667 results about "Time domain waveforms" patented technology

A communication system based upon frequency-domain MIMO processing is disclosed. A transmitting device of the communication system transforms time-domain signals into frequency-domain signals, and weights each frequency-domain signal to form weighted frequency-domain signals with each weighted frequency-domain signal being a function of each frequency-domain signal. The transmitting device transmits weighted time-domain waveforms as a function of the weighted frequency-domain signals. In response thereto, a receiving device of the communication system provides frequency-domain samples that are a function of the one or more weighted time-domain waveforms and weights each frequency-domain sample to form one or more weighted frequency-domain samples with each weighted frequency-domain sample being a function of each frequency-domain sample. The receiving device decodes the weighted frequency-domain sample to obtain the information represented by the time-domain signals.

The invention relates to a method and a system for measuring rock optical parameters based on Terahertz time-domain spectroscopy. The method comprises the steps of: detecting a rock substrate and a rock sample, and obtaining the Terahertz time-domain waveform of the rock substrate and the Terahertz time-domain waveform of the rock sample; processing the Terahertz time-domain waveform of the rock substrate and the Terahertz time-domain waveform of the rock sample, and obtaining the absorption spectrum and the refractive index spectrum data. The method and the system for measuring rock optical parameters based on the Terahertz time-domain spectroscopy provided by the invention have the advantages that the fast and nondestructive detection can be carried out on the rock, the operation of the detection method is easy, the data processing is simple, and the repeatability is good.

A speech enhancement method (and concomitant computer-readable medium comprising computer software encoded thereon) comprising receiving samples of a user's speech, determining mel-frequency cepstral coefficients of the samples, constructing a Gaussian mixture model of the coefficients, receiving speech from a noisy environment, determining mel-frequency cepstral coefficients of the noisy speech, estimating mel-frequency cepstral coefficients of clean speech from the mel-frequency cepstral coefficients of the noisy speech and from the Gaussian mixture model, and outputting a time-domain waveform of enhanced speech computed from the estimated mel-frequency cepstral coefficients.

The invention provides a rotating machinery condition monitoring and fault diagnosing system and method. The system comprises a data acquiring subsystem, a holographic spectral analysis subsystem and a space vibration mode analysis subsystem, wherein the data acquiring subsystem is used for carrying out DC blocking and filter processing on an acquired signal through a sensor and then sending the signal to the holographic spectral analysis subsystem and the space vibration mode analysis subsystem, the space vibration mode analysis subsystem is used for carrying out look-ahead analysis on a time domain waveform and an amplitude spectrum and determining possible faults of a rotor system of rotating machinery preliminarily, and then the holographic spectral analysis subsystem and a shafting space vibration mode analysis subsystem are used for extracting fault features and diagnosing fault cause. According to the rotating machinery condition monitoring and fault diagnosing system and method, the vibration condition of the rotor system can be monitored through the data acquiring subsystem when the rotating machinery is in an on-line working state, and therefore safety of the operation of the rotor system is improved, economic losses caused by machine halt are reduced, and engineering practice is better fit.

The invention relates to a self-adaptive damage compensation method and system for a digital-related optical communication system. The self-adaptive damage compensation method includes inserting two pulse modulation pilot frequency signals symmetrically distributed on an input signal frequency fc (fiber channel) at a transmitting terminal; acquiring an input signal power spectrum by the Fourier transform at a receiving terminal, and receiving the pilot frequency signals of a signal power spectrum and subjecting the pilot frequency signals to location and filtering extraction; calculating size of frequency offset of a vibration laser and performing compensation by a pilot frequency; acquiring pilot time domain waveforms by the Fourier transform and calculating a delay delta tau between two pilot light pulses, and calculating size of dispersion by the delta tau and performing the compensation; finally extracting pilot phase noises and subtracting the same from a signal phase so as to eliminate laser phase noises and nonlinear fiber damages. The self-adaptive damage compensation method has the advantages of high accuracy, low complexity, small occupation of bandwidth and fast response speed, so that self-adaptive compensation of various damages can be realized.

