Mechanical equipment and fault monitoring method of mechanical equipment

Abstract

The invention relates to a fault monitoring method for mechanical equipment and the mechanical equipment, the mechanical equipment is provided with a moving part, and the method comprises the following steps: receiving frequency spectrum information of the moving part; receiving motion information of the motion part; and performing fault monitoring on the equipment according to the corresponding relationship between the frequency spectrum information and the motion information. According to the fault monitoring method of the mechanical equipment and the mechanical equipment, the fault of the mechanical equipment can be effectively monitored.

Description

Technical Field

[0001] The present disclosure relates to the mechanical field, and in particular, to a mechanical device and a fault monitoring method for the mechanical device. Background Art

[0002] Mechanical equipment often includes moving parts, which generate driving force and transmit the driving force to complete various motions of the mechanical equipment to meet actual needs. The moving parts of mechanical parts have a service life, and this service life cannot be judged solely by age and usage time, but there are large individual differences. Traditional methods rely on maintenance personnel for inspection and maintenance, which is often regular. This means that there may be parts damaged before regular inspections, which need to be repaired and replaced, causing abnormal shutdowns of mechanical equipment. Therefore, a timely fault monitoring method is needed to judge the fault condition of the equipment at any time and greatly avoid abnormal shutdowns. Summary of the invention

[0003] In view of this, the present disclosure provides a mechanical device and a fault monitoring method for the mechanical device.

[0004] According to an exemplary embodiment of the present disclosure, a fault monitoring method for a mechanical device is provided, wherein the mechanical device has a moving part, and the method comprises: receiving frequency spectrum information of the moving part; receiving motion information of the moving part; and performing fault monitoring on the device based on a correspondence between the frequency spectrum information and the motion information.

[0005] According to an exemplary embodiment of the present disclosure, the moving component includes a moving load-bearing component and a moving driving component, and the moving driving component drives the moving load-bearing component to move. The receiving of frequency information of the moving component includes: receiving frequency spectrum information of a first type of sensor located on the moving load-bearing component; and receiving frequency spectrum information of a second type of sensor located on the moving driving component.

[0006] According to an exemplary embodiment of the present disclosure, the mechanical equipment is a medical bed, the moving load-bearing component includes a bed board, the moving driving component includes a motor, the first type of sensor is an inertial sensor, the second type of sensor is a sound sensor, the inertial sensor is arranged at a panel hinge of the bed board, and the sound sensor is arranged at the motor; receiving the motion information of the moving component includes: receiving the rotation frequency information of the motor.

[0007] According to an exemplary embodiment of the present disclosure, the motion information includes: the position, load-bearing capacity, motion direction, motion speed and motion acceleration of the bed board.

[0008] According to an exemplary embodiment of the present disclosure, the fault monitoring includes monitoring the severity of the fault and monitoring the type of the fault, and the types of the fault include: motor fault, bearing fault, slide rail fault, conveyor belt fault, push rod fault and support member deformation fault.

[0009] According to an exemplary embodiment of the present disclosure, a self-check process is further included, and the self-check process includes:

[0010] The hospital bed is controlled to move in different specific motion modes, and the frequency spectrum information of the moving parts is received, and the type of the fault is judged according to the correspondence between the frequency spectrum information and the information of the specific motion mode.

[0011] According to an exemplary embodiment of the present disclosure, the fault severity includes: a first fault severity, a second fault severity and a third severity, and the fault monitoring method includes: in response to the fault severity being the first fault severity, shutting down the medical bed; in response to the fault severity being the second fault severity, performing a self-inspection process on the medical bed at a specific time; in response to the fault severity being the third severity, shutting down the medical bed and then performing the self-inspection process.

[0012] According to an exemplary embodiment of the present disclosure, the specific timing includes: obtaining historical usage data of the medical bed, selecting idle time in the future that is greater than a first duration; receiving an input operation, obtaining the time corresponding to the input operation; and / or the standby time of the medical bed.

