Imperfection Parameter Research Articles

The Utility of Baseline Characteristics and [123I]MIBG Cardiac Adrenergic System Scintigraphy in Qualifying Patients with Post-Infarction Heart Failure for Implantable Cardioverter-Defibrillator (ICD) Placement.

Background: Post-infarction heart failure with reduced ejection fraction (HFrEF) patients often face persistent risks of sudden cardiac arrest leading to sudden cardiac death. While implanting a cardioverter-defibrillator (ICD) can enhance prognosis, complications and costs limit its widespread use. Current patient qualification criteria, relying on imperfect parameters, require refinement. The impairment of the cardiac adrenergic system in heart failure is associated with ventricular arrhythmias. The goal of the study was to assess the utility of cardiac adrenergic system scintigraphy in qualifying patients for ICD placement. Methods: In this prospective study of 85 post-infarction HFrEF patients at a single center, clinical assessments, laboratory tests, echocardiography, [123I]MIBG scintigraphy, and ICD implantation were performed. Scintigraphy involved planar chest images and evaluating the heart-to-mediastinum ratio (H/M) and washout rate (WO). SPECT imaging assessed [123I]MIBG uptake in 17 left ventricular segments to calculate the summed difference score (SDS). Results: During a median of 4-year follow-up, 22% of patients experienced appropriate ICD interventions, and 25% of patients died or underwent heart transplantation. The mean values of analyzed parameters did not significantly differ between groups. In the univariate analysis, younger age and moderately impaired left ventricular ejection fraction (LVEF) were correlated with more frequent ICD interventions. In comparison, older age and elevated NT-proBNP levels were associated with death or heart transplantation. Additionally, the univariate analysis identified SDS-15' as a prognostic factor for death/heart transplant. The multivariate analysis identified predictors for ICD interventions, including younger age, an EF of 30% or greater, and a larger left ventricular end-diastolic diameter. In contrast, older age and an LVEF of less than 25% were significant predictors of death or heart transplantation. Conclusions: Scintigraphic parameters did not effectively predict ICD interventions or death/heart transplantation, though the summed difference score demonstrated potential as a prognostic factor. Younger age with moderately impaired EF correlated with frequent ICD interventions, while in older age, EF < 25% predicted death or transplantation. Further investigation is needed for patients with borderline EF values.

SH waves in orthotropic piezomaterials considered surface effects

Nowadays, orthotropic piezomaterials have enormous potential in producing electronic devices owing to their inherent merits, e.g., intrinsically robust piezoelectricity. Nevertheless, the previous theoretical studies merely report surface effects on the physical properties of SH waves in a layered transversely isotropic piezoelectric structure. Filling such a blank is a special necessity for optimizing Surface Acoustic Wave (SAW) sensors. Thus, the present paper aims to determine how surface effects and interfacial imperfection affect the attributes of SH waves in a layered orthotropic piezoelectric semi-space by means of surface piezoelectricity theory and a linear spring model. The structure mainly consists of the piezoelectric film's bottom and top surface layers and the imperfect bonding between the piezoelectric film and elastic half-space. To explicitly figure out surface and imperfect interface effects on the mechanical behavior of SH waves in a layered piezoelectric half-space, we extensively derive the phase velocity equations of SH waves in an orthotropic piezoelectric plate and an orthotropic piezoelectric half-space. Then, a comparison study among SH waves in a layered piezoelectric semi-space, a piezoelectric plate, and a piezoelectric half-space is conducted. As a result, it is revealed that the attributes of SH waves dramatically vary as the piezoelectric films’ thickness changes from microscale to nanoscale. In addition, phase velocity increases or decreases with an increasing surface elastic constant or surface density due to the enhancement of stiffness or density of the whole structure. When the ratio of piezoelectric film thickness to wavelength is small, imperfect parameters substantially reduce the phase velocity owing to a decreasing interface elastic stiffness. The comparison study shows that the imperfect parameter does not influence the waves’ velocity, while the ratio of film thickness to wavelength is relatively considerable. Anisotropic piezoelectric constant essentially weakens surface effects on the waves’ velocity. Intriguingly, a linear function is acquired and is used to measure surface density via the slope of the linear function. The summaries supply unique guidelines and instructions to open an avenue for designing and manipulating surface acoustic wave nanosensors in the future.

