Device state detection device and device state detection method

Abstract

The invention provides a device state detection device and a device state detection method which can shorten the detection time of abnormal operation of a device and the like. Provided is a device state detection device for detecting an operation abnormality of a device or the like. The device state detection device has an abnormality detection unit. An abnormality detection unit provided in the device state detection device detects an abnormality in an object on the basis of an abnormal operation region that is defined in accordance with the operating state of the object and that is a region of vibration of the object and sound from the object when the operation of the object is abnormal.

Description

TECHNICAL FIELD

[0001] The present application relates to an apparatus state detection device and an apparatus state detection method. BACKGROUND

[0002] A device that detects abnormal operation of an apparatus used in a plant, a factory, or the like is proposed. For example, a device that detects abnormality of a rotating machine due to sound and vibration caused by abnormality of a rotating body of the rotating machine is proposed (for example, refer to Patent Document 1).

[0003] Patent Document 1: Japanese Patent Application Laid-Open No. 7-182035 SUMMARY

[0004] However, in the above-described related art, abnormality is detected by a process of confirming a diagnosis result of the sound based on data of the vibration, and thus there is a problem that detection of abnormal operation takes time.

[0005] Therefore, in the present application, an apparatus state detection device and an apparatus state detection method that shorten the detection time of abnormal operation of an apparatus or the like are proposed.

[0006] The apparatus state detection device of the present application includes an abnormality detection section that detects abnormality of an object based on an abnormal operation region, which is a region of vibration of the object and sound from the object in a case where the object has abnormal operation, and which is defined in accordance with an operation state of the object. BRIEF DESCRIPTION OF DRAWINGS

[0007] Figure 1 is a view that shows a configuration example of an apparatus state detection device related to an embodiment of the present application.

[0008] Figure 2 is a view that shows one example of an abnormal operation region related to an embodiment of the present application.

[0009] Figure 3 is a view that shows one example of a processing flow of an apparatus state detection device related to an embodiment of the present application.

[0010] Figure 4 is a view that shows one example of a processing flow of an apparatus state detection method related to an embodiment of the present application.

[0011] Figure 5 is a view that shows one example of noise removal related to an embodiment of the present application.

[0012] Figure 6 is a view that shows one example of a noise removal flow related to an embodiment of the present application.

[0013] Figure 7 FIG. 1 is a diagram showing an example of detection of a margin involved in an embodiment of the present application.

[0014] Figure 8 FIG. 2 is a diagram showing an example of detection of an anomaly involved in an embodiment of the present application.

[0015] Figure 9 FIG. 3 is a diagram showing an example of detection of an anomaly of another device involved in an embodiment of the present application.

[0016] Figure 10 FIG. 4 is a diagram showing an example of a modification of an embodiment of the present application. DETAILED DESCRIPTION

[0017] Hereinafter, an embodiment of the present application will be described in detail based on the drawings. The description will be made in the following order. Further, in each of the following embodiments, the same reference numerals are assigned to the same parts and repetitive description will be omitted.

[0018] 1. Embodiment

[0019] 2. Modification

[0020] (1. Embodiment)

[0021] [Structure of device state detection device]

[0022] Figure 1 FIG. 1 is a diagram showing an example of a structure of a device state detection device involved in an embodiment of the present application. This figure is a block diagram showing an example of a structure of a device state detection device 10. The device state detection device 10 detects a state of a device used in a plant or a factory. The state includes an abnormal state in an operation of the device. The device state detection device 10 detects a state of an object. As the object, a pump 40 is assumed. The pump 40 is a device that pressurizes and delivers a liquid such as water by rotational driving of a motor. Further, a device having a rotating mechanism such as a generator or a compressor can be assumed as the object.

[0023] The device state detection device 10 has a noise removal section 11, a preprocessing section 12, an anomaly detection section 13, a storage section 14, a recording section 15, and a processing section 16. Further, a vibration sensor 20 and a microphone 30 are also described in this figure.

[0024] The vibration sensor 20 is attached to the pump 40 and detects a vibration. The vibration sensor 20 generates a vibration signal as a signal of the vibration and outputs to the device state detection device 10.

[0025] The microphone 30 is disposed in the vicinity of the pump 40 and detects a sound from the pump 40. The microphone 30 generates a sound signal as a signal of the sound and outputs to the device state detection device 10.

[0026] Further, a composite sensor that detects vibration and sound can be used instead of the vibration sensor 20 and the microphone 30. In addition, a camera can be used instead of the vibration sensor 20. In this case, vibration is detected based on a motion of an image captured by the camera.

