Method of searching for faulty module in dynamic system |
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IPC classes for russian patent Method of searching for faulty module in dynamic system (RU 2451319):
 Method to generate tests for control of operability and diagnostics of faulty equipment / 2441271
Generation of control and diagnostic tests is carried out on the basis of mathematical models of control objects built on circuits of electric principal control objects, mathematical models of electric radio elements (ERE) and parameters of electric signals for passport modes of ERE operation, and generation of reference thermal portraits of radioelectronic equipment (REE) items - a control object - is carried out by means of synthesis on the basis of individual thermal portraits of ERE of appropriate types and a drawing of the control object overview.
 Automated repair bench (bars) / 2421787
Automated repair bench comprises a computer with software and hardware, which includes 10 input-output devices, an analogue generator, a logical analyser, a digital oscillograph, power supply units, an internal local bus, a unit of external slots for connection of a tested device, and also an intellectual controller, comprising an inbuilt 32-digit processor on a crystal (NIOS-processor), connected to the computer along a USB bus and with a main memory of a fast memory DDR type, and also with a bus arbiter connected to an address port and an input-output port of the intellectual controller, connected with the internal local bus, at the same time all internal devices of hardware are controlled by the 32-digit processor on a crystal (NIOS-processor) along the internal local bus. (n+1) relay control units are connected to the internal local bus, and each of them comprises 64 input-output lines, ensuring operation with radio-electronic equipment, comprising electromagnet relays. Each relay control unit comprises (n+1) input-output devices, every of which comprises 64 input-output lines.
 Method of creating control-diagnostic tests / 2413976
In the method of creating control-diagnostic tests before creating the tests through digital shooting in optical range, pictures of the non-component side of the article with clear identification of types of radio components thereon and their position is obtained. For each combination of input test electrical signals, simultaneously with determination of standard values of parametres of electrical response signals from outputs of a standard sample of the article of the given type which is known to be fault-free, standard digital infrared images of the standard sample of the article of the given type are obtained through digital infrared video shooting, where the said infrared images display the differences between thermal conditions of the radio components in places where they are located on the fault-free standard sample of the article of the given type. The obtained data are entered into the computer data base of the control-diagnostic installation and are used for subsequent monitoring of correct operation and diagnosing faults in articles of the given type.
 Automated device for testing microprocessor systems / 2392657
Invention relates to micro- and nanotechnology and can be used when controlling and diagnosing microprocessor systems. The automated device for testing microprocessor systems contains the following: a testing module (1), units for permanent (2) and on-line storage of data, a unit for processing results and information (5), a control unit (4) which is a switch, a setting device (8), first (6) and second (7) interfaces. The units for permanent (2) and on-line (3) storage of data and the control unit (4) can be made as part of the tested object.
 Communication network simulation method / 2379750
Invention relates to simulation and can be used in designing radio-electronic, engineering systems for evaluating operational characteristics. The outcome is achieved by measuring performance indices of a real communication network, simulating functioning processes of the simulated communication network and comparing the values.
 Microcomputer and method of its testing / 2374679
Microcomputer (ASIC) comprises multiple integral circuits (IC), which are connected to each other with interfaces that are synchronous to data sources. At first test data is input into trigger for data transfer (F1) and trigger for transfer of clock pulse (F2) into IC on the side of data transfer. Then circuit (11) of phase locking generates clock signal, in response to which the first and second triggers send test data and clock pulse. Triggers (F3, F4) for reception of IC data on the side of data reception, test data is registered, which come from the first trigger (F1) in compliance with clock pulse, which comes from trigger (F2).
 Method for distributed monitoring and adaptive control of multilevel system and apparatus for realising said method / 2450335
Method for distributed monitoring and adaptive control of a multilevel system is based on the adaptive control system principle. During normal operation, a distributed structure is viewed by a wide on-line field having low-resolution which is sufficient for detecting a local disturbance. Further, the on-line field is narrowed in the vicinity of the disturbance which is viewed in more detail and through fine analysis, the nature of what is happening in is determined (recognition) in a specific decision block. The apparatus, which is in form of a decision unit for determining the state of the multilevel system, operates in three modes: current monitoring, monitoring error estimation and training.
Process parameter transmitter having acceleration sensor / 2450311
Process parameter transmitter for use in a system for controlling or monitoring a production process has a transmitter housing and a process parameter sensor, having a sensor output signal associated with the process parameter. The accelerometer is connected to the transmitter and provides an accelerometer output signal associated with acceleration. The diagnostic circuit provides a diagnostic output signal as a function of the sensor output signal and the accelerometer output signal.
