Prediction and Analysis of Elevator Traffic Flow under the LSTM Neural Network

Elevators are essential components of contemporary buildings, enabling efficient vertical mobility for occupants. However, the proliferation of tall buildings has exacerbated challenges such as traffic congestion within elevator systems. Many passengers experience dissatisfaction with prolonged wait times, leading to impatience and frustration among building occupants. The widespread adoption of neural networks and deep learning technologies across various fields and industries represents a significant paradigm shift, and unlocking new avenues for innovation and advancement. These cutting-edge technologies offer unprecedented opportunities to address complex challenges and optimize processes in diverse domains. In this study, LSTM (Long Short-Term Memory) network technology is leveraged to analyze elevator traffic flow within a typical office building. By harnessing the predictive capabilities of LSTM, the research aims to contribute to advancements in elevator group control design, ultimately enhancing the functionality and efficiency of vertical transportation systems in built environments. The findings of this research have the potential to reference the development of intelligent elevator management systems, capable of dynamically adapting to fluctuating passenger demand and optimizing elevator usage in real-time. By enhancing the efficiency and functionality of vertical transportation systems, the research contributes to creating more sustainable, accessible, and user-friendly living environments for individuals across diverse demographics.

LiMo 2040 Sustainable urban Living and Mobility Concept-Elevator System

How can individual mobility in urban areas be maintained alongside scooters and cargo bikes if conventional vehicles are foreseeably no longer allowed to enter city centers?And how can urban living be combined with individual mobility in a sustainable and socially acceptable way?LiMo-2040 attempts to provide answers to these questions.It follows a holistic approach according to the criteria:As light,as compact and as simple(cost-effective)as possible.Modular e-vehicle concepts(consisting of vehicle cabin and chassis)are known,but have not yet been thought through to their logical conclusion.The LiMo cabin is not only a vehicle cabin,but also a component of a modern high-rise apartment.It therefore requires no parking space and combines urban living and individual mobility sustainably and cost-effectively.If a vehicle is needed,an app can be used to book a chassis that comes along autonomously and waits until the cabin,including its occupants,travels down a sophisticated rail system,docks and autonomously heads for the desired destination.

Nonlinear Pushover Analysis of the Influences on RC Footing for the External Elevator Well

In contemporary society, reducing carbon dioxide emissions and achieving sustainable development are paramount goals. One effective approach is to preserve existing RC (Reinforced Concrete) buildings rather than demolishing them for new construction. However, a significant challenge arises from the lack of elevator designs in many of these existing RC buildings. Adding an external elevator becomes crucial to solving accessibility issues, enhancing property value, and satisfying modern residential buildings using convenient requirements. However, the structural performance of external elevator wells remains understudied. This research is designed by the actual external elevator project into existing RC buildings in Jinzhong Rd, Shanghai City. Specifically, this research examines five different external elevator wells under nonlinear pushover analysis, each varying in the height of the RC (Reinforced Concrete) footing. By analyzing plastic hinge states, performance points, capacity curves, spectrum curves, layer displacement, and drift ratio, this research aims to provide a comprehensive understanding of how these structures of the external elevator well respond to seismic events. The findings are expected to serve as a valuable reference for future external elevator projects, ensuring the external elevator designs meet the seismic requirements. By emphasizing seismic resistance in the design phase, the research aims to enhance the overall safety and longevity of external elevator systems integrated into existing RC buildings.

Parameter Study on a Composite Sound-Absorbing Structure Liner in Elevator Shafts

With the growing global environmental awareness,the development of renewable and green materials has gained increased worldwide interest to substitute conventional materials and are favorable for sustainable economic development.This paper proposed a novel eco-friendly sound absorbing structure(NSAS)liner for noise reduction in elevator shafts.The base layer integrated with the shaft walls is a damping gypsum mortarboard,and a rock wool board and a perforated cement mortarboard are used to compose the NSAS.Based on the acoustic impedance theory of porous materials and perforated panels,the sound absorption theory of the NSAS was proposed;the parameter effects of the rock wool board(flow resistivity,porosity,structure factor)and perforated panel(perforated rates,thickness,density,perforated diameter)on NSAS absorption were discussed theoretically for absorption improvement,and experiments were also conducted.Numerical results showed that the perforation rate,the thickness of the perforated plate,and the porosity,flow resistance,and volume density of the rock wool board played a key issue in the absorption performances of the NSAS.Experiments verified the accuracy of the proposed theoretical model.Wideband sound absorption performance of the NSAS at frequencies between 500–1600 Hz was achieved in both numerical analysis and experiments,and the sound absorption coefficient was improved to 0.72 around 1000 Hz after parameter adjustments.The NSAS proposed in this paper can also be made of other renewable materials with preferable structure strength and still has the potential to broaden the absorption bandwidth.It can provide a reference for controlling the elevator shaft noise.

