Rotary machine diagnostic device and rotary machine diagnostic method

Abstract

To provide a rotary machine diagnostic device and rotary machine diagnostic method capable of identifying a failure occurrence place and inferring a failure cause, regarding an unbalance occurrence event of a rotor.SOLUTION: A rotary machine diagnostic device 100 comprises: an input section 110 that receives calculation condition data including reference data and an influence coefficient matrix, and a measured state value of a rotating section including vibration data, rotation speed, and phase calculation data for phase calculation; a calculation section 130 that performs calculation for identifying a failure occurrence place and inferring the failure cause on the basis of the calculation condition data and the measured state value received by the input section 110; a storage section 120 that stores a calculation result including the calculation condition data, the measured state value, a vibration mode obtained by the calculation section 130; and an output section 140 that outputs and displays contents stored in the storage section 120.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] An embodiment of the present invention relates to a rotating machine diagnostic device and a rotating machine diagnostic method. [Background technology]

[0002] In order to improve the availability of equipment in power plants, the development of a fault diagnosis system for power plants using IoT (Internet of Things) technology is being considered. However, in order to perform such fault diagnosis appropriately, the problem is how to configure a database and algorithms for detecting faults and signs of faults accurately from measurement data.

[0003] As a first example of a conventional system for the purpose of condition monitoring, a system is known in which a sensor, typically a vibration sensor, is attached to a target device and an abnormality in the device is identified based on measurement data obtained from the sensor. For example, an abnormality diagnosis system is known that includes a vibration detection sensor installed in the rotating machine to be diagnosed, a calculation processor that converts the detection signal from the vibration detection sensor into vibration data, and an information processing device that performs diagnosis based on the vibration data from the calculation processor.

[0004] As a second example, an anomaly detection device is known that calculates a vibration vector indicating the rotation angle at which the vibration of the rotating shaft is at its maximum and the magnitude of the vibration based on the measured values ​​of the vibration and rotation angle of the rotating shaft provided by multiple shaft vibration sensors, and estimates the position where the abnormality has occurred in the axial direction of the rotating shaft based on the change in this vector over time. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 3834228 [Patent Document 2] JP 2019-113364 A Summary of the Invention [Problem to be solved by the invention]

[0006] Shaft vibrations observed during operation of turbines and generators have various causes and have corresponding frequency components.Most of the vibrations have rotation-synchronous components caused by changes in the balance state due to changes in weight imbalance or shaft bending during operation, depending on the failure mode that occurs in each rotating part.

[0007] Normally, the distribution of imbalance in a rotating part is unknown, but by measuring the amplitude and phase of the rotating part during operation, it is possible to estimate the distribution. By determining where on the rotating part the imbalance has occurred and by estimating the failure event and factors that caused it, necessary measures can be implemented in a short time, leading to improved plant operation rates.

[0008] In the first example of the anomaly diagnosis system described above, data related to one type of frequency generated during operation of a rotating machine is converted to create one converted data set, and the cause of the anomaly is identified based on that converted data set. However, the same frequency may contain multiple anomaly factors, making it difficult to narrow down the cause of the anomaly with this configuration.

[0009] Furthermore, in the second example of the abnormality diagnosis system described above, similar to the first example, the location of the abnormality is estimated for a wide variety of abnormal phenomena that occur in the rotating shaft by matching the vibration vector when an abnormality actually occurs in a specific location in the rotating part of the actual machine or in the same type of machine with the current situation vector, so that abnormalities cannot be detected in the case of abnormal phenomena for which there is no actual data or in the case of a newly installed machine.

[0010] The present invention has been made to solve these problems, and has an object to provide a rotating machine diagnostic device and a rotating machine diagnostic method that make it possible to identify the location of a fault and estimate the cause of the fault when an unbalance occurs in a rotating part of a rotating machine during operation. [Means for solving the problem]

[0011] In order to achieve the above-mentioned object, a rotating machine diagnostic device according to an embodiment of the present invention is a rotating machine diagnostic device for identifying a location of a fault and estimating a cause of a fault in relation to an unbalance occurrence event of a rotating part during operation of a rotating machine, and is characterized in having an input unit that accepts calculation condition data including reference data and an influence coefficient matrix, and state measurement values ​​of the rotating part including vibration data, rotation speed, and phase calculation data for phase calculation, a calculation unit that performs calculations for identifying the location of the fault and estimating the cause of the fault based on the calculation condition data and state measurement values ​​accepted by the input unit, a memory unit that stores calculation results including the calculation condition data, the state measurement values, and the vibration mode obtained by the calculation unit, and an output unit that outputs and displays the contents stored in the memory unit. [Brief description of the drawings]

[0012] [Figure 1] 1 is a block diagram showing a configuration of a rotating machine diagnostic device according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of a rotating part of a rotating machine to which a rotating machine diagnostic device according to a first embodiment is applied. [Diagram 3] 1 is a conceptual diagram showing a vibrometer and a phase detector for a rotating part of a rotating machine to which a rotating machine diagnostic device according to a first embodiment is applied. [Figure 4] 1 is a conceptual diagram showing a vibrometer for a rotating part of a rotating machine to which a rotating machine diagnostic device according to a first embodiment is applied. [Diagram 5] 1 is a conceptual diagram showing a first example of a phase detector for a rotating part of a rotating machine to which a rotating machine diagnostic device according to a first embodiment is applied. [Figure 6] 4 is a conceptual diagram showing a second example of a phase detector for a rotating part of a rotating machine to which the rotating machine diagnostic device according to the first embodiment is applied. FIG. [Figure 7] 1 is an explanatory diagram of a model of an example of a rotating part of a rotating machine to which a rotating machine diagnostic device according to a first embodiment is applied. [Figure 8] 1 is a flowchart showing an overall procedure of a rotating machine diagnosis method according to a first embodiment. [Figure 9] FIG. 4 is a flowchart showing details of an unbalance position derivation step in the procedure of the diagnostic method during start-up and shutdown of the rotating machine diagnostic method according to the first embodiment. [Figure 10] 3 is a flowchart showing the procedure of a method for identifying and diagnosing a fault occurrence location during rated speed operation, in the rotating machine diagnosis method according to the first embodiment. FIG. [Figure 11] 4 is a display example of a polar diagram in the case of thermal vibration obtained in the procedure of the method for identifying and diagnosing a fault location during rated rotation operation in the rotating machine diagnosis method according to the first embodiment. FIG. [Figure 12] 1 is a display example of a polar diagram in the case of cyclic vibration due to hard rub obtained in the procedure of a method for identifying and diagnosing a fault occurrence location during rated rotation operation in the rotating machine diagnosis method according to the first embodiment. FIG. [Figure 13] 1 is a display example of a polar diagram in the case of cyclic vibration due to soft rub obtained in the procedure of a method for identifying and diagnosing a fault occurrence location during rated rotation operation in the rotating machine diagnosis method according to the first embodiment. FIG. [Figure 14] FIG. 11 is a flowchart showing the overall procedure of a rotating machine diagnosis method according to a second embodiment. [Figure 15] FIG. 11 is a block diagram showing the configuration of a rotating machine diagnostic device according to a third embodiment. [Figure 16] FIG. 11 is an explanatory diagram of a process performed by a data processing unit in a rotating machine diagnostic method according to a third embodiment. [Figure 17] 13 is a first judgment table showing judgment conditions in a method for identifying and diagnosing a fault occurrence location during rated rotation operation in a rotating machine diagnosis method according to a third embodiment. [Figure 18] 13 is a second judgment table showing judgment conditions in a method for identifying and diagnosing a fault occurrence location during rated rotation operation in a rotating machine diagnosis method according to a third embodiment. [Figure 19] 13 is a third judgment table showing judgment conditions in a method for identifying and diagnosing a fault occurrence location during rated rotation operation in a rotating machine diagnosis method according to a third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, a rotating machine diagnostic device and a rotating machine diagnostic method according to an embodiment of the present invention will be described with reference to the drawings. Here, the same or similar parts are denoted by the same reference numerals, and duplicated explanations will be omitted.

