Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business

Tang Yan; Liu Yong Jiang; Gong Ke

doi:doi:10.11648/j.sd.20251306.11

Research Article |

| Peer-Reviewed

Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business

Tang Yan^*

, Liu Yong Jiang

, Gong Ke

Published in Science Discovery (Volume 13, Issue 6)

Received: 30 September 2025 Accepted: 22 October 2025 Published: 22 November 2025

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

In the current digital health service technology architecture, a dedicated network operates on wavelength division systems built with OTN (Optical Transport Network) and related technologies. However, OTN-based wavelength division optical networks inherently suffer from limitations, as they can only perform hardware monitoring of service signals and detect deviations from standard optical power levels.Facing the construction and development trend of digital health transmission system，to address the current lack of system-level bottleneck detection capabilities in wavelength division systems, we introduce intelligent features such as characteristic data analysis and model-based evaluation, enabling dynamic perception of system bottlenecks. Starting from mathematical models that correlate optical capacity with carrier number capacity, we developed a bottleneck detection method for wavelength division systems. This approach requires only the collection of one type of system parameter and utilizes software tools for carrier beam data analysis to monitor system bottlenecks, perform diagnostics, and locate fault segments. During practical implementation, this method remains compatible with traditional wavelength division troubleshooting techniques, a technical trial run was conducted on the city's digital health business dedicated networkachieving Supports remote medical consultation and diagnostic testing services for municipal districts and five county-level regions, cost-effective and accurate identification of bottleneck points while significantly enhancing the security of digital health information transmission.

Published in	Science Discovery (Volume 13, Issue 6)
DOI	10.11648/j.sd.20251306.11
Page(s)	108-112
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Focusing Systems, Bottlenecks, Judging, Optical Capacity, Beam

1．引言

信息化系统的底层光传输网络，是以波分技术为基础构建的光网系统。现有波分系统是将业务侧源端不同波长的光信号，复用到一根光纤中传输至业务侧宿端的光网系统

[1, 2]

。当前，国内外电信运营商底层光网系统均采用波分技术进行构建，数字健康专网均承载在波分光网系统上，国内一些大型医疗机构，如厦门大学附属翔安医院、浙江大学医学院附属妇产科医院等，已经开展OTN等新型波分技术构建的医院基础承载光网应用，其发展趋势，势必推动国内大型医疗机构OTN光网系统的应用普及

[3, 4]

。然而，一旦波分系统出现瓶颈，将导致全业务信号传送中断。因此，面向数字健康底层光网建设及发展需求，引入特征数据、模型分析等智能特性，形成波分系统瓶颈的动态感知技术能力，实时开展波分系统瓶颈判断，以实现数字健康信息业务传送系统高效与安全的目的。

2．研究的问题导向及先进性

当前，数字健康专网负责数字健康信息业务信号的传送，而数字健康专网由波分系统进行承载，传统波分承载系统容量瓶颈判断，局限于单波光波长监测、光功率采集比对的物理方法

[5, 6]

，采用技术及操作过程如下：

1) 采用光波长监测技术，通过波长丢失告警，开展波分系统光容量瓶颈点的排查。

2) 根据波分系统硬件构成图，在网管处对系统构成的各硬件模块输入、输出的光功率监测点，进行实时性能采集。

3) 建立表模型，开展波分系统各监测点实时采集数据值和标称值的比对。

4) 从系统源点至宿点，进行实时与标称数值差异人工比对，找出系统光容量瓶颈点，针对瓶颈点开展优化、扩容或新建的选择和设计。

上述方法的技术及操作过程，凸显现有方法的具体问题如下：

1) 局限性大；目前方法不能适用波分系统容量瓶颈预测，仅仅通过波分系统已上业务的光波故障发生情况判断瓶颈，在实际应用中，波分系统必须预留未上业务光波的光功率能量空间，以便新上波扩容，因此波分系统光容量瓶颈的判断应包含波分系统预留未上业务光波的光能量空间，对未有告警提示下的波分系统光容量瓶颈判断提出了新需求。

