WO2025007993A1 - 一种传输线网络软故障定位和成像方法、装置及存储介质 - Google Patents

一种传输线网络软故障定位和成像方法、装置及存储介质 Download PDF

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WO2025007993A1
WO2025007993A1 PCT/CN2024/111081 CN2024111081W WO2025007993A1 WO 2025007993 A1 WO2025007993 A1 WO 2025007993A1 CN 2024111081 W CN2024111081 W CN 2024111081W WO 2025007993 A1 WO2025007993 A1 WO 2025007993A1
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transmission line
line network
reference model
voltage
port
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French (fr)
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官权升
陈川旭
金鑫
施展
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South China University of Technology SCUT
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South China University of Technology SCUT
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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
    • 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
    • G01R31/088—Aspects of digital computing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/52—Outage or fault management, e.g. fault detection or location

Definitions

  • the present application relates to power cable fault location and fault imaging technology, and in particular to a transmission line network soft fault location and imaging method, device and storage medium.
  • Cable networks are widely distributed in modern power systems and electrical equipment. However, during the operation of the system, cable networks will inevitably experience cable soft faults such as cable aging and insulation damage. The further deterioration of these soft faults will lead to hard faults such as short circuits or open circuits in the network, causing the system to fail. In order to ensure the stable operation of power systems and equipment, it is particularly important to conduct online monitoring of faults in cable networks.
  • the existing hard fault monitoring scheme is already very mature and can locate and analyze the characteristics of various hard faults in complex cable networks.
  • the current system has already failed, and even serious electrical fires and other accidents have occurred. Therefore, the monitoring of soft faults has become a research hotspot at this stage.
  • the existing soft fault monitoring scheme uses manual visual line inspection, but since power transmission lines are often buried underground or buried in walls, visual schemes are difficult to implement. Therefore, existing schemes use handheld infrared, ultrasonic or X-ray scanning equipment to troubleshoot line faults while visually inspecting. However, such methods are time-consuming and labor-intensive, and it is difficult to achieve real-time monitoring of cable networks. It is easy to have blind spots in monitoring and cannot fully prevent electrical fires caused by cable faults.
  • the purpose of the present application is to provide a method, device and storage medium for locating and imaging soft faults in a transmission line network.
  • a method for locating and imaging soft faults in a transmission line network comprises the following steps:
  • step of transmitting the detection signal in turn by the transmitter at each port in step S1 includes:
  • the receiver When the transmitter transmits, the receiver starts recording; the injection time of the detection signal of the next port must be greater than the recording time ⁇ after the injection of the previous port.
  • the reference model of the transmission line network is constructed using a transmission cable structure with known ports and transmission line network topology information
  • ri and rc are the core conductor radius and shielding layer radius of the cable respectively, ⁇ c is the conductivity distribution of the cable core conductor, ⁇ 0 is the magnetic permeability of the cable insulation layer, ⁇ 0 is the dielectric constant of the cable insulation layer, and ⁇ i is the conductivity distribution of the cable insulation layer.
  • step S2 The steps of initializing the model parameters based on the first arrival wave at each port in the model include:
  • the time delay and amplitude attenuation of the first arrival wave are used to initialize the capacitance and resistance parameters in the transmission network;
  • C dp is the set of cables in the direct propagation path
  • [ ⁇ ] n represents the impact caused by the nth cable
  • c ref,n and r ref,n are the capacitance and resistance of the nth cable in the transmission line network when no fault occurs.
  • step S4 the residual voltage It is necessary to perform an inversion in the time domain and re-inject the input source into the reference model at the same port p.
  • the residual voltage of all ports needs to be calculated separately.
  • the normalized residual voltage After injecting the reference model, the voltage distribution R s (x, t) and [R s (x, t)] N in the superimposed transmission line network model are obtained;
  • N normalization
  • step S5 the update gradient of the capacitance c and resistance r parameters of the reference model is and
  • the calculation formula is as follows:
  • step S6 the update step sizes ⁇ c and ⁇ r of the capacitor c and the resistor r are calculated by the following formula:
  • ⁇ c and ⁇ r are small hyperparameters used to ensure that the parameter distribution changes within the linear range; ⁇ is the position and time Dirac function on time;
  • the updated model will be used to calculate the residual of the port voltage in step S2
  • step S7 is changed according to the task
  • the parameter distribution of capacitance c and resistance r in the updated reference model is used to achieve accurate positioning and fault imaging of soft faults in the transmission line; and the dielectric constant and conductivity of the insulation layer and copper core of the transmission line are calculated on the premise that the structure of the transmission line does not change.
