Method and system for detecting state of driving part of direct-current four-channel clean air conditioning unit

Abstract

The invention relates to the technical field of clean air conditioning units, and discloses a method and system for detecting the state of a driving part of a direct-current four-channel clean air conditioning unit. According to the method, a driving part is controlled to operate under different frequency conversion signals, and vibration data under different rotating speeds are obtained through a first vibration sensor arranged on the driving part and a second vibration sensor within a set distance beside the first vibration sensor. And performing frequency spectrum conversion on the vibration data to obtain corresponding frequency spectrum data, and performing filtering calculation to obtain first component data and second component data. A first component, an overlap component, and a second component are calculated from the first component data and the second component data. And calculating a temporary component according to the first component and the second component, and if a temporary ratio of the overlapped component to the temporary component is greater than a preset reference ratio, carrying out driving part state early warning. Through active multi-rotating-speed vibration data collection and spectrum analysis of the clean air conditioning unit, detection and early warning of the state of the driving part are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of clean air-conditioning units, and in particular to a method and system for detecting the status of driving components of a DC four-channel clean air-conditioning unit. Background Art

[0002] The DC four-channel cleanroom air conditioning unit is an air handling device designed for environments with extremely high requirements for air cleanliness, temperature, and humidity. It is widely used in cleanrooms such as electronics manufacturing, biomedicine, and food processing. Equipped with multiple rotating drive components, including fans and compressors, the unit precisely controls the air flow and direction through four independent channels, achieving efficient indoor air filtration, temperature and humidity regulation, and optimized airflow organization, ensuring stable clean air for production environments.

[0003] Over time, the rotating drive components of DC four-channel cleanroom air conditioning units inevitably age. Due to a lack of effective monitoring methods, early wear, poor lubrication, or performance degradation in these components are difficult to detect. Maintenance personnel often only discover and replace these components when component failures cause unit downtime, abnormal air parameters, or even affect the cleanliness of the production environment. This not only increases repair costs but can also cause production interruptions and financial losses.

[0004] Currently, the industry relies heavily on manual inspections or passive maintenance after failures to detect the status of rotating drive components in DC four-channel clean air-conditioning units. There is an urgent need for methods to proactively detect the working status of rotating drive components. Summary of the Invention

[0005] In order to actively detect the working status of the rotating driving components of a DC four-channel clean air-conditioning unit, the present application provides a driving component status detection method and system for a DC four-channel clean air-conditioning unit.

[0006] In a first aspect, the present application provides a method for detecting the status of a drive component of a DC four-channel clean air conditioning unit, which adopts the following technical solution: A method for detecting the state of a driving component of a DC four-channel clean air conditioning unit comprises the following steps: controlling the driving component according to the acquired first frequency conversion signal until the speed of the driving component stabilizes; acquiring first vibration data based on a first vibration sensor disposed on the driving component, and acquiring second vibration data based on a second vibration sensor disposed within a set distance from the driving component; controlling the driving component according to the acquired second frequency conversion signal until the speed of the driving component stabilizes and the amplitude of the speed change is greater than a preset reference amplitude; acquiring third vibration data based on the first vibration sensor, and acquiring fourth vibration data based on the second vibration sensor; performing spectrum conversion on the first vibration data, the second vibration data, the third vibration data, and the fourth vibration data to obtain first spectrum data, second spectrum data, third spectrum data, and fourth spectrum data; Filtering and calculating the first spectrum data according to the second spectrum data to obtain first component data; filtering and calculating the third spectrum data according to the fourth spectrum data to obtain second component data; A first component, an overlapping component, and a second component are calculated based on the first component data and the second component data, wherein the overlapping component is a component whose frequency band and energy similarity between the first component data and the second component data is greater than a preset reference similarity value, the first component is a component in the first component data having a frequency different from that of the overlapping component, and the second component is a component in the second component data having a frequency different from that of the overlapping component. A temporary component is calculated based on the first component and the second component, and a temporary ratio of the overlapping component to the temporary component is calculated. If the temporary ratio is greater than a preset reference ratio, a driving component status warning is issued.

[0007] By adopting the above technical solution, the vibration response characteristics of the equipment under various operating conditions are stimulated by actively regulating the operation of the drive components at different speeds, such as normal speed and speed deviation from the rated value. Vibration data at different speeds contains rich fault information: for example, early bearing wear manifests as weak vibrations of a specific frequency at low speeds, while motor rotor imbalance can cause significant periodic vibrations at high speeds. By jointly comparing the spectral characteristics at multiple speeds, comprehensive coverage detection of mechanical faults (such as bearing wear and rotor imbalance) and electrical faults (such as abnormal frequency conversion control) of rotating components can be achieved. By detecting the motor speed and speed response as well as the wear of the bearings, the motor life can be analyzed and predicted, allowing maintenance to be carried out in advance.

