Equipment state detector and equipment state detection method

Abstract

To provide an equipment state detector for detecting operational abnormality of equipment or the like, that shortens detection time of operational abnormality of equipment or the like.SOLUTION: Provided is an equipment state detector for detecting operational abnormality of equipment or the like. The equipment state detector comprises an abnormality detection part. The abnormality detection part comprised in the equipment state detector detects abnormality of its object, on the basis of an abnormal operation area specified according to an operational state of the object, the area being an area of vibration of the object and an area of sound from the object when operation of the object is abnormal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an equipment status detection device and an equipment status detection method. [Background technology]

[0002] There have been proposed devices that detect operational abnormalities in equipment used in plants, factories, etc. For example, there has been proposed a device that detects abnormalities in rotating machinery by detecting sounds and vibrations generated by abnormal phenomena in the rotating body of rotating machinery in a plant (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 7-182035 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the above-mentioned prior art, since abnormalities are detected by a procedure of confirming the results of the acoustic diagnosis based on vibration data, there is a problem in that it takes a long time to detect abnormal operation.

[0005] Therefore, the present disclosure proposes an equipment status detection device and an equipment status detection method that shorten the time required to detect an operational abnormality in equipment or the like. [Means for solving the problem]

[0006] The equipment status detection device disclosed herein includes an abnormality detection unit that detects an abnormality in an object based on an abnormal operation area that is a range of vibrations and sounds from the object when the object is operating abnormally and is defined according to the operating state of the object. [Brief explanation of the drawings]

[0007] [Figure 1]1 is a diagram illustrating a configuration example of an equipment state detection device according to an embodiment of the present disclosure. [Figure 2] FIG. 10 is a diagram illustrating an example of an abnormal operation region according to an embodiment of the present disclosure. [Figure 3] FIG. 10 is a diagram illustrating an example of a processing procedure of an equipment state detection device according to an embodiment of the present disclosure. [Figure 4] FIG. 1 is a diagram illustrating an example of a processing procedure of an equipment state detection method according to an embodiment of the present disclosure. [Figure 5] FIG. 10 is a diagram illustrating an example of noise removal according to an embodiment of the present disclosure. [Figure 6] FIG. 10 illustrates an example of a noise removal procedure according to an embodiment of the present disclosure. [Figure 7] FIG. 10 is a diagram illustrating an example of detection of a margin according to an embodiment of the present disclosure. [Figure 8] FIG. 10 is a diagram illustrating an example of anomaly detection according to an embodiment of the present disclosure. [Figure 9] FIG. 10 is a diagram illustrating an example of detection of an abnormality in another facility according to an embodiment of the present disclosure. [Figure 10] FIG. 10 is a diagram illustrating an example of a modified example of an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The description will be given in the following order. In the following embodiments, the same components are designated by the same reference numerals, and redundant description will be omitted. 1. Embodiment 2. Variations

[0009] (1. Embodiment) [Configuration of equipment status detection device] FIG. 1 is a diagram illustrating an example configuration of an equipment status detection device according to an embodiment of the present disclosure. The same figure is a block diagram illustrating an example configuration of the equipment status detection device 10. The equipment status detection device 10 detects the status of equipment used in a plant or factory. This status includes an abnormal state during operation of the equipment. The equipment status detection device 10 detects the status of an object. The object is assumed to be a pump 40. The pump 40 is a device that is rotationally driven by a motor to pump a liquid such as water. Note that the object can also be a device with a rotating mechanism such as a generator or a compressor.

[0010] The equipment state detection device 10 includes a noise removal unit 11, a preprocessing unit 12, an abnormality detection unit 13, a memory unit 14, a recording unit 15, and a processing unit 16. The figure also shows a vibration sensor 20 and a microphone 30.

[0011] The vibration sensor 20 is attached to the pump 40 and detects vibrations. The vibration sensor 20 generates a vibration signal, which is a signal of vibration, and outputs it to the equipment state detection device 10.

[0012] The microphone 30 is disposed near the pump 40 and detects sound from the pump 40. The microphone 30 generates an acoustic signal, which is a sound signal, and outputs it to the equipment state detection device 10.

