def execute(self):
df = self.graph.get_data_from_api(['drive_run'])
measdate, switch_nums, run_time, stop_time = self.get_fe(
df, self.graph.parameter)
if measdate:
if switch_nums > 0:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11100",
'value1st': float(switch_nums),
'indices2nd': []
})
self.graph.indices.append(index)
if run_time > 0:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11101",
'value1st': float(run_time),
'indices2nd': []
})
self.graph.indices.append(index)
if stop_time > 0:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11102",
'value1st': float(stop_time),
'indices2nd': []
})
self.graph.indices.append(index)
def execute(self):
measdate, avg_sv_out, std_sv_out, max_sv_out, min_sv_out = self.get_fe(self.graph.parameter)
for i, meastime in enumerate(measdate):
index = Index({'assetid': self.graph.deviceid, 'meastime1st': meastime, 'feid1st': "10400",
'value1st': avg_sv_out[i], 'indices2nd': []})
self.graph.indices.append(index)
index = Index({'assetid': self.graph.deviceid, 'meastime1st': meastime, 'feid1st': "10401",
'value1st': std_sv_out[i], 'indices2nd': []})
self.graph.indices.append(index)
index = Index({'assetid': self.graph.deviceid, 'meastime1st': meastime, 'feid1st': "10402",
'value1st': max_sv_out[i], 'indices2nd': []})
self.graph.indices.append(index)
index = Index({'assetid': self.graph.deviceid, 'meastime1st': meastime, 'feid1st': "10403",
'value1st': min_sv_out[i], 'indices2nd': []})
self.graph.indices.append(index)
def execute(self):
if 1 == len(self.graph.channelid):
df = self.graph.get_data_from_api(['speed'])
measdate, s_total = self.get_fe_v1(df) # 计算总里程
if measdate:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11000",
'value1st': s_total,
'indices2nd': []
})
self.graph.indices.append(index)
else:
df = self.graph.get_data_from_api(['speed', 'in_force_control'])
measdate, s_total, s_in_operation, s_idler = self.get_fe_v2(
df) # 计算总里程、负载里程、空载里程
if measdate:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11000",
'value1st': s_total,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11001",
'value1st': s_in_operation,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': "11002",
'value1st': s_idler,
'indices2nd': []
})
self.graph.indices.append(index)
def execute(self):
df = self.graph.get_data_from_api(
['gap_ref', 'gap_act', 'sv_out', 'speed_ref'])
measdate, avg_sv_out, std_sv_out, max_sv_out, min_sv_out = self.get_fe(
df, self.graph.parameter)
for i, meastime in enumerate(measdate):
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10400",
'value1st': avg_sv_out[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10401",
'value1st': std_sv_out[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10402",
'value1st': max_sv_out[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10403",
'value1st': min_sv_out[i],
'indices2nd': []
})
self.graph.indices.append(index)
def get_alarm(self):
df = self.graph.get_data_from_api(['sv_ref', 'sv_act'])
if df.empty:
return
algparas = self.graph.parameter
rolling = df['sv_ref'].rolling(algparas[0] * df.dt)
roll_cv = np.abs(rolling.std() / rolling.mean()) # 计算窗口变异系数
min_cv = roll_cv.max()
if min_cv > algparas[1]: # 数据包不包含稳态工况
return
stidx = roll_cv.argmin() - np.floor(algparas[0] * df.dt / 2)
edidx = roll_cv.argmin() + np.ceil(algparas[0] * df.dt / 2)
n = (edidx - stidx) // 5 # 对稳态段切头切尾
avg_ref = np.mean(df['sv_ref'][stidx + n:edidx - n])
avg_act = np.mean(df['sv_act'][stidx + n:edidx - n])
r = np.abs(avg_ref - avg_act) / avg_ref * 100 # 计算稳态工况设定值与实际值偏差
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': df.index[0],
'feid1st': "16000",
'value1st': r,
'indices2nd': []
})
self.graph.indices.append(index)
if r > algparas[2]:
event = Event({
'assetid': self.graph.deviceid,
'meastime': df.index[0],
'level': 1,
'info': '伺服阀零偏报警'
})
self.graph.events.append(event)
def get_alarm(self):
df = self.graph.get_data_from_api(['pressure', 's1', 's2', 's3'])
if df.empty:
return
algparas = self.graph.parameter
rolling = df['s1'].rolling(algparas[0] * df.dt)
roll_cv = np.abs(rolling.std() / rolling.mean()) # 计算窗口变异系数
idx1 = roll_cv < algparas[1]
if not idx1:
return
idx2 = pd.Series((df['s2'] == algparas[2]) & (df['s3'] == algparas[3]))\
.rolling(algparas[0] * df.dt, center=True).min() # 满足
min_cv = roll_cv[idx1 & idx2].min()
if np.isnan(min_cv): # 数据包不包含稳态工况
return
stidx = roll_cv[idx1 & idx2].argmin() - np.floor(
algparas[0] * df.dt / 2)
edidx = roll_cv[idx1 & idx2].argmin() + np.ceil(
algparas[0] * df.dt / 2)
n = (edidx - stidx) // 5 # 对稳态段切头切尾