[0008] Optionally, in the step of filtering and calculating the first spectrum data according to the second spectrum data to obtain the first component data; and filtering and calculating the third spectrum data according to the fourth spectrum data to obtain the second component data, the filtering and calculating method includes the following steps: Subtract the second spectrum data from the first spectrum data, and convert the negative value after the subtraction to zero; The fourth spectrum data is subtracted from the third spectrum data, and a negative value after the subtraction is converted to zero.

[0009] By adopting this technical solution, the common components of the ambient vibration spectrum can be offset through subtraction. Data with negative differences are set to zero to avoid reverse interference from ambient signals, ensuring that the remaining data is mainly based on the vibration characteristics of the drive components.

[0010] Optionally, the method further comprises the following steps: Based on the first frequency conversion signal, after the speed of the driving component is stabilized, obtaining first speed data based on a speed sensor; Based on the second frequency conversion signal, after the speed of the driving component is stabilized, obtaining second speed data based on the speed sensor; calculating a speed difference between the first speed data and the second speed data, and adjusting the reference ratio according to an anti-correlation of the speed difference; An average speed value of the first speed data and the second speed data is calculated, an average difference between the average speed value and a preset average reference value is calculated, and the reference similarity value is adjusted according to a positive correlation of the average difference.

[0011] By adopting the above technical solution, the speed difference reflects the degree of fluctuation of the operating status of the drive components. The larger the difference, the more drastic the working conditions change and the higher the risk of potential failure. Therefore, the reference ratio for triggering the alarm needs to be lowered to make the system more sensitive to abnormal vibrations. The average difference reflects the overall speed level. When the average difference is small, the equipment is in a low-speed operation state, the vibration energy is dispersed, and the overlapping frequency bands of the fault characteristics and environmental interference are reduced. At this time, the reference similarity value is lowered to ensure that weak fault signals are not missed. When the average difference is large, the high-speed operation of the equipment causes the vibration energy to be concentrated, and the normal vibration and fault signals are prone to spectral overlap. Therefore, the reference similarity value needs to be increased to avoid misjudging normal fluctuations as faults and achieve accurate diagnosis.

[0012] Optionally, the method further comprises the following steps: During the process in which the rotation speed of the driving component gradually changes to the first rotation speed data; recording the data of the first vibration sensor to obtain first waveform data; During the process of the driving component speed gradually changing to the second speed data; recording the data of the first vibration sensor to obtain second waveform data; If the speed data corresponding to the first waveform data and the speed data corresponding to the second waveform data have no overlapping intervals, matching the first waveform data according to a preset first resonance waveform template to obtain a first matching value; then matching the second waveform data according to the preset first resonance waveform template to obtain a second matching value; A final matching value is calculated based on the first matching value and the second matching value. If the final matching value is greater than a preset reference matching value, a resonance warning prompt is issued.

[0013] By adopting the above technical solution, by recording the vibration waveform data when the speed of the driving component gradually changes, and using the preset resonance waveform template for shape matching when there is no repetitive interval at different speeds, the matching value is calculated by weighted average. If the final matching value exceeds the preset reference value, a resonance warning is triggered.

[0014] Optionally, the method further comprises the following steps: During the process in which the rotation speed of the driving component gradually changes to the first rotation speed data; recording the data of the first vibration sensor to obtain first waveform data; During the process of the driving component speed gradually changing to the second speed data; recording the data of the first vibration sensor to obtain second waveform data; If the speed data corresponding to the first waveform data and the speed data corresponding to the second waveform data have a repeated interval, and the length of the repeated interval is greater than the preset reference interval length, then, the first waveform data is matched according to the preset second resonance waveform template, and the speed with the highest matching value is the first matching speed, and the second waveform data is matched according to the second resonance waveform template, and the speed with the highest matching value is the second matching speed; If the difference between the first matching rotational speed and the second matching rotational speed is smaller than a preset matching difference, a resonance warning prompt is issued.

[0015] By employing this technical solution, a preset second resonant waveform template is used to match vibration waveform data within the repetitive speed variation interval, accurately capturing the waveform distortion characteristics unique to equipment approaching or entering a resonant state. By comparing the speeds with the highest matching values ​​in the two phases and triggering an alert when the difference falls below a threshold, timely intervention can be made before a resonant fault occurs, effectively avoiding serious accidents such as severe equipment vibration and component damage caused by resonance, and ensuring the stable operation of clean air conditioning units.

[0016] Optionally, the method further comprises the following steps: A beam sensor is provided below the bearing, wherein the beam sensor comprises at least one set of a transmitting tube and a receiving tube arranged in a beam-to-be-beam manner; Acquiring a radio signal from the radio sensor; If the radio signals are a group and the content of the radio signals is smoothed and filtered, if the content indicates that there is a foreign object, a wear warning prompt is issued.

