Method and system for detecting the state of driving components of a dc four-channel clean air conditioning unit

Abstract

The application relates to the technical field of clean air conditioning units, and discloses a driving component state detection method and system of a direct-current four-channel clean air conditioning unit. The method obtains vibration data at different rotating speeds by controlling the driving component to operate under different frequency conversion signals, using a first vibration sensor arranged on the driving component and a second vibration sensor arranged within a set distance from the first vibration sensor. The vibration data is subjected to frequency spectrum conversion to obtain corresponding frequency spectrum data, and first component data and second component data are obtained through filtering calculation. The first component data and the second component data are used to calculate a first component, an overlapping component and a second component. A temporary component is calculated according to the first component and the second component, and if a temporary ratio of the overlapping component to the temporary component is greater than a preset reference ratio, a driving component state early warning is performed. The application realizes driving component state detection and early warning by actively collecting and performing frequency spectrum analysis on the multi-rotating speed vibration data of the clean air conditioning unit.

Description

Technical Field

[0001] This application relates to the technical field of cleanroom air conditioning units, and in particular to a method and system for detecting the status of drive components of a DC four-channel cleanroom air conditioning unit. Background Technology

[0002] The DC four-channel cleanroom air conditioning unit is an air handling device specifically designed for environments with extremely high requirements for air cleanliness, temperature, and humidity. It is widely used in cleanrooms in electronics manufacturing, biopharmaceuticals, and food processing. The unit is equipped with multiple rotating drive components such as fans and compressors. By precisely controlling the airflow and direction of four independent channels, it achieves efficient filtration of indoor air, temperature and humidity regulation, and optimized airflow organization, providing a stable clean air guarantee for the production environment.

[0003] As the service life of a DC four-channel cleanroom air conditioning unit increases, the rotary drive components inevitably age. Due to a lack of effective monitoring methods, these components are difficult to detect in a timely manner when they experience early wear, poor lubrication, or performance degradation. Often, maintenance personnel only discover and replace the components when they fail, causing unit shutdown, abnormal air parameters, or even affecting the cleanliness of the production environment. This not only increases maintenance costs but may also cause production interruptions and economic losses.

[0004] Currently, the industry relies heavily on manual inspections or reactive maintenance after a failure for the condition monitoring of the rotary drive components of DC four-channel cleanroom air conditioning units. There is an urgent need for a method to proactively monitor the working status of the rotary drive components. Summary of the Invention

[0005] In order to actively detect the working status of the rotary drive components of a DC four-channel cleanroom air conditioning unit, this application provides a method and system for detecting the status of the drive components of a DC four-channel cleanroom air conditioning unit.

[0006] In a first aspect, this application provides a method for detecting the status of drive components in a DC four-channel clean air conditioning unit, employing the following technical solution:

[0007] A method for detecting the status of drive components in a DC four-channel cleanroom air conditioning unit includes the following steps:

[0008] The drive component is controlled according to the first frequency conversion signal until the speed of the drive component stabilizes; first vibration data is obtained based on the first vibration sensor installed on the drive component, and second vibration data is obtained based on the second vibration sensor installed within a set distance range next to the drive component.

[0009] The drive component is controlled according to the acquired second frequency conversion signal until the speed of the drive component stabilizes, and the magnitude of the speed change is greater than the preset reference magnitude; third vibration data is acquired based on the first vibration sensor, and fourth vibration data is acquired based on the second vibration sensor;

[0010] The first vibration data, the second vibration data, the third vibration data, and the fourth vibration data are subjected to spectral conversion to obtain first spectral data, second spectral data, third spectral data, and fourth spectral data;

[0011] First component data is obtained by filtering and calculating the first spectrum data based on the second spectrum data; second component data is obtained by filtering and calculating the third spectrum data based on the fourth spectrum data.

[0012] A first component, an overlapping component, and a second component are calculated based on the first component data and the second component data. The overlapping component is the 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 the component in the first component data whose frequency is different from the frequency of the overlapping component. The second component is the component in the second component data whose frequency is different from the frequency of the overlapping component.

[0013] A temporary component is calculated based on the first component and the second component. The temporary ratio of the overlapping component and the temporary component is calculated. If the temporary ratio is greater than a preset reference ratio, a drive component status warning is issued.

[0014] By employing the above technical solution, the vibration response characteristics of the equipment under various operating conditions are stimulated by actively controlling the operation of the drive components at different speeds, such as normal speed and speeds deviating from the rated value. Vibration data at different speeds contains rich fault information: for example, early bearing wear manifests as weak vibrations at specific frequencies at low speeds, while rotor imbalance in the motor causes significant periodic vibrations at high speeds. By jointly comparing the spectral characteristics at multiple speeds, comprehensive detection of mechanical faults (such as bearing wear and rotor imbalance) and electrical faults (such as abnormal frequency converter control) in rotating components can be achieved. By detecting the motor's speed, speed response, and bearing wear, the motor's lifespan can be analyzed and predicted, allowing for proactive maintenance.