Two-Dimensional Images of Current and Active Power Signals for Elevator Condition Recognition

In this paper, an improved two-dimensional convolution neural network(2DCNN) is proposed to monitor and analyze elevator health, based on the distribution characteristics of elevator time series data in two-dimensional images. The current and effective power signals from an elevator traction machine are collected to generate gray-scale binary images. The improved two-dimensional convolution neural network is used to extract deep features from the images for classification, so as to recognize the elevator working conditions. Furthermore, the oscillation criterion is proposed to describe and analyze the active power oscillations. The current and active power are used to synchronously describe the working condition of the elevator, which can explain the co-occurrence state and potential relationship of elevator data. Based on the improved integration of local features of the time series, the recognition accuracy of the proposed 2DCNN is 97.78%, which is better than that of a one-dimensional convolution neural network. This research can improve the real-time monitoring and visual analysis performance of the elevator maintenance personnel, as well as improve their work efficiency.

The Development of Using Elevators in Different Buildings

Elevators are one of the most important elements of vertical communication used in buildings.Especially in recent times,where high and high rise buildings have become a modern architectural phenomenon and the spread of architecture has become a feature of the age.Hence,the research discusses the technique of installing elevators in buildings.A general introduction to elevators and their types will be discussed,as well as a historical overview of the beginning of the idea of the elevator and the first buildings that were used.The technique of installing the elevator inside the building explained with the images shown components elevator.Also it will mention several speeds of modern elevators used in buildings,the world’s fastest elevator,ultra-rope technology and the reasons for choosing this technique in elevator components in high-rise buildings which may be used in the space elevator that will connect earth and space.As well it shows features of the wire used in the elevators of the Burj-Khalifa,the highest skyscraper in the world.Then it mentions a number of the most recent and newest elevators in the world,then research results and references.

Clinical features and surgical treatment of double elevator palsy in young children

AIM： To describe the clinical features of congenital double elevator palsy（CDEP） and to evaluate various surgical outcomes between the standard Knapp and augmented Knapp procedures, based on improvements in primary eye position and ocular motility.METHODS： Twenty-two patients with CDEP at Shanghai Children＇s Hospital were enrolled from July 2014 to January 2018. The forced duction test（FDT） was negative in 21 patients, aged 8 mo to 12 y（mean 5.4 y）. Patients were divided into two treatment groups： 16 patients underwent the standard Knapp procedure（group A）, with or without horizontal squint procedure; and 5 patients underwent the augmented Knapp procedure（Foster procedure; group B）. One patient underwent inferior rectus recession in the affected eye and superior rectus recession in the sound eye because of a positive FDT. The pre-and postoperative vertical deviations in the primary position and ocular motility were compared in the two groups.RESULTS： Twenty-one eyes of the 22 patients（95%） were aligned within 10 prism diopters（PD）, and all patients（100%） reached ≥25% elevation improvement after surgery. The average corrected vertical deviation in group B was statistically better than that of group A. For group A, the vertical deviation in the primary position decreased from 24.75Δ±8.35Δ to 4.56Δ±8.07Δ after surgery, for an improvement of 23.06Δ±6.51Δ（P〈0.05）. In group B, the decrease was from 35.00Δ±5.00Δ（range 30Δ-40Δ） to 1.00Δ±2.24Δ, for an improvement of 34.00Δ±4.18Δ（P〈0.05）. There were significant differences between the pre-and postoperative elevation in each group（group A, P〈0.05; group B, P〈0.05）. The average scale of improved elevation in group B（1.80±0.45） was not significantly better than that of group A（1.69±0.87; Z=-0.732, P=0.548）. The average follow-up periods lasted 21 mo in group A and 18 mo in group B.CONCLUSION： For vertical deviations 〈30Δ, the standard Knapp procedure can be chosen. For deviations greater than 30Δ-40Δ, the Foster procedure should be chosen. Because of our early interference, the inferior rectus（IR） muscle did not show mechanical restriction. Monocular elevation deficiency（MED） should be diagnosed early so that complications will be reduced and the procedure will be easier for the surgeon.

Research on Applying Bluetooth to an Elevator Wireless Control System

Compared with other elevator control systems, the wireless control system has many advantages such as easy to install and maintain. Bluetooth is a new technology of short-range wireless communication, and the idea of applying Bluetooth to the elevator wireless control system is expected to get wide application. In this paper, a wireless control prototype system is introduced, and the experiments of this system proved the feasibility of this idea.

