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Article(id=1236369224621412828, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236369220812984708, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202403152, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710172800000, receivedDateStr=2024-03-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772702993778, onlineDateStr=2026-03-05, pubDate=1732464000000, pubDateStr=2024-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772702993778, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772702993778, creator=13701087609, updateTime=1772702993778, updator=13701087609, issue=Issue{id=1236369220812984708, tenantId=1146029695717560320, journalId=1210938733613449225, year='2024', volume='53', issue='11', pageStart='1', pageEnd='168', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772702992871, creator=13701087609, updateTime=1772703093306, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236369642126627337, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236369220812984708, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236369642126627338, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236369220812984708, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=112, endPage=118, ext={EN=ArticleExt(id=1236369225137312243, articleId=1236369224621412828, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Database migration scheme based on power plant fuel management system, columnId=1211002405299294959, journalTitle=Thermal Power Generation, columnName=Thermal energy science research, runingTitle=null, highlight=null, articleAbstract=

The fuel management system of power plants is the core of coal management in thermal power plants, of which domestic substitution is a necessary path for the power plant informatization, and the localization of databases is the key. Data migration plays an important role of the handover between the old system and the new one. An optimized data migration scheme is proposed based on a thorough study on data migration methods and the data characteristics of fuel management system in power plants. Focusing on the test study of methods for verifying data consistency, the characteristics of sequential comparison and dichotomy are analyzed, and it is proved that dichotomy has certain performance advantages when the proportion of corrupt data is relatively small and the distribution is concentrated. Enlarging the proportion and decentralizing the distribution, dichotomy costs more time obviously. A data migration tool for plant fuel management system is designed and implemented, which realizes visualization of data verification. The tool supports batch operations for functions like configuring verification rules, setting execution methods and providing feedback on results. It also enriches verification rules, supports customized rules and adds the mechanism for exceptions and so on. Divided into user layer, service layer and data layer, this tool achieves data migration of plant fuel management system.

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电厂燃料管理系统作为火电厂燃煤管理的核心，进行国产化替代是电站信息化建设的必经之路，数据库国产化是其中的关键。数据迁移承担了新旧系统交接的重要环节。基于对数据迁移方法的充分研究，针对电厂燃料管理系统数据特点，提出了优化的数据迁移方案。重点对校验数据一致性的方法进行了测试，分析了逐行对比和二分法2种数据校验方法的特点，发现在问题数据占比较小、分布较集中时二分法具备一定的性能优势，随着问题数据量的增加、分布的均匀化，二分法耗时显著增加。设计开发了适于电厂燃料管理系统的数据迁移工具，实现数据校验的可视化，对校验规则配置、执行方式设置、校验结果反馈等功能支持批量操作，丰富校验规则种类，支持自定义校验规则，增加校验异常处理机制等。该数据迁移工具划分为用户层、服务层和数据层，可实现电厂燃料管理系统数据迁移。

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马晨曦（1994），男，硕士，工程师，主要研究方向为火力发电厂燃料智能管理技术，。

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马晨曦（1994），男，硕士，工程师，主要研究方向为火力发电厂燃料智能管理技术，。

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马晨曦（1994），男，硕士，工程师，主要研究方向为火力发电厂燃料智能管理技术，。

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Beijing: China Academic Journal Electronic Publishing House, 2017: 72-74., articleTitle=A study on Oracle data migration from Da Meng to Da Meng in the power industry, refAbstract=null)], funds=[Fund(id=1236369232074690599, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236369224621412828, awardId=GM-23-TYK12, language=EN, fundingSource=Science and Technology Project of Xi’an Thermal Power Research Institute Co., Ltd.(GM-23-TYK12), fundOrder=null, country=null), Fund(id=1236369232166965295, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236369224621412828, awardId=GM-23-TYK12, language=CN, fundingSource=西安热工研究院有限公司科技项目(GM-23-TYK12), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1236369227007971987, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236369224621412828, xref=1., ext=[AuthorCompanyExt(id=1236369227012166292, tenantId=1146029695717560320, journalId=1210938733613449225, 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journalId=1210938733613449225, articleId=1236369224621412828, language=EN, label=Tab.1, caption=