[0017] By employing this technical solution, the through-beam sensor, through signal transmission between the transmitting and receiving tubes, can sensitively detect foreign matter such as metal debris and flakes generated by bearing wear. When foreign matter obstructs the through-beam signal, it is smoothed and filtered to identify it as an anomaly, triggering an early warning before any significant performance degradation occurs.

[0018] Optionally, the method further comprises the following steps: If there are multiple groups of radio signals, the multiple groups of radio signals are converted into wear values, and the wear values ​​are smoothed and filtered. If the wear values ​​are greater than a preset wear reference value, a wear warning prompt is issued; A wear difference between the wear value and the wear reference value is calculated, and a rotational speed corresponding to the first frequency conversion signal and a rotational speed corresponding to the second frequency conversion signal are adjusted in anti-correlation according to the wear difference.

[0019] By employing this technical solution, multiple sets of radio signals are converted into wear values. Signal fluctuations are eliminated through smoothing filtering, enabling accurate assessment of bearing wear. Drive speed is adjusted based on the anti-correlation of wear differences. When wear intensifies, the operating speed is automatically reduced, minimizing bearing friction and debris generation, thus forming an adaptive protection mechanism.

[0020] Optionally, the method further comprises the following steps: A foreign body detection sensor is provided next to the bearing, the foreign body detection sensor comprising two parallel detection pieces connected to a detection circuit, and the rotation axis of the driving component is parallel to the plane where the detection pieces are located; Obtaining the resistance value between the two detection sheets; Control the fan speed to a speed with vibration and perform physical filtering on the resistance value; performing smoothing filtering on the resistance value; If the resistance value is less than a preset first reference resistance value, a foreign object prompt is issued; Otherwise, if the resistance value is less than a preset second reference resistance value, a wear warning prompt is issued; wherein the second reference resistance value is greater than the first reference resistance.

[0021] By employing this technical solution, a sensor consisting of two parallel detection plates detects foreign matter and wear debris in the bearing area by monitoring changes in resistance. When a conductive foreign object enters the gap between the detection plates, the resistance drops, triggering different levels of warning: below a first reference resistance value indicates foreign object intrusion, while below a higher second reference resistance value warns of severe bearing wear.

[0022] Optionally, the method further comprises the following steps: The foreign matter detection sensors are arranged in multiple groups on the circumferential side of the bearing to generate multiple groups of resistance values; An average value of the resistance values ​​is calculated, and if the average value is greater than a preset reference maintenance value, a fan maintenance prompt is issued.

[0023] By adopting the above technical solution, compared with single-point detection, the wear debris diffusion path around the bearing can be covered, especially capturing local abnormal wear caused by installation deviation or uneven load, thereby improving the accuracy of detection.

[0024] In a second aspect, the present application provides a drive component status detection system for a DC four-channel clean air conditioning unit, which adopts the following technical solution: A drive component status detection system for a DC four-channel clean air-conditioning unit comprises a processor, wherein the processor executes the steps of any one of the above-mentioned drive component status detection methods for a DC four-channel clean air-conditioning unit.

[0025] To summarize, the present application includes at least one of the following beneficial technical effects: through multi-speed vibration spectrum analysis, dynamic threshold adjustment, resonance waveform matching and multi-sensor collaborative monitoring technologies, accurate detection and early warning of mechanical faults such as bearing wear and rotor imbalance and electrical faults such as frequency conversion control abnormalities can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The present invention is a step diagram of a method for detecting the status of driving components of a DC four-channel clean air conditioning unit.

[0027] Figure 2 It is a diagram of the steps for adjusting the reference similarity value based on the positive correlation of the mean difference.

[0028] Figure 3 This is a step of providing a resonance warning prompt when the rotation speed data corresponding to the first waveform data and the rotation speed data corresponding to the second waveform data have no overlapping intervals.

[0029] Figure 4 This is a step of providing a resonance warning prompt when the rotation speed data corresponding to the first waveform data and the rotation speed data corresponding to the second waveform data have an overlapping section. DETAILED DESCRIPTION

[0030] Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings.

[0031] Throughout this specification, reference to the terms "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0032] The present application embodiment discloses a method for detecting the state of a driving component of a DC four-channel clean air conditioning unit, referring to Figure 1 , including the following steps: The drive component, which is a motor, is controlled by a frequency conversion controller based on the acquired first frequency conversion signal until the speed of the drive component stabilizes. A first vibration sensor disposed on the drive component acquires first vibration data, primarily based on motor vibration and supplemented by ambient vibration. A second vibration sensor disposed within a set distance from the drive component acquires second vibration data, primarily based on ambient vibration and supplemented by motor vibration.

