Load anomaly detection method for food processor

Abstract

The invention discloses a load anomaly detection method for a food processor, and relates to the technical field of food processors. The food processor comprises a direct current brushless motor, the load anomaly detection method is applied to the direct current brushless motor, and the method comprises the following steps: performing vector calculation based on collected three-phase current to obtain motor operation current after vector synthesis; determining a first current corresponding to each sampling period based on the sampling time of the collected three-phase current and the corresponding motor operation current; counting the first current of which the current value exceeds a preset current threshold value; and within a first preset duration, when the counting value exceeds an alarm number threshold value corresponding to the preset current threshold value, generating alarm information of load abnormity. Therefore, the method has the advantage of being accurate and timely in motor abnormity recognition.

Description

Technical Field

[0001] The present application relates to the technical field of food processing machines, and in particular to a method for detecting load anomalies in a food processing machine. Background Art

[0002] The rotor of the brushless DC motor carries a permanent magnet. When the DC motor is running, the relative movement between the magnetic field generated by the stator winding and the permanent magnet causes the magnetic field to change. This change in the magnetic field usually causes a back electromotive force, which in turn makes the current waveform appear sinusoidal. In existing products, during the operation of the food processor, the brushless DC motor drives the whisking tool to stir the ingredients in the processing chamber. During the stirring process, the technicians monitor the waveform changes of the three-phase current through the sampling resistor, and then judge whether the motor is operating normally through the peak and valley values ​​in the sinusoidal waveform. When the motor has a serious stall or high current problem, the three-phase current no longer presents a sinusoidal waveform, and the current of one phase exceeds the preset specified threshold.

[0003] When the whipping tool in the processing chamber rotates, it may occasionally encounter a problem of being blocked by large particles of food, and the motor may be temporarily stuck and then quickly resume rotation. That is, for the abnormal load that changes in real time in the above situation, the DC brushless motor may have intermittent stalling or short-term stalling problems. The monitored three-phase current changes may appear as a situation where the sine waveform is temporarily lost and then reappears. This situation makes it difficult for technicians to determine whether the DC brushless motor is indeed "seemingly blocked" due to abnormal loads. In the prior art, the food processing machine either directly ignores the short-term stalling problem of the DC brushless motor, or performs an alarm shutdown after each short-term stall. However, long-term neglect of short-term stalls will cause motor damage and shortened life; under the premise that short-term stalls will not significantly affect the current operation of the food processing machine, the alarm shutdown will be immediately triggered after each short-term stall, which will increase the number of false alarms, and the high-frequency alarm shutdown will cause inconvenience to users and a poor user experience.

[0004] Therefore, a new motor abnormality detection method is urgently needed in the prior art to accurately identify the changing abnormal load and effectively protect the motor. Summary of the invention

[0005] The purpose of the present application is to provide a method for detecting load anomalies in a food processing machine, which can timely monitor the abnormal current or stall problems caused by abnormal loads of the motor of the food processing machine by transforming the three-phase current vector into the motor running current, further determining the sampling period of abnormal current values, and giving an alarm when the count value of the abnormal sampling period exceeds the alarm quantity threshold, and reduce interference with the normal operation of the food processing machine. The present application can effectively improve the recognition accuracy and recognition speed of the motor load anomalies of the food processing machine, as well as the working efficiency of the food processing machine, and the present application can detect more types and more subtle motor abnormalities, and can provide timely and effective protection measures for the motor and the food processing machine, and improve the user experience.

[0006] The embodiment of the present application is implemented as follows:

[0007] A first aspect of an embodiment of the present application provides a load abnormality detection method for a food processing machine. The food processing machine includes a DC brushless motor. The load abnormality detection method is applied to the DC brushless motor, and the method includes: performing vector calculation based on the collected three-phase current to obtain the motor operating current after vector synthesis; determining the first current corresponding to each sampling period based on the sampling time of the three-phase current and its corresponding motor operating current; counting the first current whose current value exceeds a preset current threshold; generating load abnormality alarm information within a first preset time period when the count value exceeds the alarm quantity threshold corresponding to the preset current threshold.

[0008] Based on the above scheme, the present application reduces the difficulty of the food processing machine to identify abnormal current values ​​or loads of the DC brushless motor by aggregating the three-phase current vectors to synthesize the motor running current, thereby improving the accuracy and speed of identifying abnormal loads. The present application also reduces the problem of accumulated motor losses or even scrapping caused by long-term neglect of short-term abnormal loads in the food processing machine by continuously counting the sampling period of abnormal current values ​​and issuing an alarm when the count value exceeds the alarm quantity threshold, and can also reduce the phenomenon of false alarms in the food processing machine. The present application can improve the intelligence and accuracy of the food processing machine in identifying abnormal motor loads, and can issue an alarm in a timely manner to reduce interference with the normal use of the food processing machine, effectively improving the working efficiency of the food processing machine and the user experience.

[0009] In one embodiment, counting is performed for a first current whose current value exceeds a preset current threshold, including: when the current value of the first current exceeds a second current threshold, updating the second count value; when the current value of the first current exceeds the first current threshold and does not exceed the second current threshold, updating the first count value.

[0010] Based on the above scheme, the present application determines the sampling periods of different types of current value abnormalities according to different threshold ranges and counts them, and can summarize the cumulative number of medium current phenomena and the cumulative number of large current phenomena in multiple sampling periods. The above scheme further subdivides the abnormality types for the current abnormality of the motor, effectively improving the accuracy of the food processing machine in identifying the load abnormality type.

[0011] In one embodiment, when the count value exceeds the alarm quantity threshold corresponding to the preset current threshold, an alarm message of load abnormality is generated, including: when the first count value exceeds the first alarm quantity threshold corresponding to the first current threshold, a medium current abnormality alarm message is generated; when the second count value exceeds the second alarm quantity threshold corresponding to the second current threshold, a large current abnormality alarm message is generated; wherein the second alarm quantity threshold is less than the first alarm quantity threshold.