[0014] [First embodiment] FIG. 1 is a block diagram showing the configuration of a rotating machine diagnostic device 100 according to a first embodiment.

[0015] The rotating machine diagnostic device 100 has an input unit 110 , a storage unit 120 , a calculation unit 130 , an output unit 140 , and a time counter 150 .

[0016] The input unit 110 receives the calculation condition data and the state measurement values ​​as input. Here, the calculation condition data is information required when the calculation unit 130 performs the calculation. The calculation condition data includes, for example, the reference data and the influence coefficient matrix described later, as well as various judgment reference values ​​required for judgment in the progress of the diagnosis of the rotating machine diagnostic device 100. The state measurement values ​​are the outputs of each detector that measures the state of the rotating part 10a (FIG. 2) of the rotating machine 10, including the vibration data, the rotation speed, the phase calculation data for phase calculation, and the output and load of the rotating machine 10. Here, the vibration data is, for example, the amplitude value for each sampling time interval. These will be described in detail later with reference to FIG. 2.

[0017] The storage unit 120 includes a reference data storage unit 121 , an influence coefficient matrix storage unit 122 , a vibration data storage unit 123 , a phase storage unit 124 , and a calculation result storage unit 125 .

[0018] The reference data storage unit 121 and the influence coefficient matrix storage unit 122 respectively store the reference data and the influence coefficient matrix received by the input unit 110. The vibration data storage unit 123 stores the vibration data received by the input unit 110. The phase storage unit 124 stores the phase calculation data for phase calculation received by the input unit 110 and the rotation speed. The calculation result storage unit 125 stores the calculation results performed by the calculation unit 130, i.e., the vibration vector, the vibration vector difference, the data for the polar diagram, the unbalance distribution, the vibration mode, etc., which will be described later.

[0019] The calculation unit 130 performs calculations to identify the location of a fault in the rotating machine 10 and to estimate the cause of the fault, based on the calculation condition data and the state measurement values ​​accepted by the input unit 110. The calculation unit 130 has a phase calculation unit 131, a vibration vector derivation unit 132, a difference vector calculation unit 133, a polar diagram data creation unit 134, an unbalance calculation unit 135, a fault cause estimation unit 136, and a progress control unit 137.

[0020] The phase calculation unit 131 calculates the phase of the rotating part 10a based on the phase calculation data, the details of which will be described later with reference to FIG.

[0021] The vibration vector derivation unit 132 derives a vibration vector based on the vibration data. The derived vibration vector is stored and saved in the calculation result storage unit 125.

[0022] The difference vector calculation unit 133 calculates the vibration vector difference from the vibration vector. The calculated vibration vector difference is stored and saved in the calculation result storage unit 125.

[0023] The polar diagram data creation unit 134 creates data for a polar diagram using the phase calculated by the phase calculation unit 131 and the vibration vector created by the vibration vector derivation unit 132. The created data for a polar diagram is stored and saved in the calculation result storage unit 125.

[0024] The unbalance calculation unit 135 calculates the unbalance distribution of the rotating unit 10a based on the vibration vector created by the vibration vector derivation unit 132 and the influence coefficient matrix stored in the influence coefficient matrix storage unit 122. The calculated unbalance distribution is stored in the calculation result storage unit 125.

[0025] The failure factor estimation unit 136 determines and estimates a failure factor causing vibration of the rotating unit 10a based on the calculation results stored in the memory unit 120. The failure factor estimation unit 136 stores a judgment value for discrimination included in the calculation condition data received by the input unit 110.

[0026] The progress control unit 137 controls the progress of the sequence of operations of each element of the rotating machinery diagnosis device 100. In other words, it performs judgments required for the progress of the procedure of the rotating machinery diagnosis method and instructs each element to move to the next step. The progress control unit 137 stores judgment reference values ​​required for judgment read by the input unit 110 and uses them for judgment made by the progress control unit 137.

[0027] FIG. 2 is a conceptual diagram showing an example of a rotating part 10a of a rotating machine 10 to which the rotating machine diagnostic device 100 according to the first embodiment is applied.

[0028] 2 shows an example of a steam turbine and a generator as the rotating machine 10. The rotating section 10a has two low-pressure turbines 12, a generator 13, and an exciter 14, and a rotor shaft 11 that connects these in series. However, the rotating machine 10 is not limited to this. The rotating section 10a is rotatably supported by a plurality of bearings 15.

[0029] A vibration meter 16 is provided near each bearing 15. The vibration meter 16 measures vs i (i=1 to M). A phase detector 17 and a tachometer 18 are provided to face the rotating part 10a. The rotating machine diagnostic device 100, the vibration meter 16, the phase detector 17 and the tachometer 18 constitute a rotating machine diagnostic system 200.

[0030] Fig. 3 is a conceptual diagram showing a vibrometer 16 and a phase detector 17 for a rotating part 10a of a rotating machine 10 to which the rotating machine diagnostic device 100 according to the first embodiment is applied. Also, Fig. 4 is a conceptual diagram showing a vibrometer 16 for a rotating part of a rotating machine to which the rotating machine diagnostic device according to the first embodiment is applied.

[0031] The vibration meter 16 outputs a time change in vibration at each detection position. The vibration meter 16 is, for example, a non-contact type displacement sensor such as an eddy current type non-contact sensor that measures a gap (gap) between the rotating part 10a and the vibration meter 16.