[0013] According to an exemplary embodiment of the present disclosure, during the self-examination process, any operation on the hospital bed is received, the self-examination process is stopped, and information on the steps of the self-examination process is recorded, and the self-examination process is continued when the self-examination process is continued at the next specific opportunity.

[0014] According to an exemplary embodiment of the present disclosure, a mechanical device includes a moving part, and the mechanical device also includes a processing device, and the processing device executes any of the above-mentioned fault monitoring methods.

[0015] According to the mechanical equipment and the fault monitoring method of mechanical equipment provided by the present disclosure, the faults of the mechanical equipment can be effectively monitored, the fault information can be obtained in time, and abnormal shutdown can be avoided to a great extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings, so that those skilled in the art will be more aware of the above and other features and advantages of the present disclosure. In the accompanying drawings:

[0017] Figure 1The hardware architecture of the bed status monitoring system of the exemplary embodiment of the present disclosure;

[0018] Figure 2 The software architecture of the bed status monitoring system of the exemplary embodiment of the present disclosure;

[0019] Figure 3 A schematic diagram of a monitoring flow with a self-checking process according to an exemplary embodiment of the present disclosure;

[0020] The reference numerals are as follows:

[0021] DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present disclosure more clear, the present disclosure is further described in detail with reference to the following examples. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure.

[0023] In an exemplary embodiment, a fault monitoring method for mechanical equipment is provided, wherein the mechanical equipment has a moving part, and the method includes: receiving spectrum information of the moving part; receiving motion information of the moving part; and performing fault monitoring on the equipment according to the correspondence between the spectrum information and the motion information. Many mechanical equipment include moving parts that can perform various actions, and these mechanical equipment rely on these movements to achieve various functions. For example, a car relies on the rotation of wheels to complete the transportation function, and a robot relies on the multi-axis movement of a mechanical arm to complete various functions. Here, the type of mechanical equipment is not limited, as long as it has moving parts. Mechanical movement will inevitably produce vibrations. The inventors of the present disclosure have found that the spectrum information of these vibrations is related to the fault, and the abnormal spectrum can represent the occurrence of the fault. The spectrum information can be analyzed to monitor the fault. Further, the inventors of the present disclosure have also found that when the movement is in different states, the fault characteristics in the spectrum information will also be different accordingly. Therefore, when analyzing the spectrum information, it is matched with the motion information to obtain the fault more accurately. Here, motion information refers to information related to the movement of moving parts. For example, for a car, it can refer to the speed and torque of the moving part engine, or the speed, acceleration, load-bearing capacity of the wheels (that is, the distribution of the vehicle's weight on each wheel, and the change in wheel load-bearing capacity caused by bumps) and the steering information of the wheels. For a robot, it can refer to the speed and torque of the drive motor, or the position, movement direction, movement speed, movement acceleration and load information of the robotic arm. These motion information will cause the frequency spectrum corresponding to the same fault to change. Therefore, while recording the frequency spectrum information, the corresponding state of the moving parts is also recorded, and the fault can be judged more accurately based on the correspondence between the frequency spectrum information and the motion information.

[0024] There are many methods to monitor equipment faults based on the correspondence between spectrum information and motion information. For example, historical data can be recorded, the spectrum information and motion information corresponding to various faults can be recorded, and these data can be trained, and artificial intelligence technology can be used to obtain the correspondence between spectrum information and faults. As long as a large enough training sample is accumulated, the accuracy of recognition can fully meet the actual needs. Another alternative is to manually set judgment rules. When it is observed that the frequency information of a certain fault has specific characteristics, for example, when the component of a specific frequency under a specific motion is higher than a certain threshold, it is caused by severe wear of a specific bearing. Such a rule is set artificially. When the component of a specific frequency under a specific motion is higher than a certain threshold, it is judged to be wear of a specific bearing. Since there is a correlation between the spectrum information, motion information and faults of moving parts, as long as the historical information between them is recorded, various algorithms can be used to determine this correlation, thereby providing a judgment basis for fault monitoring.

