Method, device and electronic equipment for detecting faults based on motor current signals

Abstract

This disclosure provides a method, apparatus, and electronic device for fault detection based on motor current signals. The method includes: acquiring a first current signal feature set of a first motor operating normally; the first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current; acquiring a second current signal feature set of the first motor operating at its current state; the second current signal feature set includes a second DC component signal feature and a second ripple feature of the motor current; and determining whether the first motor is faulty based on the first DC component signal feature, the second DC component signal feature, the first ripple feature, and the second ripple feature. This allows for proactive identification of potential problems before a fault occurs, reducing equipment wear and extending equipment lifespan; it also eliminates the need for manual inspections, improving fault detection efficiency.

Description

Technical Field

[0001] This disclosure relates to the field of electrical engineering technology, and in particular to a method, apparatus and electronic device for detecting faults based on motor current signals. Background Technology

[0002] With the increasing global demand for renewable energy, solar power generation, as a clean and sustainable energy source, has been widely applied and developed. Large-scale photovoltaic (PV) power plants are an important form of this, especially common in regions with abundant solar resources. While traditional fixed PV panels are relatively inexpensive, their efficiency decreases with changes in the angle of sunlight. In contrast, tracking PV power plants can maximize the absorption of solar radiation by automatically adjusting the angle of the PV panels in real time, thereby improving power generation efficiency.

[0003] Tracking photovoltaic (PV) power plants typically employ single-axis or dual-axis tracking systems to automatically adjust the angle of the PV panels to track the sun's position, ensuring the panels always face the sun and receive maximum sunlight to improve photoelectric conversion efficiency. However, single-axis or dual-axis tracking systems are prone to malfunctions due to factors such as support frame displacement or deformation, sensor failure, or obstruction. Therefore, timely fault detection and repair are crucial. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and electronic device for detecting faults based on motor current signals, in order to at least solve the above-mentioned technical problems existing in the prior art.

[0005] According to a first aspect of this disclosure, a method for detecting faults based on motor current signals is provided, comprising:

[0006] Obtain a first current signal feature set of the first motor in normal operating state; the first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current;

[0007] Obtain the second current signal feature set of the current operating state of the first motor; the second current signal feature set includes the second DC component signal feature and the second ripple feature of the motor current;

[0008] Based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics, it is determined whether the first motor is faulty.

[0009] In the above scheme, the first current signal feature set for obtaining the normal operating state of the first motor includes:

[0010] In response to the first motor being in normal operating condition, a shunt resistor is connected in series to the circuit of the first motor, and the voltage drop of the shunt resistor is sampled at a first frequency.

[0011] The first current signal feature set is determined based on the voltage drop across the shunt resistor obtained from sampling;

[0012] Wherein, the first frequency is twice or more the motor drive frequency.

[0013] In the above scheme, determining the first current signal feature set based on the voltage drop across the sampled shunt resistor includes:

[0014] Based on the resistance value of the shunt resistor and the voltage drop across the shunt resistor, the current signal corresponding to the shunt resistor is determined;

[0015] The current signal is filtered and / or amplified;

[0016] Obtain the DC component feature in the current signal, which is the first DC component signal feature in the first current signal feature set; obtain the ripple feature in the current signal, which is the first ripple feature in the first current signal feature set;

[0017] The first ripple feature includes ripple frequency, count, waveform, and ripple peak value; the first DC component signal feature includes the amplitude of the DC signal.

[0018] In the above scheme, determining whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics, includes:

[0019] The preset current DC component signal range is determined based on the characteristics of the first DC component signal.

[0020] In response to the second DC component information feature being within the range of the preset current DC component signal, it is determined that the first motor is in a first state;

[0021] If the second DC component information feature is outside the preset current DC component signal range, then the first motor is determined to be in the second state, and a first alarm message is issued.

[0022] In the above scheme, determining the preset current DC component signal range based on the characteristics of the first DC component signal includes:

[0023] Based on the characteristics of the first DC component signal, the average amplitude of the DC signal is determined;

[0024] Based on the characteristics of the first DC component signal, at least one standard deviation is determined;

[0025] The preset current DC component signal range is determined based on the average amplitude and the at least one standard deviation.

[0026] In the above scheme, determining whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics, includes:

[0027] In response to the first motor being in a first state, a determination is made as to whether the first motor is faulty based on the first ripple characteristic and the second ripple characteristic, specifically including:

[0028] The first ripple frequency, first count, first waveform, and first ripple peak value are determined based on the first ripple characteristics.

[0029] The second ripple frequency, second count, second waveform, and second ripple peak value are determined based on the second ripple characteristics.

[0030] Based on at least two of the following: first ripple frequency, first count, first waveform, first ripple peak value, second ripple frequency, second count, second waveform, and second ripple peak value, determine whether the first motor is faulty.

[0031] In the above scheme, determining whether the first motor is faulty based on at least two of the first ripple frequency, first count, first waveform, first ripple peak value, second ripple frequency, second count, second waveform, and second ripple peak value includes at least one of the following:

[0032] If the first count differs from the second count, then a fault is determined in the first motor.

[0033] If the first ripple frequency is greater than the second ripple frequency, then the first motor is determined to be faulty.

[0034] If the second waveform shows a periodic spike or abrupt change compared to the first waveform, then the first motor is determined to be faulty.

[0035] If the peak value of the second ripple is greater than the peak value of the first ripple, and at least one ripple in the second waveform is different from the other ripples, then the first motor is determined to be faulty.

[0036] If a periodic spike or abnormal ripple appears in the second waveform, the first motor is determined to be faulty.

[0037] If a ripple different from the first waveform appears in the second waveform, then the first motor is determined to be faulty.

[0038] If a ripple different from the first waveform appears in the second waveform and the peak value of the second ripple is higher than the first preset threshold, then the first motor is determined to be faulty.

[0039] If a ripple different from the first waveform appears in the second waveform, and the amplitude of the ripple fluctuation is greater than a second preset threshold, then a first motor fault is determined.

[0040] If a ripple that is different from the first waveform appears periodically in the second waveform, then the first motor is determined to be faulty.

[0041] If the second waveform is missing at least one ripple compared to the first waveform, then the first motor is determined to be faulty.

[0042] If the slope of any peak of the second waveform is greater than the first slope in the first time interval, then the internal jamming of the first motor is determined.

[0043] If the ripples disappear in the second waveform, it is determined that the first motor is stuck inside.

[0044] If any ripple duration in the second waveform is longer than the duration of other ripples, then the first motor is determined to be jammed.

[0045] If the ripple in the second waveform is irregular and the ripple fluctuation amplitude is greater than the second preset threshold, then the first motor is determined to be jammed inside.

