WO2022257571A1 - 一种飞机线缆微弱故障诊断方法 - Google Patents
一种飞机线缆微弱故障诊断方法 Download PDFInfo
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- 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
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/083—Locating faults in cables, transmission lines, or networks according to type of conductors in cables, e.g. underground
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- 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
- G01R31/005—Testing of electric installations on transport means
- G01R31/008—Testing of electric installations on transport means on air- or spacecraft, railway rolling stock or sea-going vessels
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- 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
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/52—Testing for short-circuits, leakage current or ground faults
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- 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
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/54—Testing for continuity
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- G—PHYSICS
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- 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
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/58—Testing of lines, cables or conductors
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- Y04S10/52—Outage or fault management, e.g. fault detection or location
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- the invention belongs to the field of fault diagnosis of aircraft cables, in particular to a method for diagnosing weak faults of aircraft cables.
- Aircraft cables are an important part of the aircraft, and are usually distributed in multiple locations such as the cockpit, engine compartment, wing, and cabin inner wall interlayer. They can transmit electrical energy to various systems of the aircraft and realize information transmission between different systems. More electric aircraft and all-electric aircraft are the main trend of current aircraft development. Electric energy will replace air source and hydraulic pressure as the power source of aircraft starting, braking, deicing, landing gear and other systems. Therefore, the number and types of aircraft cables will become more and more more and more. In the process of aircraft assembly manufacturing and operation and maintenance, the problem of cable-related failures has become increasingly prominent. Once a cable fails, it will pose a serious threat to the safety of the aircraft.
- the purpose of the present invention is to provide a weak fault diagnosis method for aircraft cables that can accurately diagnose aircraft cables during aircraft cable fault diagnosis, which is a weak fault diagnosis method for aircraft cables based on enhanced spread spectrum time domain reflection , which solves the problem that the traditional spread spectrum time domain reflection method cannot diagnose weak faults of aircraft cables, and has great engineering application value for weak fault diagnosis of cables.
- the technical solution adopted in the present invention is: a method for diagnosing weak faults of aircraft cables, which is carried out on a detection platform based on PXI bus technology, and the detection platform includes two components: a hardware system and a software system Partly, the hardware system adopts an industrial control panel, a signal transmitting board, and a signal collecting board with an operating system; the software system adopts a graphical programming language LabVIEW software to realize, and the method includes the following steps:
- Step 1 Write the modulation signal generation program and the driver program of the signal transmission and acquisition board in LabVIEW.
- BPSK Binary Phase Shift keying
- Step 2 Use the signal acquisition board to collect the reflected signal y(t), and delay the incident signal x(t) by ⁇ as the reference signal x(t- ⁇ ) to perform cross-correlation with the reflected signal to obtain the correlation coefficient Rxy( ⁇ );
- IMFs Instrinsic Mode Function
- the kurtosis analysis is performed on the intrinsic mode components IMFs obtained by decomposition.
- the kurtosis value of IMF1 is the largest:
- Ku is the kurtosis
- x is the amplitude of the eigenmode component
- ⁇ and ⁇ are the statistical mean and variance of the eigenmode component, respectively.
- Step 4 select the intrinsic mode component IMF1 with the largest kurtosis value in step 3, and process it with short-time Fourier transform to obtain the time-frequency-energy distribution of the intrinsic mode component IMF1 including fault characteristics;
- Step 5 Redistribute the time-frequency-energy distribution obtained in step 4 to the center of gravity of the original time-frequency-energy distribution by using the spectrogram rearrangement method, extract time-energy information and draw a curve for the rearranged result,
- the curve contains fault information
- Step 6 Determination of the fault location of the aircraft cable: According to the curve in step 5, the vertical axis represents the energy amplitude, and the horizontal axis represents the time. According to the corresponding time difference between the energy peak and the first peak, combined with the wave velocity, the calculation can be obtained Information on the location of aircraft cable faults.