[0033] The drive component is controlled via a frequency conversion controller based on the acquired second frequency conversion signal until the speed of the drive component stabilizes and the amplitude of the speed change is greater than a preset reference amplitude. Third vibration data is acquired based on the first vibration sensor, with the third vibration data primarily based on motor vibration and supplemented by environmental vibration. Fourth vibration data is acquired based on the second vibration sensor, with the fourth vibration data primarily based on environmental vibration and supplemented by motor vibration. The first and second frequency conversion signals have different frequencies, i.e., they control different speeds of the motor.

[0034] The first vibration data, the second vibration data, the third vibration data, and the fourth vibration data are spectrum-converted by using a fast Fourier transform to obtain corresponding first spectrum data, second spectrum data, third spectrum data, and fourth spectrum data.

[0035] The first spectrum data is filtered and calculated based on the second spectrum data to obtain first component data, wherein the first component data is data with motor vibration as the main component under the first variable frequency signal. The third spectrum data is filtered and calculated based on the fourth spectrum data to obtain second component data, wherein the second component data is data with motor vibration as the main component under the third variable frequency signal.

[0036] The first component, overlapping component, and second component are calculated based on the first and second component data. The overlapping component is the component whose frequency band and energy similarity between the first and second component data exceeds a preset reference similarity value. The curve of the first and second component data is an energy curve with frequency as the horizontal axis and energy as the vertical axis. The overlapping component reflects the degree of similarity in frequency band and energy between the first and second component data. Essentially, it identifies common characteristics of equipment vibration under two different operating conditions (different variable frequency signals). On the spectrum graph, these common characteristics appear as overlapping portions of the energy curve. After frequency band alignment, the energy values ​​of the first and second component data at each frequency point are calculated. The total energy of the overlapping component is obtained by integrating the frequency points of the overlapping portion.

[0037] This component typically contains common characteristics of normal equipment operation, but during a fault, the energy surges abnormally; that is, there is fault noise, and most of the energy is included in the overlap component. The first component is the component in the first component data whose frequency differs from the overlap component's frequency; the second component is the component in the second component data whose frequency differs from the overlap component's frequency.

[0038] The temporary component is calculated by adding the first and second components. The temporary ratio of the overlapping component to the temporary component is then calculated. If the temporary ratio is greater than a preset reference ratio, such as 1.2, an abnormality is detected and a drive component status warning is issued. This ratio reflects the proportion of energy characteristic of the fault. For example, when bearing wear increases, the high-frequency noise energy generated by friction in the overlapping component will increase significantly, causing the ratio to rise above the warning threshold.

[0039] By controlling the motor's operation at different speeds, the vibration response characteristics of the equipment under different operating conditions can be determined. Vibration data at different speeds contains a wealth of fault information. For example, early bearing wear manifests as a weak vibration signal of a specific frequency at low speeds, while motor rotor imbalance triggers significant periodic vibration characteristics at high speeds. By jointly comparing and analyzing the vibration spectrum characteristics under multiple speed conditions, comprehensive detection of mechanical faults (including bearing wear, rotor imbalance, etc.) and electrical faults (such as abnormal variable frequency control) in rotating components can be achieved. Furthermore, by monitoring motor speed, speed response characteristics, and bearing wear status, a motor life analysis and prediction model can be constructed to provide early warning of equipment failures and preventive maintenance.

[0040] In the step of filtering and calculating the first spectrum data according to the second spectrum data to obtain the first component data; and filtering and calculating the third spectrum data according to the fourth spectrum data to obtain the second component data, the filtering and calculating method includes the following steps: Adopting the filtering principle of dual sensor data collaboration: The first vibration sensor is mounted closely to the drive component, collecting vibration signals that include both the device's own operating vibrations and environmental interference. The second vibration sensor, positioned at a set distance to the component, collects signals primarily from ambient vibrations. After performing spectrum conversion on the data collected by both sensor sets, the first spectrum data F1(f) can be expressed as F1(f) = V(f) + E(f), representing the superposition of the drive component's vibration spectrum V(f) and the ambient vibration spectrum E(f). The second spectrum data F2(f) is approximately equal to the ambient vibration spectrum E(f).

[0041] By performing the subtraction operation of F1(f)-F2(f), the common component of the environmental vibration can be theoretically eliminated, that is, F1(f)-F2(f)=[V(f)+E(f)]-E(f)=V(f). Similarly, the third and fourth spectrum data are processed in a similar manner, and the vibration characteristics of the driving component under another speed condition can be effectively extracted.

[0042] In actual operation, due to the influence of factors such as sensor measurement error, environmental noise fluctuation, etc., the result of F1(f)-F2(f) may be negative. If these negative values are retained, it will cause the first component data calculated to mix false environmental signal components, which will interfere with subsequent fault diagnosis. The data with negative difference is set to zero to ensure that the final retained data mainly contains positive driving component vibration characteristics.

