张恒
副研究员
专业：控制科学与工程
所属科研团队：装备智能健康评估
研究方向：装备故障预测与健康管理，剩余寿命预测，电池管理系统
email:
地址：四川省成都市一环路南一段24号四川大学基础教学楼b座217
学习和工作简历
教育经历：
2016/09-2021/06，四川大学空天科学与工程学院，机械工程，博士，导师：苗强教授
2012/09-2016/06，哈尔滨工程大学航天与建筑工程学院，质量与可靠性工程，学士
访学经历：
2019/12-2020/11，university of south carolina，美国，联合培养博士，导师：bin zhang 教授
工作经历：
2021/06-至今，四川大学，电气工程学院，副研究员（专职科研）
2021/09-2023/06，四川大学，电气工程学院，助理研究员
科研项目：
[1] 国家自然科学基金，基于lebesgue采样的动力电池组状态联合估计与寿命预测研究，主持
[2] 四川省科技厅，飞行器机载电传作动系统健康状态在线评估与预测研究，主持
[3] 博士后基金，资源受限的空间锂离子蓄电池组在轨健康管理关键技术研究，主持
[4] 国家重点研发计划项目，大规模制造产业网状结构价值链数字生态理论研究，主研
[5] 国家自然科学基金，微重力环境下低速空间旋转机构动态服役行为表征与评估，主研
代表性学术成果：
[1] lyu g, zhang h, miao q. parallel state fusion lstm-based early-cycle stage lithium-ion battery rul prediction under lebesgue sampling framework. reliability engineering & system safety, 2023, 236: 109315.
[2] lyu g, zhang h, miao q. rul prediction of lithium-ion battery in early-cycle stage based on similar sample fusion under lebesgue sampling framework. ieee transactions on instrumentation and measurement, 2023, 72: 1-11.
[3] miao j, deng c, zhang h, et al. interactive channel attention for rotating component fault detection with strong noise and limited data. applied soft computing, 2023, 138: 110171.
[4] lyu g, zhang h, zhang y j, et al. an interpretable remaining useful life prediction scheme of lithium-ion battery considering capacity regeneration. microelectronics reliability, 2022: 114625.
[5] wang j, zeng z, zhang h, et al. an hybrid domain adaptation diagnostic network guided by curriculum pseudo labels for electro-mechanical actuator. reliability engineering & system safety, 2022: 108770.
[6] yan x, h. zhang, luo c, et al. degree of cyclic target protrusion defined on squared envelope spectrum for rotating machinery fault diagnosis. measurement, 2021: 110634.
[7] h. zhang, g.x. niu, b. zhang, and q. miao, “cost-effective lebesgue sampling long short-term memory networks for lithium-ion batteries diagnosis and prognosis,” ieee transactions on industrial electronics, 2022, vol.69, no.2, pp.1958-1967.
[8] h. zhang, e. liu, b. zhang, and q. miao, “rul prediction and uncertainty management for multisensor system using an integrated data-level fusion and upf approach,” ieee transactions on industrial informatics, vol. 17, no. 7, pp. 4692 - 4701, 2021.
[9] h. zhang, z. mo, j. wang, and q. miao, “nonlinear-drifted fractional brownian motion with multiple hidden state variables for remaining useful life prediction of lithium-ion batteries,” ieee transactions on reliability, vol. 69, no. 2, pp. 768–780, 2019.
[10] h. zhang, miao q, zhang x, and liu zw, “an improved unscented particle filter approach for lithium-ion battery remaining useful life prediction,” microelectronics reliability, 2018, 81: 288-298.
[11] z.l. mo, h. zhang, j.l. wang, j.y. wang, h.y. fu, and q. miao, “adaptive meyer wavelet filters for machinery fault diagnosis based on harmonic infinite-taxicab norm and grasshopper optimization algorithm,” proceedings of the imeche, part c: journal of mechanical engineering science, 2021, vol.235, no.19, pp.4458-4474.
[12] z.l. mo, j.y. wang, h. zhang, and q. miao, “weighted cyclic harmonic-to-noise ratio for rolling element bearing fault diagnosis,” ieee transactions on instrumentation and measurement, 2020, vol.69, no.2, pp.432-442.
[13] j.y. wang, z.l. mo, h. zhang, and q. miao, “ensemble diagnosis method based on transfer learning and incremental learning towards mechanical big data,” measurement, 2020, vol. 155, 107517.
[14] 苗强, 蒋京, 张恒, 罗冲. 工业大数据背景下的航空智能发动机：机遇与挑战, 仪器仪表学报, 2019, vol.40, no.7, pp. 1-12.
人才培养：
研究生选修课程：《检测技术与自动化》、《可靠性系统工程》、《运筹学》
学术兼职：
航空学会phm分会青年委员，ieee会员，担任ieee transactions on power systems，ieee transactions on industrial informatics，ieee transactions on industrial electronics，ieee transactions on instrumentation and measurement等多个期刊审稿人。