- the improved variational mode decomposition described in step 3 is to use the center frequency comparative analysis method to determine the number of variational mode decompositions to obtain the best eigenmode components.
- Step 4 applies the short-time Fourier transform to process the intrinsic mode component IMF1 containing fault information to obtain the time-frequency-energy distribution of IMF1.
- the spectrogram rearrangement method described in step 5 is to redistribute the time-frequency-energy distribution in step 4 to the center of gravity of the original time-frequency-energy distribution.
- the extraction of time-energy information in step 5 is to determine the frequency corresponding to the maximum energy value of the transmitted signal according to the principle of maximum energy, and then extract the energy and time information at this frequency to draw a curve.
- the first peak mentioned in step 6 is the energy peak formed by the incident signal. If the time difference between a certain peak and the first peak is t, then the location of the fault point corresponding to this energy peak can be determined by the following formula:
- d is the distance between the fault point and the cable injection end
- v is the wave velocity of the electromagnetic wave in the cable
- ⁇ r is the relative permittivity of the cable insulation medium.
- Fig. 1 is a schematic diagram of the aircraft cable weak fault diagnosis method of the present invention
- Fig. 2 is a flowchart of fault signal processing of the present invention
- Fig. 3 is a flow chart of center frequency comparative analysis method described in the present invention.
- Fig. 4 is a structural diagram of the aircraft cable weak fault diagnosis platform of the present invention.
- Fig. 5 is the result after the improved variational mode decomposition described in the present invention.
- Fig. 6 is the time-frequency-energy distribution after the short-time Fourier transform of the present invention transforms the eigenmode component IMF1 in Fig. 5;
- Fig. 7 is the result that Fig. 6 result is processed by spectrogram rearrangement method described in the present invention.
- Fig. 8 is a fault information curve drawn after extracting time energy in the present invention.
- a method for diagnosing weak faults of aircraft cables of the present invention comprises: collecting reflection signals of aircraft cables by means of detection equipment built based on virtual instrument technology; processing the collected reflection signals by using improved variational mode decomposition; The decomposed eigenmode components containing fault information are subjected to short-time Fourier transform; the time-frequency energy of the eigenmode components undergoing short-time Fourier transform is redistributed by using the rearrangement spectrogram method, and its Distributed to the center of gravity; then extract the time energy information to draw the fault information curve of the aircraft cable, and diagnose whether there is a weak fault in the aircraft cable from the perspective of energy.
- a kind of aircraft cable weak fault diagnosis method of the present invention includes: 1, detection signal modulation and transmission module 2, cable fault simulation and reflection signal acquisition module 3, signal separation module 4, fault signal processing module, inject the modulated detection signal into the cable end to be tested after being processed by the signal separation module, and send the collected reflected signal to the fault signal processing module together with the incident signal after being processed by the signal separation module, and obtain the accident details.
- the flow chart of the processing of the fault signal and the fault information extraction of the present invention is the original signal is the correlation result of the traditional spread spectrum time domain reflection method, and 5 can be obtained after the improved variational mode decomposition process Intrinsic mode components IMF1-IMF5, because there are three peaks in IMF1, so IMF1 is selected for short-time Fourier transform to obtain the time-frequency energy distribution as shown in Figure 6.
- the spectrum rearrangement was used to obtain Figure 7, and then the frequency of the maximum energy point was selected, and the energy-time information at this frequency was extracted and the image was drawn as shown in Figure 8. According to the wave velocity and the distance between each peak Fault information can be obtained by time difference.
- VMD parameters such as modal component preset values, bandwidth constraints/penalty factors, noise tolerance, convergence criteria, etc.
- step (2) If there is no cross term at the center frequency, add 1 to the K value and return to step (2); when there is a cross term at the center frequency, the decomposition should stop, and K-1 at this time is the modal component obtained from the VMD decomposition signal optimal value of the number.