Test data set

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数据表名记录数/行字段数/行
HTGL1 09445
CZH9 45354
CYGL461 43118
RYGL23 39712
MCGL110 22846
HYGL219 47020
SYS5211
), ArticleFig(id=1236369231936278557, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236369224621412828, language=CN, label=表1, caption=

测试数据集

, figureFileSmall=null, figureFileBig=null, tableContent=
数据表名记录数/行字段数/行
HTGL1 09445
CZH9 45354
CYGL461 43118
RYGL23 39712
MCGL110 22846
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基于电厂燃料管理系统的数据库迁移方案
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马晨曦 1 , 陈建平 1 , 柴硕 1 , 杨睿 2 , 杜金刚 1 , 赵轩 1 , 王涛 1
热力发电 | 热能科学研究 2024,53(11): 112-118
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热力发电 | 热能科学研究 2024, 53(11): 112-118
基于电厂燃料管理系统的数据库迁移方案
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马晨曦1 , 陈建平1, 柴硕1, 杨睿2, 杜金刚1, 赵轩1, 王涛1
作者信息
  • 1.西安热工研究院有限公司，陕西　西安　710054
  • 2.华能铜川照金煤电有限公司，陕西　铜川　727103

    • 马晨曦（1994），男，硕士，工程师，主要研究方向为火力发电厂燃料智能管理技术，。

Database migration scheme based on power plant fuel management system
Chenxi MA1 , Jianping CHEN1, Shuo CHAI1, Rui YANG2, Jingang DU1, Xuan ZHAO1, Tao WANG1
Affiliations
  • 1.Xi’an Thermal Power Research Institute Co., Ltd., Xi’an 710054, China
  • 2.Huaneng Tongchuan Zhaojin Coal Power Co., Ltd., Tongchuan 727103, China
出版时间: 2024-11-25 doi: 10.19666/j.rlfd.202403152
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摘要
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电厂燃料管理系统作为火电厂燃煤管理的核心，进行国产化替代是电站信息化建设的必经之路，数据库国产化是其中的关键。数据迁移承担了新旧系统交接的重要环节。基于对数据迁移方法的充分研究，针对电厂燃料管理系统数据特点，提出了优化的数据迁移方案。重点对校验数据一致性的方法进行了测试，分析了逐行对比和二分法2种数据校验方法的特点，发现在问题数据占比较小、分布较集中时二分法具备一定的性能优势，随着问题数据量的增加、分布的均匀化，二分法耗时显著增加。设计开发了适于电厂燃料管理系统的数据迁移工具，实现数据校验的可视化，对校验规则配置、执行方式设置、校验结果反馈等功能支持批量操作，丰富校验规则种类，支持自定义校验规则，增加校验异常处理机制等。该数据迁移工具划分为用户层、服务层和数据层，可实现电厂燃料管理系统数据迁移。

电厂燃料管理系统  /  燃煤管理  /  数据迁移  /  数据校验  /  数据库

The fuel management system of power plants is the core of coal management in thermal power plants, of which domestic substitution is a necessary path for the power plant informatization, and the localization of databases is the key. Data migration plays an important role of the handover between the old system and the new one. An optimized data migration scheme is proposed based on a thorough study on data migration methods and the data characteristics of fuel management system in power plants. Focusing on the test study of methods for verifying data consistency, the characteristics of sequential comparison and dichotomy are analyzed, and it is proved that dichotomy has certain performance advantages when the proportion of corrupt data is relatively small and the distribution is concentrated. Enlarging the proportion and decentralizing the distribution, dichotomy costs more time obviously. A data migration tool for plant fuel management system is designed and implemented, which realizes visualization of data verification. The tool supports batch operations for functions like configuring verification rules, setting execution methods and providing feedback on results. It also enriches verification rules, supports customized rules and adds the mechanism for exceptions and so on. Divided into user layer, service layer and data layer, this tool achieves data migration of plant fuel management system.