Nonlinear transient response of rotating graphene platelets reinforced metal foams blades with initial geometric imperfection

In this paper, a new mechanical model including initial geometric imperfection is developed to investigate the nonlinear transient response of graphene platelets reinforced metal foams (GPLRMF) blades subjected to blast load. Combined with higher-order shear deformation plate theory (HSDT) and von-Karman geometric nonlinearity, the nonlinear motion equations are established, in which the Coriolis force, centrifugal force as well as initial geometric imperfection are simulated. Considering cantilever boundary condition, the partial differential equations are transformed into a series of ordinary differential equations by Galerkin discretization. Using the four order Runge-Kutta algorithm, the nonlinear transient response is numerically researched, and the time histories and phase trajectories are obtained. In addition, the effectiveness of the current research is validated by comparing the results with the existing valuable literatures. The influences of rotating speed, presetting angle, initial geometric imperfection, material property, damping coefficient, and blast load parameter on the dynamic deflection and instantaneous speed are presented. Numerical results reveal that the nonlinear transient dynamics of the composite blades under blast load are significantly influenced by initial geometric imperfection.

FUNCTIONAL ASSESSMENT OF WAVE PROPAGATION IN IMPERFECT CYLINDER MATERIALS

This work provides a theoretical framework to investigate the shear wave propagation properties within an Electrostrictive cylindrical layered structure. The structure is made up of a concentric, Functionally Assessed Electrostrictive Material (FAEM) cylindrical layer of limited width and an inadequately bonded Electrostrictive material cylinder. The FAEM layer has a constant functional gradient in the radial direction, and flaws at the interface are taken seriously, mirroring actual circumstances involving structural and electrical degradation. The fundamental electromechanical connected Bessel's equations are used to simplify field differential equations by mathematical modifications. Relationships for shear wave propagation under electrically short and open circumstances are established analytically. The acquired findings are verified against predefined standards and a particular issue instance. The impact of variables on the phase velocity of shear waves, including functional range and imperfection parameters, is shown through numerical simulations and graphical displays. The research also establishes boundaries for electrically short and open circumstances, taking into account the shear defect that exists between the inner and outer cylindrical layers.

Two Stochastic Methods to Model Initial Geometrical Imperfections of Steel Frame Structures

The stochastic modeling of geometrically imperfect steel frame structures requires statistical inputs for imperfection parameters, often with specific mutual correlations. The stochastic input values of geometrical imperfections are derived from European Standard EN 1090-2:2018 tolerance criteria. Two advanced stochastic methods, #RSS (random storey sway) and #RSP (random storey position), are developed based on these criteria. This paper presents a verification study, using random sampling simulations, for these two stochastic methods (#RSS and #RSP) to directly model the initial global geometrical imperfections of steel frame structures. The proposed methods have been verified for structures with equidistant storey heights and for those comprising up to 24 storeys, making them applicable to a wide range standard steel frame structures. It has been found that the performance of the #RSS method is satisfactory. An advantage of #RSS is that the random parameters are statistically independent. On the other hand, the #RSP method requires the definition of these mutual correlations in order to satisfy the criterion that 95 percent of random realizations of initial imperfections fall within the tolerance limits of the corresponding European Standard. The #RSP method, however, might have certain advantages for structures with a larger number of storeys (above 24), as closely discussed in this study. Additionally, this study provides useful provisions for the advanced numerical analyses of multi-storey steel frames of various geometries.

An investigation of torsional surface wave in a piezoelectric fiber-reinforced composite layer imperfectly bonded to a functionally graded half-space

This article presents a comprehensive study of torsional surface wave propagation in a piezoelectric fiber-reinforced composite (PFRC) layer bonded to functionally graded (FG) half-space considering electrically short and open boundary conditions. The Strength of Materials (SM) and Rule of Mixtures (ROM) approaches have been adopted to determine the effective properties of the PFRC. The non-ideal mechanical and electrical interfacial boundary has been considered for the problem which appears in various realistic scenarios. For the torsional surface wave propagation through PFRC bonded to FG half-space, the dispersion equation has been derived analytically using Whittaker function. The obtained results are validated and matched with existing results by considering special cases. The variation of phase velocity due to the influence of fiber volume fraction, interfacial imperfection parameters and functionally grading parameters have been analyzed and illustrated by means of graphs. Furthermore, the distribution of the field variables, stress and electric displacements across the composite are presented through surface plots. The model holds potential applications in designing and manufacturing transducers, actuators and sensors. The use of PFRC can be found in a wide range of cutting-edge technology, including vibration-canceling gadgets, energy harvesters, and pressure sensors.