Prediction of elevator traffic flow based on SVM and phase space reconstruction

To make elevator group control system better follow the change of elevator traffic flow (ETF) in order to adjust the control strategy,the prediction method of support vector machine (SVM) in combination with phase space reconstruction has been proposed for ETF.Firstly,the phase space reconstruction for elevator traffic flow time series (ETFTS) is processed.Secondly,the small data set method is applied to calculate the largest Lyapunov exponent to judge the chaotic property of ETF.Then prediction model of ETFTS based on SVM is founded.Finally,the method is applied to predict the time series for the incoming and outgoing passenger flow respectively using ETF data collected in some building.Meanwhile,it is compared with RBF neural network model.Simulation results show that the trend of factual traffic flow is better followed by predictive traffic flow.SVM algorithm has much better prediction performance.The fitting and prediction of ETF with better effect are realized.

Finding Main Causes of Elevator Accidents via Multi-Dimensional Association Rule in Edge Computing Environment

In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.

COMPUTATIONAL FLOW RATE FEEDBACK AND CONTROL METHOD IN HYDRAULIC ELEVATORS

The computational flow rate feedback and control method, which can be used in proportional valve controlled hydraulic elevators, is discussed and analyzed. In a hydraulic elevator with this method, microprocessor receives pressure information from the pressure transducers and computes the flow rate through the proportional valve based on pressure-flow conversion real time algorithm. This hydraulic elevator is of lower cost and energy consumption than the conventional closed loop control hydraulic elevator whose flow rate is measured by a flow meter. Experiments arc carried out on a test rig which could simulate the load of hydraulic elevator. According to the experiment results, the means to modify the pressure-flow conversion algorithm are pointed out.

Analysis and control of vibration of ropes in a high-rise elevator under earthquake excitation

In this research, the vibration of elevator ropes, including the main rope and compensation rope are investigated simultaneously in a high-rise elevator system under earthquake excitation. Moreover, the paper presents a new control method to restrain the sway of both ropes. This study considers varying rope lengths during elevator operation which cause other system parameters such as natural frequency, and damping ratio to be time-variant variables. The dynamics of the ropes are analyzed by solving the governing non-stationary, nonlinear equation numerically. In order to mitigate the vibration of ropes in several motion conditions, particularly upwards movement, downward movement, stopped at the lowest position, and stopped at the highest position, an active equipment is installed at the compensation sheave. The stability of the system using the controller is analyzed at four states: without disturbance and static car, without disturbance and mobile car, including disturbance and static car, and including disturbance and mobile car. The efficiency of the controller used for dampening the vibration of elevator ropes is validated by numerical simulation results.

A PID Sliding Mode Control for Ropeless Elevator Maglev Guiding System

In this paper, three different controllers are proposed and simulated for maglev guiding systems to have convenient and smooth elevator motion. The proposed controllers are PID, sliding mode, and PID sliding mode controllers. The advantages and disadvantages of the proposed controllers are discussed. Although, PID controller is fast, its response affected considerably by external disturbances. Unlike PID, the sliding mode controller is so robust, but its transient is unsuitable based on application conditions. However, an acceptable controller for ropeless elevator guiding system should guaranty the passengers safety and convenient. Consequently, the response of the system should be fast, robust, and without considerable overshoots and oscillations. These required advantages are compromised in the proposed parallel PID sliding mode controller. The affectivity of the introduced controllers for maglev guiding system is investigated through conducted simulations in MATLAB/Simulink environment. The obtained results illustrate that PID sliding mode controller is a so fast and robust controller for a ropeless elevator maglev guiding system.

Multi-objective Optimization of Multi-Agent Elevator Group Control System Based on Real-time Particle Swarm Optimization Algorithm

In order to get a globally optimized solution for the Elevator Group Control System (EGCS) scheduling problem, an algorithm with an overall optimization function is needed. In this study, Real-time Particle Swarm Optimization (RPSO) is proposed to find an optimal solution to the EGCS scheduling problem. Different traffic patterns and controller mechanisms for EGCS are analyzed. This study focuses on up-peak traffic because of its critical importance to modern office buildings. Simulation results show that EGCS based on Multi-Agent Systems (MAS) using RPSO gives good results for up-peak EGCS scheduling problem. Besides, the elevator real-time scheduling and reallocation functions are realized based on RPSO in case new information is available or the elevator becomes busy because it is unavailable or full. This study contributes a new scheduling algorithm for EGCS, and expands the application of PSO.