  • a transmission line network soft fault location and imaging device comprising:
  • At least one memory for storing at least one program
  • the at least one processor When the at least one program is executed by the at least one processor, the at least one processor implements the method described above.
  • a computer-readable storage medium stores a program executable by a processor, wherein the program executable by the processor is used to execute the method described above when executed by the processor.
  • the present application breaks away from the previous limitation that fault location in transmission line networks can only be targeted at point faults and the number needs to be less than the number of ports.
  • the present application can improve the accuracy of soft fault location in transmission line networks, eliminate false fault location, and realize the decoupling and imaging of soft fault characteristics caused by aging of insulation layers and copper cores in the network.
  • FIG1 is a flow chart of a method for locating and imaging soft faults in a transmission line network based on full-wave inversion in an embodiment of the present application
  • FIG2 is a topological diagram of a transmission line network in an embodiment of the present application.
  • FIG3 is a structural diagram of an RG-58 cable set in an embodiment of the present application.
  • FIG4 is an imaging diagram of the cable capacitance and resistance distribution in an embodiment of the present application; FIG4(a) and FIG4(d) are capacitance and resistance distribution diagrams obtained by the algorithm of the present patent, and FIG4(b) and FIG4(e) are capacitance and resistance distribution diagrams in actual cables.
  • “several” means one or more, “more” means more than two, “greater than”, “less than”, “exceed”, etc. are understood to exclude the number itself, and “above”, “below”, “within”, etc. are understood to include the number itself. If there is a description of "first” or “second”, it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.
  • plural means two or more.
  • “And/or” describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and/or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character “/” generally indicates that the associated objects are in an "or” relationship.
  • the present application provides a method for locating and imaging soft faults in a transmission line network based on full-wave inversion. This method can not only locate multiple soft faults of a certain length in a complex cable network. In addition, the present application can decouple the capacitance and resistance parameters of multiple soft faults while locating them, and achieve simultaneous imaging of different parameters. This method overcomes the difficulty that existing solutions cannot locate and image multiple faults in the network, and at the same time decouples multiple parameters formed by the fault, helping the existing power cable network monitoring system to obtain more comprehensive line soft fault feature information.
  • this embodiment provides a method for locating and imaging soft faults in a transmission line network based on full-wave inversion.
  • three soft faults with a certain length appearing in a Y-type cable network are located and imaged.
  • the lengths of the three cables are The length is set to 100 meters respectively, the normal cable is set to RG-58 cable, the unit capacitance is 101.85pF/m, and the unit resistance is 37.5m ⁇ /m.
  • Fault F1 is set as a soft fault in the range of 50 to 70 meters on cable C1, in which the capacitance caused by aging of the insulation layer is 130.58pF/m, and the resistance caused by aging of the conductor copper core is 375m ⁇ /m.
  • Fault F2 is set as a soft fault in the range of 20 to 50 meters on cable C2, and the capacitance caused by aging of the insulation layer is 174.1pF/m.
  • Fault F3 is set as a soft fault in the range of 70 to 80 meters on cable C3, and the resistance caused by the conductor copper core is 750m ⁇ /m.
  • the capacitance and resistance distributions corresponding to the three cables are shown in (b) and (e) of Figure 4. The method specifically includes the following steps:
  • a receiver and a transmitter are set at all ports of the transmission line network.
  • the three transmitters take turns to transmit Gaussian modulated pulses with a center frequency of 50MHz and a voltage amplitude of 1V. All receivers record the reflected signal of 5 ⁇ s respectively. where ⁇ [0,T max ].
  • the injection time of the detection signal of the next port needs to be greater than the recording time after the injection of the previous port by 5 ⁇ s.
  • the model parameters are initialized by the first arrival wave at each port.
  • the initial reference model in step S2 is generally established by using the transmission cable structure and transmission line network topology information with known ports for modeling.
  • the transmission line network topology is shown in FIG2
  • the cable structure is shown in FIG3 .
  • the model can adopt the finite difference time domain method (FDTD), the Baum-Liu-Tesha (BLT) equation, the SPICE model and other schemes.
  • FDTD finite difference time domain method
  • BLT Baum-Liu-Tesha
  • the model adopts the finite difference time domain (FDTD) scheme, and the distribution of the resistance r 0 , capacitance c 0 , inductance l 0 and reactance g 0 parameters of the model can be calculated according to the following formula:
  • ri and rc are the core conductor radius and shielding layer radius of the cable respectively.
  • the magnetic permeability of the cable insulation layer is the vacuum magnetic permeability ⁇ 0
  • the initialization is mainly to use the time delay and amplitude attenuation of the first arrival wave to initialize the capacitance and resistance parameters in the transmission network.