The invention relates to a global information system (GIS) partial discharge on-line monitoring calibration instrument and a configuration authentication method thereof. The calibration instrument is provided with a pulse signal source and a transmitting antenna. When the pulse signal source replacing a high-voltage conductor spike model injects signals of a simulation partial discharge source through an external sensor as the transmitting antenna into a GIS cavity, the calibration instrument carries out checking on sensitivity of a partial discharge ultra high frequency (UHF) detecting device in the process that the partial discharge UHF detecting device detects the signals on line on the basis of an ultrahigh frequency method. The configuration authentication method includes the steps of testing time domain waveform and spectrum characteristics of a UHF signal model radiated by a typical discharge source inside a GIS, providing technical parameters of the pulse signal source, injecting the pulse signals into the high-voltage conductor spike model on an entity GIS platform, injecting pulse signals into the GIS cavity through an internal sensor and the external sensor, and then carrying out equivalent checking.

The invention provides a bearing fault diagnosis method and system device based on improved empirical wavelet transform. The method comprises: step one, collecting different fault bearing signals as analysis signals and converting a time domain waveform into a frequency domain waveform; step two, drawing an upper envelope of a frequency spectrum and transforming a frequency peak with a tight support into a flat top; step three, screening flat tops in the frequency domain based on criteria, removing meaningless flat tops, and keeping a main frequency; step four, using a minimum value between adjacent flat tops as the boundary of spectrum segmentation; step five, establishing wavelet filters respectively for segmented frequency spectrums and decomposing the signals into N mode components; step six, calculating similarity values between mode components and the original signals by using a cross-correlation coefficient and selecting a component with the highest similarity value; and step seven, taking a fault sample, calculating an IMF component with the largest correlation coefficient of the sample, calculating a multi-scale entropy of the IMF component, and drawing the multi-scale entropy curve of the sample to realize fault classification.

The invention discloses a detection device and a detection method for series arc faults. The detection device comprises a continuous current collection module, which is used for continuously collecting current at a fixed sampling rate through an A / D (Analog to Digital) converter, a signal preprocessing module, which is used for carrying out moving average processing on collected data, an arc fault processing and analyzing module, which is used for computing a rate of change of current, a sum of previous N harmonics and a harmonic time domain waveform effective value, identifying an arc according to the three variables and giving a corresponding command, a sound-light alarm module, a drive module and a tripping control module, which are used for deciding whether sound-light alarm is carried out and a circuit is disconnected according to the command of the arc fault processing and analyzing module, and a communication module, which is communicated with the exterior through an RS485 interface. According to the detection device and the detection method, a time domain and a frequency domain are together utilized to judge whether the arc fault occurs, and through analyzing and testing, the method has the advantages of simplicity in operation, easiness in implementation, low cost and misjudgment rate and high detection probability.

The invention discloses a system for pre-testing and diagnosing the electro magnetic interference of electronic equipment, which is characterized by comprising a data collecting module, an interference source diagnosing and locating module, an environmental noise eliminating module and a visual time-frequency analyzer, wherein the data collecting module, the interference source diagnosing and locating module and the environmental noise eliminating module are respectively connected with the visual time-frequency analyzer, and the visual time-frequency analyzer achieves the drive of the data collecting module, the call of the interference source diagnosing and locating module and the environmental noise eliminating module and the monitoring and displaying of time-domain waveforms and frequency spectrums. The invention also discloses a method for pre-testing and diagnosing the electro magnetic interference of electronic equipment, which utilizes a LabView visual instrument platform and Matlab programming environmental developing software to pre-test and diagnose signals. The invention can pre-test and diagnose the electro magnetic interference of electronic equipment at common test fields, and has high automation and carrying degree and simple usage and reduces cost.