Investigating the Performance of CMIP6 Seasonal Precipitation Predictions and a Grid Based Model Heterogeneity Oriented Deep Learning Bias Correction Framework

AbstractClimate change is expected to alter the magnitude and spatiotemporal patterns of hydro‐climate variables such as precipitation, which has significant impacts on the ecosystem, human societies and water security. Global Climate Models are the major tools to simulate historical as well as future precipitation. However, due to imperfect model structures, parameters and boundary conditions, direct model outputs are subject to large uncertainty, which needs serious evaluation and bias correction before usage. In this study, seasonal precipitation predictions from 30 Coupled Model Inter‐comparison Project Phase 6 (CMIP6) models and Climate Research Unit observations are used to evaluate historical precipitation climatology in global continents during 1901–2014. A grid based model heterogeneity oriented Convolutional Neural Network (CNN) is proposed to correct the ensemble mean precipitation bias ratio. Besides, regression based Linear Scaling (LS), distribution based Quantile Mapping (QM) and spatial correlation CNN bias correction approaches are employed for comparison. Results of model performance evaluation indicate that generally precipitation prediction is more reliable in JJA than DJF on the global scale. Most models tend to have larger bias ratio for extreme precipitation. In addition, current CMIP6 models still have certain issues in accurate simulation of precipitation in mountainous regions and the regions affected by complex climate systems. Moreover, the proposed grid based model heterogeneity oriented CNN has better performance in ensemble mean bias correction than LS, QM, and spatial correlation CNN, which could consider the relative model performance and capture the features similar to actual climate dynamics.

Variable admittance control for safe physical human–robot interaction considering intuitive human intention

The trajectory planning of the arm is greatly facilitated by the physical direct teaching technology. Variable admittance control is a promising technology when a robot is interacting with a variable environment, such as a human whose stiffness might change during the interaction. Nevertheless, a canonical admittance controller with imperfect parameters may lead to robot oscillation, which brings more challenges to a variable admittance controller. In this paper, we propose an energy-based variable admittance controller with intrinsic oscillation suppression property. During the physical human–robot interaction (pHRI), the human intention is predicted based on the robot’s state and interaction force. The admittance parameters are tuned automatically to conform the robot’s motion to human intention. When the oscillation is detected online by the proposed wavelet module, our variable admittance model reveals oscillation suppression ability because of dissipating the energy generated by high-frequency oscillation. We compared the proposed variable admittance controller with other admittance controller approaches in both simulation and actual robot experiments. The proposed method shows significant improvement in oscillation suppression and human energy conservation in the human–robot interaction application.

Dispersion of an inhomogeneous sandwich plate having imperfect interfaces and supported by the Pasternak foundation

The purpose of this investigation is to see the dispersion of an inhomogeneous sandwich plate with imperfect interfaces between the layers and supported by the two parameters Pasternak foundation under long-wave low-frequency conditions. The governing equation of motion has been considered from the perspective of an anti-plane shear propagation to achieve simplicity. The overall cut-off frequency and the exact dispersion relation (EDR) are computed. In the context of the structure under investigation, one material contrast setup has been considered. The shortened polynomial dispersion relation, which corresponds to the EDR under material contrast setup, has been reported and investigated further. Additionally, the variational effects of the Pasternak foundation parameters as well as the interface imperfect parameter on the lowest dispersion curve subject to the long-wave low-frequency domain have been investigated using numerical simulations and graphical representations. This study is noteworthy because it sheds light on the behavior of elastic waves in multilayered structures and may be utilized to enhance the layout of three-layered structures used in a variety of industrial fields. Furthermore, we have provided the optimum values of the involved parameters to control and confine the sandwich plate’s vibration within the long-wave low-frequency regime.

Profiling the inflammatory bowel diseases using genetics, serum biomarkers, and smoking information

Crohn's disease (CD) and ulcerative colitis (UC) are two etiologically related yet distinctive subtypes of the inflammatory bowel diseases (IBD). Differentiating CD from UC can be challenging using conventional clinical approaches in a subset of patients. We designed and evaluated a novel molecular-based prediction model aggregating genetics, serum biomarkers, and tobacco smoking information to assist the diagnosis of CD and UC in over 30,000 samples. A joint model combining genetics, serum biomarkers and smoking explains 46% (42-50%, 95% CI) of phenotypic variation. Despite modest overlaps with serum biomarkers, genetics makes unique contributions to distinguishing IBD subtypes. Smoking status only explains 1% (0-6%, 95% CI) of the phenotypic variance suggesting it may not be an effective biomarker. This study reveals that molecular-based models combining genetics, serum biomarkers, and smoking information could complement current diagnostic strategies and help classify patients based on biologic state rather than imperfect clinical parameters.