[0025] In an exemplary embodiment, the moving part includes a moving load-bearing part and a moving driving part, the moving driving part drives the moving load-bearing part to move, and receiving the frequency information of the moving part includes: receiving the spectrum information of the first type of sensor located on the moving load-bearing part; receiving the spectrum information of the second type of sensor located on the moving driving part. In mechanical equipment, the moving load-bearing part is used to carry the operating object of the mechanical equipment or other objects that need to be carried. For example, the robot arm of a robot is used to grab parts, and the robot arm is the load-bearing part of the robot. The moving driving part is a part such as a motor that drives the moving load-bearing part. Usually, the motor of the moving driving part generates power by rotation, and then transmits the power to the moving load-bearing part through various transmission parts. The transmission part is often a reducer, a slide rail, a bearing, a screw and / or a gearbox, and the vibration generated by the transmission part will be transmitted to the moving load-bearing part. Since the vibrations generated by the moving driving part and the moving transmission part have different characteristics, for example, the moving driving part is mainly a rotational vibration, while the causes of the vibration of the moving load-bearing part are various. Therefore, two types of sensors can be used to collect vibration information on moving load-bearing components and moving driving components respectively, and process them into spectrum information to improve the accuracy of judgment. At the same time, when considering the type of sensor, the convenience and cost of installation can also be comprehensively considered.

[0026] In an exemplary embodiment, in particular, taking the mechanical device as a medical bed as an example, the motion bearing component includes a bed board, which is used to directly carry the patient, and the motion driving component includes a motor. The first type of sensor is an inertial sensor, and the second type of sensor is a sound sensor. The inertial sensor is arranged at the panel hinge of the bed board, and the sound sensor is arranged at the motor. The vibration of the bed board is caused by various reasons, and may include low-frequency vibrations that are difficult to sense with a microphone, so a more precise inertial sensor (IMU) is used to accurately obtain vibration information through the measurement of acceleration and rotational motion. Among IMUs, MEMS sensors with a size of only a few millimeters are more suitable for the technical solution of the present disclosure, and their sensing frequency range is wide and the accuracy is high. As for the drive motor, since the motion is relatively simple, mainly rotational motion, it is more suitable to use a sound sensor. This is not only cheaper, but on the other hand, the sound information is also more suitable for motor fault monitoring, such as bearing wear, eccentric rotation, and loose fasteners, which will cause changes in the sound spectrum, that is, abnormal sound. In addition, the motor is often encapsulated in a component such as a push rod, and it is often inconvenient to set an acceleration sensor on it, and more design modifications are required. However, a sound sensor such as a microphone can be set at a distance from the motor, which has little effect on the sound collection. Of course, filtering is important for sound collection to avoid interference. In addition, since the sound source is widely present in the environment. Another microphone can be set at a position farther away from the motor to collect environmental sounds, and these environmental sounds can be removed from the information collected by the microphone near the motor to accurately obtain the sound generated by the rotation of the motor. Receiving the motion information of the moving part includes: receiving the rotation frequency information of the motor, and further, the torque information of the motor can also be received. This setting takes into account that the rotation information of the motor is the main one, and the abnormal rotation of the motor can be completely collected using a microphone. On the other hand, vibration may include audio and non-audio. If inertial sensors are used, it is easy to make it difficult to distinguish whether the vibration source comes from the motor or from other vibrations. Using a sound sensor and removing the environmental sound can more accurately obtain the sound from the motor. This precise positioning of the source of vibration makes it easier to locate the cause of the abnormality.

