Quality Accidents Research Articles

Study on the escaping condition of backfill grouting based on two-phases flow for shield tunnelling during whole section rock

During the process of full section surrounding rock shield tunneling, the occurrence of synchronous grout escaping can seriously affect the assembly quality of the detached shield tail segment ring. The segment is prone to quality accidents such as floating, misalignment of the tunnel pipes, and even cracking, and even a large number of rock fractures in the shield tail gap mix with water flow towards the excavation face and pressure chamber, leading to frequent fissure water gushing out of the screw conveyor. Taking the shield tunnelling section of Nanjing Metro Line 6 as the engineering background, this paper uses the finite element software Ansys Fluent to establish the two-phases flow shield tail escaping grout model, and analyzes the influence laws of the grout properties, grouting pressure difference, grouting escaping thickness and other factors in the process of grout escaping behind the shield tail wall based on Bingham fluid. The results show that the amount of synchronized grout escaping increases linearly with the increase of grouting pressure difference and grouting escaping thickness, and decreases with the increase of grout shear yield stress. The paper also discusses the three-dimensional curved surface of grout escaping volume, grouting pressure difference and grouting fluid properties behind shield tunnel tail in a full section surrounding rock shield project of Nanjing Line 6, and gives the measures to prevent grout escaping when the allowable grout escaping volume is not more than 1m3: when the grouting escaping thickness is 20mm, the grouting pressure difference should be controlled within 0.20∼0.25MPa, and the shear yield stress of the grouting fluid should be controlled within 300∼350Pa.

A chemical accident cause text mining method based on improved accident triangle

BackgroundWith the rapid development of China’s chemical industry, although researchers have developed many methods in the field of chemical safety, the situation of chemical safety in China is still not optimistic. How to prevent accidents has always been the focus of scholars’ attention.MethodsBased on the characteristics of chemical enterprises and the Heinrich accident triangle, this paper developed the organizational-level accident triangle, which divides accidents into group-level, unit-level, and workshop-level accidents. Based on 484 accident records of a large chemical enterprise in China, the Spearman correlation coefficient was used to analyze the rationality of accident classification and the occurrence rules of accidents at different levels. In addition, this paper used TF-IDF and K-means algorithms to extract keywords and perform text clustering analysis for accidents at different levels based on accident classification. The risk factors of each accident cluster were further analyzed, and improvement measures were proposed for the sample enterprises.ResultsThe results show that reducing unit-level accidents can prevent group-level accidents. The accidents of the sample enterprises are mainly personal injury accidents, production accidents, environmental pollution accidents, and quality accidents. The leading causes of personal injury accidents are employees’ unsafe behaviors, such as poor safety awareness, non-standard operation, illegal operation, untimely communication, etc. The leading causes of production accidents, environmental pollution accidents, and quality accidents include the unsafe state of materials, such as equipment damage, pipeline leakage, short-circuiting, excessive fluctuation of process parameters, etc.ConclusionCompared with the traditional accident classification method, the accident triangle proposed in this paper based on the organizational level dramatically reduces the differences between accidents, helps enterprises quickly identify risk factors, and prevents accidents. This method can effectively prevent accidents and provide helpful guidance for the safety management of chemical enterprises.

Developing a Methodology to Establish Response Zones based on Travel Time for Controlling the Spread of Water Quality Incidents in Water Supply Systems

Water quality issues may arise within the water pipe network system due to external contamination from water leaks, aging pipes leading to damage, and the presence of suspended sediments resulting from changes in hydraulic direction. Promptly addressing these water quality problems during the supply process is crucial, as delays can swiftly escalate health risks for residents and cause economic damage to the region. Therefore, developing control techniques is imperative to minimize the rapid dissemination of accidents. This study aims to proactively identify and calculate the spread pattern of water quality incidents within the pipe network, utilizing residence time as a critical factor. A practical and efficient spread control zoning methodology was proposed to curtail the expansion of accidents. Applying the proposed methodology to the pipe network system in Cty A (Korea) involved quantitative analysis of newly defined areas based on the target residence time intended for practical management and control during water quality accidents. The results of the analysis demonstrate that the proposed method offers the potential to establish a novel concept of a response area for rapid reactions to water quality incidents. This facilitates the design of a zone centered around valves essential for crisis response, thereby creating an area with precise control over the spread of water quality accidents within a target response time.