[0015] Optionally, in the step of filtering and calculating the first spectrum data based on the second spectrum data to obtain the first component data, and filtering and calculating the third spectrum data based on the fourth spectrum data to obtain the second component data, the filtering and calculation method includes the following steps:

[0016] Subtract the second spectrum data from the first spectrum data, and change the negative value after the subtraction to zero;

[0017] Subtract the fourth spectrum data from the third spectrum data, and change the negative value of the subtraction to zero.

[0018] By employing the above technical solution, the common components of environmental vibration in the frequency spectrum can be canceled out through subtraction. Data with negative differences are set to zero to avoid reverse interference from environmental signals, ensuring that the remaining data primarily reflects the vibration characteristics of the driving components.

[0019] Optionally, the method further includes the following steps:

[0020] Based on the first frequency conversion signal, after the speed of the drive component stabilizes, the first speed data is acquired based on the speed sensor;

[0021] Based on the second frequency conversion signal, after the speed of the drive component stabilizes, the second speed data is acquired based on the speed sensor;

[0022] Calculate the speed difference between the first speed data and the second speed data, and adjust the reference ratio based on the inverse correlation of the speed difference;

[0023] Calculate the average speed of the first speed data and the second speed data, calculate the average difference between the average speed data and the preset average reference value, and adjust the reference similarity value according to the positive correlation of the average difference.

[0024] By adopting the above technical solutions, the speed difference reflects the degree of fluctuation in the operating state of the drive components. The larger the difference, the more drastic the changes in operating conditions and the higher the potential risk of failure. Therefore, it is necessary to reduce the reference ratio for triggering alarms 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 operating state, the vibration energy is dispersed, and the overlapping frequency bands of 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 leads to concentrated vibration energy, and normal vibration and fault signals are prone to spectral overlap. Therefore, it is necessary to raise the reference similarity value to avoid misjudging normal fluctuations as faults and to achieve accurate diagnosis.

[0025] Optionally, the method further includes the following steps:

[0026] As the rotational speed of the driving component gradually changes to the first rotational speed data, the data from the first vibration sensor is recorded to obtain the first waveform data.

[0027] As the rotational speed of the driving component gradually changes to the second rotational speed data, the data from the first vibration sensor is recorded to obtain the second waveform data.

[0028] If the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data have no overlapping intervals, then the first waveform data is matched according to the preset first resonance waveform template to obtain a first matching value; then the second waveform data is matched according to the preset first resonance waveform template to obtain a second matching value.

[0029] The final matching value is calculated based on the first matching value and the second matching value. If the final matching value is greater than the preset reference matching value, a resonance warning is issued.

[0030] By adopting the above technical solution, vibration waveform data is recorded when the rotation speed of the drive component changes gradually. In the case of non-repeating intervals of different rotation speeds, shape matching is performed using a preset resonance waveform template, and the matching value is calculated by weighted average. If the final matching value exceeds the preset reference value, a resonance warning is triggered.

[0031] Optionally, the method further includes the following steps:

[0032] As the rotational speed of the driving component gradually changes to the first rotational speed data, the data from the first vibration sensor is recorded to obtain the first waveform data.

[0033] As the rotational speed of the driving component gradually changes to the second rotational speed data, the data from the first vibration sensor is recorded to obtain the second waveform data.

[0034] If the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data have overlapping intervals, and the length of the overlapping interval is greater than the length of the preset reference interval, then the first waveform data is matched according to the preset second resonance waveform template, and the rotational speed with the highest matching value is the first matching rotational speed; the second waveform data is matched according to the second resonance waveform template, and the rotational speed with the highest matching value is the second matching rotational speed.

[0035] If the difference between the first matching speed and the second matching speed is less than a preset matching difference, a resonance warning will be issued.

[0036] By adopting the above technical solution, within the repetitive range of speed variation, the vibration waveform data is matched using a preset second resonance waveform template, which can accurately capture the unique waveform distortion characteristics when the equipment approaches or enters a resonance state. By comparing the speeds with the highest matching values ​​in the two stages, an early warning is triggered when the difference is less than a threshold. This allows for timely intervention before a resonance fault occurs, effectively preventing serious accidents such as severe equipment vibration and component damage caused by resonance, and ensuring the stable operation of the cleanroom air conditioning unit.

