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The development of BIM in China is still at the primary stage. The scope of application is mainly limited within the design phase and building a three-dimension model (3D), which is far away from what is expected. Based on the present situation, the paper analyzes the application process of BIM at the design phase, and puts forward the reason for optimizing the design process, then builds the new design process.

There are many participants in one construction project, however there is no direct contractual relationship between some of them and lots of disputes, claims, problems occur on organization interface, which result in great waste and low efficiency. BIM (Building information modeling) is an innovation idea and benchmarking technology which has great impact on organization and can improve the collaborative efficiency of all construction organizations. The present problems in traditional construction project organization interface management are analyzed firstly. And then, value of BIM which is applied to solve the present problems in organization interface management is analyzed and summarized. Finally, project collaborative environment logic structure at the base of BIM is constructed to achieve maximum performance of project management.

This thesis constructs the dynamical model of the imbalance-misalignment coupling faults and the finite element model of the rotor system which are supported by rolling element bearing. It analyses the impacts from the coupling faults to the system on the basis of nonlinear finite element method, dynamic theory and Newmark-beta numerical integration method. It also studies the influence of the unbalance, misalignment and coupling faults to the system by applying the dynamic response chart and time-frequency properties. The study shows that there exist unstable high and low harmonic components, the unbalanced signal overshadowed by misalignment. It also discovers that besides the working frequency, there also exist tow times frequency and other high doubling components on the response spectra with two times frequency for the most. All those study results provide some theoretical reference for the fault diagnosing of the rotor bearing system, the vibration control and the stability research.

Characteristic signals in rotating machinery fault diagnosis with the issues of complex and difficult to deal with, while the use of non-linear manifold learning method can effectively extract low-dimensional manifold characteristics embedded in the high-dimensional non-linear data. It greatly maintains the overall geometric structure of the signals and improves the efficiency and reliability of the rotating machinery fault diagnosis. According to the development prospects of manifold learning, this paper describes four classical manifold learning methods and each advantages and disadvantages. It reviews the research status and application of fault diagnosis based on manifold learning, as well as future direction of researches in the field of manifold learning fault diagnosis.

In modern times, information technology developes very quickly. Architecture engineering construction industry has gradually been revolutionized from traditional ways to technology-based methods. As the engineering construction project is very complex ,advanced tools are required to assist finishing a project. Building information modeling is disseminated to construction industry ,as an instrument to help collaboration and co-working. The practical effectiveness of BIM is mainly in architecture design, while BIM can be used as a tool in other parts of construction industry such as virtual construction ,time-dependent control and maintainance management and even the lifecycle management.This paper mainly presents five main parts and functions designed of information system based on BIM, and analyses the strengths of the system .It aims to demonstrate how engineering project overcome traditional barriers and physical distribution with the development of information technology across the whole construction lifecycle.

It is common for the imbalance-crack coupling fault in rotating machinery, while the crack information is often overshadowed by unbalanced fault information, which is difficult to extract the crack signal. In order to extract the crack signal of the imbalance-crack coupling fault, and realize the fault diagnosis, the paper mainly analyzes its mechanical properties, and then use wavelet packet to de-nosing, decomposing and reconstructing the acquisition of vibration acceleration signal, and then analyzing the characteristics of frequency domain of the fault signal by using the energy spectrum. So the experiment proved that analyze and dispose the acquisition of the fault signal by using the method of the energy spectrum and the wavelet packet, which can effectively distinguish between the crack signal and unbalanced signals in imbalance-crack coupling faults .It also can provide some reference for the diagnosis and prevention for such fault.

Vibration signals of rotating machinery on the base are very weak and always buried in noisy noise; the common denoising methods have become powerless. It presents an ensemble empirical mode decomposition method (EEMD) that is used to denoise for the base vibration signal, which not only to overcome the problem of mode mixing, but also to avoid the selection of wavelet basis function and decomposition level of the problem. Experimental results of simulation and measured data show that EEMD method can effectively reduce the base vibration signal noise, which is better than the wavelet and EMD denoising method.