- the modulated detection signal is sent by the arbitrary waveform generator, that is, the signal transmitting board, and injected into the cable to be tested through the T-shaped connector and the circulator , the T-shaped connector and the third port of the circulator are respectively connected to the two channels of the oscilloscope, that is, the signal acquisition board, so that the signal acquisition board can synchronously collect the transmitted signal and the reflected signal on the cable. Since the reflected signal superimposes the transmitted signal, it is necessary to use a unidirectional, non-reversible waveguide device circulator to separate the faulty reflected signal that does not contain the transmitted signal.
- ti is the moment when the cross-correlation starts to be calculated
- T is the period of the PN code or a chip time in the PN code.
- x(t) is the signal to be transformed
- h( ⁇ -t) is the window function
- the second peak indicates the weak position of the cable
- the first The three peaks indicate the position of the cable end
- the time difference between any two peaks indicates the propagation time t of the signal to and from the two positions. If the combined signal propagation speed is v, it can be Determine the relative distance.
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Locating Faults (AREA)
Abstract
一种飞机线缆微弱故障诊断方法，包括步骤：基于虚拟仪器技术搭建的检测设备对飞机线缆反射信号进行采集；利用改进的变分模态分解对采集到的反射信号进行处理；对分解后的含有故障信息的本征模态分量进行短时傅里叶变换；利用重排谱图法对经短时傅里叶变换的本征模态分量的时频能量进行重新分布，将其分布至重心位置；然后提取时间能量信息以绘制飞机线缆的故障信息曲线，从能量角度诊断飞机线缆是否存在微弱故障。本方法克服传统扩展频谱时域反射法无法有效检测微弱故障的问题，实现飞机线缆微弱故障的诊断，提高飞机线缆微弱故障的预警能力和检出率，为飞机线缆维护提供支持。
Description
本发明属于飞机线缆故障诊断领域，具体为一种飞机线缆微弱故障诊断方法。