[0032] FIG. 4 illustrates an example in which two vibrometers 16 are provided at the same location in the axial direction, at an angle of 90 degrees to each other. The direction may be horizontal or vertical, and the angle is not limited to 90 degrees. In this way, a plurality of vibrometers 16 may be provided at the same location in the axial direction, but in different directions (directions toward the axial center, angles). In this case, vs i A different number (i) shall be assigned to each of the following:

[0033] Fig. 5 is a conceptual diagram showing a first example of a phase detector 17 for a rotating part 10a of a rotating machine 10 to which the rotating machine diagnosis device 100 according to the first embodiment is applied. Fig. 6 is a conceptual diagram showing a second example of a phase detector 17 for a rotating part 10a of a rotating machine 10 to which the rotating machine diagnosis device 100 according to the first embodiment is applied.

[0034] 3, the phase detector 17 is generally provided at an axial position of the rotating part 10a slightly outside of the vibrometer 16. The phase detector 17 is provided to detect the rotation angle, in other words, the phase, of the rotating part 10a.

[0035] The phase detector 17 is a collective term for, for example, a reference marker 17a provided at one location in the circumferential direction on the outer circumferential surface of the rotor shaft 11 of the rotating part 10a, and a pulse detector 17b provided in the vicinity of the reference marker 17a. Here, as the reference marker 17a, for example, in the first example shown in Fig. 5, a slit 10b formed on the surface of the rotating part 10a is used, and in the second example shown in Fig. 6, a reflective tape 10c attached to the surface of the rotating part 10a is used.

[0036] The pulse detector 17b detects one pulse every time the rotating part 10a rotates once. That is, the phase detector 17 outputs one pulse every time the rotating part 10a rotates once. If the time interval between pulse occurrences is ΔT and the time counter 150 counts J times during this time, the phase α (degrees) is calculated by the following formula (1) at the jth count after the time Δt has elapsed since the previous pulse occurrence. α=360·(Δt / ΔT)=360·(j / J) …(1)

[0037] The phase calculation unit 131 performs the above-mentioned calculation and calculates the phase at the time of occurrence of the peak value for the output (time change of amplitude) of each vibration meter 16. Note that, although the phase calculation data here refers to the pulse signal in this example, it is not limited to this as long as a similar calculation is possible.

[0038] A revolution speed meter 18 is provided at the end of rotor shaft 11. Revolution speed meter 18 is a collective term for a gear (not shown) provided on rotor shaft 11 and a revolution speed detector (not shown) provided on the stationary side near the gear. The revolution speed detector converts changes in magnetic permeability due to unevenness of the gear, for example, into a pulse signal and outputs it.

[0039] FIG. 7 is an explanatory diagram of a model in an example of a rotating part 10a of a rotating machine 10 to which the rotating machine diagnosis device 100 according to the first embodiment is applied. In FIG. 7, the rotating part 10a is modeled by an out-of-plane bending stiffness Gb(x) extending along the axial direction x that depends on x, and a number of nodes n (n=1 to N) associated with this that are distributed along the axial direction x.

[0040] FIG. 8 is a flowchart showing the overall procedure of the rotating machine diagnosis method according to the first embodiment.

[0041] First, the rotating machine diagnostic device 100 reads in the calculation condition data (step S11). In detail, the input unit 110 accepts the calculation condition data including the reference data, the influence coefficient matrix A, and various judgment criteria values ​​as input. The reference data and the influence coefficient matrix are stored in the reference data storage unit 121 and the influence coefficient matrix storage unit 122, respectively. In addition, the various judgment criteria values ​​are stored in the progress control unit 137.

[0042] Next, the rotating machine diagnostic device 100 reads in the state measurement values ​​(step S12). In detail, the input unit 110 receives as input the outputs of the detectors that measure the state of the rotating part 10a of the rotating machine 10, including the vibration data, the rotation speed, and the phase calculation data for phase calculation. The phase calculation unit 131 calculates the phase of the rotating part 10a based on the phase calculation data and the output of the time counter 150. The vibration data received by the input unit 110 is stored in the vibration data storage unit 123. In addition, the rotation speed received by the input unit 110 and the phase calculated by the phase calculation unit 131 are stored in the phase storage unit 124.

[0043] Next, the progress control unit 137 determines whether the rotating machine 10 to be diagnosed is in a rated rotation operation state (step S13). Here, rated rotation operation refers to operation at the rated rotation speed other than when the rotation speed is increasing or decreasing. In other words, it refers to a state in which the rated rotation speed is reached after the rotation speed increases, a state of the rated rotation speed before the rotation speed decreases, or, if the rotating machine 10 is a power generation device, a state in which it is connected to a power system and bears a load in synchronization with the power system. Or, if it is an electric motor, it refers to a state in which it is connected to a load such as a pump or a blower and drives the load.

[0044] If the progress control unit 137 determines that the rotating machine 10 is not in a rated rotation operation state (NO in step S13), the process proceeds to a start / shutdown diagnosis step S20. If the progress control unit 137 determines that the rotating machine 10 is in a rated rotation operation state (YES in step S13), the process proceeds to a rated rotation operation diagnosis step S30.

[0045] First, the start / shutdown diagnosis step S20 will be described below.

[0046] In the start / shutdown diagnosis step S20, first, a difference vector, which is a change in the vibration vector over time, is calculated (step S21). The following sequentially describes the first step of calculating the change in the vibration vector, deriving the vibration vector by the vibration vector derivation unit 132, and the second step of calculating the difference in the vibration vector by the difference vector calculation unit 133.

[0047] First, the derivation of the vibration vector, which is the first step, will be described.

[0048] The vibration vector derivation unit 132 determines the number of rotations n k (k=1 to K), each vibration value z is calculated based on the amplitude value obtained from the output of each vibration meter 16 and the phase obtained by the phase calculation unit 131. mk (m=1~M) is the partial vibration vector Z k The elements of are derived in polar coordinates in the following equation (2) and in x, y coordinate format shown in (3) and (4). z mk =A mk ·exp[j·(Θ mk ×π / 180)]=x mk +j·y mk …(2) x mk =A mk cos(Θ mk ×π / 180) …(3) y mk =A mk sin(Θ mk ×π / 180) …(4) However, Am k is the amplitude of the m-th vibration at the rotation speed n k, Θ mk is the rotation speed n k is the phase (in degrees) of the mth vibration value in, where j is the imaginary unit.