2) 专业度高、差错率高；目前波分系统瓶颈判断局限于光功率监测的物理方法，涉及波分系统光功率监测点多且性能数据分散，因此数据采集量大，数据处理繁琐，与各监测点光功率标称值比对极易出错。

3) 难普及；目前波分系统瓶颈判断、预测和定位缺乏逻辑模型指导，具体操作方法不够简易、快速，对人要求高，培养时间长，资源投入大。

为此，以问题为导向，有必要开展波分系统瓶颈判断方法的研究及技术实现。经过科研攻关，提出了基于波分系统光容量空间逻辑模型的瓶颈判断方法（以下简称方法），并研制了相关智能技术。波分系统光容量空间是指波分系统各波道满足业务长距离传送的光能量之和。通过波分系统光容量空间能量转换为承载波数的数学模型，以系统可承载波束数据分析等软件方式，开展波分系统瓶颈监测、判断及故障段的定位，先进性如下：

1) 适用范围广；提供了基于逻辑模型对波分系统光容量瓶颈判断方法，有别于过去通过硬件监测有无光告警对波分系统光容量瓶颈进行的传统方法，并且补充了预测波分系统光容量瓶颈的功能。

2) 降低专业难度、差错率低；任意选定波分系统，通过光波道数逻辑模型，只需采集一个参数数据即可完成波分系统光容量瓶颈判断，大幅降低了数据采集量，简化了数据处理繁琐过程。

3) 易普及；操作简易，只需两步即可实现波分系统光容量瓶颈判断、预测和定位，一是采用光波道数逻辑模型完成系统容量瓶颈判断，二是针对瓶颈节点采用传统物理方法定位到具体瓶颈故障点。

3．方法原理、技术及应用

3.1．方案原理

以现有方法及技术存在的波分系统光功率监测点多、性能数据分散和适应范围窄等问题为导向，利用四个参数建立波分系统容量逻辑模型，其揭示了波分系统各组成部分及线路对承载业务光波光功率的影响程度，使高密度光波道数有了控制计算依据。只需采集一个参数通过逻辑模型计算、比对即可完成波分系统级、节点级光容量瓶颈的判断。同时，兼容现有物理方法，开展具体瓶颈点的定位。

3.2．技术实现及应用

方法的技术方案实现流程，如图1：

Download: Download full-size image

Figure 1. 图1 方法技术实现流程图。

以上方法的技术实现步骤如下：

1) 根据实际需求，选定目标波分系统中全部节点。

2) 通过网管，对选定节点的光接收方向的功放单板光功率增益余量数据进行采集。

3) 利用上述采集数据，并设置两个参数的初始值，基于波分系统容量逻辑模型计算，得出波分系统各节点可扩容的实际光波道数量。

4) 根据波分系统容量逻辑模型计算结果，比对波分系统各节点可扩容的标称光波道数量，判断波分系统光容量瓶颈或者趋势预测波分系统光容量瓶颈。

5) 经过判断，若波分系统光容量瓶颈即将或已经出现，则进一步确定波分系统中可扩光波道数量最小值的节点。

6) 通过网管，对波分系统中可扩光波道数量最小值的节点及其下游相邻的节点所涉及的各光功率监测点进行采集。

7) 结合现有的光功率监测的物理方法，定位波分系统瓶颈点。

8) 对上述波分系统瓶颈点开展优化、新建或扩容设计选择和重大故障的预处理，直至满足需求为止。

下面，结合具体的应用，展示方法及技术实现步骤，如下。

步骤1，选取波分系统，以承载数字健康专网的地级市（达州市）波分系统为例，图2为两个波分系统组网的示例图。

Download: Download full-size image

Figure 2. 图2 某地市电信运营商骨干波分系统图。

步骤2，通过网管，获取地市级骨干波分系统两个环网（7个节点）的光接收方向功放单板光功率增益余量数据。

步骤3，利用步骤2采集数据，通过波分系统光容量逻辑模型，计算波分系统各节点可扩容的实际光波道数量；在具体实施时，将波道光功率转换为波数表达的光容量逻辑模型。如下：