power plant fuel management system  /  coal management  /  data migration  /  data verification  /  database
马晨曦, 陈建平, 柴硕, 杨睿, 杜金刚, 赵轩, 王涛. 基于电厂燃料管理系统的数据库迁移方案. 热力发电, 2024 , 53 (11) : 112 -118 . DOI: 10.19666/j.rlfd.202403152
Chenxi MA, Jianping CHEN, Shuo CHAI, Rui YANG, Jingang DU, Xuan ZHAO, Tao WANG. Database migration scheme based on power plant fuel management system[J]. Thermal Power Generation, 2024 , 53 (11) : 112 -118 . DOI: 10.19666/j.rlfd.202403152
正文
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随着信息化在各行业的普及，以及计算机软件产品的迅速更新迭代，数据存储的规模呈爆发式增长，数据迁移的需求也逐步增加[1]。数据的重要性日益提升，数据成为数字经济与信息社会的核心资源。当前国内信息产业对外依赖比较严重，存在较大的供应链中断风险和信息安全隐患[2]。信息产业国产化是实现核心技术独立、保障网路安全的必经之路，其中数据库作为数据存储、管理与应用的核心软件，对信息化系统运行效果有决定性影响。数据库的国产化是信息创新产业的重要一环，是保障数据安全的必然要求[3-6]。
根据DB-Engines对数据库管理系统的热度排名，Oracle、MySQL、SQL Server等关系型数据库长期占据主流数据库管理系统主导地位。但随着我国科研投入与产业扶持的积累，国产数据库产业在近年迎来了快速发展，如达梦数据库、人大金仓等。尤其在大数据与互联网技术的推动下，诸如OceanBase、GaussDB等新型数据库产品不断涌现，国产数据库行业迎来了百花齐放的阶段[7]。
数据库的国产化替代依旧道路漫长：国产数据库需兼容主流数据库系统，降低用户学习成本；支持高并发与可靠处理海量数据；保证数据安全性、提供技术支持；发展产品生态，提供多样性需求工具等[8]。此外数据迁移也是国产化替代过程中的关键环节。随着大数据与云计算的发展，在降低成本、提高可扩展性及增强数据安全性等多因素驱动下，数据库迁移的需求日益增长。当前在数据质量优化、数据迁移架构及数据迁移方法上的研究较多，力图探索数据迁移时如何保持一致性与完整性、提高迁移效率与兼容性、保障数据安全以及非停机迁移等问题的解决方案。
电力行业是能源行业的支柱之一，担负着经济发展和民生保障等多重职责，其中煤炭作为燃煤火电厂的“口粮”，成本占比达70%左右，电厂燃料管理系统是火力发电企业实现对燃料入厂验收与场存耗用管理的关键系统，肩负着保障燃煤接卸、计量、采样、制样、化验等方面工作有序开展的重要任务[9-12]。开展领域内软件国产化替代是保障行业信息系统安全稳定运行的必经之路。
本文针对电厂燃料管理系统的国产数据库迁移工作特点，提出了对应的数据库迁移方案架构，并以此开发数据库迁移工具，希望对未来相关国产数据库迁移工作起到一定启发与促进作用。
1　电厂燃料数据的迁移特点
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数据迁移的架构选择与方案制定需要结合所迁移数据的特点量身定制，这是因为如数据量、数据类型和数据安全等诸多因素都对数据迁移产生影响。
通过梳理数据迁移的基本架构[13]发现，当前主流的数据迁移架构普遍以ETL（extract-transform-load）作为核心[14]，涉及数据复制解耦、数据识别过滤、数据重组映射、数据加载、数据验证等过程，可以满足复杂数据迁移需求。然而这些基于ETL的主流数据迁移方案并不能很好地应用在电厂燃料管理系统的数据迁移上，需要充分考虑燃料数据特点，在ETL基础上进行针对性优化。
作为电站信息管理系统的组成部分，电厂燃料管理系统同时涉及生产端与管理端的业务流程，数据的安全性、稳定性与准确性等要求都必须得到保障。其数据迁移的特点具体如下。