[0027] The noise removal section 11 removes noise from the sound signal. The sound signal from which noise is removed is input to the abnormality detection section 13. The noise removal is described in detail later. Further, FFT (Fast Fourier Transform) processing, statistical processing, or the like for frequency analysis can be performed on the sound signal from which noise is removed.

[0028] The preprocessing section 12 performs preprocessing of the vibration signal. For example, detection processing of an effective value (RMS: Root Mean Square value) of the vibration signal corresponds to the preprocessing. The detection of the effective value can be performed by calculating the effective value of the vibration signal for a prescribed period, for example. A publicly known method can be applied to the calculation of the effective value. The effective value of the vibration signal is input to the abnormality detection section 13. Further, the FFT processing, the statistical processing, or the like can be performed as preprocessing. Further, the preprocessing section 12 can be omitted. In this case, the abnormality detection section 13 described later performs processing based on the vibration signal from the vibration sensor 20.

[0029] The abnormality detection section 13 detects an abnormality of the object (the pump 40) based on an abnormal motion region. Here, the abnormal motion region is a region of vibration of the object and sound from the object in a case where the motion of the object is abnormal, and is prescribed according to an operation state of the object. The abnormal motion region is described in detail later. The abnormality detection section 13 outputs an abnormality detection signal to an external device in a case where an abnormality of the object is detected. The abnormality detection signal is a signal of an alarm (warning), for example.

[0030] In addition, the abnormality detection section 13 further detects a quasi-abnormal motion of the object based on a quasi-abnormal motion region that is a region in contact with the abnormal motion region. The quasi-abnormal motion is not an abnormal state, but is a motion of a state that needs to be known. The abnormality detection section 13 outputs a warning (alarm) if the quasi-abnormal motion is detected.

[0031] The storage section 14 stores information of the abnormal motion region. The abnormality detection section 13 detects an abnormality based on the abnormal motion region stored in the storage section 14. In addition, the storage section 14 also stores information of the quasi-abnormal motion region. The abnormality detection section 13 detects a quasi-abnormal motion based on the quasi-abnormal motion region stored in the storage section 14.

[0032] The recording section 15 records the sound signal and the vibration signal. The recording section 15 of the drawing records the sound signal output from the noise removing section 11 and the vibration signal output from the preprocessing section 12. In addition, the recording section 15 records the sound signal and the vibration signal output from the processing section 16.

[0033] The processing section 16 performs processing of the sound signal and the vibration signal recorded in the recording section 15. For example, the state evaluation of the device (for example, evaluation of breakdown, inspection, and cleaning, and the like) corresponds to the processing of the processing section 16. Specifically, the processing section 16 can evaluate each work based on the change of the sound signal and the vibration signal before and after each work. By evaluating each work by the evaluation standard, for example, it is possible to grasp the business effect of the worker, and it is possible to be applied to business improvement (improvement of cleaning degree, flow, and usage amount of consumables, and the like). In addition, by periodically measuring the sound and the vibration, it is possible to grasp the state of the target device. By comparing with the standard state of the target device, it is also possible to perform maintenance and repair corresponding to the state of the device at an appropriate timing.

[0034] Further, the device state detection device 10 can also detect the state of the target object other than the abnormal operation. For example, there is also an output detection section that detects the output of the target object (pump 40), and a structure that processes the detected output of the target object can also be realized.

[0035] [Abnormal operation region]

[0036] Figure 2 This drawing is a graph that shows the abnormal operation region. The X axis of the graph shows the vibration. In addition, the Y axis of the graph shows the sound. In the drawing, the white triangular region shows the normal operation region 100. In addition, the region with dotted circle shading shows the abnormal operation region 102. The region of the vibration and the sound at the time of abnormal operation corresponds to the abnormal operation region. In addition, the region with diagonal line shading shows the quasi-abnormal operation region 101. Further, the apex portion on the right side of the normal operation region 100 and the quasi-abnormal operation region 101 corresponds to the resonance point. At the resonance point, there is a tendency to increase the sound and the vibration, but it is not an abnormal operation.

[0037] The white circle 111 shows the operating point in the normal operation. In this state, in the case where some kind of adverse situation occurs and the vibration increases, the operating point shifts to the white circle 112. At this time, if the sound increases due to the increase in the vibration, the operating point shifts to the circle 113. Thus, the target object reaches the quasi-abnormal operation region 101. In this way, it is possible to detect whether it is the quasi-abnormal operation region and the abnormal operation region based on the position on the graph of the sound and the vibration.