Design of Lubricating Oil Circulation Refrigeration System for Cigarette Machine

In order to solve the problems of high lubricating oil temperature, fast aging of seals and serious wear of parts during high-speed operation of equipment, a lubricating oil circulation refrigeration system for cigarette machine was designed. The system uses PLC as the main controller, and controls the motor speed through Profibus bus mode to realize the circulating refrigeration of lubricating oil. Through the test with ZJ112 unit as the object,we found that the system runs well and the failure rate is low. The temperature of each lubricating part of the equipment is significantly reduced and kept below 40 ˚C. At the same time, the maintenance time of the equipment is reduced, and the occurrence of cigarette quality accidents is reduced. This technology can provide support for improving the production adaptability of cigarette units.

EDAS-aided intelligent decision-making in interior decoration design quality assessment using 2-tuple linguistic pythagorean fuzzy sets

Interior decoration design can refine its functions, improve environmental quality, improve spatial form, and is closely related to buildings, structures, equipment, etc. The quality of interior decoration design directly affects a series of issues such as safety, quality, cost savings, environmental protection, and aesthetic practicality of the project, and the quality inspection of interior decoration design can control the safety, quality, cost savings, environmental protection, and aesthetic practicality of the interior decoration project in advance, reducing the occurrence of safety and quality accidents during construction and use, And it plays a proactive role in cost saving and environmental protection of decoration projects, and can also provide reasonable suggestions in terms of aesthetics, practicality, etc., so as to make indoor decoration projects safer and more perfect. The quality evaluation of interior decoration design is a classical multiple attribute group decision making (MAGDM) problem. This paper extends the EDAS method to the 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs). On the basis of the original EDAS method, 2-tuple linguistic Pythagorean fuzzy EDAS (2TLPF-EDAS) method based on the Hamming distance and Euclid distance is built for MAGDM. The information entropy method is used to obtain the weight information based on the score function and accuracy function under 2TLPFSs. Finally, a case study for quality evaluation of interior decoration design show that the new method proposed in this paper is reasonable.

Quality Risk Evaluation of Urban Rail Transit Construction Based on AHP–FCE Method

The demand for urban transport is increasing globally, and urban rail transit is an important infrastructure for meeting this demand. The objectives of this study were to effectively control and prevent all types of risks in the construction of metro projects and improve the quality and safety control of urban metro project construction. First, 20 index factors were selected from the five dimensions of “man–machinery–materials–methods–environment” and constructed an index system for assessing urban metro construction quality risks. Second, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) methods were used to comprehensively evaluate the construction quality risks of subway projects, and the weights of the secondary indices were determined. Finally, the importance of secondary indicators was evaluated using the integrated AHP–FCE method, and the model was applied to engineering practice for validation. The results indicated that the comprehensive AHP–FCE method has good adaptability and rationality and has practical application value for metro project construction quality and safety risk assessment. It can help prevent urban metro construction quality accidents and provides a novel idea for metro project construction quality risk assessment.

A STUDY ON INTERNATIONAL COMMUNICATION STANDARDS AND PERFORMANCE STANDARDS FOR SMART WATER QUALITY SENSORS

The world is now building an artificial intelligence (AI) water quality management system to detect water quality accidents at an early stage and predict water quality vulnerable areas in advance beyond measuring the water quality. In other words, by applying big data analysis and artificial intelligence technology to the conventional water quality measurement system that monitors water quality in real time, an artificial intelligence-based water quality measurement and water quality prediction system is built at the same time, and drones and unmanned ships are also introduced. It means implementing water quality management. Water quality accident prediction based on artificial intelligence measures water quality throughout the site of use through intelligent spatial analysis based on the integrated water quality database. On the other hand, the location of the site detected through artificial intelligence is displayed on the comprehensive monitoring screen, and special management such as on-site monitoring, replacement of consumables, and maintenance is carried out to prevent water quality accidents. In particular, the prediction accuracy of artificial intelligence is to create an algorithm for predicting future values by learning the characteristics and patterns of accumulated data. It depends on the function of the smart sensor itself. However, until now, there has been no international standard for smart sensors, so it was difficult to establish system interlocking or modularization for each manufacturer and site. Therefore, we present the most important standard communication standards for smart water quality sensors in the field and international standard performance specifications for smart sensors, and this research data is provided to all organizations engaged in water quality around the world for water quality measurement and prediction system data system for AI application.