[0037] Optionally, the method further includes the following steps:

[0038] A through-beam sensor is provided below the bearing, the through-beam sensor comprising at least one set of transmitting tubes and receiving tubes arranged in opposite directions;

[0039] Acquire the through-beam signal from the through-beam sensor;

[0040] If the transmitted signals are in a group, and the content of the transmitted signals is smoothed and filtered, if the content contains foreign objects, a wear warning will be issued.

[0041] By employing the above technical solution, the through-beam sensor, through the signal exchange between the transmitting and receiving tubes, can sensitively detect foreign objects such as metal debris and flaking particles generated by bearing wear. When foreign objects obstruct the through-beam signal, they are identified as abnormal after smoothing and filtering, thus triggering an early warning before a significant performance degradation of the bearing occurs.

[0042] Optionally, the method further includes the following steps:

[0043] If there are multiple sets of through-beam signals, the multiple sets of through-beam signals are converted into wear values, and the wear values ​​are smoothed and filtered. If the wear value is greater than the preset wear reference value, a wear warning is issued.

[0044] Calculate the wear difference between the wear value and the wear reference value, and adjust the speed corresponding to the first frequency converter signal and the speed corresponding to the second frequency converter signal according to the wear difference inverse correlation.

[0045] By employing the above technical solution, multiple sets of through-beam signals are converted into wear values. Signal fluctuations are eliminated through smoothing filtering, enabling the assessment of bearing wear conditions. Based on the inverse correlation of wear difference, the drive speed is adjusted. When wear intensifies, the equipment operating speed is automatically reduced to decrease bearing friction and debris generation, forming an adaptive protection mechanism.

[0046] Optionally, the method further includes the following steps:

[0047] A foreign object detection sensor is installed next to the bearing. The foreign object detection sensor includes two parallel detection plates, which are connected to a detection circuit. The rotation axis of the drive component is parallel to the plane where the detection plates are located.

[0048] Obtain the resistance value between the two detection plates;

[0049] The fan speed is controlled to a speed that causes vibration, and the resistance value is physically filtered.

[0050] The resistance value is then smoothed using a filtering process.

[0051] If the resistance value is less than the preset first reference resistance value, a foreign object warning will be issued;

[0052] Otherwise, if the resistance value is less than the preset second reference resistance value, a wear warning will be issued; wherein the second reference resistance value is greater than the first reference resistance.

[0053] By employing the above technical solution, a sensor composed of two parallel detection plates is used to detect foreign objects 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 value drops, triggering different levels of warnings: a drop below the first reference resistance value indicates foreign object intrusion, while a drop below the higher second reference resistance value indicates severe bearing wear.

[0054] Optionally, the method further includes the following steps:

[0055] Multiple sets of the foreign object detection sensors are located on the circumference of the bearing, generating multiple sets of the resistance values;

[0056] Calculate the average value of the resistance. If the average value is greater than the preset reference maintenance value, then issue a fan maintenance reminder.

[0057] By adopting the above technical solution, compared with single-point detection, the wear debris diffusion path in the circumferential direction of the bearing can be covered, especially capturing local abnormal wear caused by installation deviation or uneven load, thus improving the accuracy of detection.

[0058] Secondly, this application provides a drive component status detection system for a DC four-channel clean air conditioning unit, employing the following technical solution:

[0059] A drive component status detection system for a DC four-channel cleanroom air conditioning unit includes a processor, wherein the processor executes the steps of the drive component status detection method for a DC four-channel cleanroom air conditioning unit as described in any one of the preceding claims.

[0060] In summary, this 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, it achieves accurate detection and early warning of mechanical faults such as bearing wear and rotor imbalance, as well as electrical faults such as frequency converter control abnormalities. Attached Figure Description

[0061] Figure 1 This is a step diagram of a method for detecting the status of drive components in a DC four-channel clean air conditioning unit.

[0062] Figure 2 This is a flowchart illustrating the steps for adjusting reference similarity values ​​based on the positive correlation of the average difference.

[0063] Figure 3 This refers to the steps for issuing a resonance warning when there is no overlap between the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data.

[0064] Figure 4 This refers to the steps for issuing a resonance warning when there is an overlap between the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data. Detailed Implementation

[0065] The embodiments of this application are described in detail below, and examples of the embodiments are shown in the accompanying drawings.

[0066] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions 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 one or more embodiments or examples.

