cc修改

Phead.py

+def cal_Phead(inletPressure_bar, outletPressure_bar, rho=1000, g=9.81): #Pressure：Pa；rho：kg/m^3；g：m/s^2
+    rho = rho
+    g = g
+    inletPressure_pa = inletPressure_bar * 100000
+    outletPressure_pa = outletPressure_bar * 100000
+    if rho * g == 0:
+        return "Error"
+    else:
+        H = (outletPressure_pa - inletPressure_pa) / (rho * g)
+    return H
+
+# print(cal_Phead(2.5,2.4))
\ No newline at end of file

Wilo_Transfer.py

+import apiUtils.api as cc
+import paho.mqtt.client as mqtt
+import json
+import time
+import Phead
+import eef
+import sys
+
+
+urlMain = "http://gm.cloud.witium.com.cn/api"
+
+# 根据当前的addr通道，自动读取对应设备的转速数据使用
+RN_RM_1 = {"RN":"RN915455426295115778","RM":"RM915455426295115776"}
+RN_RM_2 = {"RN":"RN915456080103223296","RM":"RM915456080069668864"}
+RN_RM_3 = {"RN":"RN915456298278334464","RM":"RM915456298253168640"}
+RN_RM_list = [RN_RM_1, RN_RM_2, RN_RM_3]                           
+
+# 用于获取当前转速信息的传参
+reducerNo = [RN_RM_list[1]["RN"]]
+startTime = int(time.time())*1000 - 100000
+endTime = startTime + 100000000
+wcVarList = []
+varList = [["actualSpd"]]
+monitorNoList = [RN_RM_list[1]["RM"]]
+
+# 如果获取的电机转速为0，则用固定值
+actualSpd= 2400 # TODO
+cc.setUrlMain(urlMain)
+
+# 配置MQTT信息常量
+CODEENV = "test"
+OP_SN_TYPE = "WTG93RF"
+OP_SN = "24010580W"
+BROKER_IP = "222.71.96.91"  
+BROKER_PORT = 12883
+USERNAME = "witcd"
+PASSWORD = "Witium37774020"
+
+# 构建主题
+DATA_SOURCE_TOPIC = f"WT/{OP_SN_TYPE}/{OP_SN}/opData"
+
+class MQTTForwarder:
+    def __init__(self, actualSpd, startTime, wcVarList, varList, RN_RM_list, endTime):
+        self.client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
+        self.client.username_pw_set(USERNAME, PASSWORD)
+        self.client.on_connect = self.on_connect
+        self.client.on_message = self.on_message
+        self.client.on_disconnect = self.on_disconnect
+        self.received_data = None  # 存储解析后的数据
+        self.actualSpd = actualSpd
+        self.startTime = startTime
+        self.wcVarList = wcVarList
+        self.varList = varList
+        self.RN_RM_list = RN_RM_list
+        self.endTime = endTime
+
+    def on_connect(self, client, userdata, flags, rc, properties=None):
+        if rc == 0:
+            print("成功连接到MQTT服务器")
+            client.subscribe(DATA_SOURCE_TOPIC)  # 只订阅数据源主题
+        else:
+            print(f"连接失败，错误码: {rc}")
+    
+    def on_message(self, client, userdata, msg):
+        print(f"收到消息 [{msg.topic}]: {msg.payload.decode()}")
+        if msg.topic == DATA_SOURCE_TOPIC:
+            try:
+                data = json.loads(msg.payload.decode())
+                print(type(data),data)
+                # 检查数据是否为列表，并提取第一个字典
+                if isinstance(data, list) and len(data) > 0:
+                    received_data = data[0]  # 取第一个字典
+                    print("成功解析并存储数据")
+
+                    # 从数据中提取 addr
+                    if 'addr' in received_data:
+                        addr = received_data['addr']
+                        # 动态构建发布主题
+                        PUBLISH_TOPIC = f"{DATA_SOURCE_TOPIC}/{addr}"
+                        PUBLISH_TOPIC_cc = f"{DATA_SOURCE_TOPIC}"
+                    # # 更新数据中的时间戳和地址
+                    # received_data['ts'] = startTime
+                    #######################################    涉及计算部分 cc修改        ##########################################
+                    ##########################  获取当前运行设备的转速    #################
+                    print("addr:{}".format(received_data['addr']))
+
+                    reducerNo = self.RN_RM_list[received_data["addr"] - 1]["RN"]
+                    startTime = self.startTime
+                    endTime = self.endTime
+                    wcVarList =self.wcVarList
+                    varList=self.varList
+                    monitorNoList=[self.RN_RM_list[received_data["addr"] - 1]["RM"]]
+
+                    res = cc.getHistoryDataWithWorkingConditionByMonitorList_route( 
+                                                                    reducerNo = reducerNo,
+                                                                    startTime = startTime,