飞机线缆是飞机的重要组成部分，通常分布于飞机的驾驶舱、发动机舱、机翼以及客舱内壁夹层等多个位置，它能为飞机各个系统传送电能并且实现不同系统之间信息传递。多电飞机和全电飞机是当前飞机发展的主要趋势，电能将取代气源、液压作为飞机启动、刹车、除冰、起落架等系统的动力来源，因此飞机线缆的数量和种类将会越来越多。在飞机总装制造和运营维护过程中，线缆相关的故障问题日益突出，一旦线缆发生故障，将对飞机的安全造成严重威胁。
对于飞机线缆故障，不仅要能诊断出线缆的短路、断路这类显性故障，更应该能检测出因局部破损或形态、结构变化导致的微弱故障。因为对于即将起飞或飞行中的飞机来说，线缆发生故障将可能导致电磁干扰、通信中断、电弧放电等严重问题。比如屏蔽层破损将导致线缆中信号受到电磁干扰；电源馈线磨损会导致局部阻抗增大造成局部过热引发电气线路故障；线缆发生断丝后由于频繁的振动、摩擦容易导致断丝戳穿绝缘层从而与机体或屏蔽层发生短路，如果靠近燃油管线则可能因产生的电弧而引发火灾。
无论是飞机生产过程还是维修过程，对于飞机线缆故障，机务 人员依靠现有设备和方法只能检测出短路、断路故障，无法检测出微弱故障。为了保证飞机在生产、使用以及维修过程中的安全，需要一种针对飞机线缆微弱故障的检测方法准确地诊断出飞机线缆的微弱故障。
发明内容
针对上述技术中的不足，本发明的目的是提供一种能够在飞机线缆故障诊断时准确诊断飞机线缆的微弱故障诊断方法，是基于增强扩展频谱时域反射的飞机线缆微弱故障诊断方法，解决了传统扩展频谱时域反射法无法诊断飞机线缆微弱故障的问题，对于线缆微弱故障诊断具有很大的工程应用价值。
为了解决上述技术问题，本发明采用的技术方案是：一种飞机线缆微弱故障诊断方法，该方法是在基于PXI总线技术的检测平台上进行的，该检测平台包含硬件系统和软件系统两个部分，硬件系统采用带有操作系统的工业控制平板、信号发射板卡、信号采集板卡；软件系统采用图形化编程语言LabVIEW软件实现，该方法包括以下步骤：
步骤1、在LabVIEW中编写调制信号生成程序以及信号发射、采集板卡的驱动程序，首先采用二进制相移键控(Binary Phase Shift keying，BPSK)调制方式将m序列调制到正弦载波上作为检测信号x(t)，然后通过信号发射板卡将该检测信号注入待测飞机线缆，由于线缆某个位置发生故障时阻抗产生不连续，检测信号将在该位置发生反射；
步骤2、利用信号采集板卡采集反射回来的信号y(t)，并将入射信号x(t)延迟τ后作为参考信号x(t-τ)与反射信号进行互相关运 算，从而获得相关系数Rxy(τ)；
步骤3、利用改进的变分模态分解对互相关系数R
xy(τ)进行分解获得一系列本征模态分量IMFs(Instrinsic Mode Function,IMF)，其中：s＝1、2、3…K，K为变分模态分解的本征模态分量个数K；
对分解获得的本征模态分量IMFs进行峭度分析，峭度的值越大表示突变程度越高，更有利于提取故障特征，经过多次实验计算IMF1的峭度值最大：
式中：Ku为峭度；x为本征模态分量的幅值；μ、σ分别为本征模态分量的统计均值和方差。
步骤4、选取步骤3中峭度值最大的本征模态分量IMF1，用短时傅里叶变换进行处理，获得包含故障特征的本征模态分量IMF1的时间-频率-能量分布；
步骤5、利用谱图重排法将步骤4中得到的时间-频率-能量分布重新分布到原时间-频率-能量分布的重心位置，对重排后的结果提取时间-能量信息并绘制曲线，该曲线包含故障信息；
步骤6、飞机线缆故障位置的确定：根据步骤5的曲线，纵轴表示能量幅值，横轴表示时间，根据能量波峰与第一个波峰之间对应的时间差，结合波速进行计算即可得到飞机线缆故障的位置信息。
步骤3所述改进的变分模态分解为采用中心频率对比分析法确定变分模态分解的个数获得最佳的本征模态分量。
步骤4应用短时傅里叶变换对包含故障信息的本征模态分量IMF1进行处理得到IMF1的时间-频率-能量分布。
步骤5所述谱图重排法是将步骤4的时间-频率-能量分布重新分布到原时间-频率-能量分布的重心位置。
步骤5所述提取时间-能量信息是依据能量最大原则确定发射信号能量最大值所对应的频率，然后提取该频率下的能量与时间信息绘制曲线。