[0013] It should be noted that a composite sensor that detects vibrations and sounds can be used instead of the vibration sensor 20 and the microphone 30. Also, a camera can be used instead of the vibration sensor 20. In this case, vibrations are detected from the movement of an image captured by the camera.

[0014] The noise removal unit 11 removes noise from the acoustic signal. The acoustic signal from which noise has been removed is input to the abnormality detection unit 13. Details of noise removal will be described later. Note that the acoustic signal from which noise has been removed can be subjected to FFT (Fast Fourier Transform) processing for frequency analysis, statistical processing, and the like.

[0015] The pre-processing unit 12 performs pre-processing of the vibration signal. This pre-processing corresponds to, for example, detection of the root mean square value (RMS) of the vibration signal. The detection of the effective value can be performed, for example, by calculating the effective value of the vibration signal for a predetermined period. A known method can be used to calculate the effective value. The effective value of the vibration signal is input to the abnormality detection unit 13. Note that the above-mentioned FFT processing and statistical processing can also be performed as pre-processing. Note that the pre-processing unit 12 can also be omitted. In this case, the abnormality detection unit 13, which will be described later, performs processing based on the vibration signal from the vibration sensor 20.

[0016] The abnormality detection unit 13 detects an abnormality in the object (pump 40) based on the abnormal operation area. Here, the abnormal operation area is an area of ​​vibrations and sounds from the object when the object is operating abnormally, and is defined according to the operating state of the object. Details of the abnormal operation area will be described later. When the abnormality detection unit 13 detects an abnormality in the object, it outputs an abnormality detection signal to an external device. This abnormality detection signal is, for example, an alarm signal.

[0017] Furthermore, the abnormality detection unit 13 further detects quasi-abnormal behavior of the object based on a quasi-abnormal behavior area, which is an area adjacent to the abnormal behavior area. This quasi-abnormal behavior is not an abnormal state, but is a state that needs to be made known. When the abnormality detection unit 13 detects a quasi-abnormal behavior, it outputs a warning.

[0018] The memory unit 14 stores information about the abnormal operation region. The abnormality detection unit 13 detects an abnormality based on the abnormal operation region stored in the memory unit 14. The memory unit 14 also stores information about the quasi-abnormal operation region. The abnormality detection unit 13 detects a quasi-abnormal operation based on the quasi-abnormal operation region stored in the memory unit 14.

[0019] The recording unit 15 records the acoustic signal and the vibration signal. The recording unit 15 in the figure records the acoustic signal output from the noise removal unit 11 and the vibration signal output from the pre-processing unit 12. The recording unit 15 also outputs the recorded acoustic signal and vibration signal to the processing unit 16.

[0020] The processing unit 16 processes the acoustic signals and vibration signals recorded in the recording unit 15. The processing by the processing unit 16 corresponds to, for example, equipment condition evaluation (e.g., evaluation of disassembly, inspection, cleaning, etc.). Specifically, the processing unit 16 can evaluate each task from changes in the acoustic signals and vibration signals before and after each task. By evaluating each standard task, for example, it is possible to understand the work effectiveness of workers and apply this to work improvements (such as improvements to the level of cleaning, procedures, and amount of consumables used). Furthermore, by periodically measuring acoustics and vibrations, it is possible to understand the condition of the target equipment. By comparing the results with the standard condition of the target equipment, it is also possible to perform maintenance and preservation according to the equipment condition at an appropriate time.

[0021] The equipment state detection device 10 can also detect states other than abnormal operation of the object. For example, it can be configured to further include an output detection unit that detects the output of the object (pump 40) and to perform processing on the detected output of the object.

[0022] [Abnormal operation area] FIG. 2 is a diagram illustrating an example of an abnormal operation region according to an embodiment of the present disclosure. The figure is a graph showing the abnormal operation region. The X-axis of the graph represents vibration. The Y-axis of the graph represents sound. In the figure, the open triangular region represents the normal operation region 100. The dotted hatched region represents the abnormal operation region 102. The region of vibration and sound during abnormal operation corresponds to the abnormal operation region. The diagonally hatched region represents the quasi-abnormal operation region 101. Note that the vertices on the right side of the normal operation region 100 and the quasi-abnormal operation region 101 correspond to the resonance points. At the resonance points, sound and vibration tend to increase, but do not result in abnormal operation.

