代表所述SoC性能的特征数据。
  5. 根据权利要求1至4任一所述的SoC健康监测的方法，其特征在于，所述实时获取监测SoC的传感器数据的步骤包括：
    通过预设的传感器驱动程序实时读取监测SoC性能的传感器数据；所述传感器驱动程序基于操作系统内核设置的；
    通过所述操作系统内核提供的接口实时获取所述传感器驱动程序读取到的传感器数据。
  6. 一种SoC健康监测的装置，其特征在于，包括：
    数据获取模块，用于实时获取监测SoC性能的传感器数据，所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
    分析及预测模块，用于提取所述传感器数据中包含的代表所述SoC性能的特征数据；并利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
    信息输出模块，用于输出所述SoC的性能状态信息以及性能退化趋势信息。
  7. 根据权利要求6所述的SoC健康监测的装置，其特征在于，所述可靠性退化传感器数据包括TDDB退化传感器数据、HCI退化传感器数据、BTI退化传感器数据。
  8. 一种SoC系统，其特征在于，包括系统硬件层、系统内核层、系统服务层以及应用层；
    所述系统硬件层的传感器实时监测SoC性能；
    所述系统内核层的操作系统内核实时获取所述系统硬件层的传感器数据，并传递所述传感器数据给所述系统服务层；所述传感器数据包括可靠性退化传感器数据、温度传感器数据、噪声传感器数据以及电流传感器数据；
    所述系统服务层的预测模块提取所述传感器数据中包含的代表所述SoC性能的特征数据；并利用预测算法对所述特征数据进行实时分析和预测，得到所述SoC的性能状态以及性能退化趋势；
    所述应用层预设的APP输出所述SoC系统的性能状态信息以及所述性能退化趋势信息。
  9. 根据权利要求8所述的SoC系统，其特征在于，所述可靠性退化传感器数据包括TDDB退化传感器数据、HCI退化传感器数据、BTI退化传感器数据。
  10. 根据权利要求8或9所述的SoC系统，其特征在于，所述系统内核层包括操作系统内核，以及基于操作系统内核设置的传感器驱动程序；
    所述传感器驱动程序实时读取所述系统硬件层的传感器数据；所述操作系统内核通过对应的接口实时获取所述传感器驱动程序读取到的传感器数据并传递给所述系统服务层的预测模块。
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