  • the time delay between the first arrival wave at the actual transmission line network and the reference model synthesized port p and With amplitude and The difference can be expressed as follows:
  • C dp is the set of cables in the direct propagation path
  • [ ⁇ ] n represents the impact caused by the nth cable
  • the capacitance c ini,n and resistance r ini,n on each transmission line can be expressed as:
  • the residual voltage in step S4 It needs to be inverted in the time domain and then re-injected into the reference model at the same port p as the input source. When injecting the model, the residual voltage of all ports needs to be calculated separately. And the normalized residual voltage
  • the voltage distribution R s (x, t) and [R s (x, t)] N in the transmission line network model formed by superposition after injection are recorded for calculation in step S4. It can be expressed as:
  • the update step sizes ⁇ c and ⁇ r of the capacitor c and the resistor r in step S6 can be obtained by the following formula:
  • the updated model will be used in step S2 to calculate the residual of the port voltage
  • the residual of the port voltage in step S7 The total change ratio is less than the set threshold.
  • the threshold selection can be changed according to the task. Usually, the change ratio is selected to be less than 0.1% of the current total.
  • the parameter distribution of capacitance c and resistance r in the updated reference model can be used to accurately locate and image the soft fault of the transmission line.
  • the corresponding capacitance and resistance parameter imaging results are shown in (a) and (d) in Figure 4. Under the premise that the transmission line structure does not change, the dielectric constant and conductivity of the insulation layer and copper core of the transmission line can be calculated.
  • the method of this embodiment has at least the following advantages and effects compared with the prior art:
  • This application solves the problem of locating and imaging soft faults of multiple power lines with a certain length in a complex cable network. Such soft faults often occur in real life, such as aging of the insulation layer or the copper core of the power line in a long cable. Solving such problems is more practical.
  • the present application overcomes the limitation of existing methods in locating soft faults in cable networks, that the number of faults cannot be greater than the number of cable network ports.
  • complex cable networks usually have multiple soft fault points, and a soft fault with a certain length can be equivalent to a collection of multiple point faults. This is also the main factor that causes the existing solution to fail when a soft fault with a certain length appears in a cable network.
  • the present application can realize characteristic imaging of the fault while locating it, and can decouple the effects of aging of the conductor copper core and the insulation layer, and image both of them at the same time. This allows soft fault monitoring of the cable network to obtain more accurate fault information, providing convenience for the maintenance of the cable network.
  • the present application does not require advance knowledge of the spatial distribution of the cable network, which can overcome the difficulty in patrolling the power transmission lines that are often buried inside walls in practice.
  • the present application only needs to deploy equipment at the port of the network and periodically send and record detection signals to the monitored cable network, thereby achieving real-time cable network soft fault monitoring.
  • This embodiment also provides a transmission line network soft fault location and imaging device, including:
  • At least one memory for storing at least one program
  • the at least one processor When the at least one program is executed by the at least one processor, the at least one processor implements the method shown in FIG. 1 .
  • the present embodiment provides a transmission line network soft fault location and imaging device, which can execute the method provided in the present application embodiment.
  • a transmission line network soft fault location and imaging method can execute any combination of implementation steps of the method embodiment and has the corresponding functions and beneficial effects of the method.
  • the present application also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium.
  • a processor of a computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method shown in FIG1.
  • This embodiment also provides a storage medium storing instructions or programs that can execute a method for locating and imaging soft faults in a transmission line network provided by an embodiment of the method of the present application.
  • instructions or programs When the instructions or programs are run, any combination of implementation steps of the method embodiment can be executed, and the corresponding functions and beneficial effects of the method can be obtained.
  • the function/operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram.
  • the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order.
  • the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are expected, wherein the order of various operations is changed and the sub-operation described as a part of a larger operation is performed independently.
  • the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution.
  • the computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical disks that can store program code.
  • the logic and/or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses.
  • "computer-readable medium” can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.
  • computer-readable media include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM).
  • the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