1）数据时间跨度长、数据量大，结构化数据占主导，应尽量提高数据迁移效率，减小数据迁移对业务开展的影响，缩短停机迁移时间，尽量实现非停机迁移。
2）燃料数据作为数据资产在验收结算、纪检管理、配煤掺烧等方面意义重大，数据完整性与一致性要求高，因此在迁移过程中需进行必要的数据校验，且因数据量大要尽可能提高校验效率。
3）燃料数据作为敏感数据，有很高的安全性要求，在数据迁移过程中应采取技术手段防止关键数据的泄露与未授权访问。
4）燃料管理业务升级迭代频繁，各系统版本下数据结构存在差异，在数据迁移时需兼顾规划字段映射方案并对数据进行清洗补全。
5）燃料厂侧业务各电厂均有各自特点，导致各厂数据结构有差异，在数据迁移时需要使用数据迁移工具进行个性化配置，且需兼容当前多样的数据库产品。
2　数据库迁移方案
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2.1　主流ETL方法的不足
ETL作为数据抽取、转换、装载的工具，能够对分散数据进行整合操作，涵盖数据迁移过程的核心操作，很多数据迁移的工作基于ETL的思路展开。ETL对数据处理效率的高低、迁移质量的好坏，直接影响着最终的迁移效果。
针对电厂燃料数据的迁移特点，使用预定义规则的ETL工具时往往捉襟见肘，存在较多需要优化改进的地方。
1）采取批处理、算法优化等手段加快数据处理速度，提高数据迁移效率。
2）加强对数据质量的校验功能，建立高效的数据校验流程。
3）加强对数据安全性方面的保障，建立数据加密传输及迁移日志记录等防范措施。
2.2　迁移方案架构
数据库迁移过程基本可划分为准备阶段、迁移阶段以及校验阶段[15]。在准备阶段实现新旧数据库系统的环境协调、数据结构的差异性分析并制定数据映射规则；在迁移阶段需要对旧数据库进行数据清洗、抽取并导入新数据库[16]；在校验阶段则需要对迁移结果进行评估，检查数据完整性与一致性等指标[2,17]。
本文基于上述数据迁移过程，针对电厂燃料管理数据迁移特性，对主流ETL数据迁移方法进行优化，提出了适用于电厂燃料数据的数据迁移架构，具体如图1所示。该架构包含数据抽取、数据转换、数据校验、数据安全、监控日志等模块。
1）数据抽取模块完成源数据库与对应遗留系统之间的解耦，并将遗留数据加载至中间数据库中，实现对源数据的隔离与备份。
2）数据转换模块构建完整的数据清洗规则与数据映射关系，包括缺失数据的补齐规则、冗余或无效数据的剔除规则以及数据字段的映射关系。
3）数据校验模块对比目标数据库与源数据库，校验数据指标，评价迁移效果。
4）数据安全模块实现对用户身份验证与访问控制，对关键敏感数据在抽取过程进行加密以及数据转换前完成数据解密与丢损数据恢复等操作。
5）监控日志模块对数据迁移过程进行进度实时监控与日志记录留存，并在迁移完成后输出迁移结果评估报告。
其中，数据转换模块是数据迁移的核心部分，在数据补全规则、数据剔除规则以及数据映射关系上都针对电厂燃料数据特点进行了优化设计。
1）数据补齐规则
电厂燃料管理系统数据存储标准历经多次修改，同一数据类型字段同时存在多种精度或格式的历史数据，在迁移过程中需要统一精度及格式。此外也存在空数据补全的情况：对于文本类型数据，根据业务规则指定补齐规则；对于连续性数值类型数据，在满足条件的基础上利用已有数据进行填补[18-19]，并对非原始数据进行类别标识。
2）数据剔除规则
电厂燃料管理系统在数据库层面采用逻辑删除，以留存原始数据及操作痕迹，方便数据溯源与纪检核查。在燃料入厂验收过程中，设备取数异常、人员操作失误等事件都会造成异常数据的产生。异常数据在迁移时，将根据所属事件类型及对应业务环节，进行区别性的剔除与保留。
3）数据映射关系
电厂燃料管理系统运行历经多次业务功能升级，各基层电厂升级情况不统一且多定制性优化，数据库结构复杂且迁移前后差异较大，均需要灵活高效的数据映射方案。考虑到业务级数据的迁移特点[20]，构建从源数据库到目标数据库的数据字段映射关系，包括源数据库到目标数据库字段为单对单、单对多、多对单以及多对多等情况，并根据情况的不同选择不同的数据补齐与剔除规则，以适应不同系统版本的数据架构。
此外，数据安全模块在电厂燃料数据迁移中也必不可少。采用对称加密对源数据库中敏感数据加密后写入中间数据库，并在数据转换前进行解密；使用身份验证技术加强对数据库访问及迁移权限的确认，相较于传统数据迁移方案，增加生物识别与传统账户密码验证结合等方式提高验证强度。
2.3　数据校验方法