①建立波分系统能量逻辑模型，其公式为：

，其中En为波分系统总容量光功率，E_ε为波分系统总容量冗余光功率，

为波分系统总容量中可扩容部分光功率，

为波分系统总容量中已使用的光功率。

②经过推导，光功率与波数的变换计算公式为

其中

为光功率，N为光承载波数。

③结合波分系统能量逻辑模型，通过光功率与波数变换的计算方式，构建波分系统光容量逻辑模型，计算公式为：

。

④设置

、

初始值，将7个节点采集数据

代入光波道数逻辑模型得出Xn，其中Zn值可以从网管直接获取，ε值按通信行业标准取1至2

[7, 8]

。

步骤4，利用上述波分系统容量逻辑模型计算结果，实施波分系统4个节点可扩波数计算值Xn与标称值Xn’对比，得出差值▽，进而进行瓶颈判断。其计算方式为：▽= Xn- Xn’；当▽=2时，波分系统光容量正常；当0≦▽≦2时，预测波分系统光容量即将出现瓶颈；当▽≦0时，波分系统光容量已经出现瓶颈。

步骤5，利用步骤4中波分系统光容量瓶颈判断结果进行分析，若结果显示波分系统光容量即将或已经出现瓶颈，则采用可扩光波道数量最小值的节点计算方式，确定可扩光波道数量最小值节点，计算方式为：Δmin=Min（Xn- Xn’）。

步骤6，采集网管采集波分系统中可扩光波道数量最小值节点，及其下游相邻的节点所涉及的各光功率监测点数据。

步骤7，结合现有的光功率监测的物理方法，在系统瓶颈点准确判断的基础上，定位两个波分系统光容量瓶颈的具体故障点位；如下：

① 根据波分系统各组成建立一张涉及14个维度的表模型

[9, 10]

，包括连接段落、公里数、节点、收发态、网管光功率值、线路衰耗实际值、线路衰耗标称值、网管单板实际增益、单板标称增益、单板增益余量、可扩波数计算值、可扩波数标称值和波分系统已承载波数等字段。

②依据表模型针对瓶颈点及其下游相邻点，通过网管提取相关监测点光功率数据。

③进行实际值与标称值的比对。

④准确定位两个波分系统光容量瓶颈点。

步骤8，利用步骤7准确定位波分系统光容量瓶颈点的结果，实施波分系统扩容设计，对存在隐患光缆进行整治。

上述波分系统瓶颈判断，通过综合网管系统，每隔5分钟进行波分系统参数采集及瓶颈判断，以电子运维工单形式，下发相关人员进行系统瓶颈的维护修复及建设需求上报。

以上就是基于波分系统光容量逻辑模型的瓶颈判断方法及技术应用实践。图3为方法技术实现及应用，展示了基于波分系统光容量逻辑模型的瓶颈判断、预测和传统物理定位方法融合排障的实际应用操作过程及结果。

Download: Download full-size image

Figure 3. 图3 方法技术实现及应用。

4．应用及结论

在数字健康一张专网的波分承载系统应用普及上，于2024年7月，在达州市OTN骨干网上，面向市辖区、5个县域医疗卫生远程会诊、检查检验业务传送，开展了上述方法及技术的普及应用，周期为12个月。

应用期间，波分系统光容量瓶颈共发生15次，波分系统光容量瓶颈判断准确率为100%，精确度能达到99.9%，配合传统波分故障排障法，在故障发生前定位瓶颈点，进行了光衰的预处理，实现了预防性维护，因此，光衰变化引发的信息业务传送的全阻隠性故障无一例发生。

上述提到的隐性业务全阻是指网管侧无告警信息，因光衰减等性能裂变引发的基础承载网络信号传送全中断故障。此故障发生时，网管监测人员毫无察觉，是网络维护中一直存在的难点，只能在故障发生后，通过人工采集数据、数据分析进行排障

[11-13]

。每发生一次此类隐性业务全阻故障，造成的业务价值损失巨大。参照2024年达州市卫生健康统计年报的数据进行计算，此类故障恢复时间在1小时内（按1小时计算），造成业务价值损失为346.17万元（医院门诊年诊疗数为331.1万人次，达州市门诊人均费用为301.11元）。