[0027] In an exemplary embodiment, the motion information includes: the position, load-bearing, motion direction, motion speed and motion acceleration of the bed board. In order to determine the abnormality more accurately, the motion information needs to be recorded at the same time. This is because, on the one hand, the spectrum information corresponding to some defects will only appear in a specific motion mode, and on the other hand, the defect information corresponding to some spectrum information will have changes such as aggravation or alleviation in certain specific motion modes. In this way, when recording the spectrum information, it is necessary to record the motion mode corresponding to this spectrum information, that is, in what kind of motion mode the spectrum is recorded. The motion information describing the motion mode includes but is not limited to the position, load-bearing, motion direction, speed and acceleration of the bed board. For example, the position of the bed board often corresponds to the position of each component of the moving part, which means that some motion positions will cause the defective parts to contact and thus be exposed on the spectrum. Similarly, for the motion direction of the bed board, the motion direction of the bed board includes upward motion, downward motion, and horizontal motion, such as horizontal motion extending into the inspection cavity and horizontal motion exiting the inspection cavity, or the acceleration of the motion, which will have a corresponding relationship with certain defects. In particular, for the load-bearing capacity of the bed board, it can not only be inferred by the output power of the motor, but also can be directly obtained by the pressure sensor.

[0028] In an exemplary embodiment, the monitoring of faults includes monitoring the severity of the fault and monitoring the type of fault. The types of faults include: motor fault, bearing fault, slide rail fault, conveyor belt fault, push rod fault and support deformation fault. The main purpose of analyzing the spectrum to obtain fault information is to prompt the relevant personnel of the machine status. In this embodiment, the status of the equipment is prompted to the relevant personnel in two dimensions. The first dimension is the severity of the fault. This dimension mainly prompts the relevant personnel to what extent the fault of the equipment is serious, for example, it has already needed to be shut down, or it needs further inspection and determination by maintenance personnel, or it will soon enter the level of needing to be shut down, and it is necessary to confirm and obtain relevant spare parts as soon as possible for replacement. This kind of fault severity is similar to the prediction of life, whether the life has expired, is about to expire, or needs further inspection and determination by relevant personnel. In the second dimension, the detection of faults also includes the monitoring of fault types. The type of fault can provide information on what spare parts need to be prepared and where to inspect, which is very useful reference information for maintenance personnel. As mentioned above, for a hospital bed, the various components of its moving parts will have different performances on the spectrum when different faults occur. Using this information, the types of faults can be classified. The type of fault may include which component the fault occurred in, including but not limited to motors, bearings, slide rails, conveyor belts, push rods and supports, as well as the specific damage mode of the component. For example, for a hospital bed that uses scissor legs as supports, the two scissor legs may have deformation faults or wear faults. By analyzing the vibration spectrum, it can be determined not only that the scissor legs have failed, but also what kind of fault has occurred. By combining information on the severity and type of the fault, an accurate judgment is made on the health status of the bed, which greatly avoids personal injury caused by the bed "working with a disease", or further expansion of the bed's own fault, or unexpected shutdown of the bed.

[0029] In an exemplary embodiment, a self-check process is also included, which includes: controlling the bed to move in different specific motion modes, receiving the spectrum information of the moving parts, and judging the type of fault according to the correspondence between the spectrum information and the information of the specific motion mode. The motion mode of the bed in actual use must meet the needs of transporting patients, and these motion modes may not be motion modes that can obviously expose related faults. In order to make the faults of the bed clearly exposed, a self-check process is set in this embodiment. During the self-check process, the bed moves in various pre-set ways that can maximize the exposure of various fault-related information. This process can be regarded as a "physical examination" of the bed, so as to find hidden dangers that have not been exposed in actual use, and promptly notify relevant personnel to conduct inspections and repairs, thereby further improving safety and reliability. This self-check process can be carried out regularly, in a specific cycle, such as monthly or quarterly. Of course, the self-check cycle can be set according to the time when the historical fault occurred. For example, this cycle can be related to the service life of the bed. As the age increases, the cycle is shortened accordingly. For example, if the bed is used for one year, it should be self-inspected once a year; if it is used for 2-5 years, it should be self-inspected once every six months; if it is used for 5-8 years, it should be self-inspected once a quarter; if it is used for more than 8 years, it should be self-inspected once a month.