The invention relates to a nondestructive testing analytical method for kerogen based on terahertz time-domain spectroscopy. The method comprises the following steps of: firstly, selecting a sample cell; secondly, preparing a kerogen standard sample and accommodating the kerogen standard sample in the sample cell; thirdly, detecting the kerogen standard sample and the empty sample cell by using the terahertz time-domain spectroscopy to obtain a terahertz pulse time-domain waveform of the kerogen standard sample and a terahertz pulse time-domain waveform of the empty sample cell; fourthly, carrying out data processing on the terahertz pulse time-domain waveform of the kerogen standard sample and the terahertz pulse time-domain waveform of the empty sample cell to construct a standard fingerprint spectrum library; and fifthly, analyzing the thermal evolution and hydrocarbon generating capabilities of the kerogen standard sample according to optical parameters of the standard fingerprint spectrum library. The nondestructive testing analytical method for the kerogen based on the terahertz time-domain spectroscopy which is disclosed by the invention has the advantages of quick and nondestructive detection for the kerogen, easiness in operation, simpleness in data processing, favorable repeatability and relatively accurate measuring result.

The invention discloses a high-voltage cable insulation defect partial discharge on-line monitoring diagnosis method, which involves analyzing obtained partial discharge data of various actual manufacturing typical defects from the perspectives of time domain waveform characteristics, spectrum distribution differences, separate spectrum analysis and the like, and establishing a discharge database and a comparison database of the various defects. By use of a high-voltage cable partial discharge detection system, through utilizing signal separating technologies including a three-phase amplitude relation atlas, a three-frequency range amplitude relation atlas and the like, pulse current waveform parameter characteristic value integrated information is analyzed, a discharge accumulation spectrum of on-site measuring data and a same-kind characteristic pulsed discharge cluster are formed, and finally a comparison is made between the discharge accumulation spectrum and the same-kind characteristic pulsed discharge cluster and the discharge database of the various defects so as to determine whether insulation defects exist for an on-site running cable line. The method can solve the problem of difficult on-line monitoring diagnosis of insulation defect partial discharge of a conventional cable device, and also can improve the accuracy and sensitivity of high-voltage cable insulation defect partial discharge detection diagnosis.

The invention discloses a multi-speaker voice separation method based on a convolutional neural network and depth clustering. The method comprises the following steps: 1, a training stage: respectively performing framing, windowing and short-time Fourier transform on single-channel multi-speaker mixed voice and corresponding single-speaker voice; and training mixed voice amplitude frequency spectrum and single-speaker voice amplitude frequency spectrum as an input of a neural network model; 2, a testing stage: taking the mixed voice amplitude frequency spectrum as an input of a threshold expansion convolutional depth clustering model to obtain a high-dimensional embedded vector of each time-frequency unit in the mixed frequency spectrum; using a K-means clustering algorithm to classify thevectors according to a preset number of speakers, obtaining a time-frequency masking matrix of each sound source by means of the time-frequency unit corresponding to each vector, and multiplying thematrixes with the mixed voice amplitude frequency spectrum respectively to obtain a speaker frequency spectrum; and combining a mixed voice phase frequency spectrum according to the speaker frequencyspectrum, and obtaining a plurality of separate voice time domain waveform signals by adopting short-time Fourier inverse transform.

A test procedure control unit outputs control information including time setting information in order to carry out a transition test of a connection state of a mobile communication terminal of a cellular system. In accordance with the control information, a transmission / reception unit generates a plurality of test signals including predetermined messages which correspond to a plurality of cells, and vary those in accordance with a scheduled time passage to thereby transmit those to the mobile communication terminal and receive response signals including predetermined messages from the mobile communication terminal. A reception measurement unit measures time domain waveforms of the response signals, and a message log acquiring unit acquires and stores messages and radio-communication time information when the transmission / reception unit and the mobile communication terminal exchange the respective predetermined messages. A display control unit causes to display graphs indicating measured results of the time domain waveforms and a predetermined number of radio-communication markers indicating points in radio-communication time which correspond to the radio-communication time information by a graphic display capable of simultaneously comparing at both sides of the same time base on a display unit.