 Method of testing aircraft pedal system and device to this end / 2450310
Proposed device comprises aircraft pedal actuator, transducer to measure force applied to aircraft pedal to actuate it and to generate signal corresponding to force applied, device to measure deviation of component in response to actuation of aircraft pedal, and control unit to process signals from force transducer and deviation meters to generate output signals indicating aforesaid deviation depending on force applied to aircraft pedal.
 Method of searching for faults in dynamic unit in continuous system / 2450309
Reaction of a properly operating system to an input action is first recorded on an interval at control points at discrete moments in time; output signals of a model for each of the control points obtained as a result of trial deviations of parameters of all units are determined, for which trial deviation is successively introduced into each transfer function parameter for all units of the dynamic system and output signals of the system are found for the same input action; the resultant output signals for each of the control points and each of the trial deviations at discrete moments in time are picked up; deviations of signals of the model, which are obtained as a result of trial deviations of corresponding parameters of all structural units from the reaction of the properly operating system are determined; the system with nominal characteristics is replaced with the controlled system; a similar test signal is transmitted to the input of the system; signals of the controlled system for control points at discrete moments in time are determined; deviations of signals of the controlled system for control points at discrete moments in time from nominal values are determined; diagnostic features for each of the parameters are determined from the relationship; a faulty parameter is determined from the minimum value of the diagnostic feature.
 Method of searching for faulty module in discrete dynamic system / 2444774
Unlike the existing method of searching for a faulty module in a continuous dynamic system, the reaction of a time-discrete system know to be properly functioning is recorded for discrete diagnosis cycles with pitch in control points; integral estimates of output signals are determined, for which at the moment of transmitting a test signal, discrete integration of signals is simultaneously initiated with pitch in each of the control points by transmitting signals to inputs of multiplier units, and a discrete exponential signal to second inputs of the multiplier units; output signals of the multiplier units are transmitted to inputs of the discrete integration units; integration is completed at the control instant; the obtained estimates are recorded; integral estimates of model signals are determined for each control point, for which a sample deviation of the parameter of the discrete transfer function is successively entered into each unit of the system and integral estimates of output signals of the system obtained as a result of integrating output signal estimates for each control point are found and each of the sample deviations is recorded; a defective module of the discrete system is determined by the minimum of the diagnostic feature.
 Determination method for dynamic parameters of marine movement mathematical model / 2442718
FIELD: ship navigation. SUBSTANCE: invention refers to ship navigation and can be used for forecasting the ship movements in the course of maneuvering. The fore and backward points are conditionally used. The fore and backwards points are located on the centerline plane of the ship. On a real time basis the coordinates of the fore and backward points are measured. Measurement of the coordinates is fulfilled with the help of the static shear stress receivers and with differential corrections. On the basis of the coordinate measurement results the current values of kinematic movement parameters are determined: linear speeds of the fore F (υf) and backward A (υa) points and their longitudinal (υfx, υax) and lateral (υfy, υay) components in the moving coordinates ZX0Y connected with the ship; longitudinal centre of the rotation (x0) in the moving coordinates ZX0Y connected with the ship; projection of the linear speed vector in the centre of gravity on the y axis 0Y (υy); linear speed of the ship centre of gravity (υ); curvature of the gravity path (R); angular rate of the ship (ω). The obtained results are used for calculation of the current values of the dynamic parameters of the marine movement mathematical model. On the basis of the mathematical model computer modeling is performed in order to forecast the ship movements in the course of maneuvering. EFFECT: improvement of the accuracy of forecasting of the ship movements in the course of maneuvering on the basis of an adequate mathematical model of its travel. 3 cl, 1 dwg  Method of operating industrial plant, and industrial plant control system / 2440596
Proposed method controlling certain number of plant operating parameters and process component parameters and stored in memory unit. Note here that fatigue index inherent in current state of component fatigue is defined. Note also that forecast fatigue is defined. Besides, component with maximum forecast fatigue is identified as drive component, while for multiple preset changes of states, defined is drive component forecast fatigue. Mind that proceeding from certain forecast fatigue values, one of state changes is selected and initiated.