[0049] Here, the partial vibration vector Z k Z mk The vibration vector [Z] is an M-th order vertical vector with elements (m = 1 to M). k The partial vibration vector [Z k ] is an M·K-th order vertical vector obtained by vertically arranging the elements of [Z] for k = 1 to K. The vibration vectors [Z] derived by the vibration vector derivation unit 132 are stored in the calculation result storage unit 125 one by one.

[0050] Next, the calculation of the difference vector ΔZ, which is the difference of the vibration vector Z, by the difference vector calculation section 133, which is the second step, will be described.

[0051] Each vibration value z, which is an element of the vibration vector Z mk The amount of change over time in the x-coordinate component xmk and the y-coordinate component ymk of (m=1 to M, k=1 to K) over a certain time span is calculated using the following equations (5) and (6). Δx mk =x mk (t+Δt)-x mk (t) …(5) Δy mk =y mk (t+Δt)-y mk (t) …(6)

[0052] Also, in polar coordinate form, it is given as the following equations (7) and (8) to (10). ΔA mk =√[(Δx mk ) 2 +(Δy mk ) 2 ] …(7) Here, √[x] indicates the square root of x. Φ m k=90-tan[(Δx mk / Δymk )·(180 / π)] (Δy mk > 0)…(8) Φ mk =0 (Δy mk = 0)…(9) Φ mk =270-tan[(Δx mk / Δy mk )·(180 / π)] (Δy mk < 0)…(10)

[0053] The above is the calculation of the difference vector, which is the change in the vibration vector over time, in step S21. The difference vectors [ΔZ] calculated by the difference vector calculation unit 133 are stored in the calculation result storage unit 125 one by one.

[0054] Next, the progress control unit 137 calculates ΔA mk (m=1~M, k=1~K) is the judgment reference value ΔA J Compared with the judgment standard value ΔA J It is determined whether or not there is any that exceeds (step S22).

[0055] The progress control unit 137 determines ΔA mk The judgment standard value ΔA J If it is not determined that there is any that exceeds this limit (NO in step S22), steps S12 and S13 are repeated.

[0056] The progress control unit 137 determines ΔA mk The judgment standard value ΔA J If it is determined that there is an unbalance position exceeding this limit (YES in step S22), the unbalance calculation unit 135 derives the unbalance position (step S23).

[0057] After step S23, the progress control unit 137 judges whether or not to continue driving (step S53). If it is judged that driving should be continued (step S53: YES), the process proceeds to step S11. If it is judged that driving should be continued (step S53: NO), the progress control unit 137 takes measures to stop driving, such as issuing an alarm to instruct the driver to stop driving.

[0058] FIG. 9 is a flow chart showing details of the unbalance position derivation step S23 in the procedure of the diagnostic method during start-up and shutdown of the rotating machine diagnostic method according to the first embodiment.

[0059] In the unbalance position derivation step S23, first, the unbalance calculation unit 135 calculates the unbalance vector U (step S23a). Specifically, the unbalance calculation unit 135 calculates the unbalance vector U based on the influence coefficient matrix A read by the input unit 110 and stored and contained in the influence coefficient matrix storage unit 122, and the vibration vector Z stored in the calculation result storage unit 125.

[0060] First, the unbalance vector U and the influence coefficient matrix A will be described.

[0061] The unbalance vector U is the unbalance amount u at each node n (N = 1 to N). n is an N-th order vertical vector whose elements are

[0062] The influence coefficient matrix A is the influence coefficient a whose value is the vibration value generated at the mth vibration meter (m = 1 to M) when there is a unit imbalance at node n (n = 1 to N). mn It is an M × N matrix with elements:

[0063] From this definition, the vibration vector Z, the influence coefficient matrix A, and the unbalance vector U are related by the following equation (11). Z = A · U … (11)

[0064] The following describes how to estimate the unbalance vector U. There are two cases for estimating the unbalance vector U, depending on the magnitude relationship between the number M of vibration values ​​obtained by the vibration meter 16 and the number N of nodes n, i.e., the number N of unbalance positions.

[0065] The first case is when the number M of vibration values ​​is smaller than the number N of unbalance positions.

[0066] First, the M-th order error vector E is defined by the following equation (12). E = Zt-Z m =A·UZ m …(12)

[0067] Here, the vibration vector Zt is the vector of the true vibration value that is generated due to the unbalance vector U and should be obtained by equation (11), and the vibration vector Zm is the vector of the vibration value obtained by the vibration meter 16.

[0068] In this case, the least squares method is applied to minimize the error value EE according to the following equation (13). E-E=E * W1E+U * W2U …(13)

[0069] W1 is, for example, a diagonal matrix, and may be a unit matrix. The second term is a term for avoiding unrealistic solutions (distribution of U), and matrix W2 is a diagonal matrix, and may be a unit matrix first, and the element values ​​adjusted based on the results. Each element of diagonal matrix W2 is small enough to ensure the calculation accuracy of the imbalance vector U, and large enough to stabilize the calculation.

[0070] As a result, the unbalance vector U is given by the following equation (14). U=(A * W1A+W2) -1 A * W1Z m …(14) Here, A * is the conjugate transpose matrix (N × M matrix) of the influence coefficient matrix A, which is an (M × N matrix).

[0071] The second case is when the number M of vibration values ​​is greater than the number N of unbalance positions.

[0072] In this case, the Lagrange multiplier λ is introduced to minimize the error value EE according to the following equation (15). E-E-U * W2U+λ T (AU-Z m ) …(15)

[0073] As a result, the unbalance vector U is given by the following equation (16). U=W2 -1 A * (AW2 ―1 A * ) -1 Z m …(16)

[0074] Next, each element u of the calculated imbalance vector U n That is, each element u of the calculated imbalance vector U is transformed into n The x, Y coordinate value of (u nx , u ny ) into polar coordinates (u nr , u nΘ ) where the unbalance position is concentrated at one point, u nr is the magnitude of the disproportion, u nΘ is the circumferential angle of the unbalanced portion. u nr =√(u nx 2 +u ny 2 ) …(17) u nΘ =90-tan -1 [(u ny / u nx )×180 / π] (u ny > 0) =270-tan -1 [(u ny / u nx )×180 / π] (u ny< 0) =0 (u ny =0, u nx > 0) =180 (u ny =0, u nx < 0) …(18)

[0075] Next, the imbalance calculation unit 135 calculates each element u of the calculated vector U. n The magnitude u in polar coordinates nr The elements u of the vector U that have been sorted and rearranged by the imbalance calculation unit 135 are sorted in descending order (step S23b). n The order of the elements u of the vector U is stored in the calculation result storage unit 125. n The element number n and its size u nr and circumferential angle u nΘ is output to the output unit 140.