[0067] This application discloses a method for detecting the status of drive components in a DC four-channel cleanroom air conditioning unit, referring to... Figure 1 It includes the following steps:

[0068] The first frequency conversion signal is used to control the drive component, which is a motor, via a frequency converter controller. Once the drive component's speed stabilizes, first vibration data is acquired using a first vibration sensor mounted on the drive component. This first vibration data primarily focuses on motor vibration, with environmental vibration as a secondary factor. Second vibration data is then acquired using a second vibration sensor positioned within a predetermined distance from the drive component. This second vibration data primarily focuses on environmental vibration, with motor vibration as a secondary factor.

[0069] The second frequency conversion signal is used to control the drive component via a frequency converter. Once the drive component's speed stabilizes, the speed change is greater than a preset reference range. Third vibration data is acquired based on the first vibration sensor, primarily focusing on motor vibration with secondary focus on environmental vibration. Fourth vibration data is acquired based on the second vibration sensor, primarily focusing on environmental vibration with secondary focus on motor vibration. The first and second frequency conversion signals are signals with different frequencies, meaning they control different motor speeds.

[0070] The first vibration data, the second vibration data, the third vibration data, and the fourth vibration data are transformed into their corresponding first spectrum data, second spectrum data, third spectrum data, and fourth spectrum data using Fast Fourier Transform.

[0071] The first component data is obtained by filtering and calculating the first spectrum data based on the second spectrum data. The first component data is data in which motor vibration is the main component under the first frequency conversion signal. The second component data is obtained by filtering and calculating the third spectrum data based on the fourth spectrum data. The second component data is data in which motor vibration is the main component under the third frequency conversion signal.

[0072] Based on the data from the first and second components, a first component, an overlapping component, and a second component are calculated. The overlapping component is the component where the frequency band and energy similarity between the first and second component data is greater than a preset reference similarity value. The curves of the first and second component data are energy curves with frequency on the x-axis and energy on the y-axis. The overlapping component reflects the degree of similarity in frequency band and energy between the first and second component data, essentially finding common characteristics of equipment vibration under two different operating conditions (different frequency conversion signals). On the spectrum diagram, these common characteristics are represented by the overlapping portion of the energy curves. After frequency band alignment, for each frequency point, the energy values ​​of the first and second component data at that frequency point are calculated. By integrating the frequency points of the overlapping portion, the total energy of the overlapping component is obtained.

[0073] This component typically contains common characteristics of normal equipment operation, but during a fault, there will be an abnormal surge in energy; that is, there is fault noise, and most of the energy will be included in the overlap component. The first component is the component in the first component data whose frequency differs from the frequency of the overlap component; the second component is the component in the second component data whose frequency differs from the frequency of the overlap component.

[0074] A 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 anomaly is detected, and a drive component status warning is issued. This ratio reflects the proportion of fault characteristic energy. For example, when bearing wear intensifies, the high-frequency noise energy generated by friction in the overlapping component will increase significantly, causing the ratio to rise above the warning threshold.

[0075] By controlling the motor to operate at different speeds, the vibration response characteristics of the equipment under various conditions can be observed. Vibration data at different speeds contain rich fault information. For example, early bearing wear manifests as weak vibration signals at specific frequencies at low speeds, while rotor imbalance causes significant periodic vibrations at high speeds. Through joint comparative analysis of vibration spectrum characteristics under multiple speed conditions, comprehensive detection of mechanical faults (including bearing wear and rotor imbalance) and electrical faults (such as abnormal frequency converter 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 enable early warning and preventative maintenance of equipment faults.

[0076] In the step of obtaining the first component data by filtering and calculating the first spectrum data based on the second spectrum data, and obtaining the second component data by filtering and calculating the third spectrum data based on the fourth spectrum data, the filtering and calculation method includes the following steps:

[0077] The filtering principle employs dual-sensor data collaboration:

[0078] The first vibration sensor is installed close to the drive component, and the vibration signal it collects includes the vibration of the equipment itself and environmental interference. The second vibration sensor is placed at a set distance to the side of the component, and its collected signal is mainly environmental vibration. After performing spectrum conversion on the data collected by the two sets of sensors, the first spectrum data F1(f) can be expressed as F1(f) = V(f) + E(f), that is, the superposition of the vibration spectrum V(f) of the drive component and the environmental vibration spectrum E(f); the second spectrum data F2(f) is approximately equal to the environmental vibration spectrum E(f).

[0079] By performing the subtraction operation F1(f)-F2(f), the common components of environmental vibration can theoretically be eliminated, i.e., F1(f)-F2(f)=[V(f)+E(f)]-E(f)=V(f). Similarly, by performing similar processing on the third and fourth spectrum data, the vibration characteristics of the drive component under another speed condition can be effectively extracted.