由此，基于波分系统光容量空间逻辑模型的瓶颈判断方法及技术，有效解决了波分系统光衰变化引发信息业务全阻的隐性故障监测、判断难题，有效提升了数字健康信息业务传送的安全性，创造了巨大的社会价值。

综上，当前光通信传输技术领域呈超高带宽化发展，数字健康信息系统数据量呈指数激增，其基础承载网向大容量的波分设备组网进行演进是将来的趋势，由此，波分系统瓶颈判断方法研究及技术研制补充网络智能性十分必要。面向数字健康建设及发展，基于波分系统光容量空间逻辑模型的瓶颈判断方法及技术，不限于波分系统的任何组网形式，也不限于任何以波分技术为基础衍生的新型波分技术

[14, 15]

，其普适性及安全性，不仅填补了国内外此类技术及应用的空白，而且将为数字健康信息业务传送提供高可靠的安全保障，为当地人民健康创造更大的社会价值。

致谢

本文为四川省达州市重点科技计划项目（22YKX0016）的阶段性成果之一。

ORCID

0009-0008-9467-5370 (Tang Yan)

0009-0003-2950-0199 (Liu Yong Jiang)

0009-0007-6270-0941 (Gong Ke)

References

[1]	钟昌锦, 刘斌, 付益等. 密集波分复用(DWDM)技术实现原理分析 [J]. 广东通信技术, 2021, 41(04): 66-68.
[2]	万成超, 蒲涛, 胡友鹏. DWDM设备维护中的光功率调整原则 [J]. 军事通信技术, 2012(04): 78-81.
[3]	陆源, 刘勇. 高速波分系统的OSNR测试研究 [J]. 山东通信技术. 2023, 43(02): 17-18.
[4]	陈翠芬. 高速波分系统的OSNR测试研究 [J]. 通信与信息技术, 2023(04): 31-32.
[5]	项国刚. 采用光功率监测法监测光纤劣化的可行性 [J]. 四川通信技术, 1997(06): 25-33.
[6]	杨东, 轩克辉. 光纤损耗的测试 [J]. 山东轻工业学院学报(自然科学版), 2011: 74-76.
[7]	黄祥本, 梁有程. WDM传输系统光功率调试分析 [J]. 长沙通信职业技术学院学报, 2012(02): 21-24. https://doi.org/10.3969/j.issn.1671-9581.2012.02.006
[8]	胡海良. 低损耗光纤在中电信现网的应用 [J]. 数字通信世界, 2017(11): 162. https://doi.org/10.3969/J.ISSN.1672-7274.2017.11.126
[9]	刘琳, 赵长有. 光功率测试单元系统设计 [J]. 世界电子元器件, 2003(01): 53-54. https://doi.org/10.11648/j.ijmsa.20221103.12
[10]	康世群, 吴亚楠. 通信传输网络故障压降的策略分析 [J]. 数据通信, 2025(04): 50-51.
[11]	幺宏伟. 光网络波分设备光功率异常和误码故障处理探讨 [J]. 中国新通信, 2021(02): 125-126.
[12]	贺秀娟, 徐加彦. 数字接收分系统故障检测软件开放式架构 [J]. 电子信息对抗技术, 2022, 37(04): 115-116. https://doi.org/10.3969/j.issn.1674-2230.2022.04.023
[13]	贺金花. 100G OTN技术在骨干网传输系统中的应用 [D]. 南京理工大学, 2020(02): 33-38. https://doi.org/10.27251/d.cnki.gnjdc.2018.000129
[14]	乐孜纯, 张明, 全必胜. 光网络实用组网技术 [M]. 西安电子科技大学出版社, 2008(07): 16-18.
[15]	闫斐. OTN光传送网波分系统中误码分析及研究 [J]. 广播电视网络, 2022, 29(02): 78-80. https://doi.org/10.16045/j.cnki.catvtec.2022.02.009