The invention relates to a method for removing eye electrical artifact in EEG signals, which belongs to the technical field of biological information, relates to the technology of EEG signal collection and pretreatment, and is mainly applied to the pretreatment process of the EEG signal acquisition. The method comprises that principal component analysis is carried out on EEG data containing eye electrical artifact; the components of the eye electrical artifact are determined; 1-8Hz of wave filtering is carried out on the time domain waveform of artifact components; attenuation factors of the eye electrical components in each electrode are calculated by combining regression algorithm and using the time domain waveform of artifact components; the attenuation factors are used for regulating the spatial distribution of the eye electrical artifact components; the regulated spatial distribution of the artifact components is used for removing the eye electrical artifact. The method solves the problems that in the traditional method for removing the eye electrical artifact based on principal constituent decomposition, the principal constituent decomposition is incomplete, and the decomposed eye electrical artifact components contain EEG components. The regulation of the attenuation factors causes that the components containing eye electrical are more easily distinguished.

The invention discloses a music separation method of an MFCC (Mel Frequency Cepstrum Coefficient)-multi-repetition model in combination with an HPSS (High Performance Storage System), and relates to the technical field of signal processing. In consideration of high probability of ignore of a gentle sound source and time-varying change characteristic of music, the sound source type is analyzed through a harmonic / percussive sound separation (HPSS) method to separate out a harmonic source, then MFCC characteristic parameters of the remaining sound sources are extracted, and similar operation is performed on the sound sources to construct a similar matrix so as to establish a multi-repetition structural model of the sound source suitable for tune transformation, so that a mask matrix is obtained, and finally the time domain waveform of a song and background music is obtained through ideal binary mask (IBM) and fourier inversion. According to the method, effective separation can be performed on different types of sound source signals, so the separation precision is improved; meanwhile the method is low in complexity, high in processing speed and higher in stability, and has broad application prospect in the fields such as singer retrieval, song retrieval, melody extraction and voice recognition in a musical instrument background.

The invention discloses a plane target classification method based on a time domain and a Doppler domain, and relates to classification methods for moving targets in the air. According to the implementation process of the plane target classification method, a radar conducts observation many times and receives echo signals of a plane target for clutter rejection; time domain waveform entropy and Doppler domain waveform entropy of the signals are calculated; an entropy matrix S' is constructed; the time domain waveform entropy mean value, the time domain waveform entropy 1 order moment and the Doppler domain waveform entropy mean value of each row of the entropy matrix S' are figured out; classifiers are trained by means of the time domain waveform entropy mean values, the time domain waveform entropy 1 order moments and the Doppler domain waveform entropy mean values; test samples are input to the classifiers for classification. The method mainly solves the problems that when the radar carries out observation once under the condition that beam dwell time is shorter than a time domain echo cycle of a rotating part, a micro-doppler modulation spectrum is broadened and the resolution ratio of the micro-doppler modulation spectrum is lowered. Classification accuracy is obviously improved, and the method is used for classification and identification of plane targets.

The invention provides a fault line selection method based on time domain waveform correlation analysis of a three-phase current breaking variable, and belongs to the technical field of electric system relay protection. The method includes the steps that as for a power distribution network with a feed-out line only provided with a three-phase current mutual inductor and not provided with a zero sequence current mutual inductor, when single-phase earth fault of the power distribution network occurs, a device is immediately started, and three-phase breaking currents of feeder lines on measurement positions are measured. A three-phase breaking current time domain waveform inside a time window 5 milliseconds after the fault occurs is extracted, correlation analysis of the three-phase breaking current time domain waveform is carried out to acquire an interphase correlation coefficient and a comprehensive correlation coefficient, the comprehensive correlation coefficient and the interphase correlation coefficient respectively serve as a line selection criterion characteristic quantity and a phase selection criterion characteristic quantity, and line selection and phase selection of the distribution network single-phase earth fault are achieved according to criterion principles. Theoretical analysis and a great quantity of emulation indicate that the fault line selection method is good in effect.