+                                                                    endTime = endTime,
+                                                                    wcVarList = wcVarList,
+                                                                    varList = varList ,
+                                                                    monitorNoList = monitorNoList)
+                    acutalSpd_r = res["data"]["actualSpd_"+monitorNoList[0]]
+
+                    if len(acutalSpd_r) == 0:
+                        acutalSpd_r = self.actualSpd
+                    else:
+                        if actualSpd[0] == 0:
+                            acutalSpd_r = self.actualSpd
+                        else:
+                            acutalSpd_r = actualSpd[-1]    # 确保获取的转速是最新的
+
+                    ##########################  获取MQTT中的工况数据用于计算    #################
+                    P_in = received_data["P_in"]
+                    P_out = received_data["P_out"]
+
+                    if P_in < 0 and P_out < 0:
+                        P_in = 0
+                        P_out = 0
+                    else:
+                        pass 
+                    
+                    ##########################  更新扬程    #################
+                    received_data["Phead"]= Phead.cal_Phead( inletPressure_bar= P_in, outletPressure_bar= P_out)
+
+                    ##########################  更新Umax    #################
+                    received_data["Umax"] = received_data["UA"]
+
+                    ##########################  更新能效比    #################
+                    received_data["eef"] = eef.evaluate(H_real=received_data["Phead"], P0_real=received_data["Pmax"], N_real=acutalSpd_r)["ΔP0_%"]
+                    if received_data["eef"] < 0:
+                        received_data["eef"] = 0
+                    elif received_data["eef"] > 100:
+                        received_data["eef"] = 100
+                    else:
+                        pass
+
+                    ##########################  更新流量    #################
+                    received_data["Flow"] = eef.estimate_flow(H_query=received_data["Phead"], N_query=acutalSpd_r)
+
+                    ##########################  更新频率    #################
+                    received_data["actualSpd"] = acutalSpd_r / 60
+
+                    ##########################  更新负载    #################
+                    received_data["Load_ratio"] = received_data["Pmax"] / 4.5 * 100
+                    if received_data["Load_ratio"] < 0:
+                        received_data["Load_ratio"] = 0
+                    elif received_data["Load_ratio"] > 100:
+                        received_data["Load_ratio"] = 100
+                    else:
+                        pass
+
+                    # 发布到目标主题
+                    received_data = [received_data]
+                    payload = json.dumps(received_data)
+                    result = client.publish(PUBLISH_TOPIC, payload)
+                    result_cc = client.publish(PUBLISH_TOPIC_cc, payload)
+
+                    if result.rc == mqtt.MQTT_ERR_SUCCESS:
+                        print(f"数据已发布到 {PUBLISH_TOPIC}")
+                    else:
+                        print(f"发布失败，错误码: {result.rc}")
+
+                else:
+                    print("数据格式错误：不是列表或列表为空")
+            except json.JSONDecodeError:
+                print("无法解析JSON数据")
+            except Exception as e:
+                print(f"处理消息时出错: {e}")
+    
+    def on_disconnect(self, client, userdata, rc):
+        print(f"连接断开,5秒后重试 (code: {rc})")
+        time.sleep(5)
+        client.reconnect()
+    
+    
+    def start(self):
+        self.client.connect(BROKER_IP, BROKER_PORT, keepalive=60)
+        self.client.loop_start()
+
+if __name__ == "__main__":
+    try:
+        forwarder = MQTTForwarder(actualSpd, startTime,wcVarList,varList,RN_RM_list,endTime)
+        forwarder.start()
+        
+        # 等待连接建立
+        time.sleep(2)
+        
+        # 每5秒检查并发布一次数据
+        while True:
+            time.sleep(5)
+            
+    except KeyboardInterrupt:
+        print("\n程序终止")
+    except Exception as e:
+        print(f"致命错误: {str(e)}")