[0038] This is a relationship between sound and vibration at normal times that is broken at abnormal times. Furthermore, the relationship between sound and vibration can be constructed by focusing on specific frequency components.

[0039] In addition, the region 120 and the region 130 represent normal operation regions of other devices. In addition, the region 121 and the region 131 represent abnormal operation regions of other devices. In this way, the region in which the vibration is small and the region in which the sound is small can be considered as the state of other devices different from the object.

[0040] Furthermore, the Z axis of the graph represents the rotation speed. The normal operation region 100, the quasi-abnormal operation region 101, and the abnormal operation region 102 of the graph correspond to regions at the maximum rotation speed. The normal operation region 100, the quasi-abnormal operation region 101, and the abnormal operation region 102 are generated for each specific rotation speed, but are not illustrated. Furthermore, the object in the graph is the pump 40, and thus the rotation speed is set as a parameter. The operation load rate of the object can be applied to the Z axis. Here, the operation load rate represents the ratio of the actual load with respect to the rated load (maximum load). The normal operation region 100, the quasi-abnormal operation region 101, and the abnormal operation region 102 of the graph can be understood as the state of the operation load rate 100% (rated load). In addition, for example, the quasi-abnormal operation region 101 and the abnormal operation region 102 can be defined for each specific operation load rate, such as the operation load rate 90%, 80%, and 70%.

[0041] The abnormality detection section 13 can select the quasi-abnormal operation region 101 and the abnormal operation region 102 according to the operation load rate of the object, and use them in the detection of the quasi-abnormal operation and the abnormal operation.

[0042] Furthermore, Figure 2 The Z axis of the graph can also be another parameter, such as pressure, light (absorbance).

[0043] [Process of device state detection device]

[0044] Figure 3 This is a graph that represents one example of the processing flow of the device state detection device involved in the embodiment of the present application. The graph is a flowchart that represents one example of the processing flow of the abnormality detection process of the device state detection device 10. First, the abnormality detection section 13 performs correction (calibration) of the position (attitude) of the vibration sensor 20 (step S101). In the case where a 3-axis system acceleration sensor is used as the vibration sensor 20, the magnitude of the gravitational acceleration that appears in the 3 axes changes according to the attitude of the sensor, and thus can be used for correction. In addition, correction of the mounting strength (tension condition at the time of tensioning) at the time of mounting the vibration sensor 20 to the device can also be performed.

[0045] Next, the abnormality detection section 13 determines whether or not an abnormal behavior region is generated (step S102). In a case where the abnormal behavior region is not generated (No in step S102), the abnormality detection section 13 generates the abnormal behavior region (step S103). The generation of the abnormal behavior region is described later. Next, the abnormality detection section 13 acquires the vibration signal and the sound signal (step S104). Next, the abnormality detection section 13 executes the abnormality detection process (step S110).

[0046] Next, the abnormality detection section 13 performs abnormality detection of other equipment (step S105). The abnormality detection of other equipment is described later in detail.

[0047] Next, the abnormality detection section 13 determines whether or not the process is continued (step S106). In a case where the process is continued (Yes in step S106), the abnormality detection section 13 determines whether or not the measurement condition is changed (step S107). In a case where the measurement condition is changed (Yes in step S107), the abnormality detection section 13 proceeds to the process of step S101. On the other hand, in a case where the measurement condition is not changed (No in step S107), the abnormality detection section 13 proceeds to the process of step S102.

[0048] On the other hand, in step S106, in a case where the process is not continued (No in step S106), the abnormality detection section 13 ends the process.

[0049] [Abnormality detection process]

[0050] Figure 4 is a flowchart showing one example of a processing flow of the abnormality detection process to which the embodiment of the present application relates. The drawing is a flowchart showing one example of a processing flow of the abnormality detection process (step S110) of Figure 3 First, the noise removal section 11 performs noise removal of the sound signal (step S111). Next, the abnormality detection section 13 detects a margin based on the sound signal and the vibration signal and the abnormal behavior region (step S112). Here, the margin indicates a difference in vibration and sound until the behavior of the object reaches the abnormal behavior region. The detection of the margin is described later. Next, the abnormality detection section 13 performs abnormality detection based on the margin (step S113). Then, the abnormality detection section 13 returns to the original process.