[0080] In actual calculations, due to factors such as sensor measurement errors and environmental noise fluctuations, the result of F1(f)-F2(f) may be negative. Retaining these negative values ​​would introduce false environmental signal components into the calculated first component data, interfering with subsequent fault diagnosis. Setting the negative difference data to zero ensures that the final retained data primarily contains positive vibration characteristics of the driving component.

[0081] Reference Figure 2 To achieve dynamic optimization of the fault diagnosis threshold, the method also includes the following steps:

[0082] Based on the first frequency conversion signal, after the speed of the drive component stabilizes, the first speed data v1 is obtained based on the speed sensor.

[0083] Based on the second frequency conversion signal, after the speed of the drive component stabilizes, the second speed data v2 is acquired based on the speed sensor.

[0084] Calculate the speed difference Δv = |v1-v2| between the first speed data and the second speed data. Adjust the reference ratio R according to the inverse correlation of the speed difference Δv; R = R0 - k1 × R0 × Δv, where R0 is the initial reference ratio, k1 is the adjustment coefficient, and the unit is s / m.

[0085] Calculate the average speed of the first speed data and the second speed data, V1 = (v1 + v2) / 2. Calculate the average difference between the average speed V1 and the preset average reference value V2, ΔV = |V1 - V2|. Adjust the reference similarity value S according to the positive correlation of the average difference ΔV; S = S0 + k2 × S0 × ΔV, where S0 is the initial reference similarity value and k2 is the adjustment coefficient in s / m.

[0086] The dynamic changes in the speed difference and the average speed difference directly reflect the operating conditions and potential risks of the drive components. The speed difference is a key indicator for measuring fluctuations in operating conditions; a larger difference indicates a more unstable operating state, such as frequent start-stop cycles or sudden load changes. Such drastic changes significantly increase the probability of failure. Therefore, by reducing the reference ratio for triggering alarms, the system can detect abnormal vibrations with higher sensitivity and provide timely warnings of potential faults.

[0087] The average difference is used to characterize the overall speed level of the equipment. When the average difference is small, the equipment is operating at low speed. At this time, the vibration energy distribution is relatively dispersed, and there is less overlap between fault characteristics and environmental interference signals in the spectrum. Lowering the reference similarity value helps to identify weak fault signals and prevent missed detections. However, when the average difference is large, that is, when the equipment is operating at high speed, the vibration energy is highly concentrated, and normal vibration and fault signals are very likely to overlap in the spectrum. In this case, raising the reference similarity value can effectively distinguish between normal fluctuations and fault characteristics, avoid misjudgment, and thus achieve accurate diagnosis.

[0088] Reference Figure 3 In order to detect problems in the early stages of equipment resonance risk, the method also includes the following steps:

[0089] During the gradual transition of the drive component from idle speed to a first speed (e.g., 70% of the rated speed), high-frequency sampling is used to continuously record the time-domain waveform of the first vibration sensor to obtain the first waveform data, with the horizontal axis representing speed and the vertical axis representing vibration data. During the gradual acceleration of the drive component to a second speed (e.g., 120% of the rated speed), high-frequency sampling is used to continuously record the time-domain waveform of the first vibration sensor to obtain the second waveform data, with the horizontal axis representing speed and the vertical axis representing vibration data. This process covers dynamic operating conditions such as equipment startup, acceleration, and deceleration. Compared to steady-state data acquisition, it can capture the unique vibration abrupt changes near the critical speed.

[0090] If the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data have no overlapping intervals, this covers the resonance risk across the entire operating range of the equipment. Then, the first waveform data is matched against a preset first resonance waveform template, and the waveform similarity is calculated using an improved DTW algorithm to obtain a first matching value. Similarly, the second waveform data is matched against the preset first resonance waveform template, and the waveform similarity is calculated using the improved DTW algorithm to obtain a second matching value. A first resonance waveform template library is established based on historical fault data and simulation analysis, containing the time-domain waveform characteristics of typical resonance faults.

[0091] The final matching value is calculated by weighted averaging the first and second matching values. If the final matching value is greater than the preset reference matching value, such as 0.85, a resonance warning is issued.

[0092] When the rotational speed of the drive component gradually changes to two non-repetitive intervals, the vibration waveform is recorded and matched with a preset resonance template. The matching value is calculated by weighting. If the value exceeds the threshold, a resonance warning is triggered to achieve early risk identification.

[0093] Reference Figure 4 In order to detect problems in the early stages of equipment resonance risk, in other embodiments, the method further includes the following steps:

[0094] When the drive component exhibits a repetitive interval (e.g., 1000-1200 rpm) during the gradual change between the first and second speed data, and the interval length exceeds a reference threshold (e.g., 10% of the rated speed), a 20kHz high-frequency sampling method is used to record the vibration waveform. This interval typically covers the vicinity of the equipment's critical speed, where even minor speed fluctuations can trigger significant vibration distortion.