__pycache__/cc.py

+import numpy as np
+
+def x():
+    return 1,2,3
+
+y=x()[1]
+print(y)
\ No newline at end of file

debug.log

+[0801/000125.601:ERROR:registration_protocol_win.cc(107)] CreateFile: 系统找不到指定的文件。 (0x2)

eef.py

+import pandas as pd, numpy as np
+import sys
+import datetime
+import time
+
+# ------------------------------------------------------------
+# 1) 读取 CSV 并按 ±2 rpm 归并转速
+speed_tol = 2
+df = pd.read_csv("E:\File\DESK\陈聪文档\学习代码\wilo_fea_cal_transfer-main\wilo_fea_cal_transfer-main\wilo_pump.CSV")
+df.rename(columns={"H\n(m)": "H",
+                   "P0tot\n(kW)": "P0",
+                     "Q\n(m3/h)": "Q",
+                   "N\n(rpm)": "N"}, inplace=True)
+
+uniq = np.sort(df["N"].unique())
+
+clusters, cluster = [], [uniq[0]]
+for n in uniq[1:]:
+    # 若与当前簇最后一个值差值 ≤ 容忍带 → 归同簇
+    if n - cluster[-1] <= speed_tol:
+        cluster.append(n)
+    else:
+        clusters.append(cluster)      # 结束旧簇
+        cluster = [n]                 # 开始新簇
+clusters.append(cluster)              # 别忘了最后一个簇
+
+# 建立 speed_map：把簇中的每个原始转速映射到簇内平均值
+speed_map = {}
+for c in clusters:
+    rep = int(round(np.mean(c)))      # 代表转速
+    for n in c:
+        speed_map[int(n)] = rep       # 注意 n 先转 int，避免 numpy.int64
+
+df["N_grp"] = df["N"].map(speed_map)
+
+# ------------------------------------------------------------
+# 给定 H / N 估算 Q（流量）
+def estimate_flow(H_query, N_query):
+    """估算流量 Q（单位 m³/h），df 必须含 'Q', 'H', 'N_grp'"""
+    if "Q" not in df.columns:
+        raise ValueError("数据中不包含 'Q' 列")
+
+    speeds = np.sort(df["N_grp"].unique())
+    if N_query < speeds[0] or N_query > speeds[-1]:
+        raise ValueError("N 超出试验范围")
+    j = np.searchsorted(speeds, N_query)
+    N_lo, N_hi = speeds[max(j-1,0)], speeds[min(j,len(speeds)-1)]
+
+    def q_at(N_fix):
+        sub = df[df["N_grp"] == N_fix].sort_values("H")
+        return np.interp(H_query, sub["H"], sub["Q"],
+                         left=sub["Q"].iloc[0], right=sub["Q"].iloc[-1])
+
+    Q_lo, Q_hi = q_at(N_lo), q_at(N_hi)
+    return Q_lo if N_lo == N_hi else np.interp(N_query, [N_lo, N_hi], [Q_lo, Q_hi])
+
+
+
+# ------------------------------------------------------------
+# 核心：给 H / N 求理想 P0tot
+def ideal_p0(H, N):
+    speeds = np.sort(df["N_grp"].unique())
+    if N < speeds[0] or N > speeds[-1]:
+        raise ValueError("N 超出试验范围")
+    j = np.searchsorted(speeds, N)
+    N_lo, N_hi = speeds[max(j-1,0)], speeds[min(j,len(speeds)-1)]
+
+    def p0_at(N_fix):
+        sub = df[df["N_grp"]==N_fix].sort_values("H")
+        return np.interp(H, sub["H"], sub["P0"],
+                         left=sub["P0"].iloc[0], right=sub["P0"].iloc[-1])
+    P_lo, P_hi = p0_at(N_lo), p0_at(N_hi)
+    return P_lo if N_lo==N_hi else np.interp(N, [N_lo,N_hi], [P_lo,P_hi])
+
+# ------------------------------------------------------------
+# 外部接口：输入实测 → 输出偏差
+def evaluate(H_real, P0_real, N_real):
+    P_idl = ideal_p0(H_real, N_real)
+    return {
+        "H": H_real,
+        "N": N_real,
+        "P0_real": P0_real,
+        "P0_ideal": P_idl,
+        "ΔP0_kW": P0_real - P_idl,
+        "ΔP0_%": 100-((P0_real - P_idl) / P_idl * 100)
+    }
+
+# -------------------- DEMO --------------------
+# print(evaluate(50, 4.50, 2432))
+# print(evaluate(2.4, 1.71, 2400))
+# ➜ {'H': 50, 'N': 2992, 'P0_real': 4.5,
+#    'P0_ideal': 4.232, 'ΔP0_kW': 0.268, 'ΔP0_%': 6.34}
+# -------------------- 流量估算 --------------------
+# print(f"估算流量 Q ≈ {estimate_flow(2.4, 2400):.2f} m³/h")

