A bearing fault diagnosis method based on the Markov transitionfield(MTF)and SEnet(SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions,low fault diagnosis accuracy,and poo...A bearing fault diagnosis method based on the Markov transitionfield(MTF)and SEnet(SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions,low fault diagnosis accuracy,and poor generalization of rolling bearing.Firstly,MTF is used to encode one-dimensional time series vibration sig-nals and convert them into time-dependent and unique two-dimensional feature images.Then,the generated two-dimensional dataset is fed into the SE-IShufflenetV2 model for training to achieve fault feature extraction and classification.This paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University to experimentally verify the effectiveness and superiority of the proposed method.The generalization performance of the proposed method is tested under the variable load condition and different signal-to-noise ratios(SNRs).The experimental results show that the average accuracy of the proposed method under different working conditions is 99.2%without adding noise.The accuracy under different working conditions from 0 to 1 HP is 100%.When the SNR is 0 dB,the average accuracy of the proposed method can still reach 98.7%under varying working conditions.Therefore,the bearing fault diagnosis method proposed in this paper is characterized by high accuracy,strong anti-noise ability,and generalization.Moreover,the proposed method can also overcome the influence of variable working conditions on diagnosis accuracy,providing method support for the accurate diagnosis of bearing faults under strong noise and variable working conditions.展开更多
目的基于Markov模型评价肺结节低剂量螺旋CT(LDCT)筛查的卫生经济学。方法利用2021年—2023年北京市某三甲医院的肺结节LDCT筛查数据和部分国外临床研究数据,采用成本效用分析方法,通过增量成本效用比(ICUR)确定优势筛查策略;使用R语言...目的基于Markov模型评价肺结节低剂量螺旋CT(LDCT)筛查的卫生经济学。方法利用2021年—2023年北京市某三甲医院的肺结节LDCT筛查数据和部分国外临床研究数据,采用成本效用分析方法,通过增量成本效用比(ICUR)确定优势筛查策略;使用R语言获得转移概率参数,利用TreeAge Pro 2011软件构建Markov模型。假设以我国10万名55岁及以上人群为肺结节筛查对象,模拟其疾病发展情况,并通过敏感性分析评价该模型的稳定性。结果成本效用分析显示,该模型经20次循环后,LDCT筛查策略的总成本为3543088618元,相较于不筛查策略的总成本增加了784130651元,额外获得了7996个质量调整生命年(QALY),每获得一个QALY需多花费98059.77元。采用WHO卫生经济学评价标准,LDCT筛查策略的ICUR大于1倍人均国内生产总值(GDP)但小于3倍人均GDP,为优势策略。敏感性分析显示,各变量在其敏感性分析范围内无论如何变化,都不会对ICUR产生较大影响,表明该模型具有较好的稳定性。结论在55岁及以上人群中开展每年一次肺结节LDCT筛查的ICUR小于3倍人均GDP,具有一定的经济学效用,该筛查策略有利于肺癌的“早发现、早诊断、早治疗”。展开更多
针对如何通过预测未来土地利用结构的变化,以解决不合理的土地覆被类型造成的人地矛盾逐渐尖锐,以及生态、经济、社会发展失衡等问题,通过马尔可夫-斑块生成土地利用模拟(Markov-patch-generating land use simulation,Markov-PLUS)模型...针对如何通过预测未来土地利用结构的变化,以解决不合理的土地覆被类型造成的人地矛盾逐渐尖锐,以及生态、经济、社会发展失衡等问题,通过马尔可夫-斑块生成土地利用模拟(Markov-patch-generating land use simulation,Markov-PLUS)模型,以2000、2010、2020年乐山市土地覆被数据为基础,模拟2030年在自然惯性发展、生态保护、耕地保护3种不同情景下土地覆被的数量以及空间格局的变化,并对其转化情况进行分析。结果表明,Markov-PLUS模型模拟精度较高,可以较好地预测未来乐山市不同发展情景下土地覆被的数量以及空间格局的变化。土地覆被在3种情景中都有变化,耕地、草地、灌木地以及湿地面积在3种情景中均下降,水体、人造地表面积均上升,林地在生态保护情景下上升,其余2种情景下降。3种发展情景对比发现:生态保护情景下能较好保护乐山市生态环境;耕地保护情景下需要更严格的政策干预来保护耕地。该研究通过模拟预测不同情景下乐山市未来土地覆被变化,从而为该地区土地利用规划提供可能的参考。展开更多
基金supported by Hebei Natural Science Foundation under Grant No.E2024402079Key Laboratory of Intelligent Industrial Equipment Technology of Hebei Province(Hebei University of Engineering)under Grant No.202206.