[0023] The open circle 111 represents the operating point during normal operation. In this state, if some malfunction occurs and vibration increases, the operating point moves to the open circle 112. At this time, if the increase in vibration causes an increase in sound, the operating point moves to the circle 113. As a result, the object reaches the quasi-abnormal operating region 101. In this way, it is possible to detect whether the object is in the quasi-abnormal operating region or the abnormal operating region from the position on the sound and vibration graph.

[0024] This utilizes the fact that the relationship between sound and vibration under normal conditions breaks down under abnormal conditions. It is also possible to construct a relationship between sound and vibration by focusing on specific frequency components.

[0025] Furthermore, areas 120 and 130 represent normal operation areas of the other equipment. Furthermore, areas 121 and 131 represent abnormal operation areas of the other equipment. In this way, areas with low vibrations or low sounds can be considered to be the state of other equipment different from the target object.

[0026] The Z-axis in the figure represents the rotation speed. The normal operating region 100, quasi-abnormal operating region 101, and abnormal operating region 102 in the figure correspond to the region at the maximum rotation speed. Although not shown, the normal operating region 100, quasi-abnormal operating region 101, and abnormal operating region 102 are generated for each specific rotation speed. In the figure, the object is a pump 40, so the rotation speed is used as a parameter. The operating load factor of the object can be applied to the Z-axis. Here, the operating load factor represents the ratio of the actual load to the rated load (maximum load). The normal operating region 100, quasi-abnormal operating region 101, and abnormal operating region 102 in the figure can be considered to be a state where the operating load factor is 100% (rated load). Furthermore, the quasi-abnormal operating region 101 and abnormal operating region 102 can be defined for each specific operating load factor, such as 90%, 80%, and 70%, for example.

[0027] The abnormality detection unit 13 can select the quasi-abnormal operation area 101 and the abnormal operation area 102 according to the driving load factor of the object, and use them to detect the quasi-abnormal operation and the abnormal operation.

[0028] The Z axis in FIG. 2 may represent other parameters, such as pressure or light (absorbance).

[0029] [Facility status detection device processing] 3 is a diagram illustrating an example of a processing procedure of an equipment status detection device according to an embodiment of the present disclosure. The figure is a flowchart illustrating an example of a processing procedure of an abnormality detection process in the equipment status detection device 10. First, the abnormality detection unit 13 corrects (calibrates) the position (posture) of the vibration sensor 20 (step S101). When a three-axis acceleration sensor is used as the vibration sensor 20, the magnitude of the gravitational acceleration appearing on the three axes changes depending on the posture of the sensor, and this can be used for correction. In addition, the attachment strength (the tension when tensioned) when the vibration sensor 20 is attached to the equipment can also be corrected.

[0030] Next, the abnormality detection unit 13 determines whether an abnormal operation area has been generated (step S102). If an abnormal operation area has not been generated (step S102, No), the abnormality detection unit 13 generates an abnormal operation area (step S103). The generation of an abnormal operation area will be described later. Next, the abnormality detection unit 13 acquires a vibration signal and an acoustic signal (step S104). Next, the abnormality detection unit 13 executes an abnormality detection process (step S110).

[0031] Next, the abnormality detection unit 13 detects an abnormality in the other equipment (step S105). Details of the abnormality detection in the other equipment will be described later.

[0032] Next, the abnormality detection unit 13 determines whether to continue the processing (step S106). If the processing is to be continued (step S106, Yes), the abnormality detection unit 13 determines whether the measurement conditions have been changed (step S107). If the measurement conditions have been changed (step S107, Yes), the abnormality detection unit 13 proceeds to the processing of step S101. On the other hand, if the measurement conditions have not been changed (step S107, No), the abnormality detection unit 13 proceeds to the processing of step S102.

[0033] On the other hand, in step S106, if the process is not to be continued (step S106, No), the abnormality detection unit 13 ends the process.