Inverse scattering of periodic surfaces with a superlens.

We propose a scheme for imaging periodic surfaces using a superlens. By employing an inverse scattering model and the transformed field expansion method, we derive an approximate reconstruction formula for the surface profile, assuming small amplitude. This formula suggests that unlimited resolution can be achieved for the linearized inverse problem with perfectly matched parameters. Our method requires only a single incident wave at a fixed frequency and can be efficiently implemented using fast Fourier transform. Through numerical experiments, we demonstrate that our method achieves resolution significantly surpassing the resolution limit for both smooth and non-smooth surface profiles with either perfect or marginally imperfect parameters.

Optimizing molecular potential models by imposing kinetic constraints with path reweighting.

Empirical force fields employed in molecular dynamics simulations of complex systems are often optimized to reproduce experimentally determined structural and thermodynamic properties. In contrast, experimental knowledge about the interconversion rates between metastable states in such systems is hardly ever incorporated in a force field due to a lack of an efficient approach. Here, we introduce such a framework based on the relationship between dynamical observables, such as rate constants, and the underlying molecular model parameters using the statistical mechanics of trajectories. Given a prior ensemble of molecular dynamics trajectories produced with imperfect force field parameters, the approach allows for the optimal adaption of these parameters such that the imposed constraint of equally predicted and experimental rate constant is obeyed. To do so, the method combines the continuum path ensemble maximum caliber approach with path reweighting methods for stochastic dynamics. When multiple solutions are found, the method selects automatically the combination that corresponds to the smallest perturbation of the entire path ensemble, as required by the maximum entropy principle. To show the validity of the approach, we illustrate the method on simple test systems undergoing rare event dynamics. Next to simple 2D potentials, we explore particle models representing molecular isomerization reactions and protein-ligand unbinding. Besides optimal interaction parameters, the methodology gives physical insights into what parts of the model are most sensitive to the kinetics. We discuss the generality and broad implications of the methodology.

Unified shape and appearance reconstruction with joint camera parameter refinement

In this paper, we present an inverse rendering method for the simple reconstruction of shape and appearance of real-world objects from only roughly calibrated RGB images captured under collocated point light illumination. To this end, we gradually reconstruct the lower-frequency geometry information using automatically generated occupancy mask images based on a visual hull initialization of the mesh, to infer the object topology, and a smoothness-preconditioned optimization. By combining this geometry estimation with learning-based SVBRDF parameter inference as well as intrinsic and extrinsic camera parameter refinement in a joint and unified formulation, our novel method is able to reconstruct shape and an isotropic SVBRDF from fewer input images than previous methods. Unlike in other works, we also estimate normal maps as part of the SVBRDF to capture and represent higher-frequency geometric details in a compact way. Furthermore, by regularizing the appearance estimation with a GAN-based SVBRDF generator, we are able to meaningfully limit the solution space. In summary, this leads to a robust automatic reconstruction algorithm for shape and appearance. We evaluated our algorithm on synthetic as well as on real-world data and demonstrate that our method is able to reconstruct complex objects with high-fidelity reflection properties in a robust way, also in the presence of imperfect camera parameter data.

Nonlinear dynamic modeling of geometrically imperfect magneto-electro-elastic nanobeam made of functionally graded material

Smart magneto-electro-elastic (MEE) structures with high performance are highly valuable across a vast range of aerospace and industrial applications like smart sensing, space robotics, energy harvesting and biomedical research. This work focuses on the nonlinear dynamic response of a functionally graded MEE nanobeam. Initial geometric imperfection including global and localized imperfection modes is considered to reflect the effect of undesired error during nanofabrication process. Such geometric imperfection is involved by the product of hyperbolic and trigonometric functions. The nonlinear dynamic model for the FG-MEE nanobeam is established according to Hamilton’s principle and nonlocal constitutive relation to derive its governing equations of motion. The interaction between the imperfect FG nanobeam and its multi-physical stimulus is numerically solved via differential quadrature method. After validating the proposed model with existing works, the parametric study is conducted to fully reveal the coupling effect of geometric imperfection and numerous parameters including imperfection mode and amplitude, external electric and magnetic potentials, functionally graded index, boundary constraint and size-dependent parameter on nonlinear dynamic response of the FG-MEE nanobeam. Simulation results have demonstrated the significance of the MEE coupling effect, which can be used as a guide to design smart and advanced devices for aerospace and industrial applications.