文摘A bearing fault diagnosis method based on the Markov transitionfield(MTF)and SEnet(SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions,low fault diagnosis accuracy,and poor generalization of rolling bearing.Firstly,MTF is used to encode one-dimensional time series vibration sig-nals and convert them into time-dependent and unique two-dimensional feature images.Then,the generated two-dimensional dataset is fed into the SE-IShufflenetV2 model for training to achieve fault feature extraction and classification.This paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University to experimentally verify the effectiveness and superiority of the proposed method.The generalization performance of the proposed method is tested under the variable load condition and different signal-to-noise ratios(SNRs).The experimental results show that the average accuracy of the proposed method under different working conditions is 99.2%without adding noise.The accuracy under different working conditions from 0 to 1 HP is 100%.When the SNR is 0 dB,the average accuracy of the proposed method can still reach 98.7%under varying working conditions.Therefore,the bearing fault diagnosis method proposed in this paper is characterized by high accuracy,strong anti-noise ability,and generalization.Moreover,the proposed method can also overcome the influence of variable working conditions on diagnosis accuracy,providing method support for the accurate diagnosis of bearing faults under strong noise and variable working conditions.
文摘目的基于Markov模型评价肺结节低剂量螺旋CT(LDCT)筛查的卫生经济学。方法利用2021年—2023年北京市某三甲医院的肺结节LDCT筛查数据和部分国外临床研究数据,采用成本效用分析方法,通过增量成本效用比(ICUR)确定优势筛查策略;使用R语言获得转移概率参数,利用TreeAge Pro 2011软件构建Markov模型。假设以我国10万名55岁及以上人群为肺结节筛查对象,模拟其疾病发展情况,并通过敏感性分析评价该模型的稳定性。结果成本效用分析显示,该模型经20次循环后,LDCT筛查策略的总成本为3543088618元,相较于不筛查策略的总成本增加了784130651元,额外获得了7996个质量调整生命年(QALY),每获得一个QALY需多花费98059.77元。采用WHO卫生经济学评价标准,LDCT筛查策略的ICUR大于1倍人均国内生产总值(GDP)但小于3倍人均GDP,为优势策略。敏感性分析显示,各变量在其敏感性分析范围内无论如何变化,都不会对ICUR产生较大影响,表明该模型具有较好的稳定性。结论在55岁及以上人群中开展每年一次肺结节LDCT筛查的ICUR小于3倍人均GDP,具有一定的经济学效用,该筛查策略有利于肺癌的“早发现、早诊断、早治疗”。
文摘针对如何通过预测未来土地利用结构的变化,以解决不合理的土地覆被类型造成的人地矛盾逐渐尖锐,以及生态、经济、社会发展失衡等问题,通过马尔可夫-斑块生成土地利用模拟(Markov-patch-generating land use simulation,Markov-PLUS)模型,以2000、2010、2020年乐山市土地覆被数据为基础,模拟2030年在自然惯性发展、生态保护、耕地保护3种不同情景下土地覆被的数量以及空间格局的变化,并对其转化情况进行分析。结果表明,Markov-PLUS模型模拟精度较高,可以较好地预测未来乐山市不同发展情景下土地覆被的数量以及空间格局的变化。土地覆被在3种情景中都有变化,耕地、草地、灌木地以及湿地面积在3种情景中均下降,水体、人造地表面积均上升,林地在生态保护情景下上升,其余2种情景下降。3种发展情景对比发现:生态保护情景下能较好保护乐山市生态环境;耕地保护情景下需要更严格的政策干预来保护耕地。该研究通过模拟预测不同情景下乐山市未来土地覆被变化,从而为该地区土地利用规划提供可能的参考。