[0030] In an exemplary embodiment, the fault severity includes: a first fault severity and a second fault severity, and the fault monitoring method includes: in response to the fault severity being the first fault severity, shutting down the medical bed; in response to the fault severity being the second fault severity, performing a self-check process on the medical bed at a specific time; in response to the fault severity being the third severity, shutting down the medical bed and then performing a self-check process. When the bed fault reaches a very serious level, that is, the first fault severity, it may affect the safety of use, such as the uncontrolled sudden acceleration of the bed or the sudden fall. In order to ensure the safety of the patient, the shutdown operation should be performed in this case and the maintenance personnel should be notified immediately. However, when the severity of the bed is not high, or when it is difficult to determine the type of fault or a more precise severity under the premise of low severity, that is, when the second severity, the medical bed is self-checked to make a more accurate judgment on the severity and type of the fault. The severity of the fault may also include the third severity level. In the case of a third severity level fault, the detected fault may be more serious, but based on the current data, the monitoring result is in an uncertain state, normal operation may be risky, and it is not appropriate to carry patients. At this time, the operation should be stopped immediately and self-checked immediately to further determine. Generally speaking, the self-check process will help further determine whether the fault belongs to the first severity level or the second severity level.

[0031] The bed is in busy use, and the self-check process should try to avoid affecting the normal use of the bed. This problem can be solved by performing self-check at specific times, which are times that do not affect the normal use of the bed. Among them, the specific time includes: obtaining the historical use data of the medical bed, selecting the idle time in the future that is greater than the first time length, and the use of the same equipment is often regular. For example, some equipment that is only used in outpatient clinics is often in a long standby or shutdown state at night. According to this historical information, a sufficiently long first time length standby time can be selected, and the first time length can complete all self-check processes in a complete time. The specific time also includes: receiving input operations, obtaining the time corresponding to the input operations. On the one hand, when the fault information of the bed is reported to the relevant personnel, the relevant personnel can choose the appropriate time to perform the self-check process based on their own judgment. For example, the relevant personnel can start the self-check operation immediately after finishing the patient on hand, or they can choose to instruct the bed to enter the self-check procedure after getting off work. On the other hand, for the periodic self-check process, the bed can prompt the relevant personnel that the bed needs to be self-checked, and the relevant personnel can enter the time to start the self-check under the prompt. Specific timing also includes: the standby time of medical beds. For some beds, the working time is long and not fixed. It is difficult to predict its future working time based on historical information. In fact, there is no long standby time for the bed to complete the entire self-inspection process. For example, a bed used in the emergency department may work 24 hours a day. In this case, the standby time between two working hours of the bed is used for self-inspection. For example, for CT and MR beds, there will be a considerable period of standby time between the examinations of two patients, and this time is used to complete the self-inspection process.

[0032] Regardless of the timing of the self-inspection, when the bed is about to perform normal work, this self-inspection should be paused. Therefore, during the self-inspection process, if any operation on the bed is received, which is any operation that makes the bed work, the self-inspection step will be stopped. After stopping, the self-inspection should be continued at the next specific time to avoid repeated self-inspection. Therefore, when stopping, the self-inspection process is recorded to where it has been, that is, the information of the steps that have been performed, and during the next standby time, the self-inspection process is continued according to the recorded information of the self-inspection steps that have been performed. This process can be performed multiple times, that is, the self-inspection process can be completed in multiple specific times. This self-inspection method is particularly useful for beds that work 24 hours a day in the emergency room. For example, for CT and MR beds, the time between two patient examinations is often short, and the entire self-inspection process cannot be completed. In order to resolve the conflict between normal use and self-inspection, multiple standby periods are used to gradually complete the self-inspection process.