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Abstract

本申请公开了一种传输线网络软故障定位和成像方法、装置及存储介质，属于电力线缆故障定位和故障成像技术。其中方法包括：在传输线网络的端口设置发射器和接收器，端口处的发射器发射探测信号；建立参考模型并初始化；在参考模型中注入探测信号，并计算电压信号；计算端口电压的残差，并将残差电压在时域上进行反转后在相同端口处重新注入参考模型中，计算每个位置处的电压分布；根据探测信号导致的电压分布和重新注入的残差电压分布，计算参考模型中电容和电阻参数的梯度；计算参考模型中电容和电阻的更新步长和，并对模型参数分布进行更新，直到达到预设条件。本申请摆脱了以往传输线网络故障定位只能针对点故障且数量需要小于端口数目的限制。

Description

一种传输线网络软故障定位和成像方法、装置及存储介质 技术领域
本申请涉及电力线缆故障定位和故障成像技术，尤其涉及一种传输线网络软故障定位和成像方法、装置及存储介质。
背景技术
电缆网络在现代电力系统和电气设备中广泛分布。然而，在系统运行过程中，电缆网络不可避免地会出现电缆老化、绝缘损坏等电缆软故障。这些软故障的进一步恶化将导致网络中出现短路或开路等硬故障，从而使系统发生故障。为了保证电力系统和设备的稳定运行，对电缆网络中的故障进行在线监测就显得尤为重要。
然而现有的硬故障监测方案已经非常成熟，可以实现在复杂线缆网络中对各种硬故障进行定位和特征分析。但是当线缆网络出现硬故障时，当前系统已经失效，甚至已经发生严重的电气火灾等事故。所以软故障的监测成为了现阶段的研究热点。
现有的软故障监测方案采用人工目视巡线监测，但由于电力传输线常常出现线路埋地或埋墙的空间分布，这使得目视的方案难以实行。所以现有方案在目视检查的同时会使用手持红外、超声或X光扫描设备进行线路故障排查。但此类方法费时费力，同时难以实现对线缆网络的实时监控，容易出现监测死角，无法全面预防线缆故障导致的电气火灾。
为了实现远程实时的线缆网络软故障监测，现有方案提出基于反射波测量的方案对软故障进行定位。该方案利用线缆发生软故障时注入的探测信号会发生反射这一特性来实现故障定位，但是故障的反射波容易淹没在分支的反射中，且多个软故障同时发生时会出现“伪故障点”的情况。
近年来，基于电磁时间反转的电力软故障定位方案被提出并应用于复杂网络的软故障定位中。该方案可以准确的定位故障，并且实现超分辨率的故障定位。但是在实际情况中软故障不仅存在长度不可忽略的特性，同时故障形成的原因也是绝缘层和导体铜芯两者老化共同导致的。这使得该方案难以应用在实际软故障定位和特征成像上。此外，现有方案都聚焦在故障的准确定位上，并不能实现故障关键特征(如电导率和介电常数)计算，这使得电力故障感知不够全面，火灾预警困难。因此，实际情况下的软故障定位和成像成为电力传输线实时监控的难点问题。
发明内容
为至少一定程度上解决现有技术中存在的技术问题之一，本申请的目的在于提供一种传输线网络软故障定位和成像方法、装置及存储介质。
本申请所采用的技术方案是：
一种传输线网络软故障定位和成像方法，包括以下步骤：
S1、在传输线网络的端口设置发射器和接收器，每个端口处的发射器轮流发射任意带宽受限的探测信号s＝f(x,t)，所有端口p处的接收器记录一段有限时长Tmax内的散射电压信号其中τ∈[0,Tmax]；
S2、利用传输线网络的线缆拓扑和线缆结构信息建立对应的传输线网络的参考模型，使用散射电压信号中各个端口处的首次到达波对模型参数进行模型初始化；
S3、在传输线网络的参考模型中注入相同的探测信号，并计算所有端口p处一段有限时长Tmax内的散射电压信号和传输线网络中每个位置处的电压和
S4、计算实际传输线网络和参考模型合成的端口电压的残差并将残差电压在时域上进行反转后在相同端口p处重新注入参考模型中，计算每个位置处的电压分布Rs(x,t)；
S5、根据探测信号导致的电压分布和重新注入的残差电压分布Rs(x,t)，计算参考模型中电容c和电阻r参数的梯度和
S6、计算参考模型中电容c和电阻r的更新步长ζc和ζr，并对模型参数分布进行更新；
S7、重复步骤S3-S6，直到端口电压的残差总和变动比例小于预设阀值，此时更新后参考模型中电容c和电阻r参数分布与实际传输线网络中参数分布近乎一致。
进一步地，步骤S1中所述每个端口处的发射器轮流发射探测信号的步骤，包括：
在发射器发射的同时，接收器开始进行记录；其中，下一个端口的探测信号注入时间需大于在上一个端口注入后的记录时长τ。
进一步地，所述传输线网络的参考模型采用端口已知的传输线缆结构和传输线网络拓扑信息进行构建；
模型中电阻r0、电容c0、电感l0和电抗g0的参数分布通过以下公式进行计算：



其中，ri和rc分别是电缆的核心导体半径和屏蔽层半径，σc为电缆核心导体的电导率分布，μ0为电缆绝缘层的磁导率，ε0为电缆绝缘层的介电常数，σi为电缆绝缘层的电导率分布。
进一步地，步骤S2中所述使用散射电压信号中各个端口处的首次到达波对模型参数进行模型初始化的步骤，包括：
利用首次到达波的时延和幅值衰减对传输网络中电容和电阻参数进行初始化；
其中，实际传输线网络和参考模型合成的端口p处的首次到达波之间的时延和幅值和的差异的表达式如下：