[0012] Based on the above scheme, when different types of count values ​​exceed their corresponding alarm quantity thresholds, the food processing machine generates corresponding load abnormality type alarm information, which can effectively distinguish between medium current abnormality alarms and large current abnormality alarms; the second alarm quantity threshold is set to be smaller than the first alarm quantity threshold, which allows the food processing machine to properly adjust the alarm timing based on different current abnormality types, so that it can alarm faster when a continuous large current problem occurs, and alarm later when a continuous medium current problem occurs. The above scheme can improve the refinement of the load abnormality alarm information generated by the food processing machine and realize classified and timely alarms.

[0013] In one embodiment, the brushless DC motor includes a stator coil, and the preset current threshold is obtained in the following manner: a power threshold is calculated based on the heat absorption performance parameters of the stator coil and the motor temperature rise threshold; based on the power threshold, a preset current threshold corresponding to the power threshold is determined.

[0014] Based on the above scheme, the present application pre-calculates the preset current threshold according to the heat absorption performance parameters of the stator coil of the DC brushless motor and the motor temperature rise threshold, which can make the load abnormality detection method performed by the food processor more suitable for the DC brushless motor it is equipped with, thereby improving the accuracy of the food processor in detecting abnormal motor load.

[0015] In one embodiment, the power threshold is calculated based on the heat absorption performance parameters of the stator coil and the motor temperature rise threshold, including: calculating the power threshold according to the formula: P(1-A)=(C×g×ΔT / t)(1-B); wherein P is the power threshold, in W; A is the preset operating efficiency of the DC brushless motor; C is the specific heat capacity of the stator coil material, in J / (kg×℃); g is the mass of the stator coil, in kg; ΔT is the motor temperature rise threshold, in ℃; t is the preset temperature rise time, in s; and B is the heat dissipation efficiency of the motor heat sink.

[0016] Based on the above scheme, the power threshold is calculated and then the preset current threshold is calculated according to the heat absorption performance parameters (specific heat capacity, mass) of the stator coil of the brushless DC motor, the preset operating efficiency of the brushless DC motor, the heat dissipation efficiency of the motor heat sink and the motor temperature rise threshold. This fully takes into account the relationship between the motor operating efficiency and the motor heat dissipation efficiency, so that the setting of the preset current threshold is more in line with the actual operating conditions and heating conditions of the motor, and can more accurately identify the sampling period where current abnormalities occur, thereby improving the accuracy of the food processor in identifying abnormal motor loads.

[0017] In one embodiment, based on the sampling time of the three-phase current and its corresponding motor running current, the first current corresponding to each sampling period is determined, including: based on the sampling time corresponding to the motor running current, calculating the average value of all motor running currents in each sampling period as the first current.

[0018] Based on the above scheme, the food processing machine calculates the average value of all motor operating currents in each sampling period, which can reduce the false alarm phenomenon caused by the motor operating current occasionally exceeding the preset current threshold, make the load abnormality detection of the food processing machine less affected by individual abnormal data, and improve the stability and accuracy of the food processing machine in identifying abnormal motor loads.

[0019] In one embodiment, the food processor also includes a power device, and the load abnormality detection method of the food processor also includes: when the detected bus current exceeds a third current threshold, stopping the pulse width modulation output and alarming, and / or shutting down the power device.

[0020] Based on the above scheme, when a DC brushless motor of a food processing machine has a problem of instantaneous high current, the pulse width modulation output is stopped in time, the power device is turned off and an alarm is sounded, which can interrupt the operation of the motor in many ways and enhance the protection of the DC brushless motor to reduce the occurrence of the DC brushless motor being burned due to the power not being cut off in time.

[0021] In one embodiment, the load abnormality detection method of a food processing machine also includes: timing when the motor speed and the motor operating current meet the stall timing conditions as the stall duration; when the stall duration reaches a first stall duration threshold, controlling the motor to stop running and then restart; when the number of restarts reaches the restart number threshold, generating an alarm message that the motor is continuously stalled.

[0022] Based on the above scheme, the present application records the stall duration when both the motor operating current and the motor speed parameters meet the stall timing conditions, and controls the motor to stop running when the stall duration reaches the first stall duration threshold, which can reduce the false alarm phenomenon caused by accidental short-term stall of the motor of the food processing machine, reduce the interference of accidental short-term stall on the normal operation of the food processing machine, and improve the working efficiency of the food processing machine and the accuracy of identifying continuous stall of the motor; the present application can realize the automatic and flexible response of the food processing machine to the problem of continuous stall of the motor by the food processing machine first adjusting and restarting the motor by itself when the motor is continuously stalled, and then alarming after multiple restarts of the motor are ineffective.

[0023] In one embodiment, timing is performed when the motor speed and the motor operating current meet the stall timing conditions, including: when the motor speed is less than the first speed threshold and the motor operating current is greater than the fourth current threshold, the stall duration is accumulated and timed; when the motor speed is greater than the second speed threshold and the motor operating current does not exceed the fourth current threshold, the stall duration is accumulated and timed.

[0024] Based on the above scheme, the present application accumulates the time when the motor is seriously blocked and decrements the time when the motor is running smoothly, and can reasonably time the overall blocking situation of the motor to avoid the food processor misjudging the intermittent blocking as continuous blocking when the DC brushless motor is intermittently blocked and does not affect the actual operation of the food processor. The above scheme can improve the rationality and accuracy of the food processor's detection of the continuous blocking problem of the DC brushless motor.