[0076] In response to this, the output unit 140 issues a warning to the operator or the like (step S23c). In detail, the output unit 140 outputs the position of the node n of the element with the largest element number n, the size u nr and circumferential angle u nΘ Information including the above will be displayed along with the alert.

[0077] The above is the procedure of the start / shutdown diagnosis step S20. Next, the rated speed operation diagnosis step S30 will be described with reference to FIG.

[0078] When it is determined that the rotating machine 10 is in a rated rotation operating state (YES in step S13), the input unit 110 reads the output of the rotating machine 10, i.e., the load (step S31). Here, for example, if the rotating machine 10 is a steam turbine and generator as shown in Fig. 2, the output may be the output of a utility power meter or the first stage pressure of the steam turbine.

[0079] Next, the rotating machine diagnosis device 100 calculates a vibration vector change (step S32). In detail, the vibration vector derivation unit 132 derives a vibration vector, and the difference vector calculation unit 133 calculates the difference of the vibration vector. The specific contents of these are the same as those performed in step S21, and therefore the explanation will be omitted.

[0080] Next, the rotating machine diagnosis device 100 identifies the location of the fault and estimates the cause of the fault (step S40). Details of step S40 will be described below with reference to Figs. 10 to 13 in this order.

[0081] FIG. 10 is a flow chart showing the procedure of the method of identifying and diagnosing a fault occurrence location during rated rotation operation (step S40) in the rotating machine diagnosis method according to the first embodiment.

[0082] First, the rotating machine diagnostic device 100 judges whether the vibration vector change is large or not (step S41). mk (m=1~M, k=1~K) is the judgment reference value ΔA LJ Compared with the judgment standard value ΔA LJ Determine whether there is anything exceeding

[0083] In step S41, the progress control unit 137 calculates ΔA mk (m=1~M, k=1~K) contains the judgment criterion value ΔA LJ If it is determined that there is a change exceeding this threshold (YES in step S41), the process proceeds to the next step S44 for determining whether or not the vibration change is instantaneous. The step S44 for determining whether or not the vibration change is instantaneous will be described later.

[0084] In step S41, the progress control unit 137 calculates ΔA mk (m=1~M, k=1~K) contains the judgment criterion value ΔA LJIf it is not determined that there is any value exceeding (NO in step S41), the progress control unit 137 determines whether or not the evaluation of thermal cyclic oscillation is continuing (step S42). The determination of thermal cyclic oscillation will be described later in step S49.

[0085] In step S42, when the progress control unit 137 determines that the evaluation of the thermal cyclic vibration is continuing (step S42: YES), the process proceeds to step S47, which will be described later.

[0086] In step S42, if the progress control unit 137 does not determine that the evaluation of the thermal cyclic vibration is being continued (step S42 NO), the number of times the process is performed in step S47 described later is reset, and since there is no problem, the process of END is performed.

[0087] The details of the aforementioned step S44 for determining whether or not the change is instantaneous will be described. First, the difference vector calculation unit 133 calculates a difference vector based on the vibration vector for each sampling interval derived by the vibration vector derivation unit 132. This is the same as step S21, so a detailed description will be omitted. Next, the progress control unit 137 uses a threshold value for determining the amount of instantaneous vector change to determine whether the amount of change is equal to or greater than a threshold value.

[0088] In step S44, when the progress control unit 137 determines that the vector instantaneous change amount is equal to or greater than the threshold value using the threshold value for determining the vector instantaneous change amount (step S44 YES), it performs unbalance position estimation (step S46). The specific content is the same as step S23, so the description will be omitted.

[0089] In step S44, if the progress control unit 137 does not determine that the change amount is greater than or equal to the threshold value used to determine the instantaneous vector change amount (step S44 NO), the process proceeds to determining whether or not a vibration mode, either thermal vibration or cyclic vibration, is occurring in the rotating part 10a of the rotating machine 10 and identifying the vibration mode.

[0090] First, it is determined whether or not the number of times processing is performed is equal to or greater than a designated value (step S47). In detail, the progress control unit 137 determines whether or not the number of times processing is performed is equal to or greater than a designated value for determination.

[0091] If the progress control unit 137 does not determine that the number of times the process is performed is equal to or greater than the designated value for determination (NO in step S47), the process returns to step S52 and the process is repeated. The progress control unit 137 counts the number of times the process is performed at step S47 as the number of times the process is performed.

[0092] Thermal and cyclic vibrations have the characteristic that the amplitude and phase values ​​change continuously over time. For this reason, to judge thermal and cyclic vibrations, continuous measurement data over, for example, about one hour is required. If the designated value for this judgment is too small, sufficient data cannot be obtained for judgment. On the other hand, if the designated value is too large, it takes time to make a judgment, and there is a risk that the defect will be exacerbated. Therefore, the designated value is selected within an appropriate range taking both into consideration.

[0093] When the progress control unit 137 determines that the number of processing times is equal to or greater than the designated value for determination (step S47: YES), a thermal cyclic vibration determination pre-processing is performed (step S48). Specifically, the polar diagram data creation unit 134 creates data for creating a polar diagram, and the created data for creating a polar diagram is stored and saved in the calculation result storage unit 125 as vibration mode data. In addition, the output unit 140 outputs numerical data for displaying or illustrating the polar diagram.

[0094] Next, it is determined whether the cause can be identified (step S49). Specifically, the failure factor estimation unit 136 performs factor evaluation and identification based on the vibration mode identified and stored in the calculation result storage unit 125, for example, based on the polar diagram obtained in step S48. The case based on the polar diagram will be described below.

[0095] FIG. 11 is a display example of a polar diagram in the case of thermal vibration obtained in the procedure of the method for identifying and diagnosing a fault location during rated speed operation in the rotating machine diagnosis method according to the first embodiment. Each black circle corresponds to a vibration vector at each time point derived by the vibration vector derivation unit 132. Also, the arrow corresponds to a difference vector calculated by the difference vector calculation unit 133. Note that each time point may be a value at each sampling interval of the vibration value, or may be a time point at each predetermined interval. That is, the change in the vector is a difference vector ΔZ or a combination of difference vectors a predetermined number of times. These are collectively represented as a difference vector per unit time by vector change v. Also, the rate of change in the direction of the vector change v is represented by a direction change rate β. The same applies to FIG. 12 and FIG. 13.

[0096] The thermal vibration shown by the polar diagram in Fig. 11 is a state in which the magnitude of the vector change v is equal to or greater than a predetermined value, and the vector directional change rate β is equal to or less than a predetermined value. Also, on the polar diagram, the phase keeps changing and the plot does not rotate on an orbit. The failure factor estimation unit 136 uses the stored discrimination value for judgment to judge whether or not it is a thermal vibration.