数据校验作为对数据迁移结果进行对比查验、定位异常的环节，是对迁移数据质量的重要保障，在电厂燃料数据迁移中有着举足轻重的地位。常见的评判数据质量的标准有完整性、一致性、有效性、唯一性以及业务层面数据可用性等[20-21]。
在数据完整性上，通常采用记录行统计校验对数据总量进行对比，在云存储数据的完整性验证上目前则更多依赖区块链技术来实现[22]。
在数据一致性上，常对迁移前后数据进行逐行逐列对比[20]，但存在大数据量校验效率低下的弊端；在分布式数据库中借由交换备份文件的方式实现数据同步[23]；大容量数据在对字段组合后，使用循环冗余校验或摘要算法等方式，则可提高校验效率，但存在着异常数据定位困难的问题。TiDB团队在数据一致性校验工具中引入了二分法，能在兼顾校验效率的同时实现对可疑数据范围的定位[24]。
电厂燃料数据量大、敏感度高，在纪检审查与指导生产上都具有重要意义，迁移时不仅需要系统校验完整性与一致性，而且要尽可能提高迁移与校验的效率，减少对生产过程的影响。
本节研究逐行对比与二分法在数据校验上的性能差异，并以此指导优化数据校验方法与迁移工具的设计。从电厂燃料管理系统数据库中选取7张数据表验证不同校验方法性能，测试数据集见表1。
2.3.1　测试方法
二分法校验数据一致性的步骤如图2所示。首先将数据表分批创建数据区块，并加入待检验列表。选取列表中任意数据区块，从头至尾将各记录行逐字段拼接为单字符串。对比源数据与目标数据字符串是否一致，如一致，将该数据区块从待检验列表中剔除；否则，将数据区块均匀二分后替换原有数据区块。当锁定问题记录行后，逐字段对比寻找问题字段，直到待检验列表为空结束。
逐行对比校验数据一致性则是将数据表分批，按记录行逐字段拼接字符串后并行对比。由上述步骤可知二分法较逐行对比具有如下特点。
1）二分法通过将查找范围减半提高数据校验效率，这意味着在问题数据量较小，二分法效率占优，随着问题数据占所校验数据比例增加，二分法查找所需时间将迅速增加。
2）二分法效率受问题数据在校验数据中分布形式影响较大，当问题数据分布越分散，二分法所用的时间越多。
2.3.2　测试结果
为了验证分批大小对逐行对比和二分法性能的影响，将表1所列数据表的问题数据占比设为0，并分别对分批大小为5 k、10 k、15 k时的数据校验耗时进行测试，结果如图3所示。
对于逐行对比和二分法，均在分批大小为10 k时耗时最小，说明2类方法均存在最优分批大小。当分批大小较小时，二分法的优势更明显；当分批大小较大时，二分法反而不如逐行对比。这说明当拼接字符串过长时会严重影响校验性能。
为了验证问题数据占比及其分布形式对2种校验方法的性能影响，选取CYGL数据表，并将问题数据占比分别设置为记录行数的0.01‰、0.10‰和1.00‰，问题数据的分布形式设置为相邻集中分布和等距均匀分布，测试结果如图4所示。
由图4可见，随着问题数据量的增加，逐行对比的耗时变化不大，二分法的耗时却显著增加。在问题数据占比较低时，二分法表现出一定的效率优势，但问题数据占比提高后，二分法的效率远不如逐行对比。而且问题数据的分布形式对二分法的影响十分显著，当问题数据集中分布时二分法耗时相对较低，但面对等距均匀分布的问题数据时，二分法的查找效果会迅速恶化。
通过测试逐行对比和二分法在数据校验上的性能表现，可知在面对低迁移错误率的数据校验任务时，二分法能够提供较好性能水准。
基于本节研究，在校验数据一致性时，本数据迁移架构根据燃料数据表结构动态选择不同数据校验方法，以提高数据校验效率。
3　数据迁移工具
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本节在前述数据迁移架构的基础上，开展数据迁移工具的设计开发工作。相较于普通ETL工具，适用于电厂燃料管理系统的数据迁移工具应实现如下功能：
1）分批或增量迁移，并在新旧系统并行运行后实现动态校验，减少停机时长；
2）并发迁移及校验，提高迁移效率；
3）根据表间多层连接关系设置数据清洗策略，适应复杂的数据结构；
4）兼容多数主流数据库；
5）迁移与校验过程记录，保障数据迁移安全；
6）用户生物验证登录，关联数据库操作权限；
7）敏感字段加密传输。
此外，普通ETL工具数据在燃料数据迁移中的校验功能不完善[25]。例如Kettle等ETL工具的数据检验主要针对单字段，校验规则偏弱，缺少对校验规则的操作管理、校验过程日志管理以及校验异常问题跟踪，缺少从数据迁移一致性维度对数据进行检验的能力。