[0046] If the slope of any peak of the second waveform is greater than the second slope in the first time interval, then the reducer is determined to be jammed.

[0047] If the ripples in the second waveform are irregular, then the gearbox is determined to be jammed.

[0048] If a periodic abrupt change occurs in the second waveform and the abrupt change corresponds to the gear meshing point in the reducer, then the reducer is determined to be jammed.

[0049] If the duration of the ripple in the second ripple becomes shorter, then the gearbox is determined to be jammed.

[0050] The first slope is greater than the second slope.

[0051] According to a second aspect of this disclosure, an apparatus for detecting faults based on electrode current signals is provided, the apparatus comprising:

[0052] The first acquisition unit is used to acquire a first current signal feature set of the first motor in normal operating state; the first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current;

[0053] The second acquisition unit is used to acquire a second current signal feature set of the current operating state of the first motor; the second current signal feature set includes a second DC component signal feature and a second ripple feature of the motor current.

[0054] The fault determination unit is used to determine whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics.

[0055] According to a third aspect of this disclosure, an electronic device is provided, comprising:

[0056] At least one processor; and

[0057] A memory communicatively connected to the at least one processor; wherein,

[0058] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods described in this disclosure.

[0059] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing the computer to perform the methods described in this disclosure.

[0060] This disclosure discloses a method for fault detection based on motor current signals. The method involves acquiring a first current signal feature set of a first motor operating normally, including a first DC component signal feature and a first ripple feature of the motor current; acquiring a second current signal feature set of the first motor operating at its current state, including a second DC component signal feature and a second ripple feature of the motor current; and determining whether the first motor is faulty based on the first and second DC component signal features, as well as the first and second ripple features. This allows for proactive identification of potential problems before a fault occurs, reducing equipment wear and extending equipment lifespan; it also eliminates the need for manual inspections, improving fault detection efficiency.

[0061] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0062] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which:

[0063] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0064] Figure 1The diagram shows a fault scene where the tracking bracket rotated beyond its limit.

[0065] Figure 2 A diagram showing the scene of a jammed failure in the tracking bracket rotation mechanism is provided.

[0066] Figure 3 This illustration shows a first optional flowchart of a method for detecting faults based on motor current signals provided in an embodiment of the present disclosure;

[0067] Figure 4 A schematic diagram of a second optional process for a method for detecting faults based on motor current signals provided in an embodiment of this disclosure is shown;

[0068] Figure 5 A first alternative schematic diagram of the motor current ripple characteristics is shown;

[0069] Figure 6 A second alternative schematic diagram illustrating the characteristics of motor current ripple is shown;

[0070] Figure 7 The current square wave signal after differential amplifier conversion is shown;

[0071] Figure 8 A schematic diagram of a third optional process for a method for detecting faults based on motor current signals provided in an embodiment of this disclosure is shown.

[0072] Figure 9 A schematic diagram of an optional structure of the device for detecting faults based on motor current signals provided in an embodiment of this disclosure is shown;

[0073] Figure 10 A schematic diagram of the composition structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0074] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0075] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0076] In the following description, the terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first" and "second" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this disclosure described herein can be implemented in an order other than that illustrated or described herein.

[0077] Unless otherwise defined, all technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used in this disclosure is for the purpose of describing embodiments of this disclosure only and is not intended to be limiting of this disclosure.

[0078] It should be understood that in the various embodiments of this disclosure, the sequence number of each implementation process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this disclosure.

[0079] Tracking photovoltaic (PV) power plants automatically adjust the angle of their photovoltaic panels to track the sun's position, ensuring the panels always face the sun. This ensures the panels receive maximum sunlight, thus improving photoelectric conversion efficiency. Tracking systems typically employ two main types:

[0080] Single-axis tracking system: The photovoltaic panel rotates along an axis, usually from east to west, to adapt to the movement of the sun from east to west.

[0081] Dual-axis tracking system: In addition to east-west rotation, it can also be adjusted in the north-south direction. This system can track the sun's position more accurately, but it is also relatively more expensive.

[0082] Both of the above main tracking systems currently use motor-driven solutions as their primary driving mode.

[0083] The main components of a tracking photovoltaic power generation system include:

[0084] Photovoltaic panels: Composed of multiple solar cells, responsible for converting sunlight into electrical energy.

[0085] Tracking system: Includes components such as drive unit, photovoltaic tracking controller (TCU) and sensors, used to adjust the angle of photovoltaic panel.

[0086] Drive unit: such as motor, hydraulic rod, etc., used to physically drive the tracking bracket and ultimately rotate the photovoltaic panel.

[0087] Monitoring system: Used for remote monitoring of the power plant's operating status, including functions such as power generation and fault alarms.

[0088] In summary, tracking photovoltaic (PV) power plants improve energy capture efficiency by dynamically adjusting the angle of the photovoltaic panels, making them a highly efficient method of solar energy utilization. With technological advancements and cost reductions, the application of this type of power plant will become even more widespread.

[0089] However, in modern large-scale tracking photovoltaic power generation projects, system failures related to the motor drive process can occur due to various reasons. The main phenomena include:

[0090] (1) Displacement and deformation of the support and its piles.

[0091] Cause: After long-term operation, factors such as wind load, temperature changes, and soil settlement may cause displacement or deformation of the support and piles.

[0092] Consequences: The transmission mechanism may jam, causing the motor to stall or overload, or even burn out; the main transmission beam of the support frame may also be damaged as a result.

[0093] (2) The tilt sensor failed.

[0094] Causes: Sensor aging, damage, or electromagnetic interference, etc.

[0095] Consequences: If the support rotates beyond the predetermined range, it may cause structural damage or collision with surrounding objects.

[0096] Figure 1 The diagram shows a fault scene where the tracking bracket rotated beyond its limit.

[0097] like Figure 1 As shown, it includes three photovoltaic panels, two of which are located in... Figure 1 The leftmost and rightmost photovoltaic panels are basically parallel to the ground, and the third photovoltaic panel (located in...) Figure 1 The photovoltaic panel (center) is at a significant angle to the ground. Due to the failure of the tilt sensor, the tracking bracket rotates beyond the predetermined range, causing the photovoltaic panel, which should be parallel to the ground, to rotate too violently. As a result, the photovoltaic panel is at a significant angle to the ground, and the corresponding area for receiving sunlight becomes smaller, leading to a decrease in the efficiency of the photovoltaic panel in capturing energy.

[0098] (3) Rotation jam caused by encountering an obstacle

[0099] Cause: Debris, vegetation, or other physical obstacles in the site blocked the normal rotation path of the support.