[0025] In one embodiment, the load abnormality detection method of a food processing machine also includes: for each stall monitoring cycle, if the stall duration exceeds a second stall duration threshold, marking the current stall monitoring cycle as an abnormal stall cycle; within the second preset duration, when the total number of marks of the abnormal stall cycle exceeds the stall number threshold, generating an intermittent stall alarm message.

[0026] Based on the above scheme, the present application generates intermittent stall alarm information when the number of abnormal stall cycles during intermittent stall exceeds the stall threshold, which can improve the detection accuracy of intermittent stall of brushless DC motor in food processing machine and avoid false alarm caused by short-term accidental stall. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 A structural schematic diagram of a food processing machine provided in one embodiment of the present application;

[0029] Figure 2 A schematic diagram of the structure of a load abnormality detection circuit provided in an embodiment of the present application;

[0030] Figure 3 A schematic flow chart of a method for detecting abnormal load of a food processing machine provided in one embodiment of the present application;

[0031] Figure 4 A schematic diagram of converting three-phase current into orthogonal current provided by an embodiment of the present application;

[0032] Figure 5 A schematic diagram of converting orthogonal current into rotor current provided by an embodiment of the present application.

[0033] Figure numerals: 1-food processor; 2-motor; 31-rectifier circuit; 32-load abnormality detection circuit; 321-sampling resistor; 4-processing module; 5-memory. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0035] Similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0036] The technical solution of the present application will be described clearly and completely below in conjunction with the accompanying drawings.

[0037] See also Figure 1 , Figure 1 This is a structural diagram of a food processing machine 1 provided in one embodiment of the present application. Figure 1 As shown, the food processor 1 includes a motor 2, a load abnormality detection circuit 32 for detecting abnormal load changes of the motor, a processing module 4, and a memory 5. In the embodiment of the present application, the motor 2 used in the food processor 1 is a brushless DC motor 2. Figure 2A processing module 4 is taken as an example. The processing module 4 and the memory 5 are connected via a bus, and the memory 5 stores instructions that can be executed by at least one processing module 4. The instructions are executed by at least one processing module 4, so that at least one processing module 4 executes the load abnormality detection method in the following embodiment. The method is applied to the DC brushless motor 2, and can timely monitor the current change or speed change of the motor 2 when the DC brushless motor 2 has an instantaneous high current fault, a continuous medium / high current fault, a continuous stall or an intermittent stall fault, so as to generate an alarm message according to the fault type, or automatically take action according to the fault to realize timely protection of the motor.

[0038] See also Figure 2 , Figure 2 FIG. 3 is a schematic diagram of the structure of a load abnormality detection circuit 32 provided in an embodiment of the present application. Figure 2 As shown, the hardware control circuit of the food processor 1 includes a brushless DC motor 2, a load abnormality detection circuit 32, a rectifier circuit 31 and a processing module 4. Among them, the rectifier circuit 31 is connected to the IPM module in the load abnormality detection circuit 32 through the U_MOT pin, which is used to supply power to the IPM module and the motor 2; the control unit MCU (i.e., the processing module 4) is connected to the IPM module through 6 PWM outputs, which is used to control the opening and closing of the corresponding power devices in the IPM module to further control the current output waveform of the IPM module; the IPM module is connected to the sampling resistor 321 or one side of the detection resistor R22 through the NU, NV, and NW pins, and the other side of the detection resistor R22 is connected to the CSC pin of the IPM module, and the other side of the sampling resistor 321 is grounded.

[0039] The IPM module can directly detect the bus current value of the three-phase current converged to AD_CUR through the CSC pin and the detection resistor R22 to determine whether the motor 2 has a momentary high current fault; the processing module 4 detects the voltage value across the sampling resistor 321 in real time, collects the aggregated three-phase current value after the three-phase current converges, and then disassembles the aggregated three-phase current value, vector transforms, and calculates the current value of the motor running current, so as to determine whether the motor 2 has a continuous high current or continuous medium current fault based on the motor running current value.

[0040] In addition, the motor 2 is also equipped with a speed detection element, which is configured to detect the speed of the motor 2. The processing module 4 determines whether the motor 2 has a continuous stall problem or an intermittent stall problem based on the motor speed and the motor operating current.

[0041] See also Figure 3 , Figure 3 FIG. 1 is a flow chart of a method for detecting abnormal load of a food processing machine 1 according to an embodiment of the present application. Figure 3 As shown, the method comprises the following steps:

[0042] S110: Perform vector calculation based on the collected three-phase current to obtain the motor running current after vector synthesis.

[0043] The three-phase current is collected by real-time monitoring of the voltage on both sides of the sampling resistor 321 and real-time calculation based on the resistance value of the sampling resistor 321. The vector calculation refers to the calculation process of decomposing the collected three-phase current, orthogonally transforming it, and then performing vector transformation based on the rotor angle of the motor 2 to finally obtain a stable current value related to the rotor angle of the motor 2.

[0044] In this step, the processing module 4 obtains the collected three-phase current value flowing through the motor 2 in real time through the sampling resistor 321. Since each phase current changes in a sinusoidal wave, it is impossible to accurately judge whether there is a problem with the operation of the motor 2 based directly on the collected three-phase current. The processing module 4 performs vector calculation based on the collected three-phase current value to obtain a stable current value related to the rotor angle of the motor 2 as the motor operating current value, and then in subsequent steps, based on the numerically stable motor operating current value, judge whether the motor 2 has a continuous large current problem or a continuous medium current problem.

[0045] S120: Determine a first current corresponding to each sampling period based on the sampling time of the three-phase currents and the corresponding motor running currents.