其中，Cdp是由直接传播路径中的电缆组成的集合，[·]n表示由第n条电缆造成的影响，是无损耗参考模型下的第一到达波的振幅；和分别为实际传输线网络观测的电压和参考模型的合成电压的振幅衰减；
传输线网络模型初始化每条传输线上的电容cini,n电阻rini,n表示为：

其中，cref,n和rref,n分别为未发生故障时传输线网络中第n条线缆的电容和电阻。
进一步地，步骤S4中残差电压需在时域上进行反转后作，为输入源在相同端口p处重新注入参考模型中，在注入参考模型时需分别计算所有端口的残差电压和归一化后的残差电压注入参考模型后，叠加形成的传输线网络模型中的电压分布Rs(x,t)和[Rs(x,t)]N；
其中归一化残差电压的计算公式为：
其中，N表示归一化。
进一步地，步骤S5中参考模型的电容c和电阻r参数的更新梯度和计算公式如下所示：
进一步地，步骤S6中电容c电阻r的更新步长ζc和ζr通过以下公式计算得到：

其中κc和κr是较小的超参数，用于确保参数分布变化在线性变化范围内；δ为位置与时 间上的狄拉克函数；
参考模型的参数分布的更新的表达式如下：

更新后的模型将用于步骤S2中计算端口电压的残差
进一步地，步骤S7中所述预设阀值根据任务进行改变；
在参考模型更新完成后，利用更新后的参考模型中电容c和电阻r的参数分布实现传输线软故障的精准定位和故障成像；以及结合传输线结构不发生改变的前提对传输线绝缘层和铜芯的介电系数、电导率进行计算。
本申请所采用的另一技术方案是：
一种传输线网络软故障定位和成像装置，包括：
至少一个处理器；
至少一个存储器，用于存储至少一个程序；
当所述至少一个程序被所述至少一个处理器执行，使得所述至少一个处理器实现如上所述方法。
本申请所采用的另一技术方案是：
一种计算机可读存储介质，其中存储有处理器可执行的程序，所述处理器可执行的程序在由处理器执行时用于执行如上所述方法。
本申请的有益效果是：本申请摆脱了以往传输线网络故障定位只能针对点故障且数量需要小于端口数目的限制，同时本申请能够提升传输线网络中软故障定位的精度性、消除伪故障定位，并实现网络中绝缘层和铜芯老化导致的软故障特性的解耦和成像。
附图说明
为了更清楚地说明本申请实施例或者现有技术中的技术方案，下面对本申请实施例或者现有技术中的相关技术方案附图作以下介绍，应当理解的是，下面介绍中的附图仅仅为了方便清晰表述本申请的技术方案中的部分实施例，对于本领域的技术人员而言，在无需付出创造性劳动的前提下，还可以根据这些附图获取到其他附图。
图1是本申请实施例中一种基于全波反演的传输线网络软故障定位和成像方法的流程图；
图2是本申请实施例中传输线网络拓扑图；
图3是本申请实施例中设定的RG-58线缆的结构图；
图4是本申请实施例中的线缆电容与电阻分布成像图；其中图4(a)、图4(d)为本专利算法获得的电容和电阻分布图，图4(b)、图4(e)为实际线缆中的电容和电阻分布图。
具体实施方式
下面详细描述本申请的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，仅用于解释本申请，而不能理解为对本申请的限制。对于以下实施例中的步骤编号，其仅为了便于阐述说明而设置，对步骤之间的顺序不做任何限定，实施例中的各步骤的执行顺序均可根据本领域技术人员的理解来进行适应性调整。
在本申请的描述中，需要理解的是，涉及到方位描述，例如上、下、前、后、左、右等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本申请和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请的限制。
在本申请的描述中，若干的含义是一个或者多个，多个的含义是两个以上，大于、小于、超过等理解为不包括本数，以上、以下、以内等理解为包括本数。如果有描述到第一、第二只是用于区分技术特征为目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量或者隐含指明所指示的技术特征的先后关系。
此外，在本申请的描述中，除非另有说明，“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关系。
本申请的描述中，除非另有明确的限定，设置、安装、连接等词语应做广义理解，所属技术领域技术人员可以结合技术方案的具体内容合理确定上述词语在本申请中的具体含义。
为了解决现有技术的缺点和不足，本申请提供一种基于全波反演的传输线网络软故障定位和成像方法，该方法不仅可以在复杂的线缆网络中对有一定长度的多个软故障进行定位。此外，本申请在定位的同时可以对多个软故障的电容、电阻参数进行解耦，并实现不同参数的同时成像。该方法克服了现有方案无法对网络中多个故障进行定位和成像的难点，同时解耦了故障形成的多个参数，帮助现有电力线缆网络监测系统获取更加全面的线路软故障特征信息。
如图1所示，本实施例提供一种基于全波反演的传输线网络软故障定位和成像方法，本实施例中针对Y型线缆网络中出现三个具有一定长度的软故障进行定位和成像，三条线缆长 度分别设置为100米，正常线缆设置为RG-58线缆，单位电容为101.85pF/m，单位电阻为37.5mΩ/m。故障F1设置为线缆C1上50到70米范围的软故障，其中绝缘层老化导致的电容为130.58pF/m，导体铜芯老化导致的电阻为375mΩ/m，故障F2设置为线缆C2上为20到50米范围的软故障，绝缘层老化导致的电容为174.1pF/m，故障F3设置为线缆C3上为70到80米范围的软故障，导体铜芯导致的电阻为750mΩ/m。三条线缆对应的电容电阻分布如图4中(b)和(e)所示。该方法具体包括以下步骤：
S1、在传输线网络的所有端口都设置一个接收器和一个发射器，三个发射器轮流发射高斯调制脉冲，其中心频率为50MHz，电压幅度为1V，所有接收器分别记录5μs的反射信号其中τ∈[0,Tmax]。
在本实施例中，步骤S1中所述的每个端口处的发射器轮流发射任意带宽受限的探测信号s＝f(x,t)，在发射器发射时接收器同时开始进行记录。此外，下一个端口的探测信号注入时间需要大于在上一个端口注入后的记录时长5μs。
S2、利用Y型传输线网络拓扑和RG-58结构信息建立对应的传输线网络参考模型，使用散射电压信号中各个端口处的首次到达波对模型参数进行模型初始化。
步骤S2中初始的参考模型建立一般采用端口已知的传输线缆结构和传输线网络拓扑信息进行建模，传输线网络拓扑如图2所示，线缆结构如图3所示。模型可以采用时域有限差分法(FDTD)、鲍姆-刘-特谢(BLT)方程、SPICE模型等方案。
在本实施例中，模型采用时域有限差分法(FDTD)方案，模型的电阻r0、电容c0、电感l0和电抗g0参数分布的获取可以根据以下公式进行计算：