The invention discloses a method used for testing the stability of the foundation of a fan suspended in a road tunnel and a system therefor, which is characterized in that the method comprises the three steps of acquiring standard reference information, acquiring detection information and judging comparison, wherein the information in the judging comparison refers to the time domain waveform, the frequency spectrum and the variation tendency of a signal generated by the vibration situation detected by the fan in the whole process from starting to steady running; and the system comprises a vibrating sensor, a signal amplification circuit, a filter circuit, a sample circuit, a CPU central controller, a keyboard module, a display, a data storage unit and an analysis processing computer. The invention has the obvious effects that the failure condition of a welded bracket can be detected, the loosening condition between a precast steel plate and a precast reinforcement as well as between the precast reinforcement and concrete can also be detected, the fan does not need to be detached in the testing process, the running of equipment is not affected, the principle of the system is simple, the production cost is low, the test operation is simple and convenient, and the result is reliable and visualized.

A shore bridge structure wind vibration fatigue life forecasting method based on accumulated damage of probability includes the following steps: step 1 adopting a harmonic superposition method to simulate time domain waveform of wind load borne by a shore bridge structure and according with davenport power spectrum characteristics; step 2 enabling the wind load to be acted on a finite element model of the shore bridge structure, and calculating a stress response time interval of fatigue calculation points of the shore bridge structure; step 3 adopting a rain flow counting process to deal with the stress response time interval so as to obtain fatigue statistical characteristics of amplitude stress spectrum; and step 4 adopting a probability accumulated damage model and a method of a probability theory to forecast wind vibration fatigue life of the shore bridge structure at a certain degree of reliability. The shore bridge structure wind vibration fatigue life forecasting method has the advantages of applying to a complex shore bridge structure, and being wide in scope of application, high in calculating accuracy and capable of calculating reliability fatigue life of a wind resisting structure under the action of any random wind load.

The invention discloses a speech enhancement method of a multi-sub-band spectral subtraction based on phase adjustment and amplitude compensation. The method mainly includes truncating signals acquired by a microphone and performing fast Fourier transform (FFT); performing micro maximum search on an amplitude spectrum through a phase adjustment algorithm to obtain an adjusted amplitude spectrum of noisy speech; estimating the amplitude spectrum of noise; dividing a whole band into a plurality of sub-bands and calculating the signal to noise ratio of each sub-band; performing amplitude spectrum subtraction of an over-subtraction rule on each sub-band; performing amplitude compensation on speech spectrums after the spectrum subtraction; and obtaining time domain waveforms of the signals through fast Fourier inversion and signal overlapping.

A barcode reading apparatus and method in which the spectrum of a probe light is first Fourier-transformed into space, directed upon a barcode, and then Fourier-transformed converting the spectrally encoded barcode pattern to a time domain waveform. In one implementation, the Fourier transformation from the spectrum domain into a spatial domain is performed by a dispersive element, while the Fourier transformation from the spectrally encoded barcode pattern to a time domain waveform is performed by group-velocity dispersion (GVD). The temporally encoded barcode pattern is detected by a photodetector, digitized by a digitizer, and analyzed by a digital signal processor. The invention is applicable to a number of fields which involve the reading of one- and two-dimensional barcodes, displacement sensing, surface measurements, measurement of width and gap, flow cytometry, reading of optical media, presense or absence detection, and other related fields.