[0043] Reference Figure 2 In order to realize the dynamic optimization of the fault diagnosis threshold, the method further includes the following steps: Based on the first variable frequency signal, after the speed of the driving component is stable, the first speed data v1 is obtained based on the speed sensor.

[0044] Based on the second variable frequency signal, after the speed of the driving component is stable, the second speed data v2 is obtained based on the speed sensor.

[0045] The speed difference Δv=|v1-v2| of the first speed data and the second speed data is calculated, and the reference ratio R is adjusted according to the speed difference Δv; R=R0-k1×R0×Δv, wherein R0 is the initial reference ratio, k1 is the adjustment coefficient, and the unit is s / m.

[0046] The average speed V1=(v1+v2) / 2 of the first speed data and the second speed data is calculated, and the average difference ΔV=|V1-V2| between the average speed V1 and the preset average reference value V2 is calculated, and the reference similarity S is adjusted according to the average difference ΔV; S=S0+k2×S0×ΔV, wherein S0 is the initial reference similarity; k2 is the adjustment coefficient, and the unit is s / m.

[0047] The dynamic changes of the speed difference and the average difference intuitively map the running condition and potential risk of the driving component. Among them, the speed difference is a key indicator to measure the condition fluctuation. The greater the difference, the more unstable the device running state, such as frequent start-stop, load mutation, etc. Such drastic changes can significantly increase the probability of failure. Therefore, by reducing the reference ratio of triggering an alarm, the system can capture abnormal vibration with higher sensitivity and timely warn potential faults.

[0048] The average difference value is used to represent the overall rotation speed level of the equipment. When the average difference value is small, the equipment is in a low-speed operation state, at which time the vibration energy distribution is relatively dispersed, the fault features and the environmental interference signals are less overlapped in the frequency spectrum, and the down-regulation of the reference similarity value helps to identify weak fault signals and prevent missed detection. When the average difference value is large, i.e., the equipment is in high-speed operation, the vibration energy is highly concentrated, and the normal vibration and the fault signals are extremely likely to be overlapped in the frequency spectrum, at which time the up-regulation of the reference similarity value can effectively distinguish the normal fluctuation from the fault features and avoid misjudgment, thereby achieving accurate diagnosis.

[0049] Referring to Figure 3 , in order to be able to find problems in the early stage of the resonance risk of the equipment, the method further includes the following steps: In the gradual process of the driving component from the idle speed to the first rotation speed data (such as 70% of the rated speed), the time-domain waveform of the first vibration sensor is recorded by high-frequency sampling to obtain first waveform data, with the abscissa being the rotation speed and the ordinate being the vibration data. In the gradual process of the driving component gradually increasing to the second rotation speed data (such as 120% of the rated speed), the time-domain waveform of the first vibration sensor is recorded by high-frequency sampling to obtain second waveform data, with the abscissa being the rotation speed and the ordinate being the vibration data. This process covers dynamic working conditions such as starting, speed-up, and speed-down of the equipment, and can capture the unique vibration mutation characteristics near the critical speed compared with the steady-state data acquisition.

[0050] If there is no repeated interval between the rotation speed data corresponding to the first waveform data and the rotation speed data corresponding to the second waveform data, the resonance risk of the equipment in the whole operating range is covered. Then, the first waveform data is matched according to the preset first resonance waveform template, and the waveform similarity is calculated by using the improved DTW algorithm to obtain a first matching value. Then, the second waveform data is matched according to the preset first resonance waveform template, and the waveform similarity is calculated by using the improved DTW algorithm to obtain a second matching value. The first resonance waveform template library is established based on historical fault data and simulation analysis, and contains time-domain waveform characteristics of typical resonance faults.

[0051] The final matching value is calculated by using the weighted average method according to the first matching value and the second matching value. If the final matching value is greater than a preset reference matching value, such as 0.85, a resonance early warning is prompted.

[0052] When the rotation speed of the driving component gradually changes to two non-repeated intervals, the vibration waveform is recorded and matched with the preset resonance template, the matching value is calculated by weighting, and the resonance early warning is triggered if the threshold value is exceeded, thereby realizing early risk identification.

[0053] Referring to Figure 4 , in order to be able to find problems in the early stage of the resonance risk of the equipment, in other embodiments, the method further includes the following steps: When there is a repeated interval (e.g., 1000-1200 rpm) in the first and second rotational speed data gradual change process, and the interval length exceeds the reference threshold (e.g., 10% of the rated rotational speed), a 20 kHz high-frequency sampling is used to record the vibration waveform. This interval usually covers the vicinity of the critical speed of the equipment, at which time a small rotational speed fluctuation can cause significant vibration distortion.