[0046] When judging whether the motor 2 has a problem of continuous large current or continuous medium current, the processing module 4 needs to compare multiple current values ​​within a certain time with the corresponding current thresholds. Since the sampling frequency of the three-phase current is high, the motor operating current calculated based on the sampling time is relatively large, so the evaluation time used to judge whether there is a continuous medium / large current can be used as a preset time, and the preset time is divided into multiple sampling cycles. Then, based on the time period corresponding to each sampling cycle and the sampling time corresponding to the three-phase current, the sampling cycle to which each motor operating current belongs is determined, and the first current corresponding to each sampling cycle is determined based on the motor operating current. In one embodiment, the processing module 4 can determine the first current corresponding to the most recent sampling cycle based on the motor operating current corresponding to each sampling time in the most recent sampling cycle after each sampling cycle ends.

[0047] S130: Counting the first current whose current value exceeds the preset current threshold.

[0048] In this step, after determining the first current corresponding to each sampling period based on the motor running current, the processing module 4 continuously counts the first current whose current value exceeds the preset current threshold. The preset current threshold may be a medium current threshold corresponding to a continuous medium current fault, or a large current threshold corresponding to a continuous large current fault. When the current value of the first current exceeds the preset current threshold, the processing module 4 adds 1 to the count value for the first current or the sampling period corresponding to the first current, so as to judge whether the motor has a continuous large current fault or a continuous medium current fault based on the accumulated count value within the preset time length in the subsequent steps.

[0049] S140: within the first preset time period, when the count value exceeds the alarm quantity threshold corresponding to the preset current threshold, an alarm message of load abnormality is generated.

[0050] In this step, the processing module 4 determines whether the motor 2 has a continuous large current fault or a continuous medium current fault based on the number of first currents whose current values ​​exceed the preset current threshold value within the first preset duration. For example, the duration corresponding to the sampling period is 1s, the first preset duration is 30s, each sampling period corresponds to a first current, and the first current is determined based on multiple motor operating currents within the sampling period. Then, within any time period corresponding to the first preset duration, if the first current values ​​corresponding to more than half (or other specified number) of the sampling periods exceed the preset current threshold value corresponding to the large current fault or the medium current fault, it means that the motor has a continuous large current fault or a continuous medium current fault within the time period.

[0051] In one embodiment, the processing module continuously updates the cumulative count value in the first time period most adjacent to the current time period (the time period corresponding to the first time period is the first preset time period) based on the current moment and the first preset time period, that is, after each sampling period, the processing module determines whether the first current value corresponding to the sampling period exceeds the preset current threshold, and accumulates the count value for the first current whose current value exceeds the preset current threshold in the first time period, so as to finally generate an alarm message when the count value exceeds the alarm quantity threshold in the first time period.

[0052] Based on the above scheme, the present application reduces the difficulty of the food processor in identifying abnormal current values ​​or loads of the DC brushless motor by converting the collected three-phase current vector into the motor running current, thereby improving the accuracy and speed of identifying abnormal loads; the present application reduces the problem of accumulated motor losses or even scrapping of the food processor due to long-term neglect of short-term abnormal loads by continuously counting the sampling period of abnormal current values ​​and issuing an alarm when the count value exceeds the alarm quantity threshold, and can also reduce the phenomenon of false alarms in the food processor. The present application can improve the intelligence and accuracy of the food processor in identifying abnormal motor loads, and can issue an alarm in a timely manner to reduce interference with the normal use of the food processor, effectively improving the work efficiency of the food processor and the user experience.

[0053] Please combine Figure 2 The hardware connection circuit shown and the load abnormality detection method in the above embodiment. In the embodiment of the present application, the food processor 1 can judge in real time whether the motor 2 has a momentary high current fault based on the bus current directly detected flowing through the CSC pin and the detection resistor R22, and timely control the IPM module to shut down the power device and realize motor protection when a momentary high current fault occurs; in the embodiment of the present application, the food processor 1 can also calculate the motor running current based on the collected three-phase current based on the vector transformation method, and then judge whether the motor 2 has a continuous high current or continuous medium current fault according to the motor running current, and / or, the food processor 1 can also judge whether the motor 2 has a continuous stall or intermittent stall fault according to the motor running current and the motor rotor speed. The specific details are as follows:

[0054] (I) Calculation of motor running current:

[0055] In the embodiment of the present application, vector calculation is performed based on the collected three-phase current to obtain the motor running current after vector synthesis, including the following steps S111 to S113.

[0056] S111: Based on the vector transformation method, the collected three-phase current is converted into orthogonal current.

[0057] The orthogonal current includes the first orthogonal current and the second orthogonal current; wherein the direction of the first orthogonal current is the same as the direction of the first phase current in the three-phase current. Figure 4 , Figure 4 A schematic diagram of converting three-phase current into orthogonal current provided by an embodiment of the present application. Figure 4 As shown, the three-phase current is decomposed into I a ,I b ,I c Three-phase current, according to the vector control principle of DC brushless motor 2, first for a, b, c three-phase current Ia ,I b ,I c Perform Clark transformation to obtain the orthogonal current I corresponding to the two-dimensional variables α and β α ,I β , the calculation formula is as follows (1):

[0058]

[0059] Among them, I a It is the current value of phase a in the three-phase current, in A; I b It is the current value of phase b in the three-phase current, in A; I c It is the current value of phase c in the three-phase current, in A; I α is the first orthogonal current, in A; I β is the second orthogonal current, in A.

[0060] In the above steps, the three-phase current is collected by the MCU outputting PWM control signals for the U, V, and W phases respectively, thereby controlling the corresponding power devices in the IPM module to turn on or off, so that the IPM module outputs the current to the motor 2 and controls the rotation of the motor.

[0061] S112: Based on the rotor angle and vector transformation method, the orthogonal current is converted into the rotor current.

[0062] The rotor current includes the first rotor current I d (or I D ) and the second rotor current I q (I Q ). Among them, the first rotor current I d The direction of the first phase current I a The angle between the directions of the second rotor current and the first rotor current is the rotor angle θ; the direction of the second rotor current is perpendicular to the direction of the first rotor current. a The direction is orthogonal to the first current I α The direction of the first rotor current I d direction, and the first orthogonal current I α The angle between the directions is the rotor angle θ.

