In order to reduce the false alert or missed alert which is caused by polarization degradation of
interferometric optical-fiber early-warning system, the modulation process of intrusion signal is analyzed based on
the structure model of Mach Zehnder interferometric system. Two kinds of modulation signal distortion are
studied, and the solution, 3 ×3 coupler demodulation method is derived in detail. To meet the demand of
engineering application, a parameter correction method which can corrected demodulation distortion due to
unbalanced coupler is put forward. Simulation result in Simulink showed that the demodulation method can
restore phase signal accurately while the 3×3 coupler is unbalanced or polarization degradation occurred or the
signal contains high order harmonics and it is useful for engineering application of this system.

In order to solve the inaccurate result of the external factors in the actual measurement of laser
ranging, a kind of echo simulation system is designed to test the measured results. The ranging system emits a
narrow pulse width laser to the echo system, the PIN (Positive Input Negative)pairs perform laser acquisition
and the photoelectric conversion, and the electrical signal is sent to the FPGA ( Field-Programmable Gate
Array). The FPGA carries on the 15 times frequency operation through the built-in PLL(Phase Locked Loop)
and carries on the high precision time delay. The laser actuation part utilizes the MOSFET (Metal-Oxide-
Semiconductor Field-Effect Transistor) tube switch nature to produce the narrow pulse signal and the laser
modulation simulation actual measurement the Echo laser. Finally, the simulation result is obtained in the
ranging system. The results show that the stability of the system is high by measuring the same distance multiple
times and different distances. Precision can be achieved 0. 17 m and error is 0. 03 m.

 In order to solve the problems of low convergence speed and sensitivity to local convergence for
particle swarm optimization clustering routing algorithm, a new clustering routing algorithm based on chaotic-
quantum TSPSO(Two-Swarm Particle Swarm Optimization) algorithm is proposed. The cost function of the
optimal cluster head is chosen according to the energy of the cluster head, the distance between the cluster head
and the convergence node and the distance structure of the cluster node. The main particle swarm is optimized by
using the chaotic particle swarm optimization, making the particle swarm alternately transformed between the
stable and chaotic states. The subgroups are optimized by quantum particle swarm optimization and the quantum
wave theory making the algorithm has better global convergence. The concave function decreasing strategy is
adopted to optimize the weight in the algorithm of TSPSO. The convergence speed is accelerated. The simulation
results show that the proposed algorithm can balance the energy consumption of the wireless sensor network nodes
and extend the network life cycle significantly, and compare with LEACH(Low-Energy Adaptive Clustering
Hierarchy)and PSO-C(Cluster setup using Particle Swarm Optimization algorithm)respectively extend by 80. 1%
and 41. 4%.

In order to reduce the gap between the TPC (Turbo Product Code) and Shannon’s limit performance,
we generalized the Non-sequential decoding algorithm for SISO (Soft-Input/ Soft-Output) decoding of TPC. The
proposed algorithm only decodes the reliable component codes to avoid introducing extra errors. The simulation
results show that the error rate of the NS-SISO decoding algorithm is only half of the standard SISO algorithm
when Hamming code (64,57,4) is used as component code of TPC. It can be seen that the new algorithm has a
visible error performance gain.

 In order to solve the problem of the synchronization for singular fractional-order complex dynamic
networks,the continuous frequency distributed equivalent model and the indirect Lyapunov approach are applied
in the research of the singular fractional-order systems, a fractional-order synchronization controller is proposed to
normalize the singular fractional-order system. A novel sufficient condition for synchronization of uncertain
singular fractional-order complex dynamic networks with the order α(0<α<1) is presented. The LMI (Linear
Matrix Inequalities) techniques is used to obtain the gain of controller. A numerical example is provided to
demonstrate the validity of the proposed methods.