[0100] Consequences: The support frame cannot rotate normally, resulting in a decrease in power generation efficiency, and in severe cases, it may cause mechanical damage.

[0101] Figure 2 The diagram shows a scene of a jammed failure in the rotating mechanism of the tracking bracket.

[0102] like Figure 2 As shown, it includes three photovoltaic panels, two of which are located in... Figure 2 The leftmost and rightmost photovoltaic panels are in a complete plane, at a certain angle to the ground; the third photovoltaic panel (located in...) Figure 2 The central tracking bracket is twisted and has multiple angles relative to the ground. Due to the jamming, the tracking bracket cannot fully drive the photovoltaic panel to rotate, resulting in the photovoltaic panel receiving sunlight on a significantly smaller area than other photovoltaic panels with undamaged tracking brackets, thus reducing the photovoltaic panel's energy capture efficiency.

[0103] (4) Electrical system failure

[0104] Cause: Cable aging, loose connection.

[0105] Consequences: Causes short circuits or open circuits.

[0106] All of the above tracking system failures lead to a decrease in the power generation efficiency of tracking photovoltaic power plants. In severe cases, they can also cause mechanical and electrical damage to the tracking brackets and drive motors, resulting in serious losses to the project.

[0107] In related technologies, the following solutions are mainly used to address system faults related to the motor drive process:

[0108] (1) Manual inspection

[0109] Implementation method: The project's operation and maintenance personnel conduct on-site inspections daily.

[0110] Function: To stop the equipment and arrange for maintenance after abnormal conditions are found in the support and motor.

[0111] However, manual inspection has certain limitations, mainly including: untimely inspection, manual inspection may not be able to detect faults in time, especially for hidden or gradually developing faults; risk of missed detection, manual inspection may be negligent or overlooked; and passive response, action can only be taken after a fault occurs, and it cannot prevent the occurrence of faults.

[0112] (2) Automatic detection of motors with external sensors

[0113] Execution method: Utilizing a motor equipped with an optical encoder or Hall effect sensor, information such as motor speed, voltage, position, and temperature is sensed in real time. The sensor transmits the collected information to the control system (such as a TCU), which then determines the motor's current operating status based on this data.

[0114] Function: To monitor key parameters of the motor in real time through external sensors, ensuring that the motor is in normal working condition.

[0115] However, automatic motor detection using external sensors has certain limitations, primarily including: increased design complexity, requiring the design and integration of more sensors, making the system design more complex; processing data from multiple sensors requires more complex algorithms, increasing the difficulty of software development; increased Bill of Materials (BOM) number and cost, as the added sensors and other related components increase material costs; external sensors require more installation and maintenance work, increasing overall cost; increased failure risk, as each new sensor is a potential point of failure, increasing the overall system failure risk; and the presence of multiple sensors makes the system more susceptible to the failure of a single component, reducing overall reliability.

[0116] In summary, both current mainstream solutions have certain limitations. Manual inspection may result in untimely checks and missed detections, and can only be discovered after a fault has occurred; automatic motor detection with external sensors faces problems such as design complexity, increased system costs, and a potentially higher failure rate. These limitations make it difficult for existing solutions to simultaneously achieve timeliness, accuracy, and economy in detecting and preventing motor drive faults in support systems.

[0117] In view of the deficiencies existing in the related technologies, this disclosure provides a method for detecting faults based on motor current signals to solve some or all of the above-mentioned technical problems.

[0118] Figure 3 A schematic diagram of a first optional process for a method for detecting faults based on motor current signals provided in this disclosure is shown, and the steps will be described accordingly.

[0119] Step S301: Obtain the first current signal feature set of the first motor in normal operating state.

[0120] In some embodiments, the carrier implementing the method for fault detection based on motor current signals (hereinafter referred to as the carrier) acquires a first current signal feature set of the first motor operating normally. The first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current.

[0121] Furthermore, the first DC component signal feature may include the DC amplitude of the current signal when the motor is operating normally; the first ripple feature may include the ripple feature of the current signal when the motor is operating normally, including at least one of ripple frequency, count, waveform and ripple peak value.

[0122] In some embodiments, the normal operating state of the first motor may include no displacement or deformation of the corresponding bracket and pile, normal tilt sensor operation, no encounter with obstacles, no rotational jamming, and normal operation of the electrical system.

[0123] In some embodiments, the carrier may be a computer program, electronic circuit, database, mobile application, electronic device, cloud computing platform, distributed system, artificial intelligence framework, mathematical model, automation tool, microcontroller, etc., which are software or hardware capable of implementing algorithms and methods.

[0124] Step S302: Obtain the second current signal feature set of the current working state of the first motor.

[0125] In some embodiments, the second current signal feature set includes a second DC component signal feature and a second ripple feature of the motor current.

[0126] In some embodiments, the carrier can acquire a second current signal feature set of the current operating state of the first motor to determine whether the first motor is faulty, and can also acquire a third current signal feature set of the current operating state of the second motor to determine whether the second motor is faulty.

[0127] Specifically, because different motors generate different sets of current signal characteristics during normal operation, if the carrier determines whether the first motor is faulty based on its current operating state, the determination result will be more accurate. However, if only the set of current signal characteristics generated by a single motor during normal operation is used to determine whether all motors are faulty, the computational load can be reduced, freeing up more computational resources.

[0128] Step S303: Determine whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics.

[0129] In some embodiments, if the first motor is in an abnormal operating state, i.e., there is displacement or deformation of the support and pile, the resistance of the first motor during operation will be greater than that in the normal operating state. Therefore, the DC amplitude of the generated current signal will be larger, and the ripple characteristics of the corresponding current signal will also change. By comparing the first DC component signal characteristics and the first ripple characteristics in the normal operating state with the second DC component signal characteristics and the second ripple characteristics in the current operating state, the fault of the first motor can be determined from two perspectives, making the judgment result more accurate.

[0130] Thus, the fault detection method based on motor current signals provided in this disclosure can proactively identify potential problems before a fault occurs by continuously monitoring the signal characteristics of the motor current. Compared to a uniformly set feature threshold, the method optimizes the probability of missed and false fault reports for the operating status of each support system, significantly improving the accuracy of fault detection. The real-time monitoring and rapid response mechanism can identify faults and take action more quickly, reducing the risk of equipment damage. By identifying and resolving potential problems early, the service life of the support system and motor can be extended. Unplanned downtime and maintenance costs are reduced, improving overall operating efficiency.

[0131] Figure 4 A second alternative flowchart of the method for detecting faults based on motor current signals provided in this disclosure is shown, and the steps will be described accordingly.

[0132] Step S401: Obtain the first current signal feature set of the first motor in normal operating state based on the shunt resistor.