Evaluation of Priority Control District Metered Area for Water Distribution Networks Using Water Quality-Related Big Data

Partitioning methodologies such as district metered areas (DMAs) are being applied to the stable maintenance of water distribution network systems in normal conditions such as daily operation and abnormal conditions such as water quality and leakage accidents. However, management and evaluation through the use of existing DMAs generally only have the primary goal of stable water quantity and pressure management. Therefore, the methodology can be limited to achieving the direct effects of water quality parameters such as decreased water age, proper management of residual chlorine, and decreased water quality complaints. This study uses a methodology for determining and prioritizing water quality-oriented Priority Control District Metered Areas (PCDMAs) for stable water quality management to respond to the recent large-scale rusty (red) water crisis in Korea. First, 4 evaluation criteria and 11 evaluation indicators were derived using various water quality-related structured data (water quality measurement data, pipeline data, etc.) and unstructured data (water quality complaints, etc.) based on the Geographic Information System (GIS). A comprehensive prioritization assessment was carried out with multi-criteria decision-making methods based on the analytic hierarchy process. As a result, particular indicators of complaint of water quality and the existence of vulnerable facilities (hospitals, school, etc.) were analyzed as the top five priorities, and it was shown that to be important criteria in determining water quality-oriented PCMDAs. Finally, the proposed methodology was applied to the B metropolitan city of the Republic of Korea, and the evaluation results of all the districts were derived and analyzed. The study shows that the data-based water distribution network PCDMAs selection methodology can be used as a decision-making tool to improve the accuracy and reliability of the operation and management (O&M) of the water distribution operator’s water distribution network. In future research, it will be necessary to evaluate PDDMA with detailed data related to the pipe deterioration (buried environment, the condition of internal/external of the pipe, etc.), which had a significant threshold due to data limitations. And it would be possible to make a real-time evaluation of PCDMA with the real-time water quality test data.

Development of a short-term water quality prediction model for urban rivers using real-time water quality data

Abstract We developed a classification model and a real-time prediction model for short-term dissolved oxygen (DO) at the junction of the Han River in Anyangcheon, where water quality accidents occur frequently. The classification model is an analysis model that derives the main factors affecting DO changes in the Anyangcheon mobile water quality monitoring network using decision tree, random forest, and XGBoost. The model identified the key factors affecting DO changes to be electrical conductivity, cumulative precipitation, total nitrogen, and water temperature. Random forest (sensitivity, 0.9962; accuracy, 0.9981) and XGBoost (sensitivity, 1.0000; accuracy, 0.9822) showed excellent classification performance. The real-time prediction model for short-term DO that we developed adopted artificial neural network (ANN), long short-term memory (LSTM), and gated recurrent unit (GRU) algorithms. LSTM (R2 = 0.93 − 0.97, first half; R2 = 0.95 − 0.96, second half) and GRU (R2 = 0.94 − 0.98, first half; R2 = 0.96 − 0.98, second half) significantly outperformed ANN (R2 = 0.64 − 0.86). The LSTM and GRU models we developed used real-time automatic measurement data, targeting urban rivers that are sensitive to water quality changes and are waterfront areas for citizens. They can quickly reflect and simulate short-term, real-time changes in water quality compared with existing static models.

Design of Fully Intelligent Quality Error Prevention System for Tobacco Production Line Based on Configuration Software and PLC Program

Aiming at the problems of wrong brand, mixed batch and wrong transmission of electronic parameter information in the production of cut tobacco of different brands in the tobacco industry, a fully intelligent quality error prevention system based on WinCC configuration software and PLC distributed control program is designed. The information of the production and manufacturing execution system in the general control room and the brand, batch and other information stored in the PLC of the bottom electric control cabinet is compared and verified instead of manual self-inspection. If the information is consistent, production is allowed. Otherwise, the equipment locks itself and sends alarm feedback. The design and application of the system realize the automatic error prevention of process equipment and the implementation accuracy of production control parameters, to ensure that the production process meets the requirements of process technology, effectively avoid major quality accidents, and finally guarantee the product quality.

Application Research on Extreme Learning Machine in Rapid Detection of Tool Wear in Machine Tools

In order to put an end to the product quality accidents caused by cutting tool breakage or severe wear in machining process, the paper explored an ELM model detection method based on voice recognition. In this paper, firstly it analysed the features of cutting sound signal in time-frequency domain, then discussed the extraction method of tool working state sensitive spectral energy statistical feature based on wavelet packet decomposition, and finally constructed an ELM fast detection model based on sound feature recognition. The experimental results demonstrated that the ELM detection model could achieve higher detection accuracy and faster response time. The simulation results show that the ELM model is effective and applicable in detecting tool wear with the help of sound recognition.