[0051] [Generation of information of abnormal behavior region]

[0052] The abnormal operation region is defined in accordance with the start and stop operations of the pump 40, based on the operation (1 week, etc.) of the pump 40. For example, a range of ±10% can be defined as the normal operation region, a range of ±15% as the quasi abnormal operation region, and a range of ±20% as the abnormal operation region, with respect to the range of the sound and vibration at the time of start and stop of the pump 40.

[0053] [Noise removal]

[0054] Figure 5 is a graph showing one example of noise removal involved in the embodiment of the present application. This graph is the same as Figure 2 , which is a graph showing an abnormal operation region. In addition, the circle 111 indicates an operation point in the normal operation, as is the same as Figure 2 . If the vibration does not change and the sound increases with respect to this state, the operation point is shifted to the position of the circle 114, as indicated by the white arrow of the graph. This state in which the vibration does not change and the sound increases is considered to be a state in which the sound based on the operation of other equipment is added. Therefore, the following processing is performed, that is, the amount of change in the sound is subtracted and returned to the original operation point (black arrow of the graph). Thus, noise removal can be performed. The specific flow is explained next.

[0055] Figure 6 is a graph showing one example of the flow of noise removal involved in the embodiment of the present application. The upper graph of this graph shows the change in the margin. In addition, the lower graph of this graph shows the sound signal of each period of the upper graph of this graph. The left graph of the lower graph shows the original sound signal before the change in the sound. The center graph of the lower graph shows a state in which the sound suddenly increases. In the center graph of the lower graph, the sound of the increased frequency component corresponds to the sound (noise) based on the operation of the surrounding process. Noise removal can be performed by subtracting the sound of the increased frequency component. The right graph of the lower graph shows the sound signal after the noise removal.

[0056] The noise removal section 11 continuously records the sound signal and detects the increase in the sudden sound. Next, the noise removal section 11 performs the subtraction processing of the component of the suddenly increased sound. Noise removal can be performed by the above flow.

[0057] [Margin detection]

[0058] Figure 7 is a graph showing one example of the detection of the margin involved in the embodiment of the present application. This graph is the same as Figure 2 , which is a graph showing an abnormal operation region. In addition, the circle 111 indicates an operation point in the normal operation, as is the same as Figure 2Similarly, circle 111 represents the operating point during normal operation. As mentioned earlier, the margin is the difference in vibration and sound until the object's movement reaches the abnormal operation area. This margin can be detected through the following process. First, the anomaly detection unit 13 generates the smallest circle that contacts the abnormal operation area 102, centered on circle 111. The dashed circle 211 in this figure represents this circle. Next, the anomaly detection unit 13 detects the radius of this circle 211 as the margin.

[0059] Furthermore, the anomaly detection unit 13 can further detect the difference in vibration and sound up to the point where the object's movement reaches the quasi-abnormal movement region 101, as a second margin. The anomaly detection unit 13 generates the smallest circle that contacts the quasi-abnormal movement region 101, centered on circle 111. The dashed circle 212 in the figure represents this circle. Next, the anomaly detection unit 13 detects the radius of this circle 212 as a second margin.

[0060] [Anomaly Detection]

[0061] Figure 8 This is a graph illustrating an example of anomaly detection according to an embodiment of the present invention. The graph shows an example of detecting anomalies in the operation of an object based on a margin. The horizontal axis of the graph represents time. Furthermore, the dashed lines in the graph represent the levels of the value "0". The curve 221 represents the change in margin. When the margin becomes a value of "0", the anomaly detection unit 13 can determine that the operating point of the object has reached an abnormal operation area. Furthermore, a negative margin indicates a state where the abnormal operation area contains an operating point. In this way, the anomaly detection unit 13 can detect anomalies in the operation of the object based on a margin.

[0062] Furthermore, curve 222 represents the second margin. When this second margin becomes a value of "0", the anomaly detection unit 13 can determine that the operating point of the object has reached the quasi-abnormal action area.

[0063] [Anomaly detection for other devices]

[0064] Anomaly detection unit 13 based on Figure 2 The other devices in areas 121 and 131 are used to detect anomalies in other devices.

[0065] In addition, it can also be based on Figure 6 The abnormality was detected by detecting sounds from other devices as described in the instructions. The procedure will now be explained.