[0063] See also Figure 5 , Figure 5 A schematic diagram of converting orthogonal current into rotor current provided by an embodiment of the present application. Figure 5 As shown, after the orthogonal current is calculated, the orthogonal current is Parked according to the rotor angle θ, and the orthogonal current I α ,I β Converted into the first rotor current I parallel to the rotord , the second rotor current I perpendicular to the rotor q , the calculation formula is as follows (2):

[0064]

[0065] Among them, I d is the first rotor current parallel to the rotor direction, in A; I q is the second rotor current perpendicular to the rotor direction, in A.

[0066] S113: Based on a vector synthesis method, the rotor current is synthesized into a motor operating current.

[0067] In this step, the processing module 4 converts the first rotor current I d and the second rotor current I q Vector synthesis is used to obtain the motor running current, which is calculated using the following formula (3):

[0068]

[0069] Among them, I s is the motor running current, in A.

[0070] Based on the above scheme, the present application reduces the difficulty of the food processor identifying abnormal current value or load of the brushless DC motor by disassembling the collected three-phase current and then vector synthesizing it into the motor running current, thereby improving the accuracy and speed of identifying abnormal loads.

[0071] (ii) Based on the motor running current, an alarm message is generated when a continuous high current fault or a continuous medium current fault occurs in the motor 2.

[0072] In the embodiment of the present application, the processing module determines the first current corresponding to each sampling period based on the sampling time of the three-phase current and its corresponding motor running current. Specifically, after each sampling period, the processing module 4 calculates the average value of all motor running currents in each sampling period based on the sampling time corresponding to the motor running current as the first current.

[0073] The food processing machine calculates the average value of all motor operating currents in each sampling period, which can reduce false alarms caused by the motor operating current occasionally exceeding the preset current threshold, making the food processing machine's load abnormality detection less affected by individual abnormal data, thereby improving the stability and accuracy of the food processing machine's identification of abnormal motor loads.

[0074] In other embodiments of the present application, the processing module 4 may also calculate a weighted average value of all motor operating currents in each sampling period, or determine a mode value of all motor operating currents as the first current.

[0075] The processing module 4 sets two corresponding state storage arrays for the motor 2 respectively for the problems of continuous medium current and continuous large current, and counts the first current whose current value exceeds the preset current threshold. For example, for the state storage array corresponding to the continuous large current fault, after initializing the state storage array, the processing module assigns 1 or 0 to the current storage position of the state storage array based on the latest first current value, that is, when the current value of the first current exceeds the preset current threshold corresponding to the continuous large current fault, the current storage position corresponding to the current sampling period is assigned 1, otherwise it is set to 0; then the processing module 4 continuously updates the latest state value in the state storage array based on the first preset time length and the current moment, and counts the sampling period with the storage position of 1, and in the first time period closest to the current moment (that is, the time period with a time length less than or equal to the first preset time length from the current moment), the state value is 1 and is accumulated, and the state value is 0 and remains unchanged. The storage step corresponding to the continuous medium current fault is similar to that of the large current, and will not be repeated again.

[0076] In an embodiment of the present application, a first current whose current value exceeds a preset current threshold is counted, including: when the current value of the first current exceeds the first current threshold and does not exceed the second current threshold, updating the latest state value in the state storage array corresponding to the continuous medium current fault to 1, and based on the latest state value, updating the first count value corresponding to the continuous medium current alarm; when the current value of the first current exceeds the second current threshold, updating the second count value corresponding to the continuous large current alarm.

[0077] The processing module 4 determines in real time whether an abnormality occurs in the continuous current state corresponding to the most recent period based on the continuously updated first count value and the second count value, so as to further determine whether an alarm is required for a continuous medium current fault or a continuous large current fault. During the first preset time period before the current moment, when the count value exceeds the alarm quantity threshold corresponding to the preset current threshold, an alarm message of load abnormality is generated, including: when the first count value exceeds the first alarm quantity threshold corresponding to the first current threshold, a medium current abnormality alarm message is generated; when the second count value exceeds the second alarm quantity threshold corresponding to the second current threshold, a large current abnormality alarm message is generated. The second alarm quantity threshold is less than the first alarm quantity threshold.

[0078] Based on the above scheme, the present application summarizes the cumulative number of medium current phenomena and the cumulative number of large current phenomena in multiple sampling periods, and generates corresponding alarm information of load abnormality types when the count values ​​of different types exceed their corresponding alarm quantity thresholds. The present application can further subdivide the abnormality types according to the abnormal current phenomenon of the motor, and the setting of the second alarm quantity threshold being less than the first alarm quantity threshold can enable the food processing machine to appropriately adjust the alarm timing based on different current abnormality types, so that it can alarm faster when a continuous large current problem occurs, and alarm later when a continuous medium current problem occurs. The above scheme can improve the degree of refinement of the load abnormality alarm information generated by the food processing machine and realize classified and timely alarms.

[0079] The preset current threshold corresponding to the continuous high current alarm and the preset current threshold range corresponding to the continuous medium current alarm are determined in the following manner:

[0080] Firstly, based on the heat absorption performance parameters of the stator coil in the brushless DC motor 2 and the motor temperature rise threshold, the power threshold is calculated; then, based on the power threshold, the corresponding current threshold is determined.

[0081] The power threshold calculation formula is as follows (4):

[0082] P(1-A)=(C×g×ΔT / t)(1-B); (4)

[0083] Among them, P is the power threshold, in W; A is the preset operating efficiency of the DC brushless motor 2; C is the specific heat capacity of the stator coil material, in J / (kg×℃); g is the mass of the stator coil, in kg; ΔT is the motor temperature rise threshold, in ℃; t is the preset temperature rise time, in s; B is the heat dissipation efficiency of the heat sink of the motor 2.