[0097] FIG. 12 is a display example of a polar diagram in the case of cyclic vibration due to hard rub obtained in the procedure of the method for identifying and diagnosing a fault occurrence location during rated speed operation in the rotating machine diagnosis method according to the first embodiment.

[0098] The characteristic of cyclic vibration caused by hard rub is that, as shown in Figure 12, the phase on the polar diagram keeps changing and the plot rotates in an orbit, and the magnitude of the vector change changes over time, i.e., the plot becomes larger or smaller in the radial direction in a spiral shape.

[0099] The failure factor estimation unit 136 determines whether the following conditions are met: the magnitude of the vector change v is equal to or greater than a predetermined value, the directional change rate β of the vector is equal to or greater than a predetermined value, and the directional change acceleration α of the vector, i.e., the time differential value of the directional change rate β of the vector is equal to or greater than a predetermined value.

[0100] FIG. 13 is a display example of a polar diagram in the case of cyclic vibration due to soft rub obtained in the procedure of the method for identifying and diagnosing a fault location during rated speed operation in the rotating machine diagnosis method according to the first embodiment.

[0101] The characteristic of cyclic vibration caused by soft rub is that, as shown in Figure 13, the phase on the polar diagram keeps changing and the plot rotates in an orbit, and the magnitude of the vector change over time is small, i.e., the plot keeps moving in the same circular orbit.

[0102] The failure cause estimation unit 136 determines whether the following conditions are met: the magnitude of the vector change v is equal to or greater than a predetermined value, the directional change rate β of the vector is equal to or greater than a predetermined value, and the directional change acceleration α of the vector is equal to or less than a predetermined value.

[0103] The failure factor inference unit 136 performs determination in cases other than the above three cases as necessary.

[0104] For the sake of convenience, the judgment by the failure factor estimation unit 136 has been described above in comparison with the polar diagrams shown in Fig. 11 to Fig. 13. The polar diagram is displayed by the output unit 140 to aid the understanding of the operator, etc., but is not necessarily required for the judgment by the failure factor estimation unit 136. The failure factor estimation unit 136 can directly make the judgment using the vibration vector derived by the vibration vector derivation unit 132 and stored in the calculation result storage unit 125, and the difference vector calculated by the difference vector calculation unit 133 and stored in the calculation result storage unit 125.

[0105] The progress control unit 137 determines that it is possible to determine the cause when any of the determinations made by the failure cause estimation unit 136 is met. On the other hand, when any of the determinations made by the failure cause estimation unit 136 is not met, the progress control unit 137 does not determine that it is possible to determine the cause.

[0106] In step S49, if the progress control unit 137 does not determine whether the cause can be identified (step S49 NO), the output unit 140 outputs a message indicating that the cause cannot be identified, and the output unit 140 displays the message (step S50). Then, the process proceeds to step S53. Alternatively, the process may proceed directly from step S49 to step S53 to continue the identification.

[0107] In step S49, when the progress control unit 137 determines that the cause can be identified (step S49 YES), it determines whether or not any of the causal events apply (step S51). That is, the progress control unit 137 determines whether or not the result of the determination by the failure cause estimation unit 136 indicates that the cause corresponds to any of the cases shown in Figs. 11 to 13.

[0108] In step S51, if the progress control unit 137 determines that the cause is any of the causal events (step S51: YES), the unbalance position is estimated (step S52). The estimation of the unbalance position is the same as the calculation of the unbalance position in step S23, so a description thereof will be omitted. After the estimation of the unbalance position step S52, the process proceeds to step S53.

[0109] In step S51, if the progress control unit 137 has not determined that the cause event is any one of the causes (NO in step S51), the process proceeds directly to step S53.

[0110] In step S53, it is determined whether or not to continue operation. Normally, when an abnormality occurs, operation of the rotating machine 10 is stopped rather than continued, but a determination step is provided just to be on the safe side. In this step, the operator may use a user interface to display the situation and perform a stop operation. Alternatively, depending on the cause, it may be possible to automatically continue operation or automatically stop operation. If operation is to be continued (YES in step S53), the process proceeds to step S12 in FIG. 8.

[0111] As described above, when an imbalance occurs in the rotating part 10a, it is possible to identify the location of the failure and estimate the cause of the failure, both while the rotating machine 10 is changing its rotation speed and while the rotating machine 10 is operating at rated speed.

[0112] [Second embodiment] FIG. 14 is a flowchart showing the overall procedure of the rotating machine diagnosis method according to the second embodiment.

[0113] This embodiment is characterized in that a vibration vector at a critical speed when the rotation speed of the rotating part 10a changes is extracted and evaluated. For this reason, a step (S24) of determining whether the rotation speed of the rotating part 10a is at a critical speed or not is added before step S21.

[0114] When the rotation speed increases, the rotation speed does not stop increasing at the critical speed of the rotating part 10a, but passes through the critical speed in general operation. On the other hand, if the sampling interval is rough, it is difficult to collect data at the timing when the actual rotation speed coincides. In addition, the amplitude and phase values ​​change significantly at the critical speed, and there is a concern that the final detection accuracy will deteriorate if the data before and after that time are used instead.

[0115] In light of this, the progress control unit 137 determines that the rotation speed of the rotating part 10a received by the input unit 110 has passed the critical speed, and the failure cause estimation unit 136 performs interpolation using the results obtained by the vibration vector derivation unit 132 before and after the time when the critical speed is passed, to calculate the amplitude and phase at the rotation speed of the critical speed.

[0116] In this embodiment, since the evaluation is performed at the critical speed where the amplitude value becomes large, the sensitivity to the vibration change when a fault event occurs due to imbalance of the rotating part 10a is high, and the detection accuracy is improved. In addition, the amount of measurement data stored in the memory unit 120 can be reduced.

[0117] [Third embodiment] 15 is a block diagram showing the configuration of a rotating machine diagnosis device 100a according to a third embodiment. This embodiment is a modification of the first embodiment, and identifies a vibration mode and estimates a cause of a failure using a moving speed, a moving acceleration, and a direction change rate of a vibration vector, instead of being based on a polar diagram in the first embodiment.

[0118] In the rotating machine diagnostic device 100a, the memory unit 120 further has a judgment table storage unit 126, the calculation unit 130 further has a data processing unit 138, and has a failure factor estimation unit 136a instead of the failure factor estimation unit 136 and a progress control unit 137a instead of the progress control unit 137. The judgment table storage unit 126 stores judgment tables. The judgment tables include a first judgment table 126a, a second judgment table 126b, and a third judgment table 126c, which will be described later.

[0119] First, the processing by the data processing unit 138 will be described below.