Cite This Article

Plain Text BibTeX RIS

APA Style

Yan, T., Jiang, L. Y., Ke, G. (2025). Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business. Science Discovery, 13(6), 108-112. https://doi.org/10.11648/j.sd.20251306.11

Copy | Download

ACS Style

Yan, T.; Jiang, L. Y.; Ke, G. Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business. Sci. Discov. 2025, 13(6), 108-112. doi: 10.11648/j.sd.20251306.11

Copy | Download

AMA Style

Yan T, Jiang LY, Ke G. Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business. Sci Discov. 2025;13(6):108-112. doi: 10.11648/j.sd.20251306.11

Copy | Download

@article{10.11648/j.sd.20251306.11,
  author = {Tang Yan and Liu Yong Jiang and Gong Ke},
  title = {Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business
},
  journal = {Science Discovery},
  volume = {13},
  number = {6},
  pages = {108-112},
  doi = {10.11648/j.sd.20251306.11},
  url = {https://doi.org/10.11648/j.sd.20251306.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20251306.11},
  abstract = {In the current digital health service technology architecture, a dedicated network operates on wavelength division systems built with OTN (Optical Transport Network) and related technologies. However, OTN-based wavelength division optical networks inherently suffer from limitations, as they can only perform hardware monitoring of service signals and detect deviations from standard optical power levels.Facing the construction and development trend of digital health transmission system，to address the current lack of system-level bottleneck detection capabilities in wavelength division systems, we introduce intelligent features such as characteristic data analysis and model-based evaluation, enabling dynamic perception of system bottlenecks. Starting from mathematical models that correlate optical capacity with carrier number capacity, we developed a bottleneck detection method for wavelength division systems. This approach requires only the collection of one type of system parameter and utilizes software tools for carrier beam data analysis to monitor system bottlenecks, perform diagnostics, and locate fault segments. During practical implementation, this method remains compatible with traditional wavelength division troubleshooting techniques, a technical trial run was conducted on the city's digital health business dedicated networkachieving Supports remote medical consultation and diagnostic testing services for municipal districts and five county-level regions, cost-effective and accurate identification of bottleneck points while significantly enhancing the security of digital health information transmission.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business

AU  - Tang Yan
AU  - Liu Yong Jiang
AU  - Gong Ke
Y1  - 2025/11/22
PY  - 2025
N1  - https://doi.org/10.11648/j.sd.20251306.11
DO  - 10.11648/j.sd.20251306.11
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 108
EP  - 112
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20251306.11
AB  - In the current digital health service technology architecture, a dedicated network operates on wavelength division systems built with OTN (Optical Transport Network) and related technologies. However, OTN-based wavelength division optical networks inherently suffer from limitations, as they can only perform hardware monitoring of service signals and detect deviations from standard optical power levels.Facing the construction and development trend of digital health transmission system，to address the current lack of system-level bottleneck detection capabilities in wavelength division systems, we introduce intelligent features such as characteristic data analysis and model-based evaluation, enabling dynamic perception of system bottlenecks. Starting from mathematical models that correlate optical capacity with carrier number capacity, we developed a bottleneck detection method for wavelength division systems. This approach requires only the collection of one type of system parameter and utilizes software tools for carrier beam data analysis to monitor system bottlenecks, perform diagnostics, and locate fault segments. During practical implementation, this method remains compatible with traditional wavelength division troubleshooting techniques, a technical trial run was conducted on the city's digital health business dedicated networkachieving Supports remote medical consultation and diagnostic testing services for municipal districts and five county-level regions, cost-effective and accurate identification of bottleneck points while significantly enhancing the security of digital health information transmission.