Circumferential SH wave in piezo-reinforced composite structure with imperfect interface bonding

The present study fundamentally focuses on analyzing the limitations and transference of circumferential shear horizontal (CSH) waves in a four-layered compounded cylinder. The geometrical structure consists of cylinders of infinite length composed of self-reinforced (SR), fibre-reinforced (FR), piezo-magnetic (PM), and piezo-electric(PE) materials. In order to make the structure sensitive to the application pertaining to sensors and actuators, the PM and PE cylinders have been categorically placed in the outer part of the geometry. Whereas in order to provide stiffness and stability to the structure, the inner part consists of SR and FR materials. The common boundary between each of the cylinders has been essentially considered as imperfectly bounded. At the interface of PE and PM media, mechanical, electrical, magnetic, and inter-coupled types of imperfections have been exhibited. The closed-form of dispersion relation has been deduced for two contrast cases i.e. electrically open magnetically short (EOMS) and electrically short and magnetically open (ESMO) circuit conditions. Dispersion curves have been plotted to illustrate the salient features of parameters like normalized imperfect interface parameters, initial stresses, and radii of the concentric cylinders. The comparative effect of each one of these parameters on the phase velocity of the wave has been enlisted and marked individually. Every graph has been presented with two successive modes for a comprehensive understanding. This theoretical study may be implemented to improvise the performance of surface acoustic wave (SAW) sensors, actuators, and Piezo-cables in the form of Piezo-polymer sensors consisting of piezo-electric quartz, piezo-composite concentric cylinders, and coaxial piezo-cables.

Imperfect maintenance modeling and assessment of repairable multi-component systems

Industrial systems are subject to several maintenance tasks during their operational life. To ensure optimal performance of these systems, it is crucial to build maintenance models that describe the real behavior of the system. In this scope, the herein paper provides an original approach for maintenance efficiency modeling of multi-component systems. The proposed approach seeks to model the behavior of multi-component system after the replacement of one or more of its components and evaluate this effect. As a matter of fact, from maintenance efficiency point of view, the replacement of one component can be considered as perfect maintenance for the component itself but imperfect for the whole system. To this end, a hybrid model, which considers geometric adjustment of failure intensity, proportional adjustment of failure intensity and proportional adjustment of age is provided. Then, an efficient procedure based on Bayesian networks is provided for the assessment of the imperfect maintenance model parameters. Finally, the proposed model is compared to the most common imperfect maintenance models.

Characterizing Coherent Integrated Photonic Neural Networks Under Imperfections

Integrated photonic neural networks (IPNNs) are emerging as promising successors to conventional electronic AI accelerators as they offer substantial improvements in computing speed and energy efficiency. In particular, coherent IPNNs use arrays of Mach–Zehnder interferometers (MZIs) for unitary transformations to perform energy-efficient matrix-vector multiplication. However, the underlying MZI devices in IPNNs are susceptible to uncertainties stemming from optical lithographic variations and thermal crosstalk and can experience imprecisions due to non-uniform MZI insertion loss and quantization errors due to low-precision encoding in the tuned phase angles. In this article, we, for the first time, systematically characterize the impact of such uncertainties and imprecisions (together referred to as imperfections) in IPNNs using a bottom-up approach. We show that their impact on IPNN accuracy can vary widely based on the tuned parameters (e.g., phase angles) of the affected components, their physical location, and the nature and distribution of the imperfections. To improve reliability measures, we identify critical IPNN building blocks that, under imperfections, can lead to catastrophic degradation in the classification accuracy. We show that under multiple simultaneous imperfections, the IPNN inferencing accuracy can degrade by up to 46%, even when the imperfection parameters are restricted within a small range. Our results also indicate that the inferencing accuracy is sensitive to imperfections affecting the MZIs in the linear layers next to the input layer of the IPNN.