[0033] In an exemplary embodiment, a medical examination bed is particularly taken as an example. For medical equipment beds (CT, MR, etc.), unexpected downtime must be avoided to the greatest extent possible, which requires regular maintenance of the beds to ensure the normal operation of the beds, and timely repairs are also required when problems occur in the beds. In maintenance, the maintenance cycle and maintenance methods are different depending on the frequency of use and the characteristics of the bed components. During maintenance, when a problem occurs in the bed, it is necessary to quickly locate the problem and replace the problematic components. One way to solve the bed maintenance is to take preventive (such as regular oiling and lubrication of the push rod) or corrective maintenance (reporting problems with the bed). Such maintenance methods have high costs and will cause unexpected downtime in the hospital, seriously affecting the user experience. In addition, there is a lack of means to quickly locate the problem, and it is necessary to replace parts to try to solve the problem, resulting in excessive consumption of spare parts and long maintenance time. Generally speaking, for general CT / MR medical equipment beds, there are two-axis movements, namely vertical movement and horizontal movement. The modules involved in horizontal movement mainly include horizontal transmission mechanism and horizontal drive motor. The modules involved in vertical movement mainly include vertical lifting mechanism and vertical drive motor. For the main modules of the hospital bed, the transmission parts involved are the motor body, motor gearbox, pulley (ball bearing), etc. Among the measurable physical quantities, vibration spectrum measurement can provide the most information on the root cause of the problem in the rotating device (motor, bearing, etc.). Abnormal vibration may be ball bearing failure, shaft deviation, imbalance, excessive looseness and other problems. Each problem has its own unique spectrum characteristics. For example, the vibration source of the rotating machine, the ball bearing failure can be divided into outer ring, inner ring and local defects. When a fault occurs, the fault spectrum it manifests is closely related to the frequency of the bearing rotation.

[0034] Taking into account the special use of hospital beds, this embodiment effectively uses multiple sensors to detect faults in advance, and uses the hardware and software architecture of multiple sensors installed in fixed positions and multi-sensor data fusion to improve the accuracy and reliability of fault detection. Figure 1As shown, its core is the data analysis control board 1. On the data analysis control board 1, the power conversion 1 reduces the 24V or 48V voltage (usually the mainstream servo motor voltage is 24V or 48V) from the bed control board 3 to the 5V voltage that the main controller 11 on the data analysis control board 1 can accept. The main controller 11 receives and sends relevant instructions to the sensor 2 and the bed control board 3. For the sensor 2, it can include multiple sensors, mainly using but not limited to micro-electromechanical system inertial measurement unit (MEMSIMU) sensors, microphones, ultrasonic microphones, current transformers and Hall coils. The installation positions of various sensors have different special arrangements for target faults. MEMSIMU needs to be at the connection of the bed panel. The advantage of this position is not only that it can monitor the vibration frequency in both horizontal and vertical directions at the same time, but also that the bed panel has a patient monitoring module, which is convenient for wiring. The microphone sensor needs to be deployed at the drive device end, such as the horizontal motor or the vertical motor. The current transformer and Hall coil are sensors that are originally built into the driver and motor. They just need to extract the relevant data from the motor driver for the next step of data fusion.

[0035] The software architecture of the bed status monitoring system Figure 2 As shown, the inertial sensor frequency data 51 and microphone frequency data 52 of the three axes X, Y, and Z of the bed are processed in the frequency domain and fused into a complete spectrum 54, and the current motion data 53 of the bed is converted into the shaft rotation frequency, motor current and Hall phase information 55 through the motion state (horizontal or vertical). Then, the complete spectrum 54 and the shaft rotation frequency, motor current and Hall phase information 55 are fused for data fault location 56, and the spectrum area that needs special attention is formulated according to the current motion data, that is, the vibration source is identified and classified. Finally, the health status of the bed is judged 57. At this time, the status can be reported to the bed control board, and after-sales personnel are arranged for maintenance after comprehensive judgment. At the same time, the relevant sensor data and diagnosis are uploaded as a data set. For multiple sensors, not only inertial measurement units are used, but also other types of sensors such as microphones. In fact, as long as the vibration sensor meets the actual needs, it can be selected. There are many sensors that can detect vibration, such as the most mainstream piezoelectric type. In this embodiment, the MEMSIMU sensor is used as the main sensor for detecting the vibration of the hospital bed. This is because, compared with other vibration sensors, the MEMSIMU can detect a wide range of vibration frequencies, especially those around 0HZ. It also has the characteristics of low power consumption and easy wireless transmission. It can be very simply arranged in the vertical and horizontal movement structure of the hospital bed, and can be closer to the vibration source for detection. This embodiment combines multi-sensor data fusion to collect multi-sensor data to form a data set, and then the collected data set can be used in combination with artificial intelligence to further improve the accuracy of bed health status detection.