Research on influence factors and control methods of backfill compactness

With the accelerating process of urbanization in China, civil engineering construction develops steadily, building modeling is very different, and the trend of functional diversification is gradually revealed. As the basic process of construction engineering, the quality of earthwork backfill plays an important role in engineering construction. If the quality of the backfill cannot meet the design requirements, the surface subsidence will affect the appearance of the building and cause quality defects, and the insufficient bearing capacity and uneven compaction of the backfill will cause quality accidents such as the inclination of the main structure or structural cracking. In this paper, taking a certain engineering earthwork backfill project as an example, through the dismantling of the construction process of backfill, from the source of backfill soil to the control of backfill quality process, using the measured data to analyze and study the factors affecting the compactness of backfill. The results show that the main factors affecting the compactness of backfill are soil particle size, moisture content, compaction thickness and compaction times. Through the experimental study, the targeted quality control measures are put forward to ensure that the overall quality of the construction project meets the design requirements.

Statistical Analysis and Risk control of Civil Engineering Safety Management Accidents

The management of civil construction safety must start from understanding the causes of construction safety accidents. For this reason, experts and scholars at home and abroad have conducted a lot of investigation and research, and have come up with a series of good analysis theories of the causes of construction safety accidents. This article aims to study the statistical analysis and risk control of civil construction safety management accidents. This paper is based on the safety risk assessment model of construction projects, and uses it to discover potential construction risk factors. The experiment in this paper mainly USES statistical analysis method to estimate the probability of each possible event by observing the occurrence times of each potential construction safety risk. Experimental data shows that construction safety risks are mainly caused by certain uncertain reasons during the construction process, and then the future state of the construction of the project can be accurately judged based on historical data or statistical data. The results show that after the classification of 400 accidents occurred in the investigation area, 150 of them fell from high places and 140 people died. 87 electric shocks, 75 deaths; 73 collapses, 65 deaths; Objects struck 38 times, killing 22 people; 43 mechanical injuries, 36 persons. It is the government’s responsibility to reduce construction safety and quality accidents, and it is also the minimum requirement of construction enterprises. The safety issues of civil construction must be strictly managed.

Preventive Detection Method for Leakage of Sheet Tobacco Dryer

Content Sheet Tobacco Dryer is an important and key equipment in the tobacco making workshop of cigarette factory, its function is mainly to expand and dry cut tobacco, and the drying process is mainly carried out by the sheet heating plate in the drum through heat conduction, while the energy of the sheet heating plate mainly comes from the steam inside, and there is a risk of leakage through continuous operation of the sheet and its accessories, once leakage occurs, it will cause quality accidents of tobacco products, and leakage can be well prevented and eliminated through regular leakage detection.

Root cause analysis approach based on reverse cascading decomposition in QFD and fuzzy weight ARM for quality accidents

Quality accidents (QAs) of high frequencies in various fields have caused large economic and reputational losses to manufacturers, and identification of the root causes of vicious QAs is a top priority and a major challenge for manufacturers. Especially in the era of big data, the large number of data could be collected from the product life cycle easily, these high-dimensional big data always bear so many un-correlation noise information, which has caused serious problem. The accurate and heuristic root cause analysis for QAs is an important and challenging task in exploring this mechanism due to the fuzzy and vague nature of the collected big quality data. Thus, in this study, a heuristic root cause identification solution based on the fuzzy weighted association rule mining (FWARM) for QAs is proposed. First, the formation mechanism of QAs and big quality accident data is expounded, and a big data driven root cause analysis framework of QAs is presented with the aid of reverse cascading decomposition in Quality Function Deployment (QFD). Second, principal component analysis (PCA) is adopted to eliminate redundancy and reduce data dimension of original process feature parameters from raw data in low-dimensional space so that the key variables as the potential root cause candidates can be extracted. Third, considering the fuzzy mechanism and vague nature of big data, a heuristic root cause identification approach based on FWARM is established, and the weight of nodes on the accident-relevance tree is computed by fuzzy weight coefficient. Finally, the proposed approach is verified with a case study of a quality accident analysis of a washing machine. Results shows that the proposed approach is conducive to heuristically identify the root causes of QAs in the context of big data.

