Fault detection method for organic rankine cycle system based on generalized cross-entropy-dpca algorithm
A fault detection and circulation system technology, applied in design optimization/simulation, special data processing applications, etc., can solve problems such as false positives and false positives
Active Publication Date: 2020-03-31
TAIYUAN UNIV OF TECH
View PDF3 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0005] The present invention provides an organic Rankine cycle based on the generalized cross-entropy-DPCA algorithm in order to solve the problem that the traditional DPCA method will have false positives and negative negatives because the ORC system does not obey the Gaussian distribution and has many variables. System Fault Detection Method
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0072] The present invention will be further described below in conjunction with specific examples.
[0073] Step 1: Collect data X∈R under normal working conditions N×m As normal data, and it is normalized, where N represents the number of samples, and m represents the number of variables.
[0074] The ORC system is mainly composed of six main components: evaporator, condenser, working fluid pump, expander, and valves. In the evaporator model, the inlet mass flow rate and enthalpy value are provided by the working medium pump, and the outlet mass flow rate is the mass flow rate at the inlet of the expander. Similarly, the inlet mass flow rate and enthalpy value of the condenser are provided by the expander, and the outlet mass flow rate is the inlet mass flow rate of the pump, and then the models of each component are connected in series to obtain the nonlinear model of the entire ORC system as shown in the following formula:
[0075]
[0076]
[0077] in The parame...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses an organic Rankine cycle system fault detection method based on a generalized cross-entropy-DPCA (Dynamic Principal Component Analysis) algorithm, and relates to the field of non-Gaussian random system fault diagnosis. The generalized cross-entropy-DPCA algorithm is mainly utilized; after normalization processing is carried out, a generalized Gaussian kernel function is adopted to replace a Gaussian kernel function to define the cross-entropy again to obtain a generalized cross-entropy-DPCA performance index, and the performance index is optimized to solve an optimal direction matrix; meanwhile, a confidence coefficient [Alpha]is set to solve control limits for a probability density function integral; after the direction matrix is solved, fault data under a fault working condition is adopted and is subjected to the normalization processing; then, the fault data is calculated by the direction matrix to obtain the SPE statistical magnitude and the T2 statistical magnitude of the fault data model; and the SPE statistical magnitude and the T2 statistical magnitude are compared with the calculated control limits to detect whether the system fails or not. By use of the organic Rankine cycle system fault detection method, a generalized Gaussian kernel is adopted, the method exhibits better universality, and in addition, fault detection accuracy is improved.
Description
technical field [0001] The invention relates to the field of non-Gaussian random system fault detection, in particular to an organic Rankine cycle system fault detection method based on the generalized mutual entropy-DPCA algorithm. Background technique [0002] Energy saving and emission reduction, and improving energy utilization have become important measures to maintain sustainable development. The low-temperature waste heat power generation system converts the waste heat of flue gas in the boiler tail flue into mechanical energy through Organic Rankine Cycle (ORC, Organic Rankine Cycle), and then into high-grade electric energy, which plays an important role in energy saving, water saving, and reduction of harmful gas emissions. significance. As the system runs for a long time, various components in the system may fail, resulting in a decrease in system efficiency and performance, resulting in huge economic losses and even a serious threat to personal safety. Therefor...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20
CPCG06F30/20
Inventor 任密蜂张彦云程兰续欣莹梁艳
Owner TAIYUAN UNIV OF TECH