[0034] [Anomaly detection processing] FIG. 4 is a diagram illustrating an example of a processing procedure of an abnormality detection process according to an embodiment of the present disclosure. The figure is a flowchart illustrating an example of a processing procedure of the abnormality detection process (step S110) in FIG. 3. First, the noise removal unit 11 removes noise from the acoustic signal (step S111). Next, the abnormality detection unit 13 detects a margin of safety based on the acoustic signal, the vibration signal, and the abnormal motion area (step S112). Here, the margin of safety represents the difference between vibration and sound until the motion of the object reaches the abnormal motion area. The detection of this margin of safety will be described later. Next, the abnormality detection unit 13 detects an abnormality based on the margin of safety (step S113). After that, the abnormality detection unit 13 returns to the original processing.

[0035] [Generating information on abnormal operating areas] A diagnostic range (normal operating range) is defined based on the operation of the pump 40 (for example, one week), and an abnormal operating range is defined based on the start and stop operations of the pump 40. For example, based on the range of sound and vibration when the pump 40 is started and stopped, a range of ±10% can be defined as the normal operating range, ±15% as the quasi-abnormal operating range, and ±20% as the abnormal operating range.

[0036] [Noise Reduction] FIG. 5 is a diagram illustrating an example of noise removal according to an embodiment of the present disclosure. Similar to FIG. 2, this figure is a graph showing an abnormal operation region. Also, similar to FIG. 2, circle 111 represents the operating point during normal operation. If the sound increases without a change in vibration from this state, the operating point shifts to the position of circle 114, as indicated by the hollow arrow in the figure. This state of increased sound without a change in vibration is considered to be a state in which sound due to the operation of other equipment has been added. Therefore, a process is performed to subtract the change in sound and return to the original operating point (indicated by the black arrow in the figure). This allows noise removal. Specific procedures are described below.

[0037] FIG. 6 is a diagram illustrating an example of a noise removal procedure according to an embodiment of the present disclosure. The diagram in the upper part of the figure illustrates changes in the margin. The diagram in the lower part of the figure illustrates the acoustic signal over time in the diagram in the upper part of the figure. The diagram on the left in the lower part illustrates the original acoustic signal before the sound changes. The diagram in the center of the lower part illustrates a state in which the sound suddenly increases. The sound of the increased frequency components in the diagram in the lower part corresponds to the sound (noise) caused by the operation of a surrounding process. Noise can be removed by subtracting the sound of this increased frequency component. The diagram on the right in the lower part illustrates the acoustic signal after noise removal.

[0038] The noise removal unit 11 continuously records the audio signal and detects sudden increases in sound. Next, the noise removal unit 11 performs a subtraction process of the suddenly increased sound components. Noise can be removed by the above procedure.

[0039] [Margin detection] FIG. 7 is a diagram illustrating an example of margin detection according to an embodiment of the present disclosure. Similar to FIG. 2, this figure is a graph showing an abnormal operation region. Also, similar to FIG. 2, a circle 111 represents an operating point during normal operation. As described above, margin is the difference in vibration and sound until the object's operation reaches the abnormal operation region. This margin can be detected by the following procedure. First, the abnormality detection unit 13 generates the smallest circle that is centered on the circle 111 and is tangent to the abnormal operation region 102. The dotted circle 211 in FIG. 7 represents this circle. Next, the abnormality detection unit 13 detects the radius of this circle 211 as the margin.

[0040] The abnormality detection unit 13 can further detect the difference in vibration and sound until the object's movement reaches the quasi-abnormal movement region 101 as a second margin of error. The abnormality detection unit 13 generates the smallest circle that is centered on the circle 111 and tangent to the quasi-abnormal movement region 101. The dashed circle 212 in the figure represents this circle. Next, the abnormality detection unit 13 detects the radius of this circle 212 as the second margin of error.

[0041] [Anomaly Detection] FIG. 8 is a diagram illustrating an example of abnormality detection according to an embodiment of the present disclosure. The figure illustrates an example of detecting abnormalities in the behavior of an object based on the margin of safety. The horizontal axis of the figure represents time. The dashed-dotted line in the figure represents the level of value "0." Graph 221 illustrates changes in the margin of safety. When the margin of safety reaches the value "0," the abnormality detection unit 13 can determine that the operating point of the object has reached the abnormal operation region. Note that a negative margin of safety represents a state in which the operating point is included in the abnormal operation region. In this way, the abnormality detection unit 13 can detect abnormalities in the behavior of an object based on the margin of safety.