[0054] The first waveform data is matched according to the preset second resonance waveform template using the improved dynamic time warping (DTW) algorithm, and the rotational speed with the highest matching value is the first matching rotational speed, i.e., searching for the rotational speed point with the highest matching value in the repeated interval.

[0055] The second waveform data is matched according to the second resonance waveform template using the improved dynamic time warping (DTW) algorithm, and the rotational speed with the highest matching value is the second matching rotational speed, i.e., searching for the rotational speed point with the highest matching value in the repeated interval.

[0056] The difference between the first matching rotational speed and the second matching rotational speed is calculated as the rotational speed difference, rotational speed difference = |first matching rotational speed-second matching rotational speed|; If the rotational speed difference is less than the preset matching difference (e.g., 5 rpm), a resonance warning is prompted.

[0057] In the overlapping interval of the rotational speed change of the driving component, the system performs dynamic matching on the vibration data through the preset second resonance waveform template, accurately identifies the unique waveform distortion characteristics such as amplitude mutation and frequency locking phenomenon when the equipment approaches or is in the critical resonance state. By calculating the difference between the rotational speed points with the highest matching values in the two rotational speed scanning stages, when the difference is less than the preset threshold, the early warning mechanism is automatically triggered.

[0058] In order to capture metal debris, peeling and other foreign matters generated by bearing wear, the method further includes the following steps: A pair of sensors is arranged below the bearing, and the pair of sensors includes at least one group of emitting tubes and receiving tubes arranged in pairs. For example, 8 groups of pair of sensors are arranged in a ring symmetrically 15-20 mm below the bearing seat, forming a monitoring area with an inner diameter of φ80 mm and an outer diameter of φ120 mm. Each group of sensors uses a 940 nm infrared emitting tube (divergence angle 15°) and a PIN photosensitive receiving tube, and the detection range covers 360° in the circumferential direction of the bearing and ±5 mm in the axial direction.

[0059] The pair of sensors acquires a pair of signals; when the pair of signals is a group, the system needs to verify the authenticity of the signal first: If the signal strength is stable and there is no foreign matter blocking feature such as amplitude drop, it indicates that there is no obvious wear debris in the current monitoring area. If the signal is identified as "with foreign matter" after smoothing filtering, a single-channel early warning is triggered, and a wear early warning is prompted.

[0060] Through-beam sensors utilize the principle of signal transmission between a transmitting and receiving tube to sensitively monitor foreign matter such as metal debris and flakes generated by bearing wear. When foreign matter obstructs the through-beam signal, the system uses smoothing and filtering to identify abnormal signals, triggering an early warning before bearing performance significantly degrades, enabling early detection of wear faults.

[0061] The method further comprises the steps of: If there are multiple sets of incoming signals, they are converted into wear values, which are then smoothed and filtered. If the wear value exceeds a preset wear reference value, a wear warning is issued. When metal debris passes through, the multiple sensors generate time-series signals in the order of obstruction. Using pulse-width modulation (PWM) technology, the signal strength is converted into an 8-bit binary wear value (0-255), where 0 represents no obstruction and a signal strength of 100%; 255 represents complete obstruction and a signal strength of 0%. For example, if the wear reference value is 128, a wear warning is issued if the wear value exceeds 128.

[0062] Calculate the wear difference ΔW between the wear value and the wear reference value. Based on the inverse correlation between the wear difference, adjust the speeds corresponding to the first and second frequency conversion signals. The greater the wear difference, the lower the speeds corresponding to the first and second frequency conversion signals. Conversely, the smaller the wear difference, the higher the speeds corresponding to the first and second frequency conversion signals. Use a basic linear relationship to fit the inverse proportional relationship between speed and wear difference: fi = fi0 - k × ΔW, where fi is the speed corresponding to the adjusted frequency conversion signal (Hz), i = 1 for the first frequency conversion signal, and i = 2 for the second frequency conversion signal. fi0 is the initial speed (e.g., 50 Hz corresponding to the rated speed of the equipment). ΔW is the wear difference, and k is the adjustment factor (unit: Hz / wear value). This adjustment factor must be calibrated experimentally. For example, k = 0.1 means the speed decreases by 0.1 Hz for every additional wear unit. Changing the frequency signal changes the speed corresponding to the frequency conversion signal.

[0063] The system collects multiple signals in real time through a beamforming sensor array, converting them into quantified wear data. A smoothing filter algorithm effectively eliminates noise interference, allowing for precise assessment of bearing wear. A mechanism is established to regulate the wear differential against the drive speed: when wear is detected to be increasing and the wear differential exceeds a preset threshold, the system automatically reduces the equipment's operating speed, alleviating bearing friction and suppressing the generation of metal debris. Once wear is within a controllable range, the equipment resumes normal speed operation.