[0095] An improved Dynamic Time Warping (DTW) algorithm is used to match the first waveform data according to a preset second resonance waveform template. The rotational speed with the highest matching value is the first matching rotational speed, that is, the rotational speed with the highest matching value is searched within the repetition interval.

[0096] An improved Dynamic Time Warping (DTW) algorithm is used to match the second waveform data based on the second resonance waveform template. The rotational speed with the highest matching value is the second matching rotational speed, that is, the rotational speed with the highest matching value is searched within the repetition interval.

[0097] The difference between the first matching speed and the second matching speed is calculated as the speed difference, where speed difference = |first matching speed - second matching speed|;

[0098] If the speed difference is less than the preset matching difference, such as 5 rpm, a resonance warning will be issued.

[0099] Within the overlapping range of the driving component's rotational speed changes, the system dynamically matches the vibration data using a preset second resonance waveform template, accurately identifying waveform distortion characteristics unique to the equipment when it approaches or reaches a critical resonance state, such as abrupt amplitude changes and frequency lock-in. By calculating the difference between the highest matching values ​​in the two rotational speed scanning phases, an early warning mechanism is automatically triggered when this difference is less than a preset threshold.

[0100] In order to capture foreign objects such as metal shavings and spalling generated by bearing wear, the method also includes the following steps:

[0101] A through-beam sensor is installed below the bearing. The through-beam sensor includes at least one set of transmitting and receiving tubes arranged in an opposite direction. For example, eight sets of through-beam sensors are symmetrically arranged in a ring 15-20mm below the bearing housing, forming a monitoring area with an inner diameter of φ80mm and an outer diameter of φ120mm. Each sensor set uses a 940nm infrared emitting tube (divergence angle 15°) and a PIN photosensitive receiving tube, with a detection range covering 360° circumferentially and ±5mm axially within the bearing.

[0102] Acquire the through-beam signal from the through-beam sensor; when the through-beam signal is a set, the system must first verify the authenticity of the signal:

[0103] If the signal strength is stable and there are no signs of obstruction by foreign objects, such as a sudden drop in amplitude, it indicates that there is no obvious wear and debris in the current monitoring area.

[0104] If the signal is identified as "foreign object" after smoothing and filtering, a single-channel warning will be triggered to provide a wear warning.

[0105] Through-beam sensors utilize the signal transmission principle between a transmitting and receiving tube to sensitively monitor foreign objects such as metal debris and spalling material generated by bearing wear. When foreign objects obstruct the through-beam signal, the system identifies the abnormal signal through smoothing and filtering, triggering an early warning before a significant decline in bearing performance, thus enabling early detection of wear failures.

[0106] The method also includes the following steps:

[0107] If there are multiple sets of through-beam signals, these signals are converted into wear values. These wear values ​​are then smoothed and filtered. If the wear value exceeds a preset wear reference value, a wear warning is issued. When metal debris passes by, multiple sensors generate time-series signals in the order of obstruction. Pulse width modulation (PWM) technology is used to convert the signal strength into an 8-bit binary wear value (0-255), where 0 represents no obstruction and a signal strength of 100%, and 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.

[0108] Calculate the wear difference ΔW between the wear value and the wear reference value. Adjust the speed corresponding to the first frequency converter signal and the speed corresponding to the second frequency converter signal based on the inverse correlation of the wear difference. The larger the wear difference, the smaller the speed corresponding to the first and second frequency converter signals; conversely, the smaller the wear difference, the larger the speed corresponding to the first and second frequency converter signals. A basic linear relationship is used to fit the inverse proportional relationship between the speed and the wear difference: fi = fi0 - k × ΔW; fi is the adjusted speed (Hz) corresponding to the frequency converter signal, i=1 represents the first frequency converter signal, i=2 represents the second frequency converter signal; fi0 is the initial speed (e.g., 50Hz corresponding to the equipment's rated speed); ΔW is the wear difference; k is the adjustment coefficient (unit: Hz / wear value), which needs to be calibrated experimentally. For example, k=0.1 means that for every 1 increase in wear unit, the speed decreases by 0.1Hz. Changing the frequency signal changes the speed corresponding to the frequency converter signal.

[0109] Multiple signals are collected in real time by a through-beam sensor array and converted into quantified wear value data. A smoothing filtering algorithm is used to effectively remove noise interference and accurately assess the degree of bearing wear. An inverse correlation adjustment mechanism between wear difference and drive speed is established: when wear is detected to be aggravated and the wear difference exceeds a preset threshold, the system automatically reduces the equipment operating speed to reduce bearing friction and suppress the generation of metal debris; when the wear is within a controllable range, the equipment resumes normal speed operation.