avg_pressure = np.mean(df['pressure'][stidx + n:edidx - n])
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': df.index[0],
'feid1st': "17000",
'value1st': avg_pressure,
'indices2nd': []
})
self.graph.indices.append(index)
def execute(self):
df = self.graph.get_data_from_api(
['agc_active', 'os_lc', 'os_pt', 'ds_lc', 'ds_pt'])
df['force'] = df['os_lc']
measdate, std_force, avg_force, max_force, min_force = self.get_fe(df)
if measdate:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14000),
'value1st': std_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14001),
'value1st': avg_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14002),
'value1st': max_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14003),
'value1st': min_force,
'indices2nd': []
})
self.graph.indices.append(index)
df['force'] = df['os_pt']
measdate, std_force, avg_force, max_force, min_force = self.get_fe(df)
if measdate:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14004),
'value1st': std_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14005),
'value1st': avg_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14006),
'value1st': max_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14007),
'value1st': min_force,
'indices2nd': []
})
self.graph.indices.append(index)
df['force'] = df['ds_lc']
if measdate:
measdate, std_force, avg_force, max_force, min_force = self.get_fe(
df)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14008),
'value1st': std_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14009),
'value1st': avg_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14010),
'value1st': max_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14011),
'value1st': min_force,
'indices2nd': []
})
self.graph.indices.append(index)
df['force'] = df['ds_pt']
if measdate:
measdate, std_force, avg_force, max_force, min_force = self.get_fe(
df)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14012),
'value1st': std_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14013),
'value1st': avg_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14014),
'value1st': max_force,
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': measdate,
'feid1st': str(14015),
'value1st': min_force,
'indices2nd': []
})
self.graph.indices.append(index)
def execute(self):
measdate, curr_avg, curr_std, curr_max, curr_min, torq_avg, torq_std, torq_max, torq_min \
= self.get_curr_avg_and_std()
for i, meastime in enumerate(measdate):
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10100",
'value1st': curr_avg[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10101",
'value1st': curr_std[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10102",
'value1st': curr_max[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10103",
'value1st': curr_min[i],
'indices2nd': []
})
self.graph.indices.append(index)
if torq_avg:
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10104",
'value1st': torq_avg[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10105",
'value1st': torq_std[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10106",
'value1st': torq_max[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10107",
'value1st': torq_min[i],
'indices2nd': []
})
self.graph.indices.append(index)
def execute(self):
df = self.graph.get_data_from_api(
['gap_act', 'pis_pressure', 'rod_pressure'])
measdate1, avg_pressure1, std_pressure1, max_pressure1, min_pressure1, \
measdate2, avg_pressure2, std_pressure2, max_pressure2, min_pressure2 \
= self.get_fe(df, self.graph.parameter)
for i, meastime in enumerate(measdate1):
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10300",
'value1st': avg_pressure1[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10301",
'value1st': std_pressure1[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10302",
'value1st': max_pressure1[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10303",
'value1st': min_pressure1[i],
'indices2nd': []
})
self.graph.indices.append(index)
for i, meastime in enumerate(measdate2):
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10304",
'value1st': avg_pressure2[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10305",
'value1st': std_pressure2[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10306",
'value1st': max_pressure2[i],
'indices2nd': []
})
self.graph.indices.append(index)
index = Index({
'assetid': self.graph.deviceid,
'meastime1st': meastime,
'feid1st': "10307",
'value1st': min_pressure2[i],
'indices2nd': []
})
self.graph.indices.append(index)