[0084] Taking the stator coil of motor 2 as an example, the specific heat capacity (C) of aluminum is 880J / (kg×℃), the weight of aluminum wire (g) is 0.05kg, the heat dissipation efficiency B of the heat dissipation duct is 70%, the preset operating efficiency A of the DC brushless motor is 90%, and the motor temperature rise (ΔT) is required not to exceed 100℃. When the preset temperature rise time t=10s, P=1320w, corresponding to the second current threshold of 6A; when the preset temperature rise time t=20s, P=660w, corresponding to the first current threshold of 3A.

[0085] Based on the above scheme, the present application calculates the power threshold and then calculates the preset current threshold in advance according to the heat absorption performance parameters (specific heat capacity, mass) of the stator coil of the brushless DC motor, the preset operating efficiency of the brushless DC motor, the heat dissipation efficiency of the motor heat sink and the motor temperature rise threshold. This fully takes into account the relationship between the motor operating efficiency and the motor heat dissipation efficiency, and can make the load abnormality detection method performed by the food processor more suitable for the brushless DC motor it is equipped with, so that the setting of the preset current threshold is more in line with the actual operating conditions and heating conditions of the motor, and thus can more accurately identify the sampling period where current abnormalities occur, thereby improving the accuracy of the food processor in identifying abnormal motor loads.

[0086] Correspondingly, the first alarm quantity threshold corresponding to the medium current abnormal alarm is 20, and the second alarm quantity threshold corresponding to the large current abnormal alarm is 10. For example, when the number of state values ​​1 in the state storage array corresponding to the continuous medium current alarm exceeds 20, the processing module generates medium current abnormal alarm information; when the number of state values ​​1 in the state storage array corresponding to the large current alarm exceeds 10, the processing module generates large current abnormal alarm information. In other embodiments of the present application, the alarm quantity threshold and the preset current threshold can also be set to other values ​​according to the actual operation of the food processor 1 or the parameters of the motor 2.

[0087] Based on the above scheme, the processing module performs vector transformation and vector synthesis on the collected three-phase current based on the motor rotor angle, obtains the motor operating current corresponding to each sampling time, and can convert the unstable current with sinusoidal changes into a stable current; the processing module determines the first current based on the sampling period and the motor operating current corresponding to each sampling time, and counts the first current whose current value is within the current threshold range corresponding to the continuous medium current or continuous large current fault, which can reduce the false alarm problem caused by the sudden change of the motor operating current due to environmental interference or other factors. The present application can accurately identify and promptly prompt the abnormal load of the motor, has the advantages of accurate and timely detection of motor abnormalities in food processing machines, and can detect more types and more subtle motor abnormalities, thereby improving the user experience.

[0088] (iii) Based on the motor operating current and the motor speed, determine whether the motor 2 has a continuous stall fault or an intermittent stall fault.

[0089] First, the determination of the duration of the stall:

[0090] When monitoring the motor operation, the processing module 4 counts when the motor speed and the motor running current meet the stall timing condition as the stall duration. The stall timing condition includes a cumulative timing condition and a cumulative subtraction timing condition. The cumulative timing condition is: the motor speed is less than the first speed threshold, and the motor running current is greater than the fourth current threshold; the cumulative subtraction timing condition is: the motor speed is greater than the second speed threshold, and the motor running current does not exceed the fourth current threshold.

[0091] Specifically, the processing module 4 continuously monitors the motor speed and the motor operating current when determining whether the motor 2 is stalled: when the motor speed is less than the first speed threshold and the motor operating current is greater than the fourth current threshold, the processing module 4 accumulates the timing for the stall duration; when the motor speed is greater than the second speed threshold and the motor operating current does not exceed the fourth current threshold, the processing module decrements the timing for the stall duration.

[0092] Second, the judgment process of continuous stalling:

[0093] The processing module 4 controls the motor 2 to continue running or stop running based on the stall duration, that is, when the stall duration reaches the first stall duration threshold, the processing module 4 controls the motor 2 to stop running and then restart, and accumulates the number of restarts; when the number of restarts reaches the restart number threshold, an alarm message that the motor 2 is continuously stalled is generated.

[0094] For example, the first speed threshold is 500rpm, the second speed threshold is 900rpm, and the fourth current threshold is 2A. During the operation of motor 2, if it is detected that the motor speed is <500rpm and the motor running current value is >2A, the stall timer will accumulate timing; if the motor speed is >900rpm, or the motor running current value is ≤2A, the stall timer will accumulate timing; when the stall duration accumulates to 5s, the processing module 4 controls the motor 2 to stop running for 5s, then restarts and accumulates the number of restarts; when the number of restarts is ≥2 times, the processing module 4 generates an alarm message of a continuous stall fault of the motor 2 when the motor 2 meets the stall accumulation timing condition again.

[0095] Based on the above scheme, the present application can reduce the false alarm phenomenon caused by accidental short-term stalling of the motor of the food processing machine, reduce the interference of accidental short-term stalling on the normal operation of the food processing machine, and improve the working efficiency of the food processing machine and the accuracy of detecting continuous stalling of the motor; the present application can realize the automatic and flexible response of the food processing machine to the problem of continuous stalling of the motor by allowing the food processing machine to automatically adjust and restart the motor when the motor is continuously stalled, and then alarm after multiple restarts of the motor are ineffective.

[0096] The present application adds time when the motor is severely stalled and subtracts time when the motor is running smoothly. It can perform reasonable timing for the overall stalling situation of the motor to avoid the food processor misjudging intermittent stalling as continuous stalling and shutting down to alarm when the DC brushless motor is intermittently stalled and does not affect the actual operation of the food processor. The present application can improve the rationality and accuracy of the food processor's detection of the continuous stalling problem of the DC brushless motor.