其中ri和rc分别是电缆的核心导体半径和屏蔽层半径，RG-58电缆核心导体的电导率分布为σc＝5.175×105Ω/m，电缆绝缘层的磁导率为真空磁导率μ0、介电常数为ε0r＝2.34ε0，其中ε0为真空介电系数，和电导率分布σi忽略不计(软故障情况下漏电电流较小可以忽略)。
另外，进行的初始化主要是利用首次到达波的时延和幅值衰减对传输网络中电容和电阻参数进行初始化。实际传输线网络和参考模型合成的端口p处的首次到达波之间的时延和与幅值和的差异可以表示为如下形式：

其中Cdp是由直接传播路径中的电缆组成的集合，[·]n表示由第n条电缆造成的影响，是无损耗参考模型下的第一到达波的振幅。和分别为实际传输线网络观测的电压和参考模型的合成电压的振幅衰减。传输线网络模型初始化每条传输线上的电容cini,n电阻rini,n可以表示为：

S3、在传输线网络的参考模型中注入相同的高斯调制脉冲探测信号，并计算所有端口处5μs的散射电压信号和传输线网络中每个位置处的电压和
S4、计算实际传输线网络和参考模型合成的端口电压的残差并将残差电压在时域上进行反转后在相同端口p处重新注入参考模型中，计算每个位置处的电压分布Rs(x,t)。
步骤S4中残差电压需要在时域上进行反转后作为输入源在相同端口p处重新注入参考模型中，在注入模型时需要分别计算所有端口的残差电压和归一化后的残差电压注入后叠加形成的传输线网络模型中的电压分布Rs(x,t)和[Rs(x,t)]N进行记录，用于步骤S4的计算。其中归一化残差电压可以表示为：
S5、利用探测信号导致的电压分布和重新注入的残差电压分布Rs(x,t)来计算参考模型中电容c电阻r参数的梯度和
步骤S5中参考模型的电容c电阻r参数的更新梯度和计算公式如下所示：
S6、计算参考模型中电容c电阻r的更新步长ζc和ζr，并对模型参数分布进行更新。
步骤S6中电容c电阻r的更新步长ζc和ζr可以通过下面公式得到：