步骤6中所述第一个波峰为入射信号所形成的能量波峰，若某一波峰与第一个波峰对应的时间差为t，那么此能量峰值对应的故障点位置可通过以下公式来确定：
式中d为故障点与线缆注入端的距离，v为电磁波在线缆中的波速，ε
r是线缆绝缘介质的相对介电常数。本发明的效果是：不仅能够实现飞机线缆短路、断路这类显著性故障进行诊断还能对因局部破损或形态、结构变化导致的微弱故障进行检测，大大提高了飞机线缆发生故障的预警能力。
图1是本发明飞机线缆微弱故障诊断方法示意图；
图2是本发明故障信号处理流程图；
图3是本发明中所述中心频率对比分析法流程图；
图4是本发明飞机线缆微弱故障诊断平台结构图；
图5是本发明中所述改进变分模态分解后的结果；
图6是本发明中所述短时傅里叶变换对图5中本征模态分量IMF1变换后的时间-频率-能量分布；
图7是本发明中所述谱图重排法对图6结果进行处理的结果；
图8是本发明中所述提取时间能量后绘制的故障信息曲线。
图中：
1、检测信号调制模块 2、信号分离模块
3、线缆及线缆故障模拟模块 4、故障信号处理模块
下面结合附图和实施例对本发明一种飞机线缆微弱故障诊断方法进行详细的描述。
本发明的一种飞机线缆微弱故障诊断方法，包括：基于虚拟仪器技术搭建的检测设备对飞机线缆反射信号进行采集；利用改进的变分模态分解对采集到的反射信号进行处理；对分解后的含有故障信息的本征模态分量进行短时傅里叶变换；利用重排谱图法对经短时傅里叶变换的本征模态分量的时频能量进行重新分布，将其分布至重心位置；然后提取时间能量信息以绘制飞机线缆的故障信息曲线，从能量角度诊断飞机线缆是否存在微弱故障。
如图1所示，本发明的一种飞机线缆微弱故障诊断方法，包括：1、检测信号调制与发射模块2、线缆故障模拟及反射信号采集模块3、信号分离模块4、故障信号处理模块，将调制好的检测信号经信号分离模块处理后注入到待测线缆端，将采集到的反射信号经信号分离模块处理后与入射信号共同发送给故障信号处理模块，经处理后获取到故障信息。完成检测信号的生成与发射、反射信号的采集、故障信号处理、故障信息提取。
如图2所示，本发明的故障信号的处理以及故障信息提取的流程图：原始信号即为传统扩展频谱时域反射法的相关结果，经过改进的变分模态分解处理后可得5个本征模态分量IMF1～IMF5,由于 IMF1共存在3个波峰，故选取IMF1进行短时傅里叶变换得到如图6所示的时频能量分布。为提高图6分辨率利用谱图重排进行处理得到图7，随后选取能量最大点所处频率，提取该频率下的能量-时间信息并且绘制图像如图8，根据波速和各个波峰之间的时间差可得故障信息。
如图3所示改进变分模态分解的方法：(1)确定VMD参数如模态分量预设值，带宽约束/惩罚因子，噪声容限，收敛准则等；
(2)通过VMD分解信号以获得模态分量；
(3)使用快速傅里叶变换FFT计算各个模态分量的中心频率；
(4)计算各个模态分量中心频率的平均值；
(5)根据中心频率确定是否存在交叉项；
(6)若不存在中心频率交叉项，则K值加1并返回到步骤(2)；当中心频率存在交叉项时，分解应当停止，此时的K-1就是VMD分解信号所得模态分量数的最佳值。
确定分解个数从而防止因过分解导致各个模态分量的中心频率重叠或欠分解导致故障信号细节信息丢失。
如图4所示，基于本发明设计的飞机线缆微弱故障检测平台，经过调制的检测信号由任意波形发生器即信号发射板卡发出，并通过T型连接器和环形器注入待测线缆，T型连接器和环形器的第三端口分别接到示波器即信号采集板卡的两个通道，这样信号采集板卡可以同步采集发射信号和线缆上的反射信号。由于反射信号叠加了发射信号，因此需要利用单向、非可逆的波导器件环形器分离出不含发射信号的故障反射信号。
以下为本发明诊断飞机线缆微弱故障的实施过程：
将检测信号注入待测线缆，利用信号采集板卡同步采集发射信 号和反射信号，并计算反射信号与参考信号的相关系数，互相关函数计算公式如下所示：
其中，ti为开始计算互相关的时刻，T为PN码的周期或PN码中的一个码片时间。相关后的结果如图5中“原始信号”所示。
对R