[0066] Figure 9 This diagram illustrates an example of detecting anomalies in other devices according to an embodiment of the present invention. The anomaly detection unit 13 extracts sound from other devices (…). Figure 9 (The upper section). Next, the anomaly detection unit 13 infers the vibration signal based on the previously acquired relationship between sound and vibration (the upper section).Figure 9 The abnormality detection section 13 generates vibration data (S2) by estimation (see the middle of FIG. 8). Next, the abnormality detection section 13 generates vibration data (S3) by estimation (see the lower of FIG. 8). The abnormality detection section 13 detects an abnormality of the other device using the generated vibration data and the extracted sound of the other device. Figure 9

[0067] Further, the processing of the drawing does not detect the vibration of the other device, and thus is a simple method.

[0068] Thus, the abnormality detection section 13 of the device state detection apparatus 10 of the embodiment of the present application detects an abnormality of the object using the sound signal and the vibration signal at the same time. Thereby, it is possible to shorten the detection time of the abnormality.

[0069] (2. Modified example)

[0070] In the above embodiment, it is assumed that an abnormality is detected for an apparatus having a movable portion such as the pump 40 with respect to the object. An example in which the detection of the abnormality is applied to other apparatuses is described.

[0071] Figure 10 FIG. 9 is a drawing showing one example of a modified example of the embodiment of the present application. The drawing shows an example of detecting a sound and a vibration of a pipe. The pipe vibrates and emits a vibration sound due to the flow of a liquid. In a case where a mixed phase flow is generated, in a case where a slurry flows, a vibration and the like are significantly generated. It is possible to detect the vibration and the sound to detect an abnormality of the pipe. Further, the object is not limited to the pump 40 and the pipe, and can be applied to other instruments and apparatuses.

[0072] The above describes each embodiment of the present application, and the technical scope of the present application is not limited to the above-described each embodiment as it is, and various changes can be made without departing from the spirit of the present application. In addition, the structural elements of different embodiments and modified examples can be appropriately combined.

[0073] Further, a series of processes based on each apparatus described in this specification can be realized by any one of software, hardware, and a combination of software and hardware. A program constituting the software is, for example, stored in advance in a storage medium (non-transitory media) provided inside or outside each apparatus. Also, each program is, for example, read into a RAM and executed by a processor such as a CPU when executed by a computer.

[0074] In addition, the processes described in this specification by the flowchart and the sequence diagram can also be executed not in the order shown in the drawing. Several processing steps can be executed in parallel. In addition, an additional processing step can be adopted, and a part of the processing step can be omitted.

[0075] ​In addition, the processing flow described in the above-described embodiments can be understood as a method having the above-described series of processes, and in addition, can be understood as a program for causing a computer to execute the above-described series of processes or a recording medium storing the program. As the recording medium, for example, a CD (Compact Disc), an MD (MiniDisc), a DVD (Digital Versatile Disc), a memory card, a Blu-ray (registered trademark) Disc, or the like can be used.

[0076] Furthermore, the effects described in the present specification are examples and are not limiting, and other effects can be included.

[0077] Several examples of combinations of disclosed technical features are described below.

[0078] (1) An apparatus state detection device, wherein

[0079] The apparatus state detection device has an abnormality detection section that detects an abnormality of an object based on an abnormal operation region that is a region of vibration of the object and a sound from the object in a case where an operation of the object is abnormal, and that is defined in accordance with an operation state of the object.

[0080] (2) The apparatus state detection device according to (1), wherein

[0081] The abnormality detection section detects the abnormality based on the abnormal operation region selected based on the operation state of the object.

[0082] (3) The apparatus state detection device according to (1) or (2), wherein

[0083] The abnormality detection section detects the abnormality based on a vibration signal that is a signal of vibration of the object and a sound signal that is a signal of a sound of the object.

[0084] (4) The apparatus state detection device according to (3), wherein

[0085] Further comprising a preprocessing section that performs preprocessing of the vibration signal,

[0086] The abnormality detection section detects the abnormality based on the vibration signal after the preprocessing.

[0087] (5) The apparatus state detection device according to (4), wherein

[0088] The preprocessing section performs at least one of a detection process of an effective value of the vibration signal, an FFT process, and a statistical process as the preprocessing.

[0089] (6) The device state detection apparatus according to (3), wherein

[0090] further comprising a noise removal section that removes noise included in the acoustic signal,

[0091] the abnormality detection section detects the abnormality based on the acoustic signal output from the noise removal section.

[0092] (7) The device state detection apparatus according to any one of (1) to (5), wherein

[0093] the abnormality detection section outputs an alarm when the abnormality of the object is detected.

[0094] (8) The device state detection apparatus according to any one of (1) to (7), wherein

[0095] the abnormality detection section further detects a difference in vibration and sound until the action of the object reaches the abnormal action region as a margin.