[0120] (1) Before calculating the average value of the phase data, the following preprocessing is performed to prevent the average value from becoming an abnormal value when the phase crosses 0 degrees (360 degrees).

[0121] The phase data to be averaged is expressed as Θ1, Θ2, ..., Θ N Then, for i=2 to N, the following process is carried out in order.

[0122] Θ i -Θ i-1 If >180 degrees, Θ i Replace with: Θ i -360×int((Θi -Θ i-1 +180) / 360) Θ i -Θ i-1 <180 degrees, Θ i Replace with: Θ i +360×int((Θ i -Θ i-1 +180) / 360) If neither of these is true, then Θ i is left as it is. Here, int(x) denotes the maximum integer not exceeding x.

[0123] (2) Calculate the average value of the amplitude a and phase Θ from the past N data. Here, m represents the data number of the current time. For the phase Θ, use the value preprocessed in (1).

[0124] The average count is the value of Ave_Count, and is represented as N in the following equations (19) and (20). A = Σa i / N …(19) Θ=ΣΘ i / N …(20)

[0125] Here, Σ means the sum from i=m-N+1 to i=m.

[0126] (3) The averaged amplitude a and phase Θ are converted into values ​​X and Y in the Cartesian coordinate system using the following equations (21) and (22). X = Acos(Θ × π / 180) … (21) Y = Asin(Θ × π / 180) … (22)

[0127] (4) From the average value thus obtained, the vibration vector change is calculated using the following equations (23) and (24). ΔX i =X i -X i-1 …(twenty three) ΔY i =Y i -Y i-1 …(twenty four)

[0128] FIG. 16 is an explanatory diagram of processing by a data processing unit in the rotating machine diagnosis method according to the third embodiment.

[0129] For example, if N=20, then X i , Y i is the average value of the 20 events from 19 events ago to the present, and X i―1 , Y i―1 is the average value of the 20 times from 39 to 20 times ago, X i―2 , Y i―2 is the average value of the 20 times from 59th to 40th, and ΔX and ΔY are the differences between them.

[0130] (5) Moving speed v on the polar diagram j (magnitude of vector change) and acceleration α i The calculation is performed using the following equations (25) to (27). v i =(√(ΔX i ) 2 +(ΔY i ) 2 〕) / (N·Δt) …(25) v i―1 =(√(ΔX i―1 ) 2 +(ΔY i―1 ) 2 〕) / (N·Δt) …(26) α i =(v i -v i-1 ) / (N·Δt) …(27) Here, Δt is the data sampling period (unit: minutes), and N is the number of averaging operations.

[0131] (6) Direction of vector change Φ i , and the rate of change of direction β i The calculation is performed.

[0132] ΔX obtained in (4) above i , ΔY i Then, the direction of vector change Φ is calculated by the following equation (28). j Calculate. Φ i=90-tan ―1 [(ΔX i / ΔY i )×(180 / π) (ΔY i > 0) =270-tan ―1 [(ΔX i / ΔY i )×(180 / π) (ΔY i < 0) =0 Y i = 0, ΔX i > 0) =180 Y i = 0, ΔX i < 0) …(28)

[0133] Change in direction ΔΦ i is calculated using the following formula (29), taking into account the case where the front and rear cross 0 degrees (360 degrees). ΔΦ i =Φ i -Φ i-1 (―180≦Φ i -Φ i-1 (When ≦180) =Φ i -Φ i-1 -360 (Φ i -Φ i-1 > 180) =Φ i -Φ i-1 +360 (Φ i -Φ i-1 <180) …(29)

[0134] The obtained ΔΦ i Therefore, the rate of change of direction per unit time (for example, 1 minute) is β i is calculated using the following formula (30). β i = ΔΦ i / (N·Δt) …(30)

[0135] 17 shows a first judgment table 126a indicating judgment conditions in a method for identifying and diagnosing a fault location during rated speed operation in a rotating machine diagnosis method according to a third embodiment. The first judgment table 126a is stored in a judgment table storage unit 126. This judgment table is used in a step corresponding to step S49 in FIG.

[0136] The velocity of the vibration vector on the polar diagram obtained above is v i , moving acceleration α i , directional change rate β i is used to make a judgment according to the first judgment table 126a.

[0137] The items in the first column of the first judgment table 126a that do not fall under either thermal vibration, cyclic vibration (hard rub, soft rub), or neither are classifications of causes. The second to fourth columns are the moving speed v of the judgment parameter. i , moving acceleration α i , directional change rate β i The fifth to seventh columns show the judgment results. In the first judgment table 126a, "add 1" means adding 1 to the previous judgment result read as an input value. In other words, the numerical value of the judgment result indicates the number of consecutive judgments.

[0138] The threshold values ​​(v0, β0, α0) used for the judgment can be set individually for each vibration meter 16.

[0139] The failure factor estimation unit 136a performs the following judgment process in accordance with the first judgment table 126a shown in Fig. 17. Here, the failure factor estimation unit 136a stores counters for thermal vibration judgment, cyclic vibration (hard rub) judgment, and cyclic vibration (soft rub) judgment for each vibration meter 16. (1)v i ≧v t0 , β i If β0, add 1 to the thermal vibration judgment. (2)v i ≧v c0 , βi ≧β0, α i If α 0 or higher, add 1 to the cyclic vibration (hard rub) judgment. (3)v i ≧v c0 , β i ≧β0, α i If α<0, add 1 to the cyclic vibration (soft rub) judgment. (4)(v i <v t0 , β i <β0) or (v i <v c0 , β i ≥ β0), neither of these cases applies.

[0140] FIG. 18 is a second judgment table showing judgment conditions in the method of identifying and diagnosing a fault occurrence location during rated rotation operation in the rotating machine diagnosis method according to the third embodiment.

[0141] The second judgment table 126b supplements the conditions for making the judgment using the first judgment table 126a in step S49. That is, in the thermal vibration judgment, the maximum value of the thermal vibration judgment result in each bearing direction is used. In the cyclic vibration (hard rub) judgment, the maximum value of the cyclic vibration (hard rub) judgment result in each bearing direction is used. In addition, in the cyclic vibration (soft rub) judgment, the maximum value of the cyclic vibration (soft rub) judgment result in each bearing direction is used. In addition, the processing of each of the above judgments is as follows (a) and (b).

[0142] (a) If the number of 0 judged results among the above three is 0 or 1, it means that two or all of the vibration events among thermal vibration, cyclic vibration hard rub, and cyclic vibration soft rub are occurring. In this case, 1 is added to the judgement during factor judgement. Note that the "Judgment result during factor evaluation" in the third judgement table shown in Figure 19 corresponds to 1 or 2, and "output of no action" is output for follow-up observation. After that, the evaluation cycle is repeated, and if this judgement is made three times, the process of outputting the judgement not possible is performed.