More and more attention has been paid to hospital facilities since modern pandemics have emerged such as SARS and avian influenza. Energy consumption by buildings accounts for 20-40% of energy use in developed countries, so many global organizations make efforts to develop sustainable technologies or materials to create a sustainable environment, and to reduce energy consumption when renovating building. Therefore, maintaining high standards of hygiene and reducing energy consumption has become the major task for hospital buildings. This study develops an integrated decision support system to assess existing hospital building conditions and to recommend an optimal scheme of sustainable renovation actions, considering trade-offs between renovation cost, improved building quality, and environmental impacts. A hybrid approach that combines the A* graph search algorithm with genetic algorithms (GA) is used to analyze all possible renovation actions and their trade-offs to develop the optimal solution. A simulated hospital renovation project is established to demonstrate the system. The result reveals the system can solve complicated and large-scale combinational, discrete and determinate problems such as the hospital renovation project, and also improve traditional building condition assessment to be more effective and efficient.

In the rolling process, deviation is the phenomenon that the strap width direction's centerline deviates from rolling system setting centerline,serious deviation will cause product quality drop and rolling equipment fault. This paper has established the finite element model to the hot tandem rolling aluminum strap, analyzed the strap’s deviation rule under four kinds of incentives,obtained the neural network predictive model and the control policy of the tail deviation.The result to analyze a set of fact deviation data shows this method may control tail deviation in preconcerted permission range.

Due to the great negative impact, the construction industry needs to undergo a paradigm shift from traditional construction to sustainable construction. To reach the goal of sustainable development, the construction industry needs to intensify its efforts to move to a knowledge intensive mode. Based on the analysis of e-Cognos and the concept of ontology, this paper proposes that e-Cognos ontology can be applied in the development of sustainable construction process ontology, which is a key part of knowledge management system (KMS). Following this, the application process of ontology-based KMS is analyzed using IDEF0 modeling method. Finally, this paper analyzes interorganizational collaboration model in sustainable project.

The construction, operation and demolition of building have tremendous impacts on the global energy and environment. However, initial construction costs are overly concerned in traditional construction projects and the economic, social and environmental impacts are neglected, which is a crucial barrier to the promotion of the sustainable construction. Through borrowing the theory from manufacturing industry, this paper analyzed the concept of lean construction, and combined the advantage of lean thinking with the sustainable development, promoting the sustainability and maximum value of construction projects besides the realization of three main objectives - the quality, schedule, cost of the construction project. Then, this article introduced the implementation of lean construction in the sustainable construction projects based on the view of transfer, flow, and value, and finally constructed the building objectives system which is composed of the minimum cost, the condensed duration, the superior quality and the sustainability of the construction.

To enhance the effect of fault diagnosis, a new fualt diagnosis method based on supervised incremental local tangent space alignment (SILTSA) and support vector machine (SVM) is proposed. The supervised learning approach is embedded into the incremental local tangent space alignment algorithm, to realize fault feature extraction and new data processing for equipment fault signal, and then correctly classify the faults by non-linear support vector machines. The experiment result for roller bearing fault diagnosis shows that SILTSA-SVM method has better diagnosis effect to related methods

Locally linear embedding (LLE) algorithm is an unsupervised technique recently proposed for nonlinear dimension reduction. In this paper,LLE manifold learning algorithm is introduced into the field of equipment fault diagnosis firstly, a method of the fault diagnosis based on LLE_KFDA is proposed. By LLE algorithm, original sample data is directly mapped to its’ intrinsical dimension space,which data still keep primary nonlinear form. then via kernel fisher discriminant analysis(KFDA), the characteristics data in intrinsical dimension space are mapped into knernel high-dimensional linear space,and then different fault data are discriminated based on a criterion of between-class and insid-class deviatione ratio maximum. LLE_KFDA algorithm is based on original data, avoided from fall of pattern recognition ability which caused by inappropriate or blind choice of the feature parameters in the traditional fault diagnosis method.The experiment to fault diagnosis of rolling bearing shows this method can effectively identify the equipment fault pattern, diagnostic result is good.