本文所述的数据迁移工具在数据校验方向做出如下改进：实现数据校验的可视化，对校验规则配置、执行方式设置、校验结果反馈等功能支持批量操作，丰富校验规则种类，支持自定义校验规则，增加校验异常处理机制等。
本节设计开发适用于电厂燃料管理系统的数据迁移工具，其功能架构如图5所示，划分为用户层、服务层和数据层。
用户层用来实现数据迁移工具与用户之间的操作交互，负责接收用户指令并展示相关信息。用户层功能模块有身份验证、数据导入、数据校验、配置管理以及过程监控。其中，身份验证实现身份及权限确认；数据导入提供数据库清洗、补全以及迁移等功能；数据校验实现校验规则寻优、自动校验以及校验报告生成；配置管理提供各配置项的编辑、保存、导入及导出功能；过程监控实现对迁移与校验过程的实时监控。
服务层作为数据迁移工具的核心部分，包含导入服务、校验服务、数据安全、配置服务以及基础服务等。其中，导入服务实现数据从源数据库到目标数据库的迁移工作，并根据配置对字段进行数据清洗，记录迁移过程，生成迁移报告；校验服务提供根据数据特性匹配最优校验规则的寻优功能，利用集群部署实现对数据的快速校验，并记录校验过程、生成校验报告；数据安全实现敏感数据的加密传输以及丢失或损坏数据的恢复；配置服务用于管理数据清洗、补全、迁移以及校验过程中的配置项；基础服务提供日志记录及异常信息管理、警告消息生成与推送、消息队列管理及数据缓存调度等基础功能。
数据层涉及对源数据库与目标数据库的管理，同时提供中间数据库用于数据迁移与校验过程中的数据缓存与信息记录等功能。
数据迁移工具所实现的数据校验效果如图6所示，在完成相关配置后自动进行数据导入与校验，对并行校验过程中的资源占用进行实时监视，并在校验结束后对校验结果进行汇总展示。
4　结论
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本文在研究了主流数据库迁移方法的基础上，对电厂燃料管理系统数据及迁移特点进行了分析：电厂燃料管理系统数据对迁移效率、数据校验、数据安全、数据清洗以及个性化定制等层面都有较高的要求，需对数据迁移架构进行针对性优化设计。
对此本文提出了适用于电厂燃料管理系统的数据迁移架构，对其中数据转换策略、数据安全性保障进行了特异性构建；并重点对校验数据一致性的方案进行了详细探究，分析测试了基于字段拼接的逐行对比与二分法在数据校验上的性能表现，测试结果显示二分法对低错误率数据有较好的校验性能。
最后本文基于所提出的数据迁移架构，设计开发适用于电厂燃料管理系统的数据迁移工具。
基金
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  • 西安热工研究院有限公司科技项目(GM-23-TYK12)
文献
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2024年第53卷第11期
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doi: 10.19666/j.rlfd.202403152
  • 接收时间：2024-03-12
  • 首发时间：2026-03-05
  • 出版时间：2024-11-25
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  • 收稿日期：2024-03-12
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Science and Technology Project of Xi’an Thermal Power Research Institute Co., Ltd.(GM-23-TYK12)
西安热工研究院有限公司科技项目(GM-23-TYK12)
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    1.西安热工研究院有限公司，陕西　西安　710054
    2.华能铜川照金煤电有限公司，陕西　铜川　727103
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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