[0133] In some embodiments, in response to the first motor being in normal operating condition, a circuit with a shunt resistor connected in series to the first motor is used to sample the voltage drop across the shunt resistor at a first frequency; and the first current signal feature set is determined based on the sampled voltage drop across the shunt resistor.

[0134] In specific implementation, the carrier can determine the current signal corresponding to the shunt resistor based on the resistance value of the shunt resistor and the voltage drop of the shunt resistor; specifically, after determining the current signal, the carrier can filter and / or amplify the current signal, such as using a digital filter to filter out noise in the current signal; or using a signal amplifier to increase the strength of the current signal for subsequent analysis and comparison.

[0135] In some embodiments, according to the Nyquist-Shannon sampling theorem, in order to fully capture the ripple characteristics of the motor, the first frequency should be at least twice the motor drive frequency. For example, if the motor drive frequency is 2kHz to 20kHz, then the first frequency should be set to 4kHz to 40kHz.

[0136] In some embodiments, the carrier acquires the DC component feature in the current signal, which is the first DC component signal feature in the first current signal feature set; acquires the ripple feature in the current signal, which is the first ripple feature in the first current signal feature set; wherein, the first ripple feature includes ripple frequency, count, waveform and ripple peak value; the first DC component signal feature includes the amplitude of the DC signal.

[0137] Step S402: Obtain the second current signal feature set of the current operating state of the first motor based on the shunt resistor.

[0138] The specific steps of step S402 are similar to those of step S401, and will not be repeated here.

[0139] In some embodiments, the motor current includes both a large-amplitude, very low-frequency DC component and a small-amplitude, high-frequency AC component. The DC component mainly originates from the inductive load driving the motor and varies with the motor load. The AC component is caused by the sinusoidal back electromotive force (BEMF) generated by the motor and the periodically changing motor coil impedance caused by the shorting of adjacent commutator poles by the motor brushes.

[0140] In some embodiments, the carrier converts the current signal of the first motor's current operating state, collected from the carrier, into a digital signal via an ADC analog-to-digital converter, and inputs it to the TCU's main control MCU. The MCU included in the carrier then executes step S403. The carrier includes an MCU.

[0141] Step S403: Determine whether the first motor is in the first state based on the characteristics of the DC component signal.

[0142] In some embodiments, the carrier first determines a preset current DC component signal range based on the characteristics of a first DC component signal.

[0143] In specific implementation, based on the characteristics of the first DC component signal, the average amplitude of the DC signal is determined; based on the characteristics of the first DC component signal, at least one standard deviation is determined; and based on the average amplitude and the at least one standard deviation, a preset current DC component signal range is determined. Specifically, the lower limit of the preset current DC component signal range is based on the average amplitude minus at least one standard deviation, and the upper limit of the preset current DC component signal range is based on the average amplitude plus at least one standard deviation.

[0144] In some embodiments, the carrier determines whether the second DC component information feature is within the range of the preset current DC component signal; in response to the second DC component information feature being within the range of the preset current DC component signal, the first motor is determined to be in a first state; in response to the second DC component information feature being outside the range of the preset current DC component signal, the first motor is determined to be in a second state, and a first alarm message is issued. The first state includes a normal operating state or a fault state. That is, in this embodiment, determining whether the first motor is faulty solely based on the DC component information feature may be inaccurate; it is necessary to further combine ripple characteristics to determine whether the first motor is faulty. Therefore, if the second DC component information feature is within the range of the preset current DC component signal, the first motor may be faulty or may be in a normal operating state.

[0145] Step S404: Determine whether the first motor is faulty based on the ripple characteristics.

[0146] In some embodiments, in response to the first motor being in a first state, the carrier determines whether the first motor is faulty based on the first ripple feature and the second ripple feature. Specifically, the carrier compares the second current signal feature set of the current operating state with the first current signal feature set of the normal operating state. If the ripple frequency and waveform are inconsistent with the normal features (i.e., the first current signal feature set of the normal operating state), the first motor is determined to be faulty. Based on the specific abnormal type of the ripple, a fault type judgment is given and a fault alarm is issued. Automatic shutdown or prompting maintenance personnel to check can be performed according to the fault type.

[0147] In specific implementation, the carrier determines a first ripple frequency, a first count, a first waveform, and a first ripple peak value based on a first ripple feature; determines a second ripple frequency, a second count, a second waveform, and a second ripple peak value based on a second ripple feature; and determines whether the first motor is faulty based on at least two of the first ripple frequency, the first count, the first waveform, the first ripple peak value, the second ripple frequency, the second count, the second waveform, and the second ripple peak value.

[0148] Specifically, it includes at least one of the following:

[0149] (1) In response to the difference between the first count and the second count, a first motor fault is determined; the count includes the number of ripples generated when the motor does not rotate.

[0150] Figure 5 A first alternative schematic diagram of the motor current ripple characteristics is shown.

[0151] like Figure 5As shown, this is a brushed DC motor with 2 brushes and 3 commutators (NB=2, NC=3). Each brush short-circuits each pair of commutator segments once per revolution, so a total of 6 short circuits occur per revolution (NR=LCM(2,3)=6). Correspondingly, the motor also generates 6 ripples per revolution.

[0152] Furthermore, the brushes and commutator affect the ripple count. When the first count differs from the second count, indicating a missing ripple, it signifies software corruption or poor connection in the drive circuit. This causes the tracking bracket to malfunction or operate intermittently. The bracket's inability to precisely adjust its position leads to decreased power generation efficiency, potentially causing the motor to stop.

[0153] (2) If the first ripple frequency is greater than the second ripple frequency, then the first motor is determined to be faulty. Specifically, if the first ripple frequency is greater than the second ripple frequency, it indicates that the motor speed has decreased.

[0154] Figure 6 A second alternative schematic diagram illustrating the characteristics of motor current ripple is shown.

[0155] Combination Figure 5 and Figure 6 If the x-coordinates of the two are the same, then Figure 6 The ripple frequency is significantly smaller than Figure 5 The ripple frequency, i.e. the ripple count per unit time, changes significantly compared to the normal operating mode. At this time, it can be considered that the operating speed of the first motor deviates from the normal operating state, such as no-load state or full-load stall state, and an alarm prompt will be given.

[0156] (3) If the second waveform shows a periodic spike or abrupt change compared to the first waveform, then the first motor is determined to be faulty.

[0157] In some alternative embodiments, the carrier can be directly transmitted through... Figure 5 or Figure 6 The motor current ripple characteristics shown can be used to determine whether periodic spikes or abrupt changes occur. Alternatively, a differential amplifier can be used to generate a clean, low-noise AC signal from the current signal. Through a final comparator strategy, a square wave (0V to 3.3V under normal operating conditions) is generated. Its switching frequency is equal to the motor ripple frequency. By comparing the amplitude of the square wave, it can be determined whether there are spikes or abrupt changes.