 Method to search for faulty block in dynamic system / 2439648
Response of an admittedly faultless system is registered at a control interval in control points, several integral estimates are determined for output signals of the system for various integration parameters, the produced integral estimates of output signals are registered; several deviations are determined in integral estimates of model signals for each of control points received as a result of trial deviations of block parameters, for this purpose a trial deviation is introduced alternately in each unit of a dynamic model; deviations of model signal integral estimates are determined, produced as a result of trial deviations of structural block parameters; rated values are determined for deviation of integral estimates of model signals, produced as a result of trial deviations of appropriate block parameters; a system with rated characteristics is substituted with a controlled one, integral estimates of controlled system signals are determined for control points and several integration parameters, deviations are determined for integral estimates of controlled system signals for control points from rated values, rated values are determined for deviations of integral estimates of controlled system signals.
 Method to search for faulty block in continuous dynamic system / 2439647
As opposed to the available method of searching for a faulty block in a continuous dynamic system, elements of topological links are determined for each block included into the composition of the system for each control point Pji, j=1, …, k; j=1, …, m, elements Pji are determined from multiple values {-1,0,1}, the value -1 is determined, if the sign of signal transfer from the output of the i block to the j control point is negative, the value 0 is determined, if transfer of a signal from the output of the i block to the j control point is not available, the value 1 is determined, if the signal of signal transfer from the output of the i block to the j control point is positive, rated values are determined for elements of the vector of topological links for each block, diagnostic criteria are calculated, and using minimum value of a diagnostic criterion, the defect is determined.
 Parameter control method of guided missile rotating about angle of roll, and automated control system for its implementation / 2438098
Parameter control method of guided missile rotating about angle of roll involves assignment of signals simulating the commands and rotation of missile about the roll angle, their supply to missile guidance control, comparison of current values of control commands at the outlet of control equipment with pre-set simulating values and evaluation as per comparison results of the compliance of controlled parameters with the specified ones, at which the simulating signal of missile rotation about roll angle is shaped in the form of two pulse signals. Pulse signals are offset relative to each other through 90°. At the required period of the beginning of control process there generated is the signal simulating the beginning of the guided missile flight, which is synchronised with the first front of one of two pulse signals, which corresponds to the beginning of shaping of the pitch command. Synchronised signals are allowed to shape pulse signals at the output of signal simulator of missile rotation about roll angle from the beginning of pitch command shaping; at that, from the beginning of signal shaping or its synchronisation there performed is time count during which the parameter control of guided missile is performed. Also, system for method's implementation is described.
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FIELD: information technology. SUBSTANCE: number of dynamic modules of a controlled system is determined, the reaction of a good system is recorded at an interval at control points and integral estimates of output signals of the system are determined. System signals are transmitted to the first inputs of multiplier units; an arithmetic mean value of moduli of signal time derivatives is transmitted to second inputs of the multiplier units; output signals of the multiplier units are transmitted to inputs of integration units; integration is completed at a certain moment in time; output signal estimates obtained from integration are recorded; simultaneously, integral estimates of signals of models are determined for each of the control points, obtained as a result of test deviations of parameters of each of the modules, for which a corresponding test deviation of parameters is introduced into each model for the dynamic system module. Deviations of integral estimates of signals of the model, obtained as a result of test deviations of parameters of corresponding modules, are determined. Standardised values of deviations of integral estimates of signals of the model are determined. Standardised values of deviations of integral estimates of signals are determined. Diagnostic features are determined and a faulty module is determined from the minimum value of the diagnostic feature. EFFECT: increased noise-immunity of diagnosing continuous automatic control systems. 1 dwg