[0064] In order to monitor the intrusion of foreign matter and the wear state of the bearing area, the method further includes the following steps: A foreign object detection sensor is installed next to the bearing. It consists of two parallel detection plates connected to a detection circuit. Two silver-plated metal detection plates, measuring 50mm x 20mm x 0.5mm, are placed parallel to the side of the bearing seat 10-15mm apart, with a spacing of 3mm. The planes of the detection plates are parallel to the bearing's rotational axis, ensuring that the centrifugal force generated by the bearing's rotation effectively flings wear debris or foreign matter into the detection area.

[0065] A detection circuit is used to measure the impedance change between the two detection pieces in real time.

[0066] An LC low-pass filter (cut-off frequency 5kHz) is connected to the front end of the detection circuit to suppress the electromagnetic interference and high-frequency noise of the motor.

[0067] The double exponential smoothing method is used to smooth the resistance value.

[0068] If the resistance value is less than the preset first reference resistance value, such as 500Ω, it corresponds to the intrusion of a metal foreign object with a diameter ≥ 0.2mm. This foreign object may cause the bearing to become stuck, and a foreign object prompt will be issued.

[0069] Otherwise, if the resistance value is less than the preset second reference resistance value, such as 800Ω, the corresponding bearing surface will have 0.1mm level peeling, and continuous wear will cause the clearance to increase, then a wear warning prompt will be issued; wherein, the second reference resistance value is greater than the first reference resistance.

[0070] Parallel plate resistance sensors monitor the bearing area for foreign matter and wear in real time. When conductive particles, such as metal debris, enter the gap between the two parallel detection plates, they alter the resistance characteristics between the plates. The system dynamically analyzes resistance changes to implement a two-level early warning mechanism. When the resistance drops sharply and falls below the first threshold, it indicates foreign matter intrusion, triggering an emergency alarm. When the resistance remains below the second, higher threshold but above the first, it indicates increased internal bearing wear, prompting preventive maintenance.

[0071] In other embodiments, multiple sets of foreign object detection sensors are located around the bearing, generating multiple sets of resistance values. Eight sets of parallel detection sensors are evenly distributed throughout the 360° circumference of the bearing seat (with each set spaced 45° apart). Each set of sensors is parallel to the bearing axis and 10-15 mm from the bearing outer ring.

[0072] Calculate the average value of the resistance value. If the average value is greater than the preset reference maintenance value, a fan maintenance prompt will be issued; the reference maintenance value is, for example, 1000Ω.

[0073] Compared with single-point detection, it can cover the wear debris diffusion path around the bearing, especially capture local abnormal wear caused by installation deviation or uneven load, and improve detection accuracy.

[0074] In order to more accurately judge the operating status of the fan, the reference maintenance value is dynamically set: The reference maintenance value, Rref, is adaptively adjusted based on the equipment's operating time: Rref = R0 × (1 + a × t); where R0 is the initial reference value (e.g., 1000Ω), t is the cumulative operating time (in years), and a is the aging factor (ranging from 0.05 to 0.1). For example, after two years of operation, Rref automatically increases to 1100-1200Ω to accommodate the decreasing resistance caused by natural bearing wear.

[0075] An embodiment of the present application further discloses a drive component status detection system for a DC four-channel clean air-conditioning unit, comprising a processor, wherein the processor executes the steps of the drive component status detection method for a DC four-channel clean air-conditioning unit as described in any one of the above.

[0076] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for detecting the state of a driving component of a DC four-channel clean air conditioning unit, characterized in that: The steps include: controlling the driving component according to the acquired first frequency conversion signal until the speed of the driving component stabilizes; acquiring first vibration data based on a first vibration sensor disposed on the driving component, and acquiring second vibration data based on a second vibration sensor disposed within a set distance from the driving component; controlling the driving component according to the acquired second frequency conversion signal until the speed of the driving component stabilizes and the amplitude of the speed change is greater than a preset reference amplitude; acquiring third vibration data based on the first vibration sensor, and acquiring fourth vibration data based on the second vibration sensor; performing spectrum conversion on the first vibration data, the second vibration data, the third vibration data, and the fourth vibration data to obtain first spectrum data, second spectrum data, third spectrum data, and fourth spectrum data; Filtering and calculating the first spectrum data according to the second spectrum data to obtain first component data; filtering and calculating the third spectrum data according to the fourth spectrum data to obtain second component data; A first component, an overlapping component, and a second component are calculated based on the first component data and the second component data, wherein the overlapping component is a component whose frequency band and energy similarity between the first component data and the second component data is greater than a preset reference similarity value, the first component is a component in the first component data having a frequency different from that of the overlapping component, and the second component is a component in the second component data having a frequency different from that of the overlapping component. A temporary component is calculated based on the first component and the second component, and a temporary ratio of the overlapping component to the temporary component is calculated. If the temporary ratio is greater than a preset reference ratio, a driving component status warning is issued.

2. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that: In the step of filtering and calculating the first spectrum data according to the second spectrum data to obtain the first component data; and filtering and calculating the third spectrum data according to the fourth spectrum data to obtain the second component data, the filtering and calculating method includes the following steps: Subtract the second spectrum data from the first spectrum data, and convert the negative value after the subtraction to zero; The fourth spectrum data is subtracted from the third spectrum data, and a negative value after the subtraction is converted to zero.

3. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that: The method further comprises the steps of: Based on the first frequency conversion signal, after the speed of the driving component is stabilized, obtaining first speed data based on a speed sensor; Based on the second frequency conversion signal, after the speed of the driving component is stabilized, obtaining second speed data based on the speed sensor; calculating a speed difference between the first speed data and the second speed data, and adjusting the reference ratio according to an anti-correlation of the speed difference; An average speed value of the first speed data and the second speed data is calculated, an average difference between the average speed value and a preset average reference value is calculated, and the reference similarity value is adjusted according to a positive correlation of the average difference.

4. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 3, characterized in that: The method further comprises the steps of: During the process in which the rotation speed of the driving component gradually changes to the first rotation speed data; recording the data of the first vibration sensor to obtain first waveform data; During the process of the driving component speed gradually changing to the second speed data; recording the data of the first vibration sensor to obtain second waveform data; If the speed data corresponding to the first waveform data and the speed data corresponding to the second waveform data have no overlapping intervals, matching the first waveform data according to a preset first resonance waveform template to obtain a first matching value; then matching the second waveform data according to the preset first resonance waveform template to obtain a second matching value; A final matching value is calculated based on the first matching value and the second matching value. If the final matching value is greater than a preset reference matching value, a resonance warning prompt is issued.

5. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 3, characterized in that: The method further comprises the steps of: During the process in which the rotation speed of the driving component gradually changes to the first rotation speed data; recording the data of the first vibration sensor to obtain first waveform data; During the process of the driving component speed gradually changing to the second speed data; recording the data of the first vibration sensor to obtain second waveform data; If the speed data corresponding to the first waveform data and the speed data corresponding to the second waveform data have a repeated interval, and the length of the repeated interval is greater than the preset reference interval length, then, the first waveform data is matched according to the preset second resonance waveform template, and the speed with the highest matching value is the first matching speed, and the second waveform data is matched according to the second resonance waveform template, and the speed with the highest matching value is the second matching speed; If the difference between the first matching rotational speed and the second matching rotational speed is smaller than a preset matching difference, a resonance warning prompt is issued.

6. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that: The method further comprises the steps of: A beam sensor is provided below the bearing, wherein the beam sensor comprises at least one set of a transmitting tube and a receiving tube arranged in a beam-to-be-beam manner; Acquiring a radio signal from the radio sensor; If the radio signals are a group and the content of the radio signals is smoothed and filtered, if the content indicates that there is a foreign object, a wear warning prompt is issued.

7. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 6, characterized in that: The method further comprises the steps of: If there are multiple groups of radio signals, the multiple groups of radio signals are converted into wear values, and the wear values ​​are smoothed and filtered. If the wear values ​​are greater than a preset wear reference value, a wear warning prompt is issued; A wear difference between the wear value and the wear reference value is calculated, and a rotational speed corresponding to the first frequency conversion signal and a rotational speed corresponding to the second frequency conversion signal are adjusted in anti-correlation according to the wear difference.

8. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that: The method further comprises the steps of: A foreign body detection sensor is provided next to the bearing, the foreign body detection sensor comprising two parallel detection pieces connected to a detection circuit, and the rotation axis of the driving component is parallel to the plane where the detection pieces are located; Obtaining the resistance value between the two detection sheets; Control the fan speed to a speed with vibration and perform physical filtering on the resistance value; performing smoothing filtering on the resistance value; If the resistance value is less than a preset first reference resistance value, a foreign object prompt is issued; Otherwise, if the resistance value is less than a preset second reference resistance value, a wear warning prompt is issued; wherein the second reference resistance value is greater than the first reference resistance.

9. The method for detecting the state of driving components of a DC four-channel clean air conditioning unit according to claim 8, characterized in that: The method further comprises the steps of: The foreign matter detection sensors are arranged in multiple groups on the circumferential side of the bearing to generate multiple groups of resistance values; An average value of the resistance values ​​is calculated, and if the average value is greater than a preset reference maintenance value, a fan maintenance prompt is issued.

10. A drive component status detection system for a DC four-channel clean air conditioning unit, characterized in that: The method comprises a processor, wherein the processor executes the steps of the method for detecting the state of a driving component of a DC four-channel clean air-conditioning unit according to any one of claims 1 to 9.

Images