[0042] Graph 222 represents the second margin of safety. When this second margin of safety becomes "0", the abnormality detection unit 13 can determine that the operating point of the object has reached the quasi-abnormal operation region.

[0043] [Detection of abnormalities in other equipment] The abnormality detection unit 13 detects an abnormality in the other equipment based on the areas 121 and 131 of the other equipment in FIG.

[0044] It is also possible to detect abnormalities based on the sounds of other equipment as explained in Fig. 6. This procedure will be explained next.

[0045] 9 is a diagram illustrating an example of detecting an abnormality in another piece of equipment according to an embodiment of the present disclosure. The abnormality detection unit 13 extracts the sound of the other piece of equipment (top row of FIG. 9). Next, the abnormality detection unit 13 estimates a vibration signal based on the relationship between the sound and vibration acquired in advance (middle row of FIG. 9). Next, the abnormality detection unit 13 generates vibration data through estimation (bottom row of FIG. 9). The abnormality detection unit 13 detects an abnormality in the other piece of equipment using the generated vibration data and the extracted sound of the other piece of equipment.

[0046] The process in this figure is a simple method because vibrations of other equipment are not detected.

[0047] In this way, in the equipment status detection device 10 according to the embodiment of the present disclosure, the abnormality detection unit 13 detects an abnormality in an object by simultaneously using an acoustic signal and a vibration signal, thereby shortening the time required to detect an abnormality.

[0048] (2. Modifications) In the above-described embodiment, abnormalities are detected assuming that the target is a device having a moving part such as the pump 40. An example of applying this abnormality detection to other devices will now be described.

[0049] FIG. 10 is a diagram showing an example of a modified embodiment of the present disclosure. This diagram illustrates an example of detecting sound and vibration in a pipe. When a liquid flows through a pipe, it vibrates and generates a vibration sound. When a multiphase flow occurs or when a slurry flows, vibrations and the like occur significantly. By detecting these vibrations and sounds, an abnormality in the pipe can be detected. Note that the target is not limited to a pump 40 or a pipe, and the present invention can also be applied to other devices and equipment.

[0050] Although the embodiments of the present disclosure have been described above, the technical scope of the present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure. Furthermore, components of different embodiments and modifications may be combined as appropriate.

[0051] The series of processes performed by each device described in this specification may be realized using software, hardware, or a combination of software and hardware. The programs constituting the software are stored in advance in, for example, a storage medium (non-transitory medium) provided inside or outside each device. Then, each program is loaded into RAM when executed by a computer, and executed by a processor such as a CPU.

[0052] Furthermore, the processes described herein using flowcharts and sequence diagrams do not necessarily have to be performed in the order shown. Some process steps may be performed in parallel. Furthermore, additional process steps may be employed, and some process steps may be omitted.

[0053] The processing procedures described in the above embodiments may be regarded as a method having a series of these procedures, or as a program for causing a computer to execute the series of procedures or a recording medium for storing the program. Examples of recording media that can be used include CDs (Compact Discs), MDs (Mini Discs), DVDs (Digital Versatile Discs), memory cards, and Blu-ray (registered trademark) Discs.