[0036] In the process of fault judgment, the fusion information of the bed vibration frequency and the bed movement state is used. Although the bed movement is only horizontal or vertical, for example, in vertical movement, in order to take care of the patient's feelings, the bed speed and acceleration are controlled and adjusted to make the patient more comfortable. Horizontal movement will also be combined with clinical needs, moving at different speeds. The speed span is large, from 1mm / s to 700mm / s, and there are many movement modes, such as reciprocating movement, or pulse movement. This makes the frequency and form of the vibration generated by the bed varied. This is also in the process of fault monitoring, combined with the movement state of the bed to make a comprehensive judgment, so as to obtain more accurate fault information.

[0037] exist Figure 2 The self-check process is not shown in the software architecture. The self-check process is to reproduce the fault according to the recorded motion data and frequency. It controls the bed to move at different speeds, analyzes the relationship between the fault frequency and the motion frequency, and further accurately locates the fault point. Figure 3 A method for monitoring the status of a hospital bed with a self-checking process is shown. During the self-checking process, the hospital bed itself can control its own movement to perform self-checking. The hospital bed can choose when to perform self-checking, for example, according to historical information or according to the input of relevant personnel. In this way, in addition to monitoring during the use of the hospital bed, the active movement of the hospital bed is also used to review the health status of the hospital bed. In addition to the conventional self-checking, when the hospital bed is in normal operation and an abnormal state is detected and recorded by the sensor, the hospital bed will perform self-checking during the non-use period of the bed. Because the frequency of abnormal vibration is closely related to the frequency of its own movement. Therefore, when an abnormality is detected, the hospital bed can start the self-checking process and move at different speeds, so that the frequency of abnormal vibration will also change, thereby more accurately locating the source of the fault and improving the accuracy of detection.

[0038] Combine the following Figure 3 Further explanation of the bed fault monitoring process:

[0039] S1: Data fusion fault location, during the actual use of the bed, the spectrum areas that need special attention are formulated based on the current motion data, that is, the diagnosis source is identified and classified.

[0040] S2: Determine whether the severity of the fault represented by the specific frequency band exceeds threshold 1, that is, make a judgment on the severity of the fault.

[0041] S3: When the severity exceeds threshold 1, it indicates that the health of the bed is poor. The movement of the bed is stopped immediately and the status is reported to the bed control panel. After comprehensive judgment, after-sales personnel are arranged for maintenance.

[0042] S4: When the severity does not exceed threshold 1, determine whether the severity of the fault represented by the specific frequency segment exceeds threshold 2.

[0043] S5: When the severity does not exceed threshold 2, the bed is in good health and can operate normally.

[0044] S6: When the severity exceeds threshold 2, the health status of the bed is pending, and the bed movement data and related information of the exceeded frequency band are recorded to the system. In this state, the bed can be used normally.

[0045] S7: When the bed is not in use and is in standby mode, operate the bed to enter the self-check process.

[0046] S8: Determine whether a fault point exists according to the self-check process. If the fault point does not exist, it means that the bed is in good health, and return to S5 to control the normal operation of the bed.

[0047] S9: If the fault point exists, feedback the information to after-sales personnel and arrange the time for maintenance and inspection reasonably.

[0048] This embodiment has at least the following characteristics:

[0049] 1. Through data analysis, we predict impending bed failures and accurately locate the fault points, so that the maintenance team can pre-arrange repair parts and maintenance time to improve maintenance efficiency and avoid losses caused by unexpected downtime.

[0050] 2. Accurately locating the fault point can facilitate after-sales personnel to replace accessories in a targeted manner, thereby improving efficiency and reducing spare parts costs.

