Based on measured natural frequencies and acceleration responses,a non-probabilistic information fusion technique is proposed for the structural damage detection by adopting the set-membership identification（SMI） an...Based on measured natural frequencies and acceleration responses,a non-probabilistic information fusion technique is proposed for the structural damage detection by adopting the set-membership identification（SMI） and twostep model updating procedure.Due to the insufficiency and uncertainty of information obtained from measurements,the uncertain problem of damage identification is addressed with interval variables in this paper.Based on the first-order Taylor series expansion,the interval bounds of the elemental stiffness parameters in undamaged and damaged models are estimated,respectively.The possibility of damage existence（PoDE） in elements is proposed as the quantitative measure of structural damage probability,which is more reasonable in the condition of insufficient measurement data.In comparison with the identification method based on a single kind of information,the SMI method will improve the accuracy in damage identification,which reflects the information fusion concept based on the non-probabilistic set.A numerical example is performed to demonstrate the feasibility and effectiveness of the proposed technique.展开更多
In the BOPP （Biaxially Oriented Polypropylene） production line, the tension size and smooth film received change volume has a decisive effect on the rolling quality, casting machine is a complicated electromechanica...In the BOPP （Biaxially Oriented Polypropylene） production line, the tension size and smooth film received change volume has a decisive effect on the rolling quality, casting machine is a complicated electromechanical control system, tension control of casting machine are the main factors that influence the production quality. Analyzed the reason and the tension control mathematical model generation casting machine tension in the BOPP production line, for the constant tension control of casting machine, put forward a kind of improved PID control method based on RBF neural network. By the method of Jacobian information identification of RBF neural network, combined with the incremental PID algorithm to realize the self-tuning tension control parameters, control simulation and implementation of the model using Matlab software programming. The simulation results show that, the improved algorithm has better control effect than the general PID.展开更多
Honey vaults are useful tools for password management. A vault usually contains usernames for each domain, and the corresponding passwords, encrypted with a master password chosen by the owner. By generating decoy vau...Honey vaults are useful tools for password management. A vault usually contains usernames for each domain, and the corresponding passwords, encrypted with a master password chosen by the owner. By generating decoy vaults for incorrect master password attempts, honey vaults force attackers with the vault’s storage fle to engage in online verifcation to distinguish the real vaults, thus thwarting ofine guessing attacks. However, sophisticated attackers can acquire additional information, such as personally identifable information (PII) and partial passwords contained within the vault from various data breaches. Since many users tend to incorporate PII in their passwords, attackers may utilize PII to distinguish the real vault. Furthermore, if attackers may learn partial passwords included in the real vault, it can exclude numerous decoy vaults without the need for online verifcation. Indeed, both leakages pose serious threats to the security of the existing honey vault schemes. In this paper, we explore two attack vari-antsof the inspired attack scenario, where the attacker gains access to the vault’s storage fle along with acquiring PII and partial passwords contained within the real vault, and design a new honey vault scheme. For security assurance, we prove that our scheme is secure against one of the aforementioned attack variants. Moreover, our experimental fndings suggest enhancements in security against the other attack. In particular, to evaluate the security in multiple leakage cases where both the vault’s storage fle and PII are leaked, we propose several new practical attacks (called PII-based attacks), building upon the existing practical attacks in the traditional single leakage case where only the vault’s storage fle is compromised. Our experimental results demonstrate that certain PII-based attacks achieve a 63–70% accuracy in distinguishing the real vault from decoys in the best-performing honey vault scheme (Cheng et al. in Incrementally updateable honey password vaults, pp 857–874, 2021). Our scheme reduces these metrics to 41–50%, closely approaching the ideal value of 50%.展开更多
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education (20091102120023)the Aeronautical Science Foundation of China (2012ZA51010)+1 种基金the National Natural Science Foundation of China (11002013)Defense Industrial Technology Development Program (A2120110001 and B2120110011)
文摘Based on measured natural frequencies and acceleration responses,a non-probabilistic information fusion technique is proposed for the structural damage detection by adopting the set-membership identification（SMI） and twostep model updating procedure.Due to the insufficiency and uncertainty of information obtained from measurements,the uncertain problem of damage identification is addressed with interval variables in this paper.Based on the first-order Taylor series expansion,the interval bounds of the elemental stiffness parameters in undamaged and damaged models are estimated,respectively.The possibility of damage existence（PoDE） in elements is proposed as the quantitative measure of structural damage probability,which is more reasonable in the condition of insufficient measurement data.In comparison with the identification method based on a single kind of information,the SMI method will improve the accuracy in damage identification,which reflects the information fusion concept based on the non-probabilistic set.A numerical example is performed to demonstrate the feasibility and effectiveness of the proposed technique.
文摘In the BOPP （Biaxially Oriented Polypropylene） production line, the tension size and smooth film received change volume has a decisive effect on the rolling quality, casting machine is a complicated electromechanical control system, tension control of casting machine are the main factors that influence the production quality. Analyzed the reason and the tension control mathematical model generation casting machine tension in the BOPP production line, for the constant tension control of casting machine, put forward a kind of improved PID control method based on RBF neural network. By the method of Jacobian information identification of RBF neural network, combined with the incremental PID algorithm to realize the self-tuning tension control parameters, control simulation and implementation of the model using Matlab software programming. The simulation results show that, the improved algorithm has better control effect than the general PID.
基金supported by the National Natural Science Foundation of China(Nos.62172404,62172411,61972094,62202458).
文摘Honey vaults are useful tools for password management. A vault usually contains usernames for each domain, and the corresponding passwords, encrypted with a master password chosen by the owner. By generating decoy vaults for incorrect master password attempts, honey vaults force attackers with the vault’s storage fle to engage in online verifcation to distinguish the real vaults, thus thwarting ofine guessing attacks. However, sophisticated attackers can acquire additional information, such as personally identifable information (PII) and partial passwords contained within the vault from various data breaches. Since many users tend to incorporate PII in their passwords, attackers may utilize PII to distinguish the real vault. Furthermore, if attackers may learn partial passwords included in the real vault, it can exclude numerous decoy vaults without the need for online verifcation. Indeed, both leakages pose serious threats to the security of the existing honey vault schemes. In this paper, we explore two attack vari-antsof the inspired attack scenario, where the attacker gains access to the vault’s storage fle along with acquiring PII and partial passwords contained within the real vault, and design a new honey vault scheme. For security assurance, we prove that our scheme is secure against one of the aforementioned attack variants. Moreover, our experimental fndings suggest enhancements in security against the other attack. In particular, to evaluate the security in multiple leakage cases where both the vault’s storage fle and PII are leaked, we propose several new practical attacks (called PII-based attacks), building upon the existing practical attacks in the traditional single leakage case where only the vault’s storage fle is compromised. Our experimental results demonstrate that certain PII-based attacks achieve a 63–70% accuracy in distinguishing the real vault from decoys in the best-performing honey vault scheme (Cheng et al. in Incrementally updateable honey password vaults, pp 857–874, 2021). Our scheme reduces these metrics to 41–50%, closely approaching the ideal value of 50%.