[0143] (b) If the number of judgments judged as 0 among the above three judgment results is 2 or 3, the judgment result will be 0. In this case, it will be judged that only one of thermal vibration, cyclic vibration hard rub, and cyclic vibration soft rub is occurring, or none of them are occurring. In this case, the "judgment result during factor evaluation" in the third judgment table shown in Figure 19 corresponds to 0, and a new judgment will be made.

[0144] FIG. 19 is a third judgment table showing judgment conditions in the method of identifying and diagnosing a fault occurrence location during rated rotation operation in the rotating machine diagnosis method according to the third embodiment.

[0145] The progress control unit 137a performs a comprehensive judgment based on the judgment results from the first judgment table 126a and the second judgment table 126b, in accordance with the third judgment table 126c shown in Fig. 18, as follows: That is, the third judgment table 126c is used at a stage corresponding to step S51 in Fig. 10.

[0146] The third determination table 126c shown in Fig. 19 shows an example for thermal vibration, and similar tables are prepared for cyclic vibration (soft rub) and cyclic vibration (hard rub), but the description will be omitted. An example for thermal vibration will be described below.

[0147] The first column of the third judgment table 126c is the result of the factor evaluation judgment for thermal vibration in step S49, and each row is the classification of the number of times. The second column is the judgment result other than thermal vibration. The third column shows the processing for each case.

[0148] In cases where the judgment result for thermal vibration is 0 in all bearing directions, if the cyclic vibration (hard rub) judgment is 0, the cyclic vibration (soft rub) judgment is 0, and the thermal vibration judgment is 0, the output indicates that nothing will be done. Also, if the cyclic vibration (hard rub) judgment is greater than 0, the cyclic vibration (soft rub) judgment is greater than 0, or the thermal vibration judgment is greater than 0, the process proceeds to the imbalance position estimation step.

[0149] For all bearing directions, if the number of judgments for thermal vibration is 1 or 2, an output is issued indicating that nothing will be done.

[0150] In all bearing directions, if the number of thermal vibration judgments is 3 or more, an output is issued indicating that judgment is impossible.

[0151] For all bearings and directions, if the number of judgments for the event is 1 or 2, an output is issued indicating that nothing will be done.

[0152] If the number of times the event is judged is three or more for all bearings and directions, a message indicating that judgment is impossible is output.

[0153] The vibration mode determination results obtained by each of the first judgment table 126a, the second judgment table 126b, and the third judgment table 126c described above are stored and saved in the calculation result memory unit 125, and can be output and displayed by the output unit 140.

[0154] As described above, in this embodiment, a table for judgment is stored, and judgment can be made efficiently.

[0155] According to the embodiments described above, it is possible to provide a rotating machine diagnostic device and a rotating machine diagnostic method that enable identification of a fault occurrence location and estimation of a fault cause in the event of rotor imbalance. [Other embodiments]

[0156] Although several embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. In addition, since each embodiment is not mutually exclusive, the features of multiple or all of the embodiments may be combined. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0157] 10...rotating machine, 10a...rotating part, 10b...slit, 10c...reflective tape, 11...rotor shaft, 12...low pressure turbine, 13...generator, 14...exciter, 15...bearing, 16...vibration meter, 17...phase detector, 17a...reference marker, 17b...pulse detector, 18...tachometer, 100...rotating machine diagnostic device, 110...input section, 120...memory section, 121...reference data memory section, 121a...judgment table, 122...influence coefficient Matrix storage unit, 123... vibration data storage unit, 124... phase storage unit, 125... calculation result storage unit, 126... judgment table storage unit, 130... calculation unit, 131... phase calculation unit, 132... vibration vector derivation unit, 133... difference vector calculation unit, 134... polar diagram data creation unit, 135... unbalance calculation unit, 136... fault cause estimation unit, 137... progress control unit, 138... data processing unit, 140... output unit, 150... time counter

Claims

1. A rotating machine diagnostic device for identifying a location of a fault and estimating a cause of a fault in relation to an unbalance occurring event during rotation of a rotating part included in a rotating machine, comprising: the rotating machine is provided with a vibration meter provided near each bearing, and a tachometer and a phase detector provided to face a rotating part of the rotating machine, The rotating machine diagnostic device includes: an input unit that receives data of an influence coefficient matrix, vibration data from the vibration meter, a rotation speed of the rotating part from the rotation speed meter, and phase calculation data from the phase detector for calculating a phase of the rotating part; Calculating a phase based on the phase calculation data received by the input unit; deriving a vibration vector using the phase and the vibration data; Calculating a moving speed, a moving acceleration, and a directional change rate of the vibration vector based on the vibration vector; identifying a vibration mode of the rotating part for estimating the cause of the failure from among a plurality of vibration modes based on the moving speed, the moving acceleration, and the direction change rate; a calculation unit that performs a calculation to identify the fault occurrence location by calculating an imbalance distribution of the rotating part based on the vibration vector and the influence coefficient matrix; The fault occurrence location obtained by the calculation unit is displayed, and an output unit that displays information related to the failure factor based on the vibration mode obtained by the calculation unit; and A rotating machine diagnostic device comprising:

2. 2. The rotating machine diagnostic device according to claim 1, wherein the rotating machine is in operation when the rotational speed of the rotating part passes through a critical speed.

3. A rotating machine diagnosis method for identifying a location of a fault and estimating a cause of a fault in relation to an unbalance occurring event during rotation of a rotating part included in the rotating machine, comprising: the rotating machine is provided with a vibration meter provided near each bearing, and a tachometer and a phase detector provided to face a rotating part of the rotating machine, The rotating machine diagnosis method includes: A first input step in which an input unit accepts data of an influence coefficient matrix; a second input step in which the input unit receives vibration data from the vibration meter, a rotation speed of the rotating part from the rotation speed meter, and phase calculation data from the phase detector for calculating a phase of the rotating part; Calculating a phase based on the phase calculation data received by the input unit; deriving a vibration vector using the phase and the vibration data; Calculating a moving speed, a moving acceleration, and a directional change rate of the vibration vector based on the vibration vector; identifying a vibration mode of the rotating part for estimating the cause of the failure from among a plurality of vibration modes based on the moving speed, the moving acceleration, and the direction change rate; a calculation step of performing a calculation to identify the fault occurrence location by calculating an imbalance distribution of the rotating part based on the vibration vector and the influence coefficient matrix; The fault occurrence location obtained by the calculation unit is displayed, and a display step of displaying information related to the cause of the failure based on the vibration mode obtained by the calculation unit; A rotating machine diagnostic method comprising:

Images