[0051] 3. Furthermore, the status monitoring data and maintenance records of the hospital bed can be used for reference to determine the root cause of the fault, and the specific components that need to be optimized and improved can be accurately located, which can better help R&D personnel to optimize and improve the design of the hospital bed and improve the reliability of the hospital bed.

[0052] According to another aspect of the embodiment of the present disclosure, a mechanical device is provided, the mechanical device includes a moving part, and the mechanical device also includes a processing device, which is used to execute the anti-collision method of any of the above embodiments of the present disclosure. The processing device executes the method in the form of running a computer program.

[0053] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0054] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0055] In the context of the present disclosure, a computer-readable storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specific examples of readable storage media include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0056] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0057] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but only by the claims after authorization and their equivalent scope. Various elements in the embodiments or examples can be omitted or replaced by their equivalent elements. In addition, each step can be performed in an order different from that described in the present disclosure. It is important that with the evolution of technology, many elements described herein can be replaced by equivalent elements that appear after the present disclosure.

[0058] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

Claims

1. A method for monitoring a fault of a mechanical device, wherein the mechanical device has a moving part, characterized in that: The method comprises: receiving spectrum information of the moving part; Receiving motion information of the moving part; The device is monitored for faults based on the correspondence between the frequency spectrum information and the motion information.

2. The mechanical equipment fault monitoring method according to claim 1, characterized in that: The moving component includes a moving load-bearing component and a moving driving component, the moving driving component drives the moving load-bearing component to move, and the receiving of the frequency information of the moving component includes: receiving spectrum information of a first type of sensor located on the load-bearing component; Receive spectrum information of a second type of sensor located on the motion driving component.

3. The mechanical equipment fault monitoring method according to claim 2, characterized in that: The mechanical device is a medical bed, the moving load-bearing component includes a bed board, the moving driving component includes a motor, the first type of sensor is an inertial sensor, the second type of sensor is a sound sensor, the inertial sensor is arranged at a panel hinge of the bed board, and the sound sensor is arranged at the motor; The receiving the motion information of the moving component includes: receiving the rotation frequency information of the motor.

4. The mechanical equipment fault monitoring method according to claim 3, characterized in that: The movement information includes: the position, load-bearing capacity, movement direction, movement speed and movement acceleration of the bed board.

5. The mechanical equipment fault monitoring method according to claim 4, characterized in that: The fault monitoring includes monitoring of fault severity and monitoring of fault types. The fault types include: motor fault, bearing fault, slide rail fault, conveyor belt fault, push rod fault and support member deformation fault.

6. The mechanical equipment fault monitoring method according to claim 5, characterized in that: Also included is a self-test process, the self-test process comprising: The hospital bed is controlled to move in different specific motion modes, and the frequency spectrum information of the moving parts is received, and the type of the fault is judged according to the correspondence between the frequency spectrum information and the information of the specific motion mode.

7. The mechanical equipment fault monitoring method according to claim 6, characterized in that: The fault severity includes: a first fault severity, a second fault severity and a third fault severity, and the fault monitoring method includes: In response to the fault severity being the first fault severity, shutting down the medical bed; In response to the fault severity being the second fault severity, performing a self-check process on the medical bed at a specific timing; In response to the fault severity being the third severity, the medical bed is shut down and then the self-check process is performed.

8. The mechanical equipment fault monitoring method according to claim 7, characterized in that: The specific occasions include: Acquire the historical usage data of the medical bed and select an idle time in the future that is greater than the first duration; Receive an input operation, and obtain a time corresponding to the input operation; and / or The standby time of the medical bed.

9. The mechanical equipment fault monitoring method according to claim 8, characterized in that: During the self-check process, any operation on the hospital bed is received, the self-check process is stopped, and information on the steps of the self-check process that have been performed is recorded, and the self-check process is continued when the self-check process is continued at the next specific opportunity.

10. A mechanical device comprising a moving part, characterized in that: The mechanical device also includes a processing device, and the processing device executes the fault monitoring method described in any one of claims 1-9.

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