[0097] Judgment process of intermittent stall:

[0098] The processing module 4 performs the stall timing for each stall monitoring cycle based on the stall duration determination method in the above embodiment (i.e. based on the cumulative timing condition and the cumulative timing condition). If the stall duration exceeds the second stall duration threshold value within a stall monitoring cycle, the processing module 4 marks the current stall monitoring cycle as an abnormal stall cycle and accumulates the number of abnormal stall cycles. Within the second preset duration, when the total number of abnormal stall cycles exceeds the stall count threshold value, the processing module 4 generates an intermittent stall alarm message.

[0099] In another embodiment, the processor performs stall timing for each stall monitoring cycle only when the motor operating current and the motor speed meet the cumulative timing conditions. If the accumulated stall duration exceeds the second stall duration threshold within a stall monitoring cycle, the processing module 4 marks the current stall monitoring cycle as an abnormal stall cycle and accumulates the number of abnormal stall cycles. Within the second preset duration, when the total number of abnormal stall cycles exceeds the stall count threshold, the processing module 4 generates an alarm message indicating that the motor has an intermittent stall fault.

[0100] During the process of beating ingredients in the food processor 1, if the beating tool encounters large particles of material, the motor 2 may have intermittent jamming problems during actual operation. For example, after the motor 2 is jammed for 2 to 3 seconds, it runs quickly for 2 to 3 seconds, but it is unable to enter the continuous stall alarm state repeatedly. If the motor 2 is in this working condition for a long time, it is easy to be damaged rapidly due to overheating. Therefore, the judgment method for intermittent stall faults provided by the present application can effectively avoid the problem of motor heating and shortened life caused by the difficulty of timely alarm due to intermittent jams. The food processor can also identify subtle intermittent stall phenomena through the motor speed and current when the motor maintains operation, which expands the type range of motor fault identification, effectively improves the operating efficiency and quality of the motor, extends the life of the motor, reduces the heat dissipation pressure, reduces the unnecessary heating of the motor, and improves the user experience.

[0101] For example, the monitoring duration corresponding to the stall monitoring cycle is 1s, the second stall duration threshold is 20ms, the second preset duration is 30s, and the stall number threshold is 15 times. If the motor 2 stalls for more than 20ms within a certain 1s, it is considered that the operation of the motor 2 is abnormal in the stall monitoring cycle corresponding to this 1s; if the motor is abnormal for more than 15s within 30s (that is, the total number of abnormal stall cycles exceeds 15 times), the processing module 4 generates an alarm message of intermittent stall.

[0102] In the above embodiment, the processing module can also adopt the method of judging a continuous large current fault or a continuous medium current fault, based on the motor operating current and the motor speed corresponding to multiple sampling times, determine the first current and the first speed corresponding to each stall monitoring cycle, and then judge whether the motor has a continuous stall fault or an intermittent stall fault based on the first current and the first speed corresponding to each stall monitoring cycle.

[0103] When the number of abnormal stall cycles of intermittent stall phenomenon exceeds the stall number threshold, the application generates intermittent stall alarm information, which can improve the detection accuracy of intermittent stall of brushless DC motor in food processing machine and avoid false alarm caused by short-term accidental stall.

[0104] (iv) Based on the bus current detected by the IPM module, timely judgment and protection are performed when a transient high current problem occurs in motor 2.

[0105] In this step, when the bus current detected by the IPM module exceeds the third current threshold, the processing module 4 stops the pulse width modulation output and issues an alarm, and / or controls the IPM module to shut down the power device.

[0106] like Figure 2 As shown, after receiving the PWM signal output by the MCU, the IPM module controls the internal power device to open or close according to the signal output pin corresponding to the PWM signal, so that the corresponding U switches to U_MOT high potential or NU low potential (V, W also switch to U_MOT high potential or NV, NW low potential) to drive the motor to run. The IPM module aggregates the current to the VSS pin of the IPM module through the sampling resistor 321 and grounds it, or aggregates the current to the CSC pin of the IPM module through the detection resistor R22, so the current connected and detected by the processing module 4 at AD_CUR is the bus current of the motor 2, and AD_CUR is connected to the CSC pin of the IPM module through the detection resistor R22. The current detected by the IPM module through the CSC pin is also the bus current of the motor 2.

[0107] When the CSC pin of the IPM module detects that the bus current is too large, the FAULT pin of the IPM module outputs a FAULT level signal to the processing module (MCU), which can be a low level signal. After the processing module 4 (MCU) detects the bus current at AD_CUR, it processes the waveform of the bus current, and then monitors the bus current and realizes vector control of the motor 2; at the same time, the processing module 4 (MCU) detects the FAULT level signal of the IPM module, and determines whether the motor 2 has an instantaneous high current fault based on the level of the FAULT signal, and alarms for the fault and controls the IPM module to shut down the power device.

[0108] Taking the third current threshold of 20A as an example, the food processor 1 performs double protection through the IPM module and the processing module 4 (MCU) when the motor 2 has an instantaneous high current fault. The first protection is: when the bus current is greater than 20A, the processing module 4 (MCU) detects the current abnormality at AD_CUR, that is, immediately shuts down the PWM output, and alarms for the instantaneous high current fault; the second protection is: when the bus current is greater than 20A, the CSC foot of the IPM module detects that the current in the detection circuit where the detection resistor R22 is located is abnormal, that is, all power devices are shut down through hardware control from the inside of the IPM module, and the FAULT pin is set low at the same time. When the processing module 4 (MCU) connected to the IPM module through the FAULT pin detects that the FAULT signal is low, it immediately shuts down the PWM output and alarms for the instantaneous high current fault.