[0158] Figure 7 The current square wave signal after being converted by a differential amplifier is shown.

[0159] In some embodiments, if the second waveform exhibits periodic spikes or abrupt changes compared to the first waveform, it indicates poor contact between the brushes and commutator of the first motor, leading to interruption or instability of the current signal. Correspondingly, this can cause unstable rotation of the tracking bracket, resulting in decreased tracking accuracy or even jamming. The tracking bracket will be unable to properly follow the sun's position, reducing power generation efficiency, and in severe cases, may lead to bracket damage or motor burnout.

[0160] (4) If the peak value of the second ripple is greater than the peak value of the first ripple, and at least one ripple in the second waveform is different from the other ripples, then the first motor fault is determined.

[0161] In some embodiments, excessive motor load leads to increased current demand, but the motor cannot provide sufficient torque. This results in increased current ripple amplitude and an irregular waveform, causing the second ripple peak to be larger than the first ripple peak, and at least one ripple in the second waveform to differ from the others. Consequently, the support structure rotates slowly or not at all, especially under strong winds or heavy loads. The support structure cannot adjust its position in time, leading to decreased power generation efficiency, motor overheating, and potential motor damage.

[0162] (5) If a periodic spike or abnormal ripple appears in the second waveform, the first motor is determined to be faulty.

[0163] In some embodiments, bearing damage increases mechanical resistance, affecting the smooth operation of the motor and causing periodic spikes or abnormal waveforms in the current ripple, i.e., periodic spikes or abnormal ripples appear in the second waveform. Consequently, this can cause vibration or abnormal noise when the support rotates, potentially leading to unstable support movement. The support cannot be precisely positioned, resulting in decreased power generation efficiency, and the vibration may damage other mechanical components.

[0164] (6) If the second waveform shows a ripple that is different from the first waveform, then the first motor is determined to be faulty.

[0165] In some embodiments, a short circuit inside the motor windings causes abnormal current flow, resulting in continuous abnormal waveforms in the current ripple. This may be accompanied by a sudden current surge, meaning that the second waveform exhibits ripples different from the first waveform, and the peak value of the second ripple may exceed a first preset threshold (the first preset threshold can be set according to actual needs, but is used here to compare and determine the current surge). Consequently, this can cause the bracket to suddenly stop rotating or fail to start. If the bracket malfunctions, the motor may burn out, requiring replacement.

[0166] (7) If a ripple different from the first waveform appears in the second waveform and the amplitude of the ripple fluctuation is greater than the second preset threshold, then the first motor is determined to be faulty.

[0167] In some embodiments, unstable power supply voltage leads to unstable motor power supply, causing irregular current ripple, which may be accompanied by large fluctuations. That is, ripples different from the first waveform appear in the second waveform, and the amplitude of the ripple fluctuation is greater than a second preset threshold. Correspondingly, this can cause intermittent stagnation or acceleration when the bracket rotates. The bracket cannot adjust its position smoothly, the power generation efficiency decreases, and the motor may overheat.

[0168] (8) If the second waveform periodically produces ripples that are different from the first waveform, then the first motor is determined to be faulty.

[0169] In some embodiments, commutator wear can lead to uneven motor commutation, or loose internal motor components can cause unstable mechanical connections, resulting in periodic irregular waveforms in the current ripple. Specifically, the second waveform may periodically exhibit ripples different from the first waveform. Consequently, this can cause the support to experience stuttering or discontinuous movement, vibration, or abnormal noise during rotation. The support cannot smoothly adjust its position, leading to decreased power generation efficiency, potential motor overheating or damage, and vibration that could damage other mechanical components.

[0170] (9) If the second waveform is missing at least one ripple compared to the first waveform, then the first motor is determined to be faulty.

[0171] In some embodiments, damage or poor connection of components (such as MOSFETs, IGBTs, etc.) in the drive circuit can cause the second waveform to lack at least one ripple compared to the first waveform, i.e., irregular fluctuations or absences appear in the current ripple; consequently, this can lead to the tracking bracket failing to rotate normally or operating intermittently. The bracket cannot be precisely positioned, resulting in decreased power generation efficiency and potentially causing the motor to stop.

[0172] If the jamming fault occurs inside the motor, such as when the rotor is stuck by a foreign object or the bearing is damaged, the current ripple will exhibit the following characteristics:

[0173] (10) If the slope of any peak of the second waveform is greater than the first slope in the first time interval, then the first motor is determined to be stuck inside.

[0174] (11) If the ripples in the second waveform disappear, it is determined that the first motor is stuck inside; at this time, the first motor cannot rotate, so the ripples disappear.

[0175] (12) If the duration of any ripple in the second waveform is longer than the duration of other ripples, then the first motor is determined to be stuck inside; if the duration of the ripple is longer, the first motor will generate a larger current when trying to overcome the stuck.

[0176] (13) If the ripple in the second waveform is irregular and the ripple fluctuation amplitude is greater than the second preset threshold, then the first motor is determined to be stuck inside; if the second waveform may become very irregular and a large sudden change occurs.

[0177] If a jamming fault occurs in the gearbox, such as a stuck gear or a damaged transmission component, the current ripple will also exhibit some specific characteristics:

[0178] (14) If the slope of any peak of the second waveform is greater than the second slope in the first time interval, then the reducer is determined to be jammed; specifically, the peak-to-peak value of the current ripple will also increase, but the increase may not be as obvious as that of the internal jamming of the motor. The first slope is greater than the second slope.

[0179] (15) If the ripple is irregular in the second waveform, the gearbox is determined to be stuck; the frequency of the current ripple may still exist, but there will be obvious irregularity.

[0180] (16) If a periodic abrupt change occurs in the second waveform and the abrupt change corresponds to the gear meshing point in the reducer, then the reducer is determined to be jammed; the waveform of the current ripple may show periodic abrupt changes that correspond to the gear meshing point in the reducer.

[0181] (17) If the duration of the ripple in the second ripple becomes shorter, the gearbox is determined to be jammed; the duration of the current ripple may be shorter because the jamming of the gearbox may cause the motor to stop quickly.

[0182] After determining the first motor to be faulty based on the above, the carrier can send an alarm message to instruct staff to repair the first motor.

[0183] Thus, the method for fault detection based on motor current signals provided in this disclosure can achieve real-time monitoring and fault detection of brushed DC motors in photovoltaic tracking systems. Through multiple steps including motor current sampling, signal processing, data analysis, and fault diagnosis, it ensures that abnormal conditions in the tracking system can be detected and addressed promptly. Without installing additional sensors, this solution not only improves the reliability of the photovoltaic tracking system but also optimizes maintenance plans and reduces unplanned downtime, demonstrating high practical value and economic efficiency.

