PCA-based method of soft fault detection and identification for the ongoing commissioning of chillers

Role of green finance in renewable energy development in the tourism sector

An assessment of socioeconomic indicators and energy consumption by considering green financing

This 5th International High Performance Buildings Conference is one of 3 Purdue Conferences presented on the same CD-ROM , held at Purdue, West Lafayette (Indiana), USA. 91 papers were presented on the following themes: building envelope systems, indoor environment and air quality, visual and thermal comfort, building energy modeling and simulation, building materials, lighting and daylighting, building performance monitoring and diagnostics, HVAC systems, mixed-mode cooling and natural ventilation, building controls, net-zero energy building design, renewable and sustainable energy technologies for buildings, and related case studies on high performance building design and operation. The two other Purdue Conferences presented on the CD-ROM are: the 24th International Compressor engineering Conference (132 papers), and the 17th International Refrigeration and Air-Conditioning Conference (251 papers).

2018 Purdue Conferences. 5 th International High Performance Buildings Conference at Purdue.

Does green finance and renewable energy promote tourism for sustainable development: Empirical evidence from China

Green technological innovation, green finance, and financial development and their role in green total factor productivity: Empirical insights from China

The invention discloses a parking air conditioning system. The parking air conditioning system is in communication connection with a mobile phone terminal and comprises a car networking terminal module and an air conditioning equipment module. The car networking terminal module comprises a processor, a wireless communication module, a voltage collecting module, a temperature and humidity collecting module and a relay module, wherein the wireless communication module is connected with the processor; the voltage collecting module is connected with the processor and used for collecting power supply voltage of the parking air conditioning system and transmitting the information about the power supply voltage to the processor; the temperature and humidity collecting module is connected with the processor and used for collecting the temperature and humidity inside a car and the temperature outside the car and transmitting the information about the temperature and humidity inside the car and the temperature outside the car to the processor; and the relay module is connected with the processor. The air conditioning equipment module comprises a fan and one or two PTC heaters, wherein the fan is connected with the relay module, and the PTC heaters are connected with the relay module. By virtue of an original air conditioning system of the car, corresponding equipment is additionally arranged, so that the functions of ventilation, air exchange, purification, preheating, freeze prevention and the like are achieved, the air quality inside the car is effectively improved, and the driving environment is improved.

Parking air conditioning system

An improved approach of fault detection for chiller sensors is presented based on the sensitivity analysis for the original data set used to train the Principal Component Analysis (PCA) model. Sensor faults are inevitable due to the aging, environment, location and so on. Meanwhile, because of the wide range of operational conditions, the fault of a certain sensor is very difficult to be directly detected by its own historical data. PCA is a multivariate data-based statistical analysis method and it is very useful for the sensor fault detection in HVAC&R. The undetectable zone of a certain sensor by Q-statistic is derived from the definition of Q-statistic which is usually employed as a boundary to detect the sensor fault situation. Due to the similar style between Q-statistic and Hawkins’ 2 H T , the undetectable zone by Hawkins’ 2 H T is also obtained. Undetectable zone is a predictive index to indicate the detectability of different sensors by different statistics. Since undetectable zone is the character of the original training data set, it can indicate the quality for the selected training data. One field data set is employed to validate the presented approach. Results show that the undetectable zone of a certain sensor by Q-statistic is quite different from that by Hawkins’ 2 H T . Therefore, the undetectable zone can be used to improving the performance of PCA-based chiller sensor fault detection by choosing different fault detection statistics with less undetectable zone for different sensor.

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Jiani Liu

Papers

Green technological innovation, green finance, and financial development and their role in green total factor productivity: Empirical insights from China

Parking air conditioning system

Improving the Performance of PCA-Based Chiller Sensor Fault Detection by Sensitivity Analysis for the Training Data Set