[0096] (9) The device state detection apparatus according to any one of (1) to (8), wherein

[0097] the abnormality detection section further detects a quasi-abnormal action of the object based on a quasi-abnormal action region that is a region in contact with the abnormal action region.

[0098] (10) The device state detection apparatus according to (9), wherein

[0099] the abnormality detection section outputs a warning when the quasi-abnormal action of the object is detected.

[0100] (11) The device state detection apparatus according to (9), wherein

[0101] the abnormality detection section further detects a difference in vibration and sound until the action of the object reaches the quasi-abnormal action region as a second margin.

[0102] (12) The device state detection apparatus according to any one of (1) to (11), wherein

[0103] the abnormality detection section further detects an abnormality of another object that approaches the object.

[0104] (13) The device state detection apparatus according to any one of (1) to (12), wherein

[0105] The operation state is an operation load rate that is a ratio of a load to a rated load.

[0106] (14) The device state detection apparatus according to (1), wherein

[0107] Further provided is a processing section that processes a vibration signal that is a signal of vibration of the object and an acoustic signal that is a signal of sound of the object.

[0108] (15) A device state detection method, wherein

[0109] The device state detection method includes a step of detecting an anomaly of an object based on an abnormal action region that is a region of vibration of the object and sound from the object in a case where an action of the object is abnormal, and that is defined in accordance with an operation state of the object.

[0110] Explanation of Reference Signs

[0111] 10 Device state detection apparatus

[0112] 11 Noise removal section

[0113] 12 Preprocessing section

[0114] 13 Abnormality detection section

[0115] 15 Recording section

[0116] 16 Processing section

[0117] 20 Vibration sensor

[0118] 30 Microphone

[0119] 40 Pump

Claims

1. A device for detecting equipment status, wherein, The equipment status detection device has an abnormality detection unit that detects abnormalities in the object based on an abnormal action area. The abnormal action area is the area of ​​vibration and sound from the object when the object's action is abnormal, and is defined according to the object's operating state.

2. The equipment status detection device according to claim 1, wherein, The anomaly detection unit detects the anomaly based on the abnormal action area selected according to the operating state of the object.

3. The equipment status detection device according to claim 1, wherein, The anomaly detection unit detects the anomaly based on a vibration signal, which is a signal of vibration of the object, and an acoustic signal, which is a signal of sound of the object.

4. The equipment status detection device according to claim 3, wherein, The equipment condition detection device also includes a preprocessing unit for preprocessing the vibration signal. The anomaly detection unit detects the anomaly based on the preprocessed vibration signal.

5. The equipment status detection device according to claim 4, wherein, The preprocessing unit performs at least one of the following preprocessing steps: detection and processing of the effective value of the vibration signal, FFT processing, and statistical processing.

6. The equipment status detection device according to claim 3, wherein, The device status detection device also includes a noise removal unit for removing noise contained in the sound signal. The anomaly detection unit detects the anomaly based on the acoustic signal output from the noise removal unit.

7. The equipment status detection device according to claim 1, wherein, The anomaly detection unit outputs an alarm when it detects an anomaly in the object.

8. The equipment status detection device according to claim 1, wherein, The anomaly detection unit further detects the difference between vibration and sound until the object's movement reaches the abnormal movement area, as a margin.

9. The equipment status detection device according to claim 1, wherein, The anomaly detection unit further detects quasi-abnormal actions of the object based on a quasi-abnormal action region, which is the region in contact with the abnormal action region.

10. The equipment status detection device according to claim 9, wherein, The anomaly detection unit outputs a warning when it detects a quasi-abnormal action of the object.

11. The equipment status detection device according to claim 9, wherein, The anomaly detection unit further detects the difference between vibration and sound until the object's movement reaches the quasi-abnormal movement region as a second margin.

12. The equipment status detection device according to claim 1, wherein, The anomaly detection unit further detects anomalies in other objects that are close to the object being detected.

13. The equipment status detection device according to claim 1, wherein, The operating state is the operating load rate, which is the ratio of the load to the rated load.

14. The equipment status detection device according to claim 1, wherein, The device status detection apparatus further includes a processing unit that processes vibration signals, which are vibration signals of the object, and sound signals, which are sound signals of the object.

15. A method for detecting equipment condition, wherein, The device status detection method includes the following steps: detecting abnormalities of an object based on an abnormal action area, wherein the abnormal action area is the area of ​​vibration and sound from the object when the object's action is abnormal, and is defined according to the operating state of the object.

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