Intelligent Process Fault Diagnosis for Nonlinear Systems with Uncertain Plant Model via Extended State Observer and Soft Computing

There have been many studies on observer-based fault detection and isolation (FDI), such as using unknown input observer and generalized observer. Most of them require a nominal mathematical model of the system. Unlike sensor faults, actuator faults and process faults greatly affect the system dynamics. This paper presents a new process fault diagnosis technique without exact knowledge of the plant model via Extended State Observer (ESO) and soft computing. The ESO’s augmented or extended state is used to compute the system dynamics in real time, thereby provides foundation for real-time process fault detection. Based on the input and output data, the ESO identifies the un-modeled or incorrectly modeled dynamics combined with unknown external disturbances in real time and provides vital information for detecting faults with only partial information of the plant, which cannot be easily accomplished with any existing methods. Another advantage of the ESO is its simplicity in tuning only a single parameter. Without the knowledge of the exact plant model, fuzzy inference was developed to isolate faults. A strongly coupled three-tank nonlinear dynamic system was chosen as a case study. In a typical dynamic system, a process fault such as pipe blockage is likely incipient, which requires degree of fault identification at all time. Neural networks were trained to identify faults and also instantly determine degree of fault. The simulation results indicate that the proposed FDI technique effectively detected and isolated faults and also accurately determine the degree of fault. Soft computing (i.e. fuzzy logic and neural networks) makes fault diagnosis intelligent and fast because it provides intuitive logic to the system and real-time input-output mapping.

Compression and shearing force on kernel rupture in shelling fresh lotus seeds

The mechanical properties of fresh lotus seeds are still poorly understood,which complicates the design of mechanical shelling machinery.Therefore,this work carried out four-factor orthogonal tests to determine the maximum permitted compressive force and minimum necessary shearing force to shell fresh lotus seeds without rupturing the kernel.It was found that the mean compression force that cracked the fresh lotus seed and led to kernel rupture was 213.03 N.Both the compressive force and the seed deformation upon kernel rupture were affected,in descending order of significance,by loading mode,seed grade,loading rate,and seed standing time.On the other hand,the shearing force needed to shell the seeds had a mean value of 7.84 N,far less than the compressive force that cracked the seed shell.The shearing force was affected,in descending order of significance,by seed standing time,tip angle of cutter blade,and loading rate,but not significantly affected by seed grade.The results suggested that mechanical shelling of fresh lotus seeds should ideally be carried out for fresh lotus seeds with a standing time of no more than 6 h using a cutter blade with an angle of about 40°at a loading rate of 30-90 mm/min.

A general synthesis strategy for the multifunctional 3D polypyrrole foam of thin 2D nanosheets

A 3D macroporous conductive polymer foam of thin 2D polypyrrole （PPy） nanosheets is developed by adopting a novel intercalation of guest （monomer Py） between the layers of the lamellar host （3D vanadium oxide foam） template-replication strategy. The 3D PPy foam of thin 2D nanosheets exhibits diverse functions including reversible compressibility, shape memory, absorption/adsorption and mechanically deformable supercapacitor characteristics. The as-prepared 3D PPy foam of thin nanosheets is highly light weight with a density of 12 mg·cm^-3 which can bear the large compressive strain up to 80% whether in wet or dry states; and can absorb organic solutions or extract dye molecules fast and efficiently. In particular, the PPy nanosheetbased foam as a mechanically deformable electrode material for supercapacitors exhibits high specific capacitance of 70 F·g^-1 at a fast charge-discharge rate of 50 mA·g^-1, superior to that of any other typical pure PPy-based capacitor. We envision that the strategy presented here should be applicable to fabrication of a wide variety of organic polymer foams and hydrogels of low-dimensional nanostructures and even inorganic foams and hydrogels of low-dimensional nanostructures, and thus allow for exploration of their advanced physical and chemical properties.