The invention discloses an automatic digital array reception channel performance test system based on cPCI. The system comprises a host computer and a data acquisition board card based on a cPCI interface, wherein the data acquisition board card comprises a cPCI interface unit, a processing control unit, a buffering unit and a photoelectric conversion unit, the photoelectric conversion unit is connected with the processing control unit, the data is acquired by the processing control unit through the photoelectric conversion unit and is stored in the buffering unit, the processing control unit realizes communication with the host computer through the cPCI interface unit, work parameters are configured by the processing control unit on the basis of a control instruction of the host computer, the buffering data is transmitted to the host computer, the host computer is used for emitting a control instruction to the data acquisition board card for performing data acquisition, the reception data is drafted into frequency domain and / or a time domain waveforms which are then outputted, test index operation is carried out on the basis of the reception data, and output is carried out. Through the system, performance test on each reception part of a digital array radar device is carried out, rapid, high-efficiency and accurate performance evaluation can be realized, and fault positioning can be further realized.

The invention relates to a terahertz-spectrum-based quick nondestructive detection method for coal. The terahertz-spectrum-based quick nondestructive detection method comprises the following steps of: selecting a sample cell; preparing a standard coal material sample and an ordinary coal sample; detecting the standard coal material sample and an empty sample cell by utilizing a terahertz time-domain spectrometer to obtain a terahertz pulse time-domain waveform of the standard coal material sample and a terahertz pulse time-domain waveform of the empty sample cell; performing data processing on the terahertz pulse time-domain waveforms of the standard coal material sample and the empty sample cell to construct a standard fingerprint database; and detecting and analyzing the ordinary coal sample, and obtaining the sort, ash content and carbon content data of the ordinary coal sample according to the standard fingerprint database. According to the method provided by the invention, the coal can be quickly and nondestructively detected; the method is easy to operate, simple in data processing, high in repeatability and accurate in test result; and a coal property can be quickly and accurately analyzed.

A method for determining a power cable partial discharge defect type based on spectral analysis comprises the following steps: 1) reading a power cable partial discharge amount time-domain waveform which is free of background noise and interference and collected by a power cable partial discharge detecting instrument, performing equivalent time-frequency analysis on the obtained partial discharge time-domain waveform, performing normalization processing on signals, performing time-domain conversion on the normalized signals, converting time-domain characteristic waveform to a frequency-domain waveform to obtain a frequency-domain characteristic pattern of the partial discharge waveform, and extracting a corresponding partial discharge waveform frequency spectrum characteristic value; performing other steps. The method has the benefits that the detection speed and accuracy are high, and the detection procedure is simple; a visualized power cable partial discharge frequency-domain oscillogram is output, so that the power cable defect style can be intuitively assessed by a detector, and the intelligence level of power cable partial discharge detection and the detection efficiency can be improved.

The invention discloses a single-channel monitor-free voice and noise separating method based on low-rank and sparse matrix decomposition. The method includes the steps of converting a time domain waveform of noise-contained voice to a time frequency domain via short-time Fourier transform to obtain a magnitude spectra with noises; decomposing the magnitude spectra with the noises into a sum of a noise magnitude spectra, a voice magnitude spectra and a residual noise magnitude spectra by a low-rank and sparse matrix decomposition algorithm; and finally reconstructing a voice time-domain waveform from the voice magnitude spectra via short-time Fourier transform. Without any priori information about voice and noise, the method is the single-channel monitor-free voice and noise separating method, pure voice can be separated from noise-contained voice by the aid of an algorithm, and the single-channel monitor-free voice and noise separating method is simple, effective, and particularly suitable for voice extraction in strong-noise environment.