[0110] To monitor foreign object intrusion and wear conditions in the bearing area, the method also includes the following steps:

[0111] A foreign object detection sensor is installed next to the bearing. The sensor consists of two parallel detection plates connected to a detection circuit. Two silver-plated metal detection plates, each measuring 50mm × 20mm × 0.5mm, are arranged parallel to each other 10-15mm from the side of the bearing housing, with a spacing of 3mm. The plane of the detection plates is parallel to the bearing's rotation axis to ensure that the centrifugal force generated by the bearing's rotation can effectively throw wear debris or foreign objects into the detection area.

[0112] A detection circuit is used to measure the impedance change between the two detection plates in real time.

[0113] An LC low-pass filter (cutoff frequency 5kHz) is connected at the front end of the detection circuit to suppress electromagnetic interference and high-frequency noise from the motor.

[0114] The resistance value is smoothed using a double exponential smoothing method.

[0115] 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. Foreign objects of this size may cause bearing jamming, so a foreign object warning will be issued.

[0116] Otherwise, if the resistance value is less than the preset second reference resistance value, such as 800Ω, and 0.1mm-level peeling occurs on the bearing surface, continuous wear will lead to an increase in clearance, then a wear warning will be issued; wherein, the second reference resistance value is greater than the first reference resistance.

[0117] A parallel-plate resistance sensor is used to monitor the bearing area for foreign objects and wear in real time. When conductive particles, such as metal debris, enter the gap between the two parallel detection plates, they change the resistance characteristics between the plates. The system implements a two-level early warning mechanism by dynamically analyzing the resistance value changes: when the resistance value drops sharply and falls below the first threshold, it is determined that external foreign object intrusion has occurred, triggering an emergency alarm; when the resistance value remains below a higher second threshold but above the first threshold, it is identified as accelerated internal wear of the bearing, prompting preventive maintenance.

[0118] In other embodiments, multiple sets of foreign object detection sensors are arranged around the bearing to generate multiple sets of resistance values. Eight sets of parallel detection plates (each set spaced 45° apart) are evenly distributed within a 360° circumference of the bearing housing. Each set of sensors is parallel to the bearing axis and 10-15 mm away from the outer ring of the bearing.

[0119] Calculate the average resistance value. If the average value is greater than the preset reference maintenance value, a fan maintenance reminder will be issued. The reference maintenance value is, for example, 1000Ω.

[0120] Compared to single-point detection, it can cover the wear debris diffusion path in the circumferential direction of the bearing, especially capturing local abnormal wear caused by installation deviation or uneven load, thus improving the accuracy of detection.

[0121] To more accurately determine the operating status of the fan, the reference maintenance values ​​are dynamically set:

[0122] 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 coefficient (taken as 0.05-0.1). For example, after 2 years of operation, Rref automatically increases to 1100-1200Ω to adapt to the decreasing resistance value caused by natural bearing wear.

[0123] This application also discloses a drive component status detection system for a DC four-channel cleanroom air conditioning unit, including a processor, wherein the processor executes the steps of the drive component status detection method for a DC four-channel cleanroom air conditioning unit as described in any of the above embodiments.

[0124] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for detecting the status of drive components in a DC four-channel cleanroom air conditioning unit, characterized in that, Includes the following steps: The drive component is controlled according to the first frequency conversion signal until the speed of the drive component stabilizes; first vibration data is obtained based on the first vibration sensor installed on the drive component, and second vibration data is obtained based on the second vibration sensor installed within a set distance range next to the drive component. The drive component is controlled according to the acquired second frequency conversion signal until the speed of the drive component stabilizes, and the magnitude of the speed change is greater than the preset reference magnitude. The third vibration data is obtained based on the first vibration sensor, and the fourth vibration data is obtained based on the second vibration sensor. The first vibration data, the second vibration data, the third vibration data, and the fourth vibration data are subjected to spectral conversion to obtain first spectral data, second spectral data, third spectral data, and fourth spectral data; First component data is obtained by filtering and calculating the first spectrum data based on the second spectrum data; second component data is obtained by filtering and calculating the third spectrum data based on the fourth spectrum data. A first component, an overlapping component, and a second component are calculated based on the first component data and the second component data. The overlapping component is the 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 the component in the first component data whose frequency is different from the frequency of the overlapping component. The second component is the component in the second component data whose frequency is different from the frequency of the overlapping component. A temporary component is calculated based on the first component and the second component. The temporary ratio of the overlapping component and the temporary component is calculated. If the temporary ratio is greater than a preset reference ratio, a drive component status warning is issued.

2. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that, In the step of obtaining first component data by filtering and calculating the first spectrum data based on the second spectrum data, and obtaining second component data by filtering and calculating the third spectrum data based on the fourth spectrum data, the filtering and calculation method includes the following steps: Subtract the second spectrum data from the first spectrum data, and change the negative value after the subtraction to zero; Subtract the fourth spectrum data from the third spectrum data, and change the negative value of the subtraction to zero.

3. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that, The method also includes the following steps: Based on the first frequency conversion signal, after the speed of the drive component stabilizes, the first speed data is acquired based on the speed sensor; Based on the second frequency conversion signal, after the speed of the drive component stabilizes, the second speed data is acquired based on the speed sensor; Calculate the speed difference between the first speed data and the second speed data, and adjust the reference ratio based on the inverse correlation of the speed difference; Calculate the average speed of the first speed data and the second speed data, calculate the average difference between the average speed data and the preset average reference value, and adjust the reference similarity value according to the positive correlation of the average difference.

4. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 3, characterized in that, The method also includes the following steps: As the rotational speed of the driving component gradually changes to the first rotational speed data, the data from the first vibration sensor is recorded to obtain the first waveform data. As the rotational speed of the driving component gradually changes to the second rotational speed data, the data from the first vibration sensor is recorded to obtain the second waveform data. If the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data have no overlapping intervals, then the first waveform data is matched according to the preset first resonance waveform template to obtain a first matching value; then the second waveform data is matched according to the preset first resonance waveform template to obtain a second matching value. The final matching value is calculated based on the first matching value and the second matching value. If the final matching value is greater than the preset reference matching value, a resonance warning is issued.

5. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 3, characterized in that, The method also includes the following steps: As the rotational speed of the driving component gradually changes to the first rotational speed data, the data from the first vibration sensor is recorded to obtain the first waveform data. As the rotational speed of the driving component gradually changes to the second rotational speed data, the data from the first vibration sensor is recorded to obtain the second waveform data. If the rotational speed data corresponding to the first waveform data and the rotational speed data corresponding to the second waveform data have overlapping intervals, and the length of the overlapping interval is greater than the length of the preset reference interval, then the first waveform data is matched according to the preset second resonance waveform template, and the rotational speed with the highest matching value is the first matching rotational speed; the second waveform data is matched according to the second resonance waveform template, and the rotational speed with the highest matching value is the second matching rotational speed. If the difference between the first matching speed and the second matching speed is less than a preset matching difference, a resonance warning will be issued.

6. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that, The method also includes the following steps: A through-beam sensor is provided below the bearing, the through-beam sensor comprising at least one set of transmitting tubes and receiving tubes arranged in opposite directions; Acquire the through-beam signal from the through-beam sensor; If the transmitted signals are in a group, and the content of the transmitted signals is smoothed and filtered, if the content contains foreign objects, a wear warning will be issued.

7. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 6, characterized in that, The method also includes the following steps: If there are multiple sets of through-beam signals, the multiple sets of through-beam signals are converted into wear values, and the wear values ​​are smoothed and filtered. If the wear value is greater than the preset wear reference value, a wear warning is issued. Calculate the wear difference between the wear value and the wear reference value, and adjust the speed corresponding to the first frequency converter signal and the speed corresponding to the second frequency converter signal according to the wear difference inverse correlation.

8. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 1, characterized in that, The method also includes the following steps: A foreign object detection sensor is installed next to the bearing. The foreign object detection sensor includes two parallel detection plates, which are connected to a detection circuit. The rotation axis of the drive component is parallel to the plane where the detection plates are located. Obtain the resistance value between the two detection plates; The fan speed is controlled to a speed that causes vibration, and the resistance value is physically filtered. The resistance value is then smoothed using a filtering process. If the resistance value is less than the preset first reference resistance value, a foreign object warning will be issued; Otherwise, if the resistance value is less than the preset second reference resistance value, a wear warning will be issued; wherein the second reference resistance value is greater than the first reference resistance.

9. The method for detecting the status of drive components of a DC four-channel clean air conditioning unit according to claim 8, characterized in that, The method also includes the following steps: Multiple sets of the foreign object detection sensors are located on the circumference of the bearing, generating multiple sets of the resistance values; Calculate the average value of the resistance. If the average value is greater than the preset reference maintenance value, then issue a fan maintenance reminder.

10. A status detection system for drive components of a DC four-channel cleanroom air conditioning unit, characterized in that, The system includes a processor that performs the steps of the drive component status detection method for a DC four-channel clean air conditioning unit as described in any one of claims 1-9.

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