readme.md

+# **水泵特征计算与能耗分析工具**  
+**`02_feaCal.py`**  
+
+---
+
+## **项目简介**  
+本工具用于读取威乐（WILO）水泵的现有特征数据（如流量、扬程等），并计算其能耗性能。核心脚本 `02_feaCal.py` 通过处理输入数据（如 `wilo_pump.CSV`），生成水泵的能耗和扬程分析结果。  
+
+---
+
+## **功能特性**  
+1. **数据输入**  
+   - 支持从 `CSV` 文件（如 `wilo_pump.CSV`）读取水泵特征参数。  
+   - 可扩展其他数据源（如数据库、API）。  
+
+2. **核心计算**  
+   - 根据流量（如 `m³/s` 或 `L/s`）、扬程等参数，计算水泵的能耗（功率）。  
+   - 支持单位自动转换（如 `L/s ↔ m³/s`）。  
+
+3. **输出结果**  
+   - 生成能耗报告或可视化图表（需结合其他工具如 `matplotlib`）。  
+
+4. **集成扩展**  
+   - 与 `apiUtils` 模块交互，支持数据远程传输（如 MQTT 或 HTTP）。  
+
+---
+
+## **文件结构**  
+```plaintext
+.
+├── 02_feaCal.py          # 主脚本：水泵特征与能耗计算
+├── wilo_pump.CSV         # 水泵特征数据源
+├── apiUtils/             # 数据通信工具（如 MQTT/HTTP）
+├── 01_wcTransfer.py      # 辅助脚本（功能待明确）
+├── Phead.py              # 扬程计算相关（可能依赖）
+└── __pycache__/          # Python 缓存目录
+```
+
+---
+
+## **快速开始**  
+### **依赖安装**  
+```bash
+pip install pandas numpy  # 数据处理（如需 MQTT 则添加 paho-mqtt）
+```
+
+### **运行脚本**  
+```bash
+python 02_feaCal.py 
+```
+
+---
+
+## **扩展开发**  
+- **自定义计算**：修改 `02_feaCal.py` 中的 `calculate_energy()` 方法。  
+- **集成 API**：通过 `apiUtils` 模块将结果发送至云端。  
+- **可视化**：结合 `matplotlib` 绘制能耗曲线图。  
+
+---
+
+## **注意事项**  
+1. 文件状态说明：  
+   - `M`：已修改（需提交）  
+   - `U`：未跟踪（新文件）  
+   - `IM`：忽略修改（如配置文件）  
+2. 确保 `wilo_pump.CSV` 的字段格式与脚本匹配。  
+
+--- 
+
+**License**  
+MIT © 2025 上海辉度能力中心
\ No newline at end of file