[0184] Figure 8 A third optional flowchart of the method for detecting faults based on motor current signals provided in this disclosure is shown, and the steps will be described accordingly.

[0185] In some embodiments, the method involved in this disclosure includes: making reasonable use of the sampling, computing, and storage resources of the TCU: utilizing modules such as the MCU main control, motor drive module, and ADC comparator in the photovoltaic tracking controller. High-frequency sampling and analysis: performing high-frequency sampling of the motor drive current during normal operation of the support system, and analyzing the DC component range and ripple characteristics of the motor current. Ripple characteristic detection refers to the process of obtaining motor operating status information by detecting fluctuations (i.e., ripple) in current or voltage during motor operation. These fluctuations are usually caused by factors such as internal mechanical friction of the motor, poor contact between the commutator and brushes, and load changes. Feature learning mode: in the initial stage of the tracking system operation, the feature learning mode is activated, and the data during normal system operation in this mode is sampled, processed, and saved, and finally recorded as a feature set of the normal operating state of the motor (including electrode current DC component characteristics and ripple characteristics), and new sampling signals are compared with this set in subsequent work. Threshold determination and fault alarm: when the new sampling signal deviates from the feature set by a certain range, the TCU automatically issues a motor stop command and gives a corresponding fault type alarm according to the degree and type of deviation.

[0186] In practice, the process includes data acquisition and analysis: The TCU utilizes its sampling module, ADC module, and comparators to perform high-frequency sampling and preprocessing of the motor current signal (preprocessing includes removing burrs and spikes). The acquired data is then processed (e.g., filtered), stored, and analyzed by the MCU main control. Feature extraction: Key features such as the average value, peak value, ripple amplitude, and count of the DC component of the motor current are extracted from the acquired data. Normal range setting: An adaptive normal range threshold is set based on the motor operating characteristics learned by the system. Real-time monitoring: During system operation, the TCU continuously samples the motor current signal and compares it in real-time with the saved normal operating characteristics. Fault diagnosis and alarm: When the motor current deviates from the normal range, the system automatically triggers the fault diagnosis process and provides corresponding alarm prompts based on the specific situation.

[0187] Specifically, the following steps are included:

[0188] Step S501: Start the feature learning mode of the tracking system.

[0189] In some embodiments, in response to a power input, the motor drive module starts and drives the brushed DC motor (first motor) to run, thus initiating the tracking system feature learning mode. The carrier determines whether the first motor is in normal operating condition; if so, step S502 is executed; otherwise, a fault alarm is triggered, prompting maintenance personnel to perform maintenance.

[0190] Step S502: Obtain the first current signal feature set of the first motor in normal working state, and set the normal working range threshold.

[0191] In some embodiments, in response to the first motor being in normal operating condition, the carrier connects a shunt resistor in series with the circuit of the first motor and samples the voltage drop of the shunt resistor at a first frequency; the first current signal feature set is determined based on the sampled voltage drop of the shunt resistor; wherein the first frequency is 2 times or more of the motor drive frequency.

[0192] In specific implementation, the carrier uses a shunt resistor connected in series with the motor circuit to sample the motor current. The motor current is indirectly measured by measuring the voltage drop across the shunt resistor. Optionally, a digital filter is used to filter noise in the current signal. A signal amplifier is used to increase the strength of the sampled signal for subsequent analysis and comparison. Sampling frequency: According to the Nyquist-Shannon sampling theorem, in order to fully capture the ripple characteristics of the motor, the sampling frequency should be at least twice the motor drive frequency. For example, if the motor drive frequency is 2kHz to 20kHz, the sampling frequency should be set to 4kHz to 40kHz.

[0193] In some embodiments, the current measured in series with the brushed motor (first motor) contains both a large amplitude of extremely low-frequency DC components and a small amplitude of high-frequency AC components; the DC components mainly originate from the inductive load of the drive motor and vary with the load; the AC components are caused by the sinusoidal back electromotive force (BEMF) generated by the motor and the periodically changing motor coil impedance caused by the shorting of adjacent commutator poles by the motor brushes; signal conversion: the acquired current signal is converted into a digital signal by an ADC analog-to-digital converter and input to the TCU's main control MCU.

[0194] Furthermore, the carrier sets a normal operating range threshold based on the first current signal feature set. The normal operating range threshold may include a preset current DC component signal range, ripple peak range, ripple amplitude, and count.

[0195] In practice, the MCU analyzes the acquired signals through a pre-set program. The DC component signal characteristics are set to a preset range of N standard deviations of historical normal values ​​(initially set to N=2, with subsequent adaptive learning and adjustment of N based on actual operating conditions). If the acquired DC current signal value falls within this range, it is considered normal data; otherwise, it is considered abnormal data. Optionally, a digital filter is used in the signal acquisition module to remove noise from the current signal and reduce ripple waveform distortion.

[0196] In practice, measuring the ripple per unit time can provide the ripple velocity (or ripple frequency) ω. R (In Hz). The motor speed ω is calculated by dividing the ripple frequency by the number of ripples per revolution, based on the number of commutator segments and brushes. M Number of ripples per revolution N R The calculation method is to take the least common multiple (LCM) of the number of brushes (NB) and the number of commutators (NC).

[0197] Calculation formula: N R =LCM(NB, NC)

[0198] Formula for calculating motor speed:

[0199]

[0200] In some embodiments, the normal operating state characteristics are automatically learned and adjusted based on the characteristics of each tracking system (or motor), rather than using a one-size-fits-all approach. This means that the system can more accurately identify the normal operating state of each motor; by learning the operating state characteristics to set the safe operating state range, false alarms and missed alarms caused by improper setting of the safe state range can be reduced.

[0201] Step S503, fault diagnosis.

[0202] In some embodiments, a dual-channel detection and cross-validation approach is used for fault diagnosis. This involves employing a dual-channel detection method that combines motor current values ​​and current ripple characteristics, enabling monitoring of the motor's operating status from two dimensions. The data from the two channels corroborate each other, improving the accuracy of fault detection. Even if the data from one channel is abnormal, the data from the other channel can still serve as a reference, reducing the possibility of misjudgments and missed diagnoses.

[0203] In some embodiments, the carrier compares the collected motor current ripple characteristics (i.e., the second ripple characteristics) with the normal ripple characteristics (i.e., the first ripple characteristics) stored in the TCU's internal learning state. If the ripple frequency and waveform characteristics are inconsistent with the normal characteristics, it is judged as a feature abnormality. Based on the specific abnormal type of the ripple, a fault type judgment is given and a fault alarm is issued accordingly. Automatic shutdown or prompting maintenance personnel to check can be performed based on the fault type.