Intelligent Decisions Modeling for Energy Saving in Lifts:An Application for Kleemann Hellas Elevators

The present work proposes a methodological approach for modeling decisions regarding energy reduction in an elevator. This is achieved with the integration of existing as well as acquired knowledge, in a decision module implemented in the electronics of an elevator. So far, elevators do not exploit information regarding their recent usage. In the developed system decisions are driven based on information arising from monitoring the use of the elevator. Monitoring provides various records of usage which consequently are used to predict elevator’s future usage and to adapt accordingly its functioning. Till now, there are only elevators that encompass in their electronics algorithms with if then rules in order to control elevator’s functioning. However, these if then rules are based only on good practice knowledge of similar elevators installed in similar buildings. Even this knowledge which unavoidably is associated with uncertainty is not encoded in a mathematically consisted way in the algorithms. The design, the implementation and a first pilot evaluation study of an elevator’s intelligent decision module are presented. The study concludes that the presented application sufficiently reduces energy consumption through properly controlled functioning.

HYDRAULIC ACTIVE GUIDE ROLLER SYSTEM FOR HIGH-SPEED ELEVATOR BASED ON FUZZY CONTROLLER

Increase of elevator speed brings about amplified vibrations of high-speed elevator. In order to reduce the horizontal vibrations of high-speed elevator, a new type of hydraulic active guide roller system based on fuzzy logic controller is developed. First the working principle of the hydraulic guide system is introduced, then the dynamic model of the horizontal vibrations for elevator cage with active guide roller system and the mathematical model of the hydraulic system are given. A fuzzy logic controller for the hydraulic system is designed to control the hydraulic actuator. To improve the control performance, preview compensation for the controller is provided. Finally, simulation and experiments are executed to verify the hydraulic active guide roller system and the control strategy. Both the simulation and experimental results indicate that the hydraulic active guide roller system can reduce the horizontal vibrations of the elevator effectively and has better effects than the passive one, and the fuzzy logic controller with preview compensation can give superior control performance.

Elevator Simulation电梯仿真软件的应用

目前高职院校机电专业已经把电梯作为一个典型的工业案例引入到学生的PLC课堂中,但多数院校主要是通过单部电梯的实验箱模型来完成实践操作,这种电梯的实验箱具有一定的局限性,只是单部的运动,而现实生活中更多是多部电梯接收复杂的信号,同时运动载客。为了让实验案例更加接近实际生活应用,引入了Elevator Simulation电梯仿真软件,通过以太网通信连接编程计算机与电梯仿真模型机,在计算机上引入博途V14软件进行编程控制,通过Elevator Simulation电梯仿真软件对电梯进行仿真调试,不仅提高了学生的操作能力,更提升了学生的工程创造能力。

Fuzzy Optimization of an Elevator Mechanism Applying the Genetic Algorithm and Neural Networks

Considering the indefinite character of the value of design parameters and being satisfied with load-bearing capacity and stiffness, the fuzzy optimization mathematical model is set up to minimize the volume of tooth corona of a worm gear in an elevator mechanism. The method of second-class comprehensive evaluation was used based on the optimal level cut set, thus the optimal level value of every fuzzy constraint can be attained; the fuzzy optimization is transformed into the usual optimization. The Fast Back Propagation of the neural networks algorithm are adopted to train feed-forward networks so as to fit a relative coefficient. Then the fitness function with penalty terms is built by a penalty strategy, a neural networks program is recalled, and solver functions of the Genetic Algorithm Toolbox of Matlab software are adopted to solve the optimization model.

Fault Prediction of Elevator Door System Based on PSO-BP Neural Network

Nowadays, the elevator has become an indispensable means of indoor transportation in people’s life, but in recent years this kind of traffic tools has caused many casualties because of the gate system fault. In order to ensure the safe and reliable operation of the elevator, the failure of elevator door system was predicted in this paper. Against the fault type of elevator door system: elevator door opened, excessive vibration when elevator door opened or closed, elevator door did not open or closed when reached the specified level. Three fault types were used as the output of the prediction model. There were 8 reasons for the failure, used them as input. A model based on particle swarm optimization (PSO) and BP neural network was established, using MATLAB to emulation;the results showed that: PSO-BP neural network algorithm was feasible in the fault prediction of the elevator door system.

Evaluation of Home Elevator Performance Based on Extension Fuzzy Theory

It is quite difficult as to how to choose an appropriate home elevator, because the factories manufacturing home elevator are numerous and the models of production are different. Therefore, this article combines .fuzzy math with extension theory on the basis of matter element theory, extension set theory and correlation function, constructs a classical matter element and a segmentfield matter element by classifying home elevator performance and making a performance index membership zero dimension, and establishes an extension fuzzy evaluation model of home elevator performance levels. The example in this article shows that the established method is able to evaluate actual home elevator performance.