其中κc＝1×10-2和κr＝1×10-8是较小的超参数，用于确保参数分布变化在线性变化范围内。同时模型参数分布的更新可以表示为如下形式：

更新后的模型将用于步骤S2计算端口电压的残差
S7、重复步骤S3-S6直到端口电压的残差总和变动比例小于设定的阀值0.1％，此时更新后参考模型中电容c和电阻r参数分布与实际传输线网络中参数分布近乎一致。
步骤S7中端口电压的残差总和变动比例小于设定的阀值，阈值选取可以根据任务进行改变，通常选择变化比例小于当前总和的0.1％。此外，可以利用更新后的参考模型中电容c和电阻r参数分布实现传输线软故障的精准定位和故障成像，其对应的电容电阻参数成像结果如图4中(a)和(d)所示。结合传输线结构不发生改变的前提可以对传输线绝缘层和铜芯的介电系数、电导率进行计算。
综上所述，本实施例方法相对于现有技术，至少具有如下的优点及效果：
(1)本申请解决了复杂线缆网络中具有一定长度的多个电力线软故障定位和成像问题。这类软故障经常发生在实际生活中，如电力线绝缘层或导体铜芯都是较长一段线缆内都发生老化现象，解决此类问题更具有实际价值。
(2)本申请克服了现有方法在线缆网络软故障定位中，故障数目不能大于线缆网络端口数目的限制。在实际生活中，复杂线缆网络通常会出现多个软故障点，同时具有一定长度的软故障可以等效为多个点故障的集合，这也是现有方案在线缆网络中出现具有一定长度的软故障时失效的主要因素。
(3)本申请的在定位的同时可以实现故障的特征成像，而且可以解耦导体铜芯和绝缘层老化带来的影响，并同时对两者进行成像，这使得线缆网络的软故障监测可以获得更加准确的故障信息，为线缆网络的维护提供了便利。
(4)本申请在实施中不需要提前知道线缆网络的空间分布，这可以克服在实际中电力传输线常常掩埋在墙体内部所导致的巡线困难问题，本申请只需要在网络的端口处部署设备，并定时向所监测的线缆网络发送探测信号并记录，就可以实现实时的线缆网络软故障监测。
本实施例还提供一种传输线网络软故障定位和成像装置，包括：
至少一个处理器；
至少一个存储器，用于存储至少一个程序；
当所述至少一个程序被所述至少一个处理器执行，使得所述至少一个处理器实现如图1所示方法。
本实施例的一种传输线网络软故障定位和成像装置，可执行本申请方法实施例所提供的 一种传输线网络软故障定位和成像方法，可执行方法实施例的任意组合实施步骤，具备该方法相应的功能和有益效果。
本申请实施例还公开了一种计算机程序产品或计算机程序，该计算机程序产品或计算机程序包括计算机指令，该计算机指令存储在计算机可读存介质中。计算机设备的处理器可以从计算机可读存储介质读取该计算机指令，处理器执行该计算机指令，使得该计算机设备执行图1所示的方法。
本实施例还提供了一种存储介质，存储有可执行本申请方法实施例所提供的一种传输线网络软故障定位和成像方法的指令或程序，当运行该指令或程序时，可执行方法实施例的任意组合实施步骤，具备该方法相应的功能和有益效果。
在一些可选择的实施例中，在方框图中提到的功能/操作可以不按照操作示图提到的顺序发生。例如，取决于所涉及的功能/操作，连续示出的两个方框实际上可以被大体上同时地执行或所述方框有时能以相反顺序被执行。此外，在本申请的流程图中所呈现和描述的实施例以示例的方式被提供，目的在于提供对技术更全面的理解。所公开的方法不限于本文所呈现的操作和逻辑流程。可选择的实施例是可预期的，其中各种操作的顺序被改变以及其中被描述为较大操作的一部分的子操作被独立地执行。
此外，虽然在功能性模块的背景下描述了本申请，但应当理解的是，除非另有相反说明，所述的功能和/或特征中的一个或多个可以被集成在单个物理装置和/或软件模块中，或者一个或多个功能和/或特征可以在单独的物理装置或软件模块中被实现。还可以理解的是，有关每个模块的实际实现的详细讨论对于理解本申请是不必要的。更确切地说，考虑到在本文中公开的装置中各种功能模块的属性、功能和内部关系的情况下，在工程师的常规技术内将会了解该模块的实际实现。因此，本领域技术人员运用普通技术就能够在无需过度试验的情况下实现在权利要求书中所阐明的本申请。还可以理解的是，所公开的特定概念仅仅是说明性的，并不意在限制本申请的范围，本申请的范围由所附权利要求书及其等同方案的全部范围来决定。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM， Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，“计算机可读介质”可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。
计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本申请的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
在本说明书的上述描述中，参考术语“一个实施方式/实施例”、“另一实施方式/实施例”或“某些实施方式/实施例”等的描述意指结合实施方式或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一个实施方式或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施方式或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施方式或示例中以合适的方式结合。
尽管已经示出和描述了本申请的实施方式，本领域的普通技术人员可以理解：在不脱离本申请的原理和宗旨的情况下可以对这些实施方式进行多种变化、修改、替换和变型，本申请的范围由权利要求及其等同物限定。
以上是对本申请的较佳实施进行了具体说明，但本申请并不限于上述实施例，熟悉本领域的技术人员在不违背本申请精神的前提下还可做作出种种的等同变形或替换，这些等同的变形或替换均包含在本申请权利要求所限定的范围内。