To solve the adaptive finite-time control problem for fractional order hyperchaotic Lorenz systems with
uncertain parameters, based on the related lemmas of fractional calculus and the finite-time Lyapunov principle,
an adaptive finite time controller is designed to guarantee the system’s adaptive finite-time stability. The accuracy
and effectiveness of the proposed controller are verified by numerical simulations. The method is simple and
effective, which can make the state variables of the system converge to the equilibrium point in a finite time. The
convergence speed is fast and the robust performance is good.

 In order to solve the problem of extracting navigation region in vision positioning and navigation of
unmanned aerial vehicle, a navigation region extraction algorithm based on superpixels’ saliency is proposed.
Firstly, the land image is divided into superpixel regions with high internal similarity by using SLIC (Simple
Linear Iterative Clustering), the saliency value of each superpixel is calculated to obtain the superpixel saliency
map. And the quasi guidance areas are extracted based on the navigation region filtering rules. Finally,
navigation areas are obtained through estimating the matching probability of the quasi guidance areas. The results
of our experiment show that the precision and recall of the proposed method are respectively 89% and 87% on
the test set, which means the method can basically meet the requirements of UAV (Unmanned Aerial Vehicle)
vision positioning and navigation.

Artillery shock wave signal test usually uses the notch algorithm to eliminate the power frequency
interference,but this method often loses the effective signal component. Therefore, an improved FastICA
algorithm is proposed to eliminate the power frequency interference. The FastICA algorithm based on negative
entropy is improved by using the Newton iteration form of fifth order convergence. The algorithm has high
accuracy of negative entropy algorithm, and has a fast convergence time and few iterations. The simulation results
show that the proposed algorithm has 0. 999 99 and 45 dB on the similarity coefficient and signal to noise ratio,
which is obviously superior to the traditional notch algorithm of 0. 996 and 21 dB. And compared with the
FastICA algorithm based on negentropy, the improved algorithm is the same as its precision,but the number of
iterations is reduced by 26. 7%. And compared with the kurtosis algorithm with faster convergence speed, the
improved algorithm has fewer iterations,faster convergence and higher stability. The algorithm has the advantages
of high precision, fast convergence speed and few iterations, and is suitable for real-time processing of shock
wave.

 As an advanced geophysical method, microseismic monitoring technology which has a good prospect is
widely used in many fields, such as geothermal exploration, oil and gas development. The formation mechanism
and characteristics of microseismic and the basic concepts of microseismic monitoring technology are introduced.
The basic principle of microseismic monitoring method, data processing and other main processes are described
briefly. Denoising is the primary task of data processing. Some basic methods of noise reduction are pointed out,
and the feasibility and superiority of applying deep learning in microseismic monitoring are proposed. Finally,
the applications and development prospects of microseismic monitoring technology are summarized.

 In order to solve the problem of geothermal resources exploration and development, the retrieval of
land surface temperature based on thermal infrared remote sensing data has become a new technology to find
geothermal resources. We used multiple months Landsat-8 data with the atmospheric correction method (RTE:
Radiative Transfer Equation) to perform land surface temperature retrieval. Through the comparison of
temperature inversion results and the verification of the point coordinates of the hot springs, the accuracy of
August and September were relatively high and reliable. By comparison the spatial distribution of the high
temperature regions and the fracture tectonic we conclude that they have a very high degree of similarity.
Therefore, it is possible to infer the existence of geothermal resources through the high temperature regions and
geological structures of inversion results.

 In order to solve the problem of poor generality in the transformation of EXPRESS into the ontology,
the lack of formalization and automatic conversion of mapping rules. A formal rule and an automatic conversion
algorithm for two kinds of interlingual mapping are proposed without dependence on the domain. The mapping
rule and algorithm are used to implement the automatic conversion of international standard data model
(Epicentre) of petroleum exploration and development based on EXPRESS to ontology. The correctness,
integrity and consistency of the Epicentre ontology are verified, by means of Jena. The results show that the
mapping rule and the automation algorithm are effective and universal.