VL  - 13
IS  - 6
ER  -

Copy | Download

Author Information

Tang Yan

Information Technology Section, Dazhou Health and Family Planning Information Center, Dazhou, China

Contact Email

http://orcid.org/0009-0008-9467-5370
Liu Yong Jiang

Information Center, Dazhou Third People's Hospital, Dazhou, China

http://orcid.org/0009-0003-2950-0199
Gong Ke

Information Center, Dazhou First People's Hospital, Dazhou, China

http://orcid.org/0009-0007-6270-0941

Download PDF

Submit an Article

Figure 1

Figure 1. 图 1 方法技术实现流程图。
Figure 2

Figure 2. 图 2 某地市电信运营商骨干波分系统图。
Figure 3

Figure 3. 图 3 方法技术实现及应用。

Plain Text BibTeX RIS

APA Style

Yan, T., Jiang, L. Y., Ke, G. (2025). Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business. Science Discovery, 13(6), 108-112. https://doi.org/10.11648/j.sd.20251306.11

Copy | Download

ACS Style

Yan, T.; Jiang, L. Y.; Ke, G. Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business. Sci. Discov. 2025, 13(6), 108-112. doi: 10.11648/j.sd.20251306.11

Copy | Download

AMA Style

Yan T, Jiang LY, Ke G. Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business. Sci Discov. 2025;13(6):108-112. doi: 10.11648/j.sd.20251306.11

Copy | Download

@article{10.11648/j.sd.20251306.11,
  author = {Tang Yan and Liu Yong Jiang and Gong Ke},
  title = {Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business
},
  journal = {Science Discovery},
  volume = {13},
  number = {6},
  pages = {108-112},
  doi = {10.11648/j.sd.20251306.11},
  url = {https://doi.org/10.11648/j.sd.20251306.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20251306.11},
  abstract = {In the current digital health service technology architecture, a dedicated network operates on wavelength division systems built with OTN (Optical Transport Network) and related technologies. However, OTN-based wavelength division optical networks inherently suffer from limitations, as they can only perform hardware monitoring of service signals and detect deviations from standard optical power levels.Facing the construction and development trend of digital health transmission system，to address the current lack of system-level bottleneck detection capabilities in wavelength division systems, we introduce intelligent features such as characteristic data analysis and model-based evaluation, enabling dynamic perception of system bottlenecks. Starting from mathematical models that correlate optical capacity with carrier number capacity, we developed a bottleneck detection method for wavelength division systems. This approach requires only the collection of one type of system parameter and utilizes software tools for carrier beam data analysis to monitor system bottlenecks, perform diagnostics, and locate fault segments. During practical implementation, this method remains compatible with traditional wavelength division troubleshooting techniques, a technical trial run was conducted on the city's digital health business dedicated networkachieving Supports remote medical consultation and diagnostic testing services for municipal districts and five county-level regions, cost-effective and accurate identification of bottleneck points while significantly enhancing the security of digital health information transmission.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Bottleneck Determination Technology and Application of Wavelength Division System for Signal Transmission in Digital Health Business

AU  - Tang Yan
AU  - Liu Yong Jiang
AU  - Gong Ke
Y1  - 2025/11/22
PY  - 2025
N1  - https://doi.org/10.11648/j.sd.20251306.11
DO  - 10.11648/j.sd.20251306.11
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 108
EP  - 112
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20251306.11
AB  - In the current digital health service technology architecture, a dedicated network operates on wavelength division systems built with OTN (Optical Transport Network) and related technologies. However, OTN-based wavelength division optical networks inherently suffer from limitations, as they can only perform hardware monitoring of service signals and detect deviations from standard optical power levels.Facing the construction and development trend of digital health transmission system，to address the current lack of system-level bottleneck detection capabilities in wavelength division systems, we introduce intelligent features such as characteristic data analysis and model-based evaluation, enabling dynamic perception of system bottlenecks. Starting from mathematical models that correlate optical capacity with carrier number capacity, we developed a bottleneck detection method for wavelength division systems. This approach requires only the collection of one type of system parameter and utilizes software tools for carrier beam data analysis to monitor system bottlenecks, perform diagnostics, and locate fault segments. During practical implementation, this method remains compatible with traditional wavelength division troubleshooting techniques, a technical trial run was conducted on the city's digital health business dedicated networkachieving Supports remote medical consultation and diagnostic testing services for municipal districts and five county-level regions, cost-effective and accurate identification of bottleneck points while significantly enhancing the security of digital health information transmission.

VL  - 13
IS  - 6
ER  -

Copy | Download