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As traditional grating-based spectrometers can not offer fast apertures and small volume systems synchronously,this paper designs a convex grating by using holography and develops an imaging spectrometer with the convex grating as a core element.It acquires the image of target by pushbroom scanning,then obtains the data cubes of the imaging spectra.The image spectrometer has a space resolution of 2.4 nm,a spectral line bend of 0.1%,the chromatic distortion of 0.6%,and a volume of 209 mm×199 mm×110 mm.The principle of imaging spectrometer with convex grating is analyzed and its constructs are described.Then,a spectral experiment in the laboratory is carried out and the spectra of extraventricular flowers are tested.The result demonstrates that the real spectral resolution is 2.1 nm,line bend is 0.09% and the chromatic distortion is 0.6%.These data satisfy the design requirement,and obtained spectra are ideal results.

A method based on the Senamont method was proposed to precisely measure the birefringence of an infrared crystal.Two specimens with the Optical Pass Differences(OPD) within 1 wavelength caused by the birefringence were compared to overcome the measured OPD limit of Senamont method and to extend the method to the infrared band.According to the new method,a set of apparatus for measuring the birefringence of infrared crystal was developed.Moreover,by applying the Jones matrix,the expressions of signal intensity with various error sources were proposed to analyze precisely the influences of the error sources including the azimuth error of a polarizer,the orientation error of the quarter wave plate,the azimuth error of the specimen and the orientation error of the analyzer,then the measuring precision of this method was evaluated.The experiment results indicate that the measured OPD error for a standard quarter wave plate is 0.00376 μm,and the relative error is 0.44%,which is within the precision and satisfies the system targets.

The coal sample preparation is an important part for the study of coal's character, and therefore, the man-made secondary carbonization method of coal sample preparation was explored in the text. Firstly, the scheme of secondary carbonization was designed, and then, according to it, the heat transmission and the temperature field evolvement rule were analyzed in the process of carbonization. Finally, the secondary carbonization experiment of coal sample preparation was conducted, and the coal sample was obtained successfully. The results show that the temperature rise velocity in the center of coal sample is from fast to slow in the process of secondary carbonization, and the reasonable calefaction time is about 15000 seconds.

The main point of intelligent fault diagnosis theory is fault mode distinguishing principle based on data processing methods. Pointing to the problems of the traditional fault diagnosis mode, a fault diagnosis method based on the virtual instrument and neural networks is proposed. The signals collection and management based on virtual instrument is introduced, the basic method of the neural networks for distinguishing the faults is analyzed. For fastness and accuracy, connecting the wavelet analysis with the neural networks organically, and based on the wavelet transfer and the neural networks, the system of the speedy features extraction and identification for the faults is founded. The method of the feature extraction for the faults based on the wavelet analysis are established, the realization idea of the fault diagnosis based on the neural networks is put forward, and the hardware and software structure of the fault diagnosis based on the neural networks are discussed. The experimental and simulated results show: it is feasible that analyses for the faults with the neural networks and the wavelet analysis. The method can remarkably heighten the accuracy and credibility of the fault diagnosis results, and the results are of repeatability.

Virtual instrument is an integration of the latest PC technology, advanced testing technique and strong software package, and the development of visual instrument system is, in the domain of the automatic test and fault diagnosis equipment, etc, the trend of modern technology. It is developed, applied virtual instrument technology, grey system theory, and database, the fault diagnostic system for shipboard chemical defense equipment, in order to update entirely the means of the equipment testing. The modularization and universalization are proposed in its database-based design concept, realizing the design of software and hardware. The ODBC technique is applied for the interconnection of databases to ensure the generality and flexibility of the system. The system mode the best of virtual instrument platform and grey diagnosis method, broke through conventional check diagnosis patterns for warships chemical defense equipment, solved the problems of state prediction and trouble-mode recognition of warships chemical defense equipment. It has been proved by experiments that the system has merits both high accuracy and economical practicability. Also it can reduce the application development cycle and cost.

Recovery of depth information plays a key role in the micromanipulation robot system for performing micron or sub-micron orientation and measurement tasks. Based on the model of defocused optical system and combined with characteristics of frequency response curves of defocus optical transfer function (OTF), a new method of estimating the depth information for micro-manipulation is proposed. The depth information can be calculated by using the depth equation derived from a sequence of calibration images when acquiring the energy parameter of the micromanipulator in the certain position. We experiment with the choice of the high-pass cut-off frequency in order to identify the optimum filter for the specific micromanipulation tool. Experimental results show that the method is efficient, robust, and useful in practical applications.