[0204] In specific implementation, the carrier can first compare the characteristics of the DC component signal with the normal characteristic value, that is, determine whether the second DC component information characteristic is within the range of the preset current DC component signal; if the second DC component information characteristic is within the range of the preset current DC component signal, then further ripple comparison is performed; if the second DC component information characteristic is not within the range of the preset current DC component signal, then a motor operation status alarm is issued, causing the first motor to enter the stop mode, and the fault status is reported to the host computer.

[0205] The ripple comparison includes: comparing the second ripple feature and the first ripple feature; if the ripple feature is normal, the first motor maintains normal operation, and further sampling is performed. The sampled current signal features are added to the first current signal feature set, and the preset current DC component signal range and normal ripple features are updated. Alternatively, if the ripple feature is abnormal, a motor operation status alarm is issued, causing the first motor to enter a stop mode, and the fault status is reported to the host computer.

[0206] For abnormal ripple characteristics, please refer to step S404, which will not be repeated here.

[0207] In some embodiments, analyzing the characteristics of motor current ripple can more accurately determine the type of fault. Different fault types will produce different current ripple characteristics. In addition to detecting faults in the tracking system, the system can also detect faults in the motor itself, including faults caused by motor aging or motor failure. Depending on the fault type, the system can automatically provide corresponding alarm information to help maintenance personnel quickly locate the problem.

[0208] Thus, the method for fault detection based on motor current signals provided in this disclosure, by utilizing high-frequency sampling and analysis within the TCU's internal module, enables effective learning and monitoring of important operating characteristics such as motor drive current and ripple. This proactively identifies potential problems before a fault occurs, reducing false alarms and improving the timeliness and accuracy of fault detection. This method not only improves the reliability and operational efficiency of the support system but also reduces maintenance costs and extends equipment lifespan. Specifically, by continuously monitoring the fluctuation characteristics of motor current, potential problems can be proactively identified before a fault occurs. This reduces unplanned downtime; early problem detection facilitates timely intervention, minimizing downtime. It also improves maintenance efficiency; accurate fault type identification helps maintenance personnel quickly locate problems, increasing maintenance efficiency. Furthermore, early problem identification and resolution reduce equipment wear and extend its lifespan. Finally, it reduces maintenance costs by decreasing the frequency of faults, lowering repair costs, and improving the overall system's economics.

[0209] Figure 9A schematic diagram of an optional structure of a device for detecting faults based on motor current signals provided in an embodiment of this disclosure is shown, and the details will be explained in terms of each part.

[0210] In some embodiments, the device 600 for detecting faults based on motor current signals includes a first acquisition unit 601, a second acquisition unit 602, and a fault judgment unit 603.

[0211] The first acquisition unit 601 is used to acquire a first current signal feature set of the first motor in normal operating state; the first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current;

[0212] The second acquisition unit 602 is used to acquire a second current signal feature set of the current operating state of the first motor; the second current signal feature set includes a second DC component signal feature and a second ripple feature of the motor current;

[0213] The fault determination unit 603 is used to determine whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics.

[0214] The first acquisition unit 601 is specifically used to, in response to the first motor being in normal working condition, connect the shunt resistor in series to the circuit of the first motor and sample the voltage drop of the shunt resistor at a first frequency.

[0215] The first current signal feature set is determined based on the voltage drop across the shunt resistor obtained from sampling;

[0216] Wherein, the first frequency is twice or more the motor drive frequency.

[0217] The first acquisition unit 601 is specifically used to determine the current signal corresponding to the shunt resistor based on the resistance value of the shunt resistor and the voltage drop of the shunt resistor;

[0218] The current signal is filtered and / or amplified;

[0219] Obtain the DC component feature in the current signal, which is the first DC component signal feature in the first current signal feature set; obtain the ripple feature in the current signal, which is the first ripple feature in the first current signal feature set;

[0220] The first ripple feature includes ripple frequency, count, waveform, and ripple peak value; the first DC component signal feature includes the amplitude of the DC signal.

[0221] The fault unit is specifically used to determine a preset current DC component signal range based on the characteristics of the first DC component signal.

[0222] In response to the second DC component information feature being within the range of the preset current DC component signal, it is determined that the first motor is in a first state;

[0223] If the second DC component information feature is outside the preset current DC component signal range, then the first motor is determined to be in the second state, and a first alarm message is issued.

[0224] The fault unit is specifically used to determine the average amplitude of the DC signal based on the characteristics of the first DC component signal.

[0225] Based on the characteristics of the first DC component signal, at least one standard deviation is determined;

[0226] The preset current DC component signal range is determined based on the average amplitude and the at least one standard deviation.

[0227] The fault unit is specifically used to determine whether the first motor is faulty based on the first ripple feature and the second ripple feature in response to the first motor being in a first state, specifically including:

[0228] The first ripple frequency, first count, first waveform, and first ripple peak value are determined based on the first ripple characteristics.

[0229] The second ripple frequency, second count, second waveform, and second ripple peak value are determined based on the second ripple characteristics.

[0230] Based on at least two of the following: first ripple frequency, first count, first waveform, first ripple peak value, second ripple frequency, second count, second waveform, and second ripple peak value, determine whether the first motor is faulty.

[0231] The fault unit is specifically used for at least one of the following:

[0232] If the first count differs from the second count, then a fault is determined in the first motor.

[0233] If the first ripple frequency is greater than the second ripple frequency, then the first motor is determined to be faulty.

[0234] If the second waveform shows a periodic spike or abrupt change compared to the first waveform, then the first motor is determined to be faulty.

[0235] If the peak value of the second ripple is greater than the peak value of the first ripple, and at least one ripple in the second waveform is different from the other ripples, then the first motor is determined to be faulty.

[0236] If a periodic spike or abnormal ripple appears in the second waveform, the first motor is determined to be faulty.

[0237] If a ripple different from the first waveform appears in the second waveform, then the first motor is determined to be faulty.

[0238] If a ripple different from the first waveform appears in the second waveform and the peak value of the second ripple is higher than the first preset threshold, then the first motor is determined to be faulty.

[0239] If a ripple different from the first waveform appears in the second waveform, and the amplitude of the ripple fluctuation is greater than a second preset threshold, then a first motor fault is determined.

[0240] If a ripple that is different from the first waveform appears periodically in the second waveform, then the first motor is determined to be faulty.

[0241] If the second waveform is found to lack at least one ripple compared to the first waveform, then the first motor is determined to be faulty.