In order to solve the problem of low prediction precision and long prediction time of steam flooding
development effect, we propose a novel prediction method, which is based on the combination of improved
artificial bee colony algorithm and RBF (Radial Basis Function) neural network. In the proposed method, we
apply the optimal solution of the population to modify the search equation of the employed bees and the onlooker
bees, perform the random perturbation of the population optimal solution and individual search solution with the
idea of differential evolution algorithm, and adopt hybrid encoding to optimize the parameters of RBF neural
networks. We use the Qi 40 block of Liaohe Oilfield as an example and make a trial calculation. The trial results
show that the method has better nonlinear fitting ability and higher prediction accuracy for steam flooding
development effect prediction.

In order to achieve informatization of management in organic analysis field,we introduce the Org-LIMS
(Organic Laboratory Information Management System) in National Research Center for Geoanalysis, establish
processes for main function modules such as sample management, customer management, inspection plan, task
allocation, data transmission, quality control and audit report combined with the characteristics of organic
compound analysis process and management requirements for organic laboratory, using C/ S(Client/ Server)
architecture model. The C/ S architecture uses Sybase Powerbuilder visual database development technology
achieving information management for the organic sample analysis process. The ability and quality of organic
compound analysis was improved with the implemetation of Org-LIMS and promoted the scientific and
standardized management of the laboratory.

 In order to overcome the disadvantages of traditional oil and water well parameter acquisition methods,
such as complex operation and low precision and so on, a new type of measuring instrument based on wireless
radio frequency technology was designed. The design principle and method of the gauge were explained. The
wireless radio frequency sensor which was packaged including the sensor module (pressure, current) took charge
of data collection of oil and water wells and the RFID read-write module, by which the oil and water wells data
was written into the RFID card. For the testing instrument, the system structure is simple, stable and reliable.
The accuracy of data acquisition meets the requirement and has changed the traditional mode of data acquisition.
By utilizing this Instrument, the workload of the staff is greatly reduced and the work efficiency is improved.
Therefore, the designed wireless radio frequency sensor detection instrument is effective.

 In order to study the cause of the deterioration of wheel hub electric car ride comfort and the quality
requirements of the driven motor, set up a quarter wheel body with two degrees of freedom vehicle vibration
system model, calculate the invariant point to indicate the reasons for the deterioration of ride comfort, also give
the weight requirements of the driving motor to improve ride comfort, and use Simulink to simulate and verify the
result. The results show that the frequency invariant point does not change with the change of spring stiffness and
damping coefficient, and the amplitude frequency characteristic value of the input speed of road surface for the
vehicle body acceleration corresponding to frequency invariant points is close to the maximum value, it has a
great influence on ride comfort, causing wheel hub electric vehicle ride comfort deterioration, and we can give
the quality requirements of the drive motor.

For the purpose of reducing power and improving production capacity of plasma loudspeaker, based on
the theoretical analysis, we analyze the characteristics and principles of the two typical methods, ZVS(Zero
Voltage Switch) and PWM (Pulse-Width Modulation), combining the advantages of the two schemes, propose a
soft switch control method based on PWM pulse width modulation. The driving circuit adopts IR2110 chip to
enhance the driving ability of the circuit. The switch part adopts the soft switch method to improve the overall
efficiency of the circuit. By comparing the power input, the switching tube heating condition and the arc length,
it is found that the output power is 12 W when the arc length is 1. 5 cm, the surface temperature of the two
switches are 50℃ and 58℃. The experimental results show that the proposed scheme reduces the power
consumption, improves the stability and safety of the overall circuit, and reduces the distortion of the PWM wave
which controls the switch. Therefore, it has better practical application and product capability.

 In order to accurately describe the volt-ampere characteristics of high-power LED(Light Emitting
Diode), the classical Shockley equation is combined with the LED physical model to deduce the theory, the
Taylor equation is developed and the model is segmented to construct the electrical parameter model of high
power LED. The volt-ampere characteristic curve of the high-power LED is verified to be closer to the actual volt-
ampere characteristic curve than the classical PN junction model, which is more consistent with the measured
curve, and the error is less than 1%.