Claims (10)

  1. 一种传输线网络软故障定位和成像方法，包括以下步骤：
    S1、在传输线网络的端口设置发射器和接收器，每个端口处的发射器轮流发射探测信号s＝f(x,t)，所有端口p处的接收器记录一段有限时长Tmax内的散射电压信号其中τ∈[0,Tmax]；
    S2、利用传输线网络的线缆拓扑和线缆结构信息建立对应的传输线网络的参考模型，使用散射电压信号中各个端口处的首次到达波对模型参数进行模型初始化；
    S3、在传输线网络的参考模型中注入探测信号，并计算所有端口p处一段有限时长Tmax内的散射电压信号和传输线网络中每个位置处的电压和
    S4、计算实际传输线网络和参考模型合成的端口电压的残差并将残差电压在时域上进行反转后在相同端口p处重新注入参考模型中，计算每个位置处的电压分布Rs(x,t)；
    S5、根据探测信号导致的电压分布和重新注入的残差电压分布Rs(x,t)，计算参考模型中电容c和电阻r参数的梯度和
    S6、计算参考模型中电容c和电阻r的更新步长ζc和ζr，并对模型参数分布进行更新；
    S7、重复步骤S3-S6，直到端口电压的残差总和变动比例小于预设阀值。
  2. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，步骤S1中所述每个端口处的发射器轮流发射探测信号的步骤，包括：
    在发射器发射的同时，接收器开始进行记录；其中，下一个端口的探测信号注入时间需大于在上一个端口注入后的记录时长τ。
  3. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，所述传输线网络的参考模型采用端口已知的传输线缆结构和传输线网络拓扑信息进行构建；
    模型中电阻r0、电容c0、电感l0和电抗g0的参数分布通过以下公式进行计算：



    其中，ri和rc分别是电缆的核心导体半径和屏蔽层半径，σc为电缆核心导体的电导率分布，μ0为电缆绝缘层的磁导率，ε0为电缆绝缘层的介电常数，σi为电缆绝缘层的电导率分布。
  4. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，步骤S2中所述使用散射电压信号中各个端口处的首次到达波对模型参数进行模型初始化的步骤，包括：
    利用首次到达波的时延和幅值衰减对传输网络中电容和电阻参数进行初始化；
    其中，实际传输线网络和参考模型合成的端口p处的首次到达波之间的时延和幅值和的差异的表达式如下：

    其中，Cdp是由直接传播路径中的电缆组成的集合，[·]n表示由第n条电缆造成的影响，是无损耗参考模型下的第一到达波的振幅；和分别为实际传输线网络观测的电压和参考模型的合成电压的振幅衰减；
    传输线网络模型初始化每条传输线上的电容cini,n电阻rini,n表示为：

    其中，cref,n和rref,n分别为未发生故障时传输线网络中第n条线缆的电容和电阻。
  5. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，步骤S4中残差电压需在时域上进行反转后作，为输入源在相同端口p处重新注入参考模型中，在注入参考模型时需分别计算所有端口的残差电压和归一化后的残差电压注入参考模型后，叠加形成的传输线网络模型中的电压分布Rs(x,t)和[Rs(x,t)]N；
    其中归一化残差电压的计算公式为：
    其中，N表示归一化。
  6. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，步骤S5中参考模型的电容c和电阻r参数的更新梯度和计算公式如下所示：
  7. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，步骤S6中电容c电阻r的更新步长ζc和ζr通过以下公式计算得到：

    其中κc和κr是超参数；δ为位置与时间上的狄拉克函数；
    参考模型的参数分布的更新的表达式如下：

    更新后的模型将用于步骤S2中计算端口电压的残差
  8. 根据权利要求1所述的一种传输线网络软故障定位和成像方法，其中，步骤S7中所述预设阀值根据任务进行改变；
    在参考模型更新完成后，利用更新后的参考模型中电容c和电阻r的参数分布实现传输线软故障的精准定位和故障成像；以及结合传输线结构不发生改变的前提对传输线绝缘层和铜芯的介电系数、电导率进行计算。
  9. 一种传输线网络软故障定位和成像装置，包括：
    至少一个处理器；
    至少一个存储器，用于存储至少一个程序；
    当所述至少一个程序被所述至少一个处理器执行，使得所述至少一个处理器实现权利要求1-8任一项所述方法。
  10. 一种计算机可读存储介质，其中存储有处理器可执行的程序，所述处理器可执行的程序在由处理器执行时用于执行如权利要求1-8任一项所述方法。
PCT/CN2024/111081 2023-07-06 2024-08-09 一种传输线网络软故障定位和成像方法、装置及存储介质 Ceased WO2025007993A1 (zh)

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