[0242] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0243] Figure 10 A schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0244] like Figure 10 As shown, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. The RAM 803 may also store various programs and data required for the operation of the electronic device 800. The computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0245] Multiple components in electronic device 800 are connected to I / O interface 805, including: input unit 806, such as keyboard, mouse, etc.; output unit 807, such as various types of displays, speakers, etc.; storage unit 808, such as disk, optical disk, etc.; and communication unit 809, such as network card, modem, wireless transceiver, etc. Communication unit 809 allows electronic device 800 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0246] The computing unit 801 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above, such as a method for detecting faults based on motor current signals. For example, in some embodiments, the method for detecting faults based on motor current signals can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 800 via ROM 802 and / or communication unit 809. When the computer program is loaded into RAM 803 and executed by the computing unit 801, one or more steps of the method for detecting faults based on motor current signals described above can be performed. Alternatively, in other embodiments, the computing unit 801 may be configured by any other suitable means (e.g., by means of firmware) to perform a method for detecting faults based on motor current signals.

[0247] Various embodiments 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-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0248] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0249] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0250] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0251] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0252] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0253] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0254] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0255] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for fault detection based on motor current signal, characterized in that, The method includes: Obtain a first current signal feature set of the first motor in normal operating state; the first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current; Obtain the second current signal feature set of the current operating state of the first motor; the second current signal feature set includes the second DC component signal feature and the second ripple feature of the motor current; Based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics, it is determined whether the first motor is faulty.

2. The method according to claim 1, characterized in that, The first current signal feature set for obtaining the normal operating state of the first motor includes: In response to the first motor being in normal operating condition, a shunt resistor is connected in series to the circuit of the first motor, and the voltage drop of the shunt resistor is sampled at a first frequency. The first current signal feature set is determined based on the voltage drop across the shunt resistor obtained from sampling; Wherein, the first frequency is twice or more the motor drive frequency.

3. The method according to claim 2, characterized in that, The determination of the first current signal feature set based on the voltage drop across the sampled shunt resistor includes: Based on the resistance value of the shunt resistor and the voltage drop across the shunt resistor, the current signal corresponding to the shunt resistor is determined; The current signal is filtered and / or amplified; Obtain the DC component feature in the current signal, which is the first DC component signal feature in the first current signal feature set; obtain the ripple feature in the current signal, which is the first ripple feature in the first current signal feature set; The first ripple feature includes ripple frequency, count, waveform, and ripple peak value; the first DC component signal feature includes the amplitude of the DC signal.

4. The method according to claim 1, characterized in that, The method of determining whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics, includes: The preset current DC component signal range is determined based on the characteristics of the first DC component signal. In response to the second DC component information feature being within the range of the preset current DC component signal, it is determined that the first motor is in a first state; If the second DC component information feature is outside the preset current DC component signal range, then the first motor is determined to be in the second state, and a first alarm message is issued.

5. The method according to claim 4, characterized in that, The step of determining the preset current DC component signal range based on the characteristics of the first DC component signal includes: Based on the characteristics of the first DC component signal, the average amplitude of the DC signal is determined; Based on the characteristics of the first DC component signal, at least one standard deviation is determined; The preset current DC component signal range is determined based on the average amplitude and the at least one standard deviation.

6. The method according to claim 4, characterized in that, The method of determining whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics, includes: In response to the first motor being in a first state, a determination is made as to whether the first motor is faulty based on the first ripple characteristic and the second ripple characteristic, specifically including: The first ripple frequency, first count, first waveform, and first ripple peak value are determined based on the first ripple characteristics. The second ripple frequency, second count, second waveform, and second ripple peak value are determined based on the second ripple characteristics. Based on at least two of the following: first ripple frequency, first count, first waveform, first ripple peak value, second ripple frequency, second count, second waveform, and second ripple peak value, determine whether the first motor is faulty.

7. The method according to claim 6, characterized in that, The method of determining whether the first motor is faulty based on at least two of the following: first ripple frequency, first count, first waveform, first ripple peak value, second ripple frequency, second count, second waveform, and second ripple peak value, includes at least one of the following: If the first count differs from the second count, then a fault is determined in the first motor. If the first ripple frequency is greater than the second ripple frequency, then the first motor is determined to be faulty. If the second waveform shows a periodic spike or abrupt change compared to the first waveform, then the first motor is determined to be faulty. If the peak value of the second ripple is greater than the peak value of the first ripple, and at least one ripple in the second waveform is different from the other ripples, then the first motor is determined to be faulty. If a periodic spike or abnormal ripple appears in the second waveform, the first motor is determined to be faulty. If a ripple different from the first waveform appears in the second waveform, then the first motor is determined to be faulty. If a ripple different from the first waveform appears in the second waveform and the peak value of the second ripple is higher than the first preset threshold, then the first motor is determined to be faulty. If a ripple different from the first waveform appears in the second waveform, and the amplitude of the ripple fluctuation is greater than a second preset threshold, then a first motor fault is determined. If a ripple that is different from the first waveform appears periodically in the second waveform, then the first motor is determined to be faulty. If the second waveform is missing at least one ripple compared to the first waveform, then the first motor is determined to be faulty. If the slope of any peak of the second waveform is greater than the first slope in the first time interval, then the internal jamming of the first motor is determined. If the ripples disappear in the second waveform, it is determined that the first motor is stuck inside. If any ripple duration in the second waveform is longer than the duration of other ripples, then the first motor is determined to be jammed. If the ripple in the second waveform is irregular and the ripple fluctuation amplitude is greater than the second preset threshold, then the first motor is determined to be jammed inside. If the slope of any peak of the second waveform is greater than the second slope in the first time interval, then the reducer is determined to be jammed. If the ripples in the second waveform are irregular, then the gearbox is determined to be jammed. If a periodic abrupt change occurs in the second waveform and the abrupt change corresponds to the gear meshing point in the reducer, then the reducer is determined to be jammed. If the duration of the ripple in the second ripple becomes shorter, then the gearbox is determined to be jammed. The first slope is greater than the second slope.

8. A device for detecting faults based on motor current signals, characterized in that, The device includes: The first acquisition unit is used to acquire a first current signal feature set of the first motor in normal operating state; the first current signal feature set includes a first DC component signal feature and a first ripple feature of the motor current; The second acquisition unit is used to acquire a second current signal feature set of the current operating state of the first motor; the second current signal feature set includes a second DC component signal feature and a second ripple feature of the motor current. The fault determination unit is used to determine whether the first motor is faulty based on the first DC component signal characteristics and the second DC component signal characteristics, as well as the first ripple characteristics and the second ripple characteristics.

9. An electronic device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-7.

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