The invention relates to the field of control and diagnostics of automatic control systems and their elements. The known method of dynamic control block the system control (Patent RF №2136033, MKI6G05B 23/02, 1999), based on the integration of the output and input signals of the block with a weight of e-αtwhere α is a real constant. The disadvantage of this method is that its application for control of multiple units of a control system of an arbitrary structure leads to the necessity of integration of input and output signals of each of the controlled block. The closest technical solution (prototype) is a way of finding a bad block in a dynamic system (a Positive decision from 12.07.2010, for a patent on the invention under the application №2009123999/08(033242), MKI6G05 23/02, 2010). The disadvantage of this method is that it involves the integration of special test signals using exponential weighting function and enables the detection of defects with low visibility, that is, has low noise immunity. Technical problem on which this invention is directed, is to expand the functionality of the method by applying the working diagnosis (without using testoval the impact), increasing the noise immunity of the method of diagnosing a continuous automatic control systems by improving the distinctiveness of defects and reduction of hardware costs for the calculation of the weighting function. This is achieved by replacing the exponential weight function, which is the arithmetic mean of modules derived time signal system with the nominal characteristics of the controlled system and models with pilot deviations. This object is achieved in that a fixed number m dynamic blocks of the controlled system, record the reaction of a known good system fj(t), j=1, 2,..., k on the interval Δji(d)=Rji(d)-(Fj(d), j=1,...,k; i=1,...,m, define the normalized Delta values of the integral estimates of the signal is s models, the resulting trial deviations of the respective blocks determine the deviation of the integral of the estimated signals of the controlled system for the k control points ∆ Fj(d)=Fj(d)-(Fj(d), j=1,...,k, define the normalized Delta values of the integral estimates of the signals of the controlled system determine diagnostic characteristics: the minimum values of the diagnostic characteristic to determine a defective unit. The essence of the method consists in the following. The method is based on the use of pilot deviations of the model parameters of a continuous dynamical system. To obtain diagnostic features dynamic elements are integral evaluation on the time interval Tkin the k control points The weight function in equation (4) in the average value of the modules derived signals at the test points carries information about the importance of time from the point of view of the rate of change of the signals in all the control points. More than the average rate of change of the signals, the more weight is integrated output signal. Using the vector interpretation of expression (3), we write it in the next view of the where φi(d) the angle between the normalized vector (a vector of unit length) of the variance of the integral estimates of the signals of the object Thus, the normalized diagnostic feature (3) represents the value of the square of the sine of an angle formed in the k-dimensional space (where k is the number of control points) normalized vectors trial variance of the integral of the estimated signal model and the real deformation of the integral estimates of the signals of the diagnostic object. Trial deviation of the parameter block that minimizes the value of the diagnostic sign (3), indicates the presence of a defect in this unit. The region of possible values of the diagnostic characteristic lies in the interval [0,1]. Thus, the proposed method of finding the defective block is to perform the following operations: 1. As dynamic systems consider a system consisting of randomly connected m dynamic elements. 2. Pre-determine the testing time TTo≥TPPwhere TPPthe time of transition processsystem. Transition time estimate for the nominal values of the parameters of the dynamic system. 3. Record the number of control points k. 4. At the same time serves the test signal x(t) (unit step) or work input control system with nominal parameters, the input of the controlled system, the inputs of the m models with nominal parameters, each of which introduced a trial deviations of one block so that the i-th system introduced trial deviation in the i-th block. 5. At the same time record the response of the system with the nominal characteristics of the fj(t), the response of the controlled system fj(t), reaction models with a trial variance in the i-th block of pji(t) in k control points j=1, 2,..., k on the interval 6. At the same time define the integral evaluation of the output signals Fj(d), j=1,...,k system with nominal characteristics of the controlled system Fj(d), j=1,...,k, models with a trial variance in the i-th block of Pji(d), j=1,..., k; i=1,...,m (formula 4). To this effect, when the input signal is simultaneously begin the integration of the signals in each of the k control points in the system with the nominal characteristics of the controlled system, models with a trial deviations blocks with weight function equal to the average of arithmetices the mu value of modules derived signals at the test points, where the averaging is done according to the number of control points, to which output signals of each system serves to first inputs of the k blocks multiplication on the second input units of the multiplication serves an average of modules derived signals at the test points, where the averaging is done according to the number of control points of the output signals, the output signals of the k blocks multiplication served on inputs k blocks of integration, integration completed at time Ttoobtained by integrating the evaluation of the output signals Fj(d), j=1,...,k, Fj(d), j=1,...,k, and Pji(d), j=1,...,k; i=1,...,m register. 7. Determine the deviation of the integral of the estimated signal model, the resulting trial deviations of the respective blocks ΔPji(d)=Pji(d)-(Fj(d), j=1,...,k; i=1,...,m. 8. Define the normalized variance of the integral of the estimated signal model, the resulting trial deviations of the respective units according to the formula:
9. Determine the deviation of the integral of the estimated signals of the controlled system for the k control points from the nominal values ∆ Fj(d)=Fj(d)-(Fj(d), j=1,...,k. 10. Calculate the normalized values of the variance of the integral estimates of signals to the control system by the formula:
11. Calculate the diagnostic signs of a defective block by the formula (3). 12. The minimum values of the diagnostic sign determine the defective block. Because diagnostic criteria (3) have a range of possible values bounded by the interval [0,1], then the difference between the closest to the minimum characteristic and minimal sign (which indicates that the defective block) quantifies the appearance of the defect with respect to the location of the block on the block diagram, type and parameters of the transfer functions of the blocks and all of the terms of diagnosis, in which these values are diagnostic features (number and location of control points, the value of the interval Tto). The best appearance of defects is provided when the difference is equal to (in terms of the vector interpretation of the normalized vectors of deformation of integral transformations of the dynamic characteristics of these blocks for trial orthogonal deviations). The worst visibility - when the difference is equal to zero (in terms of the vector interpretation of the normalized vectors of deformation of integral transformations of the dynamic characteristics of these units to test deviations collinear). Consider the implementation of the FPIC of the BA search single defect system, structural diagram of which is presented on the figure (see drawing). Transfer function block:
where the nominal parameter values: T1=5; K1=1; K2=1; T2=1; K3=1; T3=5 C. When modeling as an input signal we use a pseudo-random signal (when modeling were used unit Band-Limited White Noise in Matlab). The time control will choose Ttoequal to 10 C. The value trial deviations of the model parameters chosen equal to 10%. Modeling of finding defects in the first block (in the form of reduction of the parameter T120%) leads to the calculation of diagnostic signs by the formula (3): J1=0, J2=0.2067, J3=0.2266. The appearance of the defect: ΔJ=J3-J1=0.2067. For comparison, see diagnostic signs of a defective block with exponential weight one option of integration α=0.5 (a Positive decision from 12.07.2010, for a patent on the invention under the application №2009123999/08(033242), MKI6G05 23/02, 2010): J1=0, J2=0.7828, J3=0.07399. The appearance of the defect ΔJ=J3-J1=0.07399. The results show that the actual appearance of finding defects by this method is higher, therefore, you who have and robustness of the method. Modeling of finding defects in the second block (in the form of reduction of the parameter T220%) of the diagnostic object using the differential weight and with the same input gives the following values of diagnostic features: J1=0.2752, J2=0.006981, J3=0.7004. The appearance of the defect ΔJ=J3-J2=0.2682. For comparison, see diagnostic signs of a defective block with exponential weight one option of integration α=0.5: J1=0.7828, J2=0, J3=0.7462. The appearance of the defect: ΔJ=J3-J2=0.7462. Modeling of finding defects in the third block (in the form of reduction of the parameter T320%) of the diagnostic object under the same conditions gives the following values: J1=0.1824, J2=0.5691, J3=0.003594. The appearance of the defect: ΔJ=J1-J3=0.1788. For comparison, see diagnostic signs of a defective block with one parameter of integration α=0.5: J1=0.07403, J2=0.7463, J3=0. The appearance of the defect ΔJ=J1-J3=0.07403. The minimum value of the diagnostic sign in all cases correctly points to the defective block, and this method in two cases out of three improves the actual appearance of defects, followed the Sabbath.) increases the immunity of the diagnosis. In addition, the inventive method allows the diagnosis of the real functioning of the diagnostic object (working diagnosis). The way of finding a bad block in a dynamic system, based on the fact that a fixed number m of dynamic elements included in the system, determine the testing time TTo≥TPPuse the input signal x(t) on the interval t∈[0, TK]fix a number k control points in the system, record the response of the controlled system fj(t), j=1, 2, ..., k, record the response of the system with the nominal characteristics of the fj(t), j=1, ..., k, in the interval t∈[0, TK] k control points that define the integral evaluation of the output signals of the system, which at the time of filing of the signal at the input of the system with nominal characteristics simultaneously begin the integration of the signals in each of the k control points by submitting to the first inputs of the k blocks multiplying output signals of the system, on a second input units of the multiplication serves weighting function, the output signals of the k blocks multiplication served on inputs k blocks of integration, integration completed at time Ttoobtained by integrating the evaluation of the output signals of the register definition is given in the integral evaluation of the output signals of the model for each of the k control points, the resulting trial deviations of each of the m blocks, and for each block of a dynamic system is administered trial deviation parameter transfer function and find the integral evaluation of the output signals of the model for the weighting function and the input signal x(t), obtained by integrating the evaluation of the output signals for each of the k control points and each of the m test register deviations, determine the deviation of the integral of the estimated signal model, the resulting trial deviations of the respective blocks ΔPji(d)=Pji(d)-(Fj(d), j=1, ..., k; i=1, ..., m, define the normalized variance of the integral of the estimated signal model, the resulting trial variance parameters of the corresponding blocks from the relation:
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