New hyperbolic statistics for the equilibrium distribution function of interacting electrons

New statistics of a low-parameter distribution of the sech (ε, µ) type are presented, which reproduce the results of plasma simulation by the method of dynamics of many particles (DMP) with high accuracy. The distribution is based on a conceptual model of a two-component plasma — virtual quasiparticles of negative energy (exciton phase ε&lt;0); the scattering region of positive energy (gas phase ε&gt;0). Optimization and elementary estimates of the applicability of the sech (ε, µ) distribution statistics were made after the results of DMP experiments. The sech (ε,µ) distribution reduces the number of parameters of the three-piece DMP distribution from 4 energy diffusion coefficients (D1, D2, D3, D4) to two — the chemical potential µ and the asymmetry coefficient α. The functional relationship D1, D2, D3, D4 with the chemical potential of the system µ in the sech (ε, µ) distribution is introduced in a similar way to the Einstein relation between mobility and energy diffusion constants. The functional variety of the differential equation belongs to the family of elliptic functions. It is much wider than the hyperbolic solution given, which has significant physical application for complex values of the energy ε. The proposed simplified scheme grounded in the physical interpretation of negative energies can be written for the electrometric electrons of the atmosphere, which previously presented significant methodological difficulties. The chemical potentials of the fluid (metastable states) and gas phases are presented as functions of the plasma imperfection parameter. The problem is posed as an application to the problem of electrometric electrons in the atmosphere. The proposed distribution is not represented in mathematical statistics and statistical physics; it is new and extremely relevant.

Effect of imperfect interface on the effective properties of elastic micropolar multilaminated nanostructures

AbstractIn this paper, the problem of a heterogeneous elastic micropolar nanostructure with a periodic structure subject to imperfect contact conditions is analyzed through the two‐scale asymptotic homogenization method (AHM). The imperfect interface is modeled as a generalization of the well‐known spring model; that is, the homogeneous imperfect interface is described by the following conditions: tractions and coupled stress are continuous, but displacements and microrotations are discontinuous across the imperfect interface. The jumps in displacements and microrotations are proportional to the interface traction and coupled stress components, respectively. In particular, micropolar multilaminated nanocomposites with centro‐symmetric isotropic constituents and imperfect contact conditions are studied. From AHM, the solutions for the displacement and microrotation fields are found by means of two‐scale series expansions depending on a local (microscopic) variable and a global (macroscopic) variable. The local problem statements and the corresponding effective properties are explicitly described. The formulation depends on the constituent physical properties, the imperfection parameters, the cell length in the y3‐direction, and the phase's volume fractions. Numerical results are illustrated and discussed. We concluded that the effective moduli are affected by the imperfections and the cell length in the y3‐direction.

Effect of detector photoelectric parameters on ptychographic iterative engine

An analytical solution model for ptychographic iterative engine (PIE) is proposed. In this model, PIE can be described as a system of linear equations between the sample and the illumination in the frequency domain. This system of linear equations (&lt;i&gt; &lt;b&gt;AX&lt;/b&gt; &lt;/i&gt; = &lt;i&gt; &lt;b&gt;B&lt;/b&gt; &lt;/i&gt;) is derived with the spectrum of the illumination as the coefficient (&lt;i&gt; &lt;b&gt;A&lt;/b&gt; &lt;/i&gt;), the spectrum of the sample as the unknown (&lt;i&gt; &lt;b&gt;X&lt;/b&gt; &lt;/i&gt;), and the intensity of the diffraction pattern as the vector (&lt;i&gt; &lt;b&gt;B&lt;/b&gt; &lt;/i&gt;). Hence, the sample can be recovered by solving this linear system. In PIE, the detector (such as Pike F-100, AVT) has a large resolution, meaning that 1000 × 1000 linear equations can be generated by recording a single pattern. It is still the case, however, that the number of obtained equations is smaller than the number of unknowns, leading to the inability to obtain a unique solution about the sample. Relative motions of sample and illumination, can generate more diffraction patterns to construct a sufficient number of linear independent equations. For coefficient (&lt;i&gt; &lt;b&gt;A&lt;/b&gt; &lt;/i&gt;), since the initial illumination is known, the illumination after shifting can still be obtained by recording its shifting distance. Hence the unique solution for the sample can be directly obtained by solving this linear independent system of equations. Simultaneously, the photoelectric parameters of the detector have a significant influence on the imaging quality of PIE. Using this linear system, the photoelectric parameters of the detector can be characterized by the number of linear equations and unknowns in each equation. According to the conditions that there is a unique solution in the system of equations and the requirements of the photoelectric parameters (such as pixel sampling interval, width of target surface, pixel size, sensitivity and dynamic range), the influence of the reconstruction for PIE is quantified theoretically. Obviously, the numerical simulation results based on this theory not only verify the correctness of the theoretical analysis and predictions, but also reveal the physical mechanism of recovering high-quality results in imperfect photoelectric parameters of detector, which can contribute to improving the quality of their reconstruction and optimizing the experimental setup.