Research on Quality Management Measures of Green Building Construction

Urbanization has led to the rapid development of the construction industry.However,this has also led to higher requirements for the construction engineering management.Other than the quality monitoring of engineering construction,the energy-saving properties of the building should also be considered.Therefore,a scientific management approach should be adopted to improve green building management.This paper primarily examines the importance of quality management in green building construction,along with the factors influencing it.It also identifies the quality issues present in current green building construction.Finally,it proposes measures for quality management in the green building construction process to facilitate the industry’s healthy development.

Problems and Measures in the Management of Building Decoration Engineering

Building decoration engineering mainly carries out various decoration works for buildings,which can provide protection for building components,avoid the influence of nature as far as possible,and help to improve the function of buildings and prolong their life.At the same time,the building decoration project is an important part of the whole construction project,and the probability of bad situation is relatively large,so it is necessary to carry out in-depth exploration for the corresponding management work,clarify the existing problems,and put forward corresponding measures according to the actual situation.

BIM-Based Strategies for Construction Quality Control in Building Engineering

In order to improve the construction quality and steadily promote the improvement in the level of the construction industry,this paper expounds BIM-based strategies for construction quality control.This paper first identifies the factors affecting the construction quality,analyzes the advantages and value of the application of BIM in construction,and finally analyzes the scenario of applying BIM for future references.

Buildings and civil engineering works-Sealants-Determination of changes in cohesion and appearance of elastic weatherproofing sealants after exposure of statically cured specimens to artificial weathering and mechanical cycling

Foreword ISO(the International Organization for Standardization)is a worldwide federation of national standards bodies(ISO member bodies).The work of preparing International Standards is normally carried out through ISO technical committees.Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee.

Work-Related Accidents on a Hospital Construction Site in Benin

Introduction: Work-related accidents are frequent and serious in the construction sector. The aim of the study was to determine the frequency and factors associated with occupational accidents on the construction site of a referral hospital in Benin. Methods: A cross-sectional study was carried out. The sample size was calculated using the Schwartz form adjusted for the number of workers on site and was 129 workers. Random sampling was used. The dependent variable was work-related accidents. The other variables were socio-demographic and occupational characteristics. Data were collected through a questionnaire survey. Medians and proportions were calculated. An association was sought using Chi-square and Fisher tests with a threshold of p Results: A total of 132 workers were included. Their median age was 30 years with an ITQ of [27 - 38];men were the most represented 126 (95.45%) with a level of education higher than or equal to high school in 101 (76.52%) and in the majority with a permanent status 85 (64.39%). Seniority of more than 5 years was observed in 92 (69.7%). Workers working more than 8 hours of overtime per week numbered 57 (43.18%). Exposure to vibrating objects was 49 (37.12%). In terms of psychosocial constraints, 82.58% had high psychological demands;79.53% low decision-making latitude;50.76% low social support. The frequency of work-related accidents was 6.82%, and the only associated factor was the type of worker (p = 0.016). On the other hand, there were 10.2% accidents among workers handling vibrating objects versus 4.98% among those not using them. With regard to psychosocial constraints, the following frequencies were recorded respectively: 6.42% among those with high psychological demand versus 8.7% among those with low psychological demand;7.62% among those with low decision-making latitude versus 3.7% among those with high decision-making latitude;8.96% among those with low social support versus 4.62% among those with high support. Conclusion: Work-related accidents on construction sites must be avoided by all possible means including the management of psychosocial constraints.

A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

Many kinds of electrical equipment are used in civil and building engineering.The motor is one of the main power components of this electrical equipment,which can provide stable power output.During the long-term use of motors,various motor faults may occur,which affects the normal use of electrical equipment and even causes accidents.It is significant to apply fault diagnosis for the motors at the construction site.Aiming at the problem that signal data of faulty motor lack diversity,this research designs a multi-layer perceptron Wasserstein generative adversarial network,which is used to enhance training data through distribution fusion.A discrete wavelet decomposition algorithm is employed to extract the low-frequency wavelet coefficients from the original motor current signals.These are used to train themulti-layer perceptron Wasserstein generative adversarial model.Then,the trainedmodel is applied to generate fake current wavelet coefficients with the fused distribution.A motor fault classification model consisting of a feature extractor and pattern recognizer is built based on perceptron.The data augmentation experiment shows that the fake dataset has a larger distribution than the real dataset.The classification model trained on a real dataset,fake dataset and combined dataset achieves 21.5%,87.2%,and 90.1%prediction accuracy on the unseen real data,respectively.The results indicate that the proposed data augmentation method can effectively generate fake data with the fused distribution.The motor fault classification model trained on a fake dataset has better generalization performance than that trained on a real dataset.