[0109] When a brushless DC motor of a food processing machine has a problem of instantaneous high current, the pulse width modulation output is stopped in time, the power device is turned off and an alarm is sounded, which can interrupt the operation of the motor in many ways and enhance the protection of the brushless DC motor to reduce the occurrence of the brushless DC motor being burned due to failure to cut off the power in time.

[0110] Based on the above embodiments, the food processing machine can not only judge whether the motor has an instantaneous high current fault based on the bus current directly monitored, but also perform disassembly and vector conversion based on the collected three-phase current value, and further accurately judge whether the motor has a continuous medium current fault, a continuous high current fault, a continuous stall fault or an intermittent stall fault after obtaining a stable motor operating current. The motor load abnormality detection method for the food processing machine provided in this application expands the range of fault detection types, can perform accurate, continuous and timely fault detection on the motor of the food processing machine, and can generate alarm prompts or automatically perform protection operations in a timely manner. This application can detect more subtle faults that are not easy to find directly, effectively reduce the excess heat generated by the motor due to faults, reduce the power consumption of the food processing machine, and improve the motor operation efficiency, thereby enhancing the user experience.

[0111] In several embodiments provided in the present application, the disclosed device or method can also be implemented in other ways. The method embodiment described above is only schematic, and each box in the flow chart or block diagram can represent a part of a module, a program segment or a code, and a part of a module, a program segment or a code includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flow chart, and the combination of the boxes in the block diagram and / or the flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0112] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0113] The embodiment of the present application provides a computer-readable storage medium, wherein the storage medium stores a computer program. The computer program can be executed by the processing module 4 to complete the load abnormality detection method.

[0114] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory 5 (ROM, Read-Only Memory), random access memory 5 (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0115] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for detecting abnormal load of a food processing machine, characterized in that: The food processing machine includes a brushless DC motor, and the load abnormality detection method is applied to the brushless DC motor. The method includes: Perform vector calculation based on the collected three-phase current to obtain the motor running current after vector synthesis; Determine a first current corresponding to each sampling period based on the sampling time of the aggregated three-phase current and the corresponding motor running current; Counting the first current whose current value exceeds a preset current threshold; Within the first preset time period, when the count value exceeds the alarm quantity threshold corresponding to the preset current threshold, an alarm message of load abnormality is generated.

2. The method for detecting abnormal load of a food processing machine according to claim 1, characterized in that: Counting the first current whose current value exceeds a preset current threshold comprises: When the current value of the first current exceeds a second current threshold, updating a second count value; When the current value of the first current exceeds the first current threshold and does not exceed the second current threshold, the first count value is updated.

3. The method for detecting abnormal load of a food processing machine according to claim 2, characterized in that: When the count value exceeds the alarm quantity threshold corresponding to the preset current threshold, generating alarm information of load abnormality includes: When the first count value exceeds a first alarm quantity threshold corresponding to the first current threshold, generating medium current abnormality alarm information; When the second count value exceeds a second alarm quantity threshold corresponding to the second current threshold, a high current abnormality alarm message is generated; wherein the second alarm quantity threshold is smaller than the first alarm quantity threshold.

4. The method for detecting abnormal load of a food processing machine according to claim 1, characterized in that: The brushless DC motor includes a stator coil, and the preset current threshold is obtained in the following manner: Calculating a power threshold based on the heat absorption performance parameter of the stator coil and the motor temperature rise threshold; Based on the power threshold, the preset current threshold corresponding to the power threshold is determined.

5. The method for detecting abnormal load of a food processing machine according to claim 4, characterized in that: The calculating of the power threshold based on the heat absorption performance parameter of the stator coil and the motor temperature rise threshold comprises: According to the formula: P(1-A)=(C×g×ΔT / t)(1-B), the power threshold is calculated; Among them, P is the power threshold, in W; A is the preset operating efficiency of the DC brushless motor; C is the specific heat capacity of the stator coil material, in J / (kg×℃); g is the mass of the stator coil, in kg; ΔT is the motor temperature rise threshold, in ℃; t is the preset temperature rise time, in s; B is the heat dissipation efficiency of the motor heat sink.

6. The method for detecting abnormal load of a food processing machine according to claim 1, characterized in that: The determining of the first current corresponding to each sampling period based on the sampling time of the aggregated three-phase current and the corresponding motor running current includes: Based on the sampling time corresponding to the motor running current, an average value of all the motor running currents in each sampling period is calculated as the first current.

7. The method for detecting abnormal load of a food processing machine according to claim 1, characterized in that: The food processor further comprises a power device, and the method further comprises: When the detected bus current exceeds the third current threshold, the pulse width modulation output is stopped and an alarm is sounded, and / or the power device is turned off.

8. The method for detecting abnormal load of a food processing machine according to claim 1, characterized in that: The method further comprises: When the motor speed and the motor running current meet the stall timing condition, timing is performed as the stall duration; When the stall duration reaches a first stall duration threshold, controlling the motor to stop running and then restart; When the restart times reach the restart times threshold, an alarm message indicating that the motor is continuously stalled is generated.

9. The method for detecting abnormal load of a food processing machine according to claim 8, characterized in that: The timing is performed when the motor speed and the motor running current meet the stall timing condition, including: When the motor speed is less than a first speed threshold and the motor operating current is greater than a fourth current threshold, accumulating timing for the stall duration; When the motor speed is greater than the second speed threshold and the motor operating current does not exceed the fourth current threshold, the stall duration is decremented.

10. The method for detecting abnormal load of a food processing machine according to claim 1, characterized in that: The method further comprises: For each stall monitoring period, if the stall duration exceeds a second stall duration threshold, the current stall monitoring period is marked as an abnormal stall period; Within the second preset time period, when the total number of marks of the abnormal stall cycle exceeds the stall number threshold, an intermittent stall alarm message is generated.

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