The invention discloses a device for monitoring the state and diagnosing the fault of a power electronic circuit. The device has a structure that: a magnetic field detection module detects the magnetic field strength of the power electronic circuit, a signal conditioning module amplifies a voltage signal and an analog-to-digital conversion module performs analog-to-digital conversion; a fault diagnosis module comprises a time-domain and frequency-domain conversion module, a characteristic sort module and a comprehensive diagnosis module; the time-domain and frequency-domain conversion module is used for extracting the frequency characteristics of a time-domain waveform and supplies the frequency characteristics to characteristic sort sub-modules respectively; the characteristic sort sub-modules compare the received subsets to obtain partial diagnosis results corresponding to each characteristic subset and supply the results to the comprehensive diagnosis module; and the comprehensive diagnosis module synthesizes the partial diagnosis results of each characteristic subset to obtain a final diagnosis result. The device realizes the natural isolation of a detector from a main circuit; the different kinds of information carried by the magnetic field signal are treated respectively and then comprehensively judged, so the accuracy is higher; and the device can be applied to various power electronic circuits.

The invention provides an online partial discharge detection signal recognition method of a cable. The method comprises the following steps: a partial discharge time domain waveform of a known source is acquired; a partial discharge waveform time domain waveform sample library is established; a wavelet packet is used to denoise each partial discharge time domain waveform in the sample library; a self-adaptive wavelet neural network model with a preset number of layers is constructed; according to each denoised partial discharge time domain waveform, a PSO algorithm is used to train the constructed self-adaptive wavelet neural network model; a BP algorithm is then used to train the trained self-adaptive wavelet neural network model for a second training so as to get a well-trained wavelet neural network; and the partial discharge signal of a to-be-recognized source is received, the well-trained wavelet neural network is inputted for recognition, and the source of the to-be-recognized partial discharge signal is obtained. The method of the invention is fast in recognition speed and high in recognition precision.

The invention relates to a lightning stroke fault recognition method for an EHV (extra-high voltage) DC transmission line based energy spectrum similarity, and belongs to the technical field of power system relay protection. The method comprises the steps: extracting the ratio of a positive time domain waveform to an area formed by the enclosing of the zero axis of the positive time domain waveform and the ratio of a positive time domain waveform of any fault type to the area formed by the enclosing of the zero axis of the positive time domain waveform during stable operation when the voltage of the EHV DC transmission line fluctuates, and recognizing the fault and lightning stroke interference according to the ratios; switching to fault classification recognition if the interference is a fault, carrying out the wavelet decomposition recognition of an additional component through wavelet, and judging whether the fault is a grounding fault or a lightning stroke fault; and switching to a shielding failure and back flashover fault recognition if the fault is the lightning stroke fault. The method achieves the time frequency analysis of the simulation data, achieves the extraction of data in a short time period, and integrates area ratios, energy spectrum similarity and modular maximum value. The method achieves the extraction of a set of criteria for thunder interference, grounding faults, back flashover faults and shielding failures, and can achieve the accurate, quick and effective recognition of various types of conditions.

An information acquiring apparatus includes a light source portion for generating pulse-shaped pump light, and first and second probe light in synchronization with each other. A generating portion generates terahertz pulses when irradiated with the pump light. A detecting portion detects pulses of terahertz radiation from the object. A first delay portion adjusts an optical path difference between optical paths of the pump light and the first probe light reaching the detecting portion, so that the detecting portion detects a field intensity of a fixed point on the time domain waveform of the terahertz pulse from the object, following the fixed point. A second delay portion adjusts an optical path difference between the optical path of the pump light and the second probe light reaching the detecting portion by a sum of an additional optical path adjustment amount and the optical path difference, so that the detecting portion obtains the time domain waveform. A correction processing portion compensates for influence of a change in condition of the object on the time domain waveform, using the field intensity of the fixed point, or the adjustment amount adjusted by the first delay portion.

A signal processing apparatus includes a signal output unit for outputting a measurement signal, the measurement signal being produced by synthesizing a signal composed of a concatenation of 2d period signals with a sinusoidal signal, each period signal having a time-domain waveform period being 2n samples, the sinusoidal wave having a wave count within the concatenation period of 2d period signals being other than an integer multiple of 2d, and n and d being respectively natural numbers, and an analyzing unit for frequency analyzing a response signal obtained as a result of picking up the measurement signal output from the signal output unit.