[0054] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0055] Some examples of combinations of the disclosed technical features are set out below. (1) An equipment status detection device comprising an abnormality detection unit that detects an abnormality in an object based on an abnormal operation area defined according to the operating state of the object, which is an area of ​​vibrations and sounds from the object when the object is operating abnormally. (2) The equipment state detection device according to (1), wherein the abnormality detection unit detects the abnormality based on the abnormal operation area selected based on the operating state of the object. (3) The equipment status detection device according to (1) or (2), wherein the abnormality detection unit detects the abnormality based on 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. (4) a pre-processing unit that performs pre-processing of the vibration signal; The abnormality detection unit detects the abnormality based on the preprocessed vibration signal. The equipment status detection device according to (3) above. (5) The equipment state detection device according to (4), wherein the preprocessing unit performs at least one of detection processing of an effective value of the vibration signal, FFT processing, and statistical processing as the preprocessing. (6) further comprising a noise removal unit that removes noise contained in the acoustic signal; The abnormality detection unit detects the abnormality based on the acoustic signal output from the noise removal unit. The equipment status detection device according to (3) above. (7) The equipment state detection device according to any one of (1) to (5), wherein the abnormality detection unit outputs an alarm when an abnormality in the object is detected. (8) The equipment status detection device according to any one of (1) to (7), wherein the abnormality detection unit further detects the difference in vibration and sound until the operation of the object reaches the abnormal operation region as a margin of error. (9) The equipment status detection device described in any one of (1) to (8), wherein the abnormality detection unit further detects quasi-abnormal operation of the object based on a quasi-abnormal operation area that is an area adjacent to the abnormal operation area. (10) The equipment state detection device according to (9), wherein the abnormality detection unit outputs a warning when detecting a quasi-abnormal operation of the object. (11) The equipment state detection device according to (9), wherein the abnormality detection unit further detects, as a second margin, a difference in vibration and sound until the operation of the object reaches the quasi-abnormal operation region. (12) The equipment state detection device according to any one of (1) to (11), wherein the abnormality detection unit further detects an abnormality in another object in the vicinity of the object. (13) The equipment state detection device according to any one of (1) to (12), wherein the operating state is an operating load factor, which is a ratio of a load to a rated load. (14) The equipment state detection device according to (1) above, further comprising a processing unit 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. (15) An equipment status detection method including detecting an abnormality in an object based on an abnormal operation area defined according to the operating state of the object, which is an area of ​​vibrations of the object and sounds from the object when the object is operating abnormally. [Explanation of symbols]

[0056] 10 Equipment status detection device 11 Noise reduction section 12 Pretreatment section 13 Abnormality detection unit 15 Recording section 16 Processing section 20 Vibration Sensor 30. Mike 40 Pump

Claims

1. An equipment status detection device comprising an abnormality detection unit that detects an abnormality in an object based on an abnormal operation area defined according to the operating state of the object, which is an area of ​​vibrations and sounds from the object when the object is operating abnormally.

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

3. The equipment state detection device according to claim 1 , wherein the abnormality detection unit detects the abnormality based on 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.

4. a pre-processing unit that performs pre-processing of the vibration signal; The abnormality detection unit detects the abnormality based on the preprocessed vibration signal. The equipment state detection device according to claim 3.

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

6. further comprising a noise removal unit that removes noise contained in the acoustic signal; The abnormality detection unit detects the abnormality based on the acoustic signal output from the noise removal unit. The equipment state detection device according to claim 3.

7. The equipment state detection device according to claim 1 , wherein the abnormality detection unit outputs an alarm when an abnormality in the object is detected.

8. The equipment state detection device according to claim 1 , wherein the abnormality detection unit further detects, as a margin of safety, a difference in vibration and sound until the movement of the object reaches the abnormal movement region.

9. The equipment state detection device according to claim 1 , wherein the abnormality detection unit further detects a quasi-abnormal operation of the object based on a quasi-abnormal operation region that is a region adjacent to the abnormal operation region.

10. The equipment state detection device according to claim 9 , wherein the abnormality detection unit outputs a warning when a quasi-abnormal operation of the object is detected.

11. The equipment state detection device according to claim 9 , wherein the abnormality detection unit further detects, as a second margin, a difference in vibration and sound until the operation of the object reaches the quasi-abnormal operation region.

12. The equipment state detection device according to claim 1 , wherein the abnormality detection unit further detects an abnormality in another object in the vicinity of the object.

13. 2. The equipment state detection device according to claim 1, wherein the operating state is an operating load factor, which is a ratio of a load to a rated load.

14. The equipment state detection device according to claim 1 , further comprising a processing unit 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.

15. An equipment status detection method including detecting an abnormality in an object based on an abnormal operation area defined according to the operating state of the object, which is an area of ​​vibrations of the object and sounds from the object when the object is operating abnormally.

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