wilo_pump.CSV

+"I0tot
+(A)","I1tot
+(A)","P0tot
+(kW)","P1tot
+(kW)","P2
+(kW)","N
+(rpm)","Q
+(m3/h)","H
+(m)"
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+3.77,3.59,2.186,2.119,1.994,3320,3.5,64.0
+5.07,5.18,3.101,3.014,2.873,3320,9.0,62.3
+6.24,6.70,3.947,3.835,3.672,3320,14.5,58.3
+6.93,7.61,4.429,4.301,4.119,3320,20.0,49.9
+7.04,7.76,4.500,4.371,4.184,3320,23.7,41.2
+6.92,7.62,4.423,4.297,4.116,3320,27.3,30.2
+6.69,7.33,4.272,4.150,3.976,3320,31.0,16.8
+6.49,7.06,4.130,4.012,3.830,3321,34.1,4.6
+2.25,2.20,1.257,1.208,1.102,2988,0.0,52.4
+2.87,2.86,1.627,1.572,1.459,2989,3.2,51.9
+3.90,4.04,2.296,2.225,2.097,2989,8.1,50.5
+4.78,5.15,2.914,2.828,2.684,2990,13.1,47.2
+5.26,5.79,3.264,3.168,3.017,2991,18.0,40.5
+5.33,5.88,3.315,3.217,3.065,2992,21.3,33.4
+5.24,5.78,3.260,3.164,3.011,2992,24.6,24.5
+5.08,5.58,3.152,3.059,2.906,2991,27.9,13.7
+4.95,5.39,3.045,2.954,2.810,2990,30.7,3.7
+1.74,1.78,0.913,0.871,0.782,2660,0.0,41.5
+2.10,2.29,1.171,1.125,1.032,2661,2.8,41.1
+3.03,3.22,1.649,1.586,1.482,2660,7.2,39.9
+3.77,4.08,2.082,2.008,1.894,2660,11.6,37.3
+4.10,4.57,2.324,2.245,2.123,2660,16.0,32.0
+4.12,4.64,2.362,2.280,2.157,2660,19.0,26.4
+4.07,4.57,2.326,2.244,2.122,2660,21.8,19.3
+3.97,4.42,2.250,2.172,2.054,2661,24.8,10.8
+3.83,4.27,2.168,2.097,1.981,2660,27.3,2.9
+1.29,1.40,0.638,0.602,0.530,2326,0.0,31.7
+1.57,1.79,0.810,0.770,0.695,2325,2.5,31.4
+2.10,2.49,1.123,1.075,0.995,2326,6.3,30.4
+2.58,3.14,1.415,1.357,1.270,2326,10.2,28.5
+2.85,3.51,1.577,1.514,1.423,2325,14.0,24.4
+2.89,3.56,1.600,1.536,1.445,2326,16.6,20.0
+2.84,3.50,1.576,1.513,1.422,2328,19.1,14.6
+2.74,3.40,1.529,1.467,1.378,2328,21.7,8.1
+2.66,3.28,1.476,1.416,1.332,2325,23.9,2.1
+0.93,1.08,0.430,0.397,0.340,1997,0.0,23.4
+1.13,1.37,0.541,0.505,0.445,1999,2.1,23.1
+1.46,1.87,0.737,0.696,0.634,1998,5.4,22.4
+1.77,2.35,0.920,0.874,0.809,1998,8.7,21.1
+1.96,2.62,1.025,0.974,0.907,1999,12.0,18.0
+1.99,2.66,1.040,0.989,0.922,1999,14.2,14.8
+1.97,2.62,1.025,0.974,0.908,1999,16.4,10.8
+1.92,2.54,0.995,0.946,0.880,1999,18.6,6.0
+1.84,2.46,0.965,0.915,0.852,1999,20.5,1.6
+0.69,0.83,0.277,0.246,0.204,1663,0.0,16.2
+0.77,1.00,0.337,0.306,0.262,1663,1.8,16.0
+0.97,1.35,0.454,0.419,0.373,1667,4.5,15.6
+1.16,1.68,0.561,0.523,0.475,1668,7.3,14.6
+1.26,1.87,0.621,0.581,0.532,1668,10.0,12.5
+1.27,1.89,0.630,0.589,0.540,1668,11.9,10.2
+1.26,1.87,0.621,0.581,0.532,1668,13.7,7.4
+1.24,1.81,0.604,0.564,0.515,1668,15.5,4.1
+1.21,1.75,0.585,0.545,0.498,1668,17.1,1.0
+0.51,0.61,0.168,0.142,0.110,1328,0.0,10.3
+0.56,0.73,0.202,0.174,0.141,1330,1.4,10.1
+0.66,0.94,0.261,0.230,0.198,1332,3.6,9.9
+0.74,1.15,0.316,0.284,0.251,1334,5.8,9.3
+0.83,1.27,0.347,0.314,0.280,1334,8.0,7.9
+0.86,1.28,0.351,0.317,0.283,1333,9.5,6.4
+0.84,1.26,0.345,0.312,0.278,1332,10.9,4.6
+0.78,1.23,0.336,0.304,0.270,1332,12.4,2.5
+0.78,1.19,0.327,0.295,0.261,1333,13.6,0.5
+0.44,11.00,0.102,0.078,0.056,1000,0.0,5.8
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