Time-varying Reliability Analysis of Long-span Continuous Rigid Frame bridge under Cantilever Construction Stage based on the Monitored Strain Data

Abstract: In general, the material properties, loads, resistance of the prestressed concrete continuous rigid frame bridge in different construction stages are time-varying. So, it is essential to monitor the internal force state when the bridge is in construction. Among them, how to assess the safety is one of the challenges. As the continuous monitoring over a long-term period can increase the reliability of the assessment, so, based on a large number of monitored strain data collected from the structural health monitoring system (SHMS) during construction, a calculation method of the punctiform time-varying reliability is proposed in this paper to evaluate the stress state of this type bridge in cantilever construction stage by using the basic reliability theory. At the same time, the optimal stress distribution function in the bridge mid-span base plate is determined when the bridge is closed. This method can provide basis and direction for the internal force control of this type bridge in construction process. So, it can reduce the bridge safety and quality accidents in construction stages.

Variation of Ground Temperature along the Stratum Depth in Ice-rich Tundra of Hinggan Mountains Region, NE China

A pile foundation in a permafrost region is in a negative-temperature environment, so concrete is affected by the negative temperature of the surrounding soil. It not only affects the formation of concrete strength but also leads to engineering quality accidents in serious cases. With the support of the two permafrost bridge projects of the national highway from Beijing to Mohe in the Greater Khingan Mountains region, a systematic remote dynamic monitoring method for ground temperature in ice-rich tundra is proposed. Based on the actual measurement of temperature at different strata depths and the comprehensive consideration of surface temperature, terrestrial heat flux and other parameters, the ground temperature profile evolution in relation to depth in Greater Khingan was established. The theoretical ground temperature profile curve is similar to the measured profile. The results show that the variation trends of ground temperatures in relation to the strata depth at different monitoring sites is similar, and all show seasonal variation: From June to November, the ground temperature at different depths tends to be constant. From December to May, the ground temperature at any depth within the range of 0 to 5.5 m follows the curve of the cosine function. Below 5.5 m, the earth temperature no longer varies with depth. The research results can be used as reference for pile foundation construction in a negative-temperature environment in ice-rich tundra.

Research on pavement quality control based on bayes’ theorem

In order to meet the fine construction requirements of municipal engineering, improve the pavement stone paving technology level. Through the statistics of municipal engineering sidewalk construction common technical quality problems. Established the pavement surfacing technology quality control index system, and establish the quality control of causal relationship between spatial topology relationship structure model, using the mature of bayes’ theorem to the pavement stone pavement quality control study, forecast the quality of each control factor to influence the quality of the pavement stone pavement, the size of the causal backstepping method is used to analyze mechanism of quality control factor, finally, complete quality control evaluation by mutual information theory, find out the biggest quality control factor. Taking the project of yanjiang avenue (minsheng road to qingchuan bridge) in wuhan as an example, this paper applies bayes’ theorem and mutual information theory to the research of municipal pavement quality control. The results show that the probability of stone pavement quality accidents in this project is 2.83%, the roadbed quality control is not in place is the largest quality control factor affecting the fine construction of this project.

Research on Engineering Quality Management Based on PDCA Cycle

With the increase in the number of construction companies and construction personnel, the occurrence of engineering quality accidents has also increased. Therefore, the management of project quality is very important. This article mainly introduces the connotation of construction quality and construction quality management, analyzes the factors influencing construction quality and the characteristics of construction quality control, and applies PDCA circulation principles to project quality management, hoping to help improve the level of project management.

Super-low friction and lightweight hydraulic cylinder using multi-directional forging magnesium alloy and its application to robotic leg

One of the most important missions for robots is to operate in severe environments, and these situations require robots to have ‘toughness’ which can overcome large shocks, degraded communication quality, unexpected condition, and other critical accidents. Although there are many kinds of approaches to realize tough robotic systems, developing a tough actuators is one of the key technologies for them. We focus on hydraulic actuators and attempt to develop a tough robotic actuator with greater toughness than the electromagnetic actuators used in conventional robotic systems. In general, hydraulic actuators have enough toughness for severe environments, but their controllability and lightness are insufficient for robot systems. Herein, we propose novel hydraulic actuators that realizes lightweight with a multidirectional-forging magnesium alloy and have high controllability by low friction pistons. Prototypes were developed to examine the fundamental characteristics of the actuators and compare the two approaches for the low-friction pistons: one is based on a packing mechanism using an elastic restoring pressure, and the other utilizes a fluid-bearing technology. After basic experiments, the prototype was applied to a robotic leg to verify their potential in actual robotic systems. The robotic leg successfully jumped 260 mm in height with 21 MPa.