xy(τ)进行改进变分模态分解，分解后的各个本征模态分量如图5中IMF1至IMF5所示，接着对IMF1进行短时傅里叶变换，并计算其能量，变换后的时间频率能量分布如图6所示；其计算如下所示：
其中，x(t)为要变换的信号，h(τ-t)为窗函数。
然后将谱图重排法应用于图6得到的时间频率能量分布可以得到能量重新排布的本征模态分量IMF1，如图7所示；将时频谱中点处(t,f)的能量值分布到点
处：
最后提取能量和时间信息绘制故障信息曲线，如图8所示。图8中，从左往右第一个峰值(t＝1.19×10
-6s)表示检测信号的发射位置，第二个峰值(t＝1.221×10
-6s)表示线缆微弱位置，第三个峰值(t＝1.325×10
-6s)表示线缆末端位置，任意两个峰值之间的时间之差表示信号往返这两个位置的传播时间t，如结合信号传播速度为v则可以确定相对距离。
与图5中所示的“原始信号”相比，可以明显发现除了信号发射位置的波峰与线缆末端的波峰，中间还存在一个波峰，这是图5中“原始信号”中所没有体现的线缆微弱故障位置。
Claims (6)
- 一种飞机线缆微弱故障诊断方法，该方法基于PXI总线技术检测平台，包括硬件系统和软件系统，所述硬件系统包括带有操作系统的工业控制平板、信号发射板卡、信号采集板卡；所述软件系统为图形化编程语言LabVIEW软件，具体步骤如下：步骤1、在LabVIEW中编写调制信号生成程序以及信号发射、采集板卡的驱动程序，首先采用二进制相移键控调制方式将m序列调制到正弦载波上作为检测信号x(t)，然后通过信号发射板卡将该检测信号注入待测飞机线缆，当线缆某个位置发生故障时阻抗产生不连续，检测信号将在该位置发生反射；步骤2、利用信号采集板卡采集反射回来的信号y(t)，并将入射信号x(t)延迟τ后作为参考信号x(t-τ)与反射信号进行互相关运算获得互相关系数R xy(τ)；步骤3、利用改进的变分模态分解对互相关系数R xy(τ)进行分解获得一系列本征模态分量IMFs(Instrinsic Mode Function,IMF)，其中：s＝1、2、3…K，K为变分模态分解的本征模态分量个数K；当s＝1时，IMF1的峭度值最大，峭度计算公式为：
式中：Ku为峭度；x为本征模态分量的幅值；μ、σ分别为本征模态分量的统计均值和方差。步骤4、选取步骤3中峭度值最大的本征模态分量IMF1，用短时傅里叶变换进行处理，获得包含故障特征的本征模态分量IMF1的时间-频率-能量分布；步骤5、利用谱图重排法将步骤4中得到的时间-频率-能量分布重新分布到原时间-频率-能量分布的重心位置，对重排后的结 果提取时间-能量信息并绘制曲线，该曲线包含故障信息；步骤6、飞机线缆故障位置的确定：根据步骤5的曲线，纵轴表示能量幅值，横轴表示时间，根据能量波峰与第一个波峰之间对应的时间差，结合波速进行计算即可得到飞机线缆故障的位置信息。 - 根据权利要求1所述的飞机线缆微弱故障诊断方法，其特征是：步骤3所述改进的变分模态分解为采用中心频率对比分析法确定变分模态分解的个数获得最佳的本征模态分量。
- 根据权利要求1所述的飞机线缆微弱故障诊断方法，其特征是：步骤4应用短时傅里叶变换对包含故障信息的本征模态分量IMF1进行处理得到IMF1的时间-频率-能量分布。
- 根据权利要求1所述的飞机线缆微弱故障诊断方法，其特征是：步骤5所述谱图重排法是将步骤4的时间-频率-能量分布重新分布到原时间-频率-能量分布的重心位置。
- 根据权利要求1所述的飞机线缆微弱故障诊断方法，其特征是：步骤5所述提取时间-能量信息是依据能量最大原则确定发射信号能量最大值所对应的频率，然后提取该频率下的能量与时间信息绘制曲线。
- 根据权利要求1所述的飞机线缆微弱故障诊断方法，其特征是：步骤6中所述第一个波峰为入射信号所形成的能量波峰，若某一波峰与第一个波峰对应的时间差为t，那么此能量峰值对应的故障点位置可通过以下公式来确定：
式中d为故障点与线缆注入端的距离，v为电磁波在线缆中的波速，ε r是线缆绝缘介质的相对介电常数。
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