Operational time-series data modeling via LSTM network integrating principal component analysis based on human experience

Today’s information technologies involve increasingly intelligent systems, which come at the cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring-point and long-term data which make equipment health prediction a “big data” problem. It is difficult to extract information from such condition monitoring data to accurately estimate or predict health statuses. Deep learning is a powerful tool for big data processing that is widely utilized in image and speech recognition applications, and can also provide effective predictions in industrial processes. This paper proposes the Long Short-term Memory Integrating Principal Component Analysis based on Human Experience (HEPCA-LSTM), which uses operational time-series data for equipment health prognostics. Principal component analysis based on human experience is first conducted to extract condition parameters from the condition monitoring system. The long short-term memory (LSTM) framework is then constructed to predict the target status. Finally, a dynamic update of the prediction model with incoming data is performed at a certain interval to prevent any model misalignment caused by the drifting of relevant variables. The proposed model is validated on a practical case and found to outperform other prediction methods. It utilizes a powerful deep learning analysis method, the LSTM, to fully process big condition monitoring series data; it effectively extracts the features involved with human experience and takes dynamic updates into consideration.     

双时基频率校准电路

提供精确的时间基准是精密仪器和高精度设备计时和工作的关键技术之一。文中采用两套晶振电路，通过分频产生高频和低频两个频率信号，采用编码的方法对两个频率信号在每一个时钟周期内进行动态校核，只有两个晶振的频率在允许的精度范围内，或同时增大（缩小）相同的倍数，校核后频率信号才是正确的，且能给系统提供精确的时间基准。该方法能有效防止系统的时钟周期因意外的原因伸长或缩短。整个电路可以作为精密仪器或高精度设备的一个模块电路。     

A versatile data acquisition system for time resolved X-ray scattering using gas proportional detectors with delay line readout

A data acquisition system for time resolved X-ray scattering experiments using linear, quadrant or area gas proportional detectors with delay line readout based on commercially available hardware (National Instruments) is described. The system can easily be configured for recording data from point detectors (e.g. photomultipliers and photodiodes) and/or ancillary data only. Applications involving measurements with two different types of time to digital converters illustrate the features and performances of the system.     

A time series bootstrap procedure for interpolation intervals

A sieve bootstrap procedure for constructing interpolation intervals for a general class of linear processes is proposed. This sieve bootstrap provides consistent estimators of the conditional distribution of the missing values, given the observed data. A Monte Carlo experiment is used to show the finite sample properties of the sieve bootstrap and finally, the performance of the proposed method is illustrated with a real data example.     

Cycle detection using a stack

We present an algorithm for detecting periodicity in sequences produced by repeated application of a given function. Our algorithm uses logarithmic memory with high probability, runs in linear time, and is guaranteed to stop within the second loop through the cycle. We also present a partitioning technique that offers a time/memory tradeoff. Our algorithm is especially well suited for sequences where the cycle length is typically small compared to the length of the acyclic prefix.     

Developing Cost Response Models for Company-Level Cost Flow Forecasting of Project-Based Corporations

The difficulty in applying the standard curve (S-curve) and cost-schedule integration (CSI) techniques for company-level cost flow forecasting in a project-based industry is the prerequisite of forecasting future unknown individual projects and contract classifications. By analyzing cost flows at the company level through a pool of macroeconomic and internal financial data, this paper proposes an innovative approach to firm-specific model estimation. First, a series of data transformations introduce linear relationships between cost, macroeconomic, and internal financial variables. Second, multivariate regression analysis is employed for initial model building. Third, for the purposes of model restructuring, a subsequent application of Yule–Walker estimates and incomplete principal component analysis is used. This paper uses a sample of four project-based construction firms to demonstrate model performance. Using this methodology, mean absolute percentage error (MAPE) values of the forecasting models range from 0.27 to 0.60%. As such, the transformed cost, macroeconomic, internal financial data could strongly predict company-level cost flow forecasting. While converting the predicted cumulative cost data to periodic cost flows, the MAPE values were augmented, ranging from 7.04 to 17.55%, thus, requiring future research.     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.     

压电量测系统漏电影响分析

本文通过对压电量测系统等效电路图的逐步简化,得出矩形脉冲信号的漏电方程;并对系统在各种情况下的时间常数,漏电相对误差进行了计算,最后就系统在校准和现场测试中经常碰到的几种情况,进行了定量估算,从而解决了压电量测系统在使用中的一些具体问题。     

高效防气防砂一体化管柱的研制与应用

为解决文南油田高气液比井出砂易造成卡泵的问题,研制了高效防气防砂一体化管柱。该管柱主要由闭式气锚、重力式防气装置和激光割缝筛管3部分组成。闭式气锚的分离作用消除了气体对抽油泵的影响,提高了泵效;重力防气装置利用液气分离原理和高烟囱原理进行液气分离,液流回流时间可达10min,排气最高压差可达0.2MPa;经激光割缝筛管过滤后的液体含砂粒外径小于0.05mm。该管柱在文南油田现场应用16井次,累计增液6000t,增油2717t,平均单井泵效提高7%。     

Theoretical Investigation of Time Suboptimal Control of Industrial Manipulators Along Specified Paths

A method for the time suboptimal control of an industrial manipulator from an initial position and orientation to a final position and orientation as it moves along a specified path is proposed. Nonlinear system equations that describe the manipulator motion are linearized at each time step along the path. A method which gives the control inputs (joint angular velocities) for time suboptimal control of the manipulator is developed. In the formulation, joint angular velocity and acceleration limitations are also taken into consideration. A six degree of freedom